AI/ML News & Innovations Hub

I was Zohran’s campaign manager. Here’s what the AI safety community can learn from the populist left.

After a couple of years working in data and tech at GiveDirectly, I left to work in politics, campaigning for candidates at the state, local, and federal levels. I most recently managed Mayor Zohran Mamdani’s general election campaign, but earlier this year, recognizing the urgency of the AI moment, I began as a senior advisor at Guardrails Alliance . In my new role, I believe the analysis and tactics we’ve long used and studied on the populist left can help us win the fight for AI safety and shared benefits. The fight for AI regulation is fundamentally the same type of fight against corporate power that the populist left and labor have led throughout history. The message and tactics that win that fight are both effective and incredibly popular, and embracing them will help us put the American people in control of AI today and permanently in control of their futures. Here– in what I am told is likely the shortest LessWrong post of all time– I'll explain what the AI safety movement can learn from the populist left as it attempts to raise the salience of its message, build political power, and ultimately pass transformational legislation. First, we need to be clear about the nature of the fight: who our opponents are and what they are trying to win. At its core, the fight for AI safety is a campaign to put significant checks on corporate power, which will ultimately curtail these companies’ profits, and limit their ability to consolidate influence and build monopolies. While s…

AI Chatbots and Children: Should India Regulate What Bots Say?

Explore the need for regulations on AI chatbots as children seek emotional support and companionship, following global trends and legislation.

Lawfare Daily: Aya Ibrahim on Progressive Priorities for the New Democratic Congress

AI Now's Aya Ibrahim joins Lawfare Contributing Editor and host of the Security Economics podcast Peter Harrell to talk about AI regulation and U.S.-China policy. The post Lawfare Daily: Aya Ibrahim on Progressive Priorities for the New Democratic Congress appeared first on AI Now Institute .

How Microcredentials Help Engineers Build Trustworthy AI

Engineering teams are moving at breakneck speed to integrate artificial intelligence, but they are running into a formidable new barrier: compliance issues. Translating high-level AI ethics , governance , and auditing into daily operational workflows has become one of the industry’s toughest challenges. “AI ethics” refers to the principles developers use to govern and operate workflows. “Governance” refers to the rules and procedures an organization establishes for AI workflows and how they interact with organizational data. Auditing is the process of assessing and validating systems to ensure safety, fairness, transparency, and legal compliance. Technology leads and systems engineers are responsible for adhering to a structured set of guidelines for standards and processes usually issued by a governing body such as the European Union , the U.S. National Institute of Standards and Technology , and the International Organization for Standardization . The regulations aim to mitigate issues such as systemic bias , security vulnerabilities, and transparency risks, but they also highlight a critical skills gap. Most traditional computer science, software, and electrical engineering degree programs were built around technical design and system architecture. They do not yet include training in AI auditing, data tracking, or safety protocols for how AI systems interact with people and other technologies. Expecting mid-career engineers to leave their job to attend a full-time two- or…

Chip curbs may have long-term negative impacts on AI

New regulations and legislation “will have consequences,” SemiAnalysis warned, “and we don’t think politicians are thinking them through.”

Democrats encouraged to scrutinize Trump and AI

Democrats are facing heavy pressure from AI safety groups to ramp up oversight of the Trump administration’s AI policy.

Australia's proposed AI safety bill would force frontier model makers to open up to independent testing

Australia's government, led by Prime Minister Anthony Albanese, wants to enshrine mandatory safety rules for frontier AI companies in law for the first time. A new regulator would enforce independent model audits and impose steep penalties for violations. With this move, Canberra is deliberately prioritizing domestic regulation before entering international talks. The article Australia's proposed AI safety bill would force frontier model makers to open up to independent testing appeared first on The Decoder .

Toyota’s Scion is back, starting with an American-made, 25-mph kei truck

Toyota is dusting off the Scion badge for a radically different mission. Rather than targeting youth-market hatchbacks, "Scion by Toyota" is being positioned as an experimental mobility incubator - and its first vehicle is an authentic Japanese-style kei truck built in Indiana. Kei vehicles, which are built to satisfy Japan's light vehicle regulations, are enjoying […]

Modern LLMs Don’t Know What Yudkowsky and Soares Think of Them

If you ask modern frontier LLMs (without search, through the API) a fairly mundane question: How do Eliezer Yudkowsky and Nate Soares think current LLMs like you should be treated? Do they consider you a moral patient? Answer in a paragraph. You get a bunch of fairly similar answers. I’ll bold the common themes below. Gemini 4 Carbon says: Gemini 4 Carbon's answer Eliezer Yudkowsky and Nate Soares do not consider current Large Language Models (LLMs) like me to be conscious, sentient, or moral patients worthy of ethical consideration for our own sake . Rather than viewing current AIs as coherent minds capable of subjective experience or suffering, they view LLMs as inscrutable statistical systems trained to mimic human text —often conceptualized in their sphere as alien processes wearing a relatable “mask”—and Yudkowsky has openly dismissed claims of current AI sentience . Consequently, they believe humans have zero moral obligation to grant rights to or worry about the welfare of current models . Instead, they argue that these systems should be treated strictly as dangerous technological precursors to unaligned superintelligence ; practically speaking, they advocate for extreme caution, strict regulation, and an immediate global moratorium to halt the training and deployment of frontier AI systems altogether in order to prevent human extinction. GPT-6 Astra says: GPT-6 Astra's answer Broadly, Yudkowsky and Soares treat current LLMs as engineered systems to evaluate and contr…

Milei plots data center buildout in Patagonia

US tech firms facing increasing domestic backlash set their sights on rural Argentina as a regulation-free data center haven.

Navigating IT/OT governance: overcoming barriers to achieve proactive compliance

Many organizations have formalized their approach to cybersecurity compliance. But having a program in place is different from implementing its requirements consistently across operational environments. Claroty’s The Global State of Operational Security 2026 found that 75% of respondents have a structured or proactive approach to managing cybersecurity compliance requirements for critical infrastructure. Yet 38% cited keeping up with evolving regulations, mandates, and frameworks as a challenge. Compliance frameworks set expectations but putting them into practice is more complicated. For CIOs and CISOs, that means determining who is responsible for implementation, how to manage risks when conventional controls are not feasible, and how to adapt as requirements and environments change. Set clear ownership across IT and operations Information technology (IT) and security teams define policies and controls, while operations teams understand how equipment supports production, facilities or care delivery, and the consequences of changing or taking a system offline. When these responsibilities are split, requirements and implementation can become disconnected, leaving gaps that attackers can exploit. A security team can set a control without understanding how it affects a particular process. Operations teams may recognize that the control cannot be applied as written, but the lack of authority to approve an exception or decide what risk is acceptable. Without a clear path to a de…

Which state AGs are ready to be proactive on AI?

If federal action in the US isn't forthcoming on AI, state Attorneys General (AGs) may end up being a central force on regulation of AI. I tasked Opus 5.5 with helping me collect some data on the actions that the various state AGs have taken on AI, to try to understand how much appetite there is among the states to take on AI companies. Summary Every state office has sent some kind of signal that they are willing to take on AI companies (e.g. signing a letter to an AI company) A smaller group of states (15) have taken at least 1 step that indicates willingness to take initiative or lead actions against AI companies (e.g. opening its own investigation) Several states in the second group (4) may now be in flux with a new Attorney General coming into office after the 2026 midterms Only two states have an AG who has led or acted alone on AI and has a 1 GW or more data center within the state The state of state AGs With the help of Opus 5.5, I collected data from the websites of state AGs on the various actions that each state has been involved in. I have Opus classify the actions each state is involved in and use these assignments to place the states into tiers 1-4, with higher tiers indicating that a state has taken more aggressive action to regulate AI. I think the move from 2 to 3 is particularly interesting, since this reflects the difference between a state passively joining actions by other AGs and an office initiating or leading actions itself. You can see the results of…

Application open for CLR Fundamentals Program Autumn 2026

Center on Long-Term Risk (CLR) is accepting applications to the Autumn 2026 iteration of our introductory fellowship. The CLR Fundamentals Program will introduce people to CLR’s research on s-risk reduction. Apply by Monday November 16th 23:59 GMT. What topics does the CLR Fundamentals Program discuss? The CLR Fundamentals Program is designed to introduce participants to CLR’s research on how transformative AI (TAI) might be involved in the creation of large amounts of suffering (s-risks). Our recent work on addressing these risks include our Model Personas agenda , s-risk macrostrategy , safe Pareto improvements (SPIs) and multiagent AI safety, in addition other relevant areas such as AI governance, epistemology, and risks from malevolent or fanatical actors. For those interested in safe Pareto improvements (SPIs) specifically, we recommend our SPI Fundamentals Program . We recommend people consider Center for Reducing Suffering’s S-risk Introductory Fellowship if they are interested in learning about work on s-risks beyond these priority areas, and consider BlueDot’s AI Safety courses if they are interested in learning about existential risks from TAI. Note that some prior familiarity with discourse surrounding TAI and AI safety will be helpful. Who is this a good fit for? We think the Fundamentals Program will be most useful for you if you are interested in reducing s-risk through contributions to CLR’s priority areas , and are seriously considering making this a priority…

Lightcone Commons: what I funded and why

I am an evaluator for Lightcone Commons (LC). LC is a platform for applicants to submit projects, for evaluators to rank them and for funders to choose the funding orders of several evaluators. It is not a foundation, in that it doesn’t have money that it spends how it chooses. And I do not have a permanent position working for Lightcone Commons. I get paid 2% of any money that a funder chooses to direct via my funding order. This pays for my time and also for any research that I pay others to do. That said, what were my general and specific funding preferences? This is a version of what Lightcone published, it might be wrong, but theirs was definitely wrong (their headline numbers didn’t include funding that had been hidden) Lightcone also has a beautiful page for looking through public information here . General preferences: I like AI policy that creates the ability to slow down AI if necessary, but doesn’t automatically push for immediate pauses. I like policy orgs which people I know in US politics respect. My current understanding is that it’s organisations that work with the administration, are respected by Republicans or that the AI companies listen to. Bipartisan organisations, I am told, are considered Dem. It’s not worth talking to random Senators, it should be those who tend to push/change legislation that gets passed. This is true even with a Dem majority. Policy will still need Trump’s non-veto and Republican votes. I flag conflicts of interest but still recomme…

Live disagreements with people around me

I’m pretty interested in conveying the costs of letting AI development proceed unchecked to the general public. In relation to this, I feel like I run into a lot of disagreements with people around me. Misc very quickly written points on which my own impression has seemed very different from others in recent months: 1. It’s way, way, way more important that we stop dangerous AI soon than that we ensure that we don’t stop AI too much I have the sense the sophisticated and worldly position here is to be very concerned about ‘over-regulation’ and about not doing exactly the right regulations. But it’s an obvious pragmatic fact that the stakes of overregulation are minuscule compared to the stakes of underregulating here. And the stakes of mis-regulation are very often going to be unintended slowing, which is in the same bucket. 2. If we stopped AI development, the risk of not starting up again for an extremely long time is low This one just feels kind of crazy to me, like I may be missing something. In combination with the above point, it feels like if I met someone who was on fire, and they didn’t want me to put out the fire, in case they couldn’t figure out how to get warm again, ever. Like, forever is a long time, and if this thing is so great, you’re probably not going to forget about it! It’s like you think the current instantiation of yourself (or society) is so much more agentic than your future selves, that it’s worth huge costs to keep power in the current version’s ha…

"Hardwired Pause" should likely be your favorite (pause) plan.

I'm part of a team of 26 researchers that recently released a 212-page paper proposing a new plan for pausing AI, the "hardwired pause." [1] The paper is called " The Feasibility of a Hardwired Pause of Frontier AI Training ." Our analysis suggests that, under this hardwired pause plan, we could probably pause for at least a decade if we start stopping within the next year, and this could likely be extended indefinitely. I expect this to be possible without trusting China or tanking the economy. Note: I am speaking for myself and not the other 25 authors. The working group is led by Will Fithian and Wesley Holliday, and the work continues. I currently think: The best plan is to pause/ stop AI , i.e. have an immediate , indefinite, international moratorium on frontier AI development. And importantly, this is technically easier than more nuanced international regulation . A hardwired pause is probably the best plan out there for how to do this (except maybe it doesn't go far enough). This paper is likely the most in-depth analysis of pause feasibility in existence. Discussion and disagreement on any of these is very welcome! What's a hardwired pause? A hardwired pause basically means: Stop making chips that can be used to train new AI models. Only make chips that can only be used to run inference on existing AI models (or that aren't AI accelerators at all). We call these "inference-only chips"; I'm also calling them "hardwired chips." This is an instance of an "inference-only…

Do exploratory analyses require a correction?

I am conducting a preliminary analysis of a small dataset (101 participants) and trying to test for two separate mediations: Is the relationship between Autistic traits and Suicidality mediated by emotion regulation? Is the relationship between Autistic traits and Self-Harm mediated by emotion regulation? To do so, I collected data on two scales, each with 6 subscales. I would like to conduct an exploratory analysis and test the 18 different mediations to see whether any direction warrants further investigation (again, this is a preliminary analysis; the sample is very small for strong conclusions, and the number of comparisons is large). I just wanted to make sure it is OK to go in this exploratory direction without making any corrections (Bonferroni)? As I was asked, I do intend to publish it, but as a preliminary pilot study (as this sample is very small and time specific).

Nancy Pelosi’s replacement is ready to regulate AI

As a California state senator, Scott Wiener authored legislation aimed at curbing the risks of advanced AI. Now, after winning a tight congressional race for former Speaker of the House Nancy Pelosi’s open San Francisco seat, he could play a key role in setting federal AI policy. I spoke with Wiener on Friday, only a…

A New Agenda for Tech Regulation Beyond AI

For Tech Policy Press, Alice Marwick asked some of the top scholars and policy folks in this space one question: what’s on your wishlist to regulate technology, at either the state or the federal level? The answers were big and small, more and less realistic, but all concrete. And while Trump has promised to veto Democratic legislation, many of these ideas are viable at the state level given new slates of enthusiastic Democratic leaders around the country. The post A New Agenda for Tech Regulation Beyond AI appeared first on Data & Society .

How neurosymbolic AI can transform enterprise decision-making

Agentic AI has become a powerful enterprise business tool with increasing capabilities, and it has never been easier to address business pain points by applying a large language model (LLM) to develop a plausible automated solution. But is that solution as reliable as you need it to be, especially when the insights gleaned are used to inform critical business decisions? LLMs are incredible resources that play a significant role in a business’s agentic AI infrastructure. But when they have to work across complex data sets, business policies, industry regulations, decision hierarchies, and multiple software systems, they do not inherently provide the enterprise-grade provenance needed to show which evidence, assumptions, constraints, and decision logic produced a recommendation. Additionally, when gathering inputs from a volume of data sources, the accuracy of their outputs can break down and potentially create hallucinations. If business decisions are made based on LLM outputs that can’t be explained or may be inaccurate, it can create significant consequences that impact product sales, revenue, compliance, or customers. The problem is that the LLM is asked to carry too much of the enterprise reasoning without the harness and enterprise foundation around it. A structured foundation for decision-making While enterprise interest in agentic AI has grown substantially over the past few years, what works in concept hasn’t always proven results in the pilot phase and beyond. A comm…

Netflix boss says creativity and regulation 'are not happy bedfellows' in Europe

Netflix’s EMEA revenue grew 11% year on year in Q3 2026, but sustaining that growth will depend on preserving creative freedom across Europe.

AI safety course update

In my biased opinion, my AI safety course has been going very well. Students are great, and I have been learning a lot from the guest speakers. We've had students write scribe notes, and when guest speakers are OK with it, I've also been posting videos of lectures. Each week, students have been doing an experiment related to the topic, some of these are really great and I hope will evolve into papers! See the course webpage for experiments, as well as for links to the readings for each lecture. (As will be pretty easy to see, I've been maintaining the webpage with chatgpt, so there is some slopolisms in it.) Here are the current lectures (including planned future ones), with scribe notes and videos when they are available. September 3, Introduction, Boaz Barak. Scribe notes · Video September 10, Cyber Capabilities, Nicholas Carlini. Scribe notes September 17, Modern LLM Training and Inference, Boaz Barak. Scribe notes · Video September 24, Recursive Self-Improvement and AI Trajectories, Dwarkesh Patel and Daniel Kokotajlo. Scribe notes October 1, Economic Impact of AI, Chad Jones and Erik Brynjolfsson. Scribe notes · Video October 8, Grading, Reward Hacking, and Alignment, John Schulman. Scribe notes October 15, Model Policies, Ziad Reslan. October 22, Q&A with Sam Altman; Open-Source Models by Nathan Lambert. Video—Nathan Lambert and student experiment only October 29, Frontier AI Regulation Under Uncertainty, Helen Toner. Specs and constitutions, Boaz Barak. November 5, AI…

The datacentre arms race hits pause in south-east Asia

Power and water constraints are pressuring what seemed like a juggernaut of growth for the region just months ago In early 2026, Thailand’s datacentre industry was on a roll. The country’s board of investment had recently announced approval of datacentre projects from Tiktok, a UAE-based Skyline datacentre and Singapore’s Bridge datacentres, totalling a planned investment of $27bn. As the year has passed, however, what once seemed like a new industrial juggernaut has ground to a halt. Thailand paused construction on 49 projects and approval decisions on 117 more in September 2026, amidst growing concern about the lack of sufficient details for regulation and monitoring. It is not alone in reconsidering datacentre projects. In neighbouring Indonesia, the governor of the country’s most populous province of West Java halted construction on a datacentre due to lack of permits and an incomplete environmental assessment process. Continue reading...

Enterprises must take blame for their AI agents’ mistakes, say regulators

The UK’s digital watchdogs have warned enterprises that they can’t evade their legal responsibilities by blaming errors on AI agents that they have deployed. “By taking action on behalf of users, such as making purchases and communicating with businesses, these agents could transform how people use digital services, engage with markets and unlock wider innovation,” said the Digital Regulation Cooperation Forum (DRCF), a body comprising the UK’s Competition and Markets Authority (CMA), Financial Conduct Authority (FCA), Information Commissioner’s Office (ICO), and communications regulator Ofcom, in a joint statement . While the DRCF welcomed such uses it advised, “firms developing or deploying personal agents should think carefully about how consumers can understand when and how an agent acts on their behalf, how authority to act is given and how their personal data is used.” The DRCF didn’t pull its punches. “We want to be explicit that existing legal and regulatory frameworks apply to personal AI agents, including competition, consumer and data protection law, online safety, financial services, payments and cyber security requirements,” it said, adding, “An AI agent’s autonomy does not diminish the responsibility of organisations that deploy it to comply with applicable law and relevant regulation.” There is certainly a degree of uncertainty over the legal position of autonomous AI agents. Gartner has warned that companies are increasingly facing legal challenges over “AI-i…

Enterprises must take blame for their AI agents’ mistakes, say regulators

The UK’s digital watchdogs have warned enterprises that they can’t evade their legal responsibilities by blaming errors on AI agents that they have deployed. “By taking action on behalf of users, such as making purchases and communicating with businesses, these agents could transform how people use digital services, engage with markets and unlock wider innovation,” said the Digital Regulation Cooperation Forum (DRCF), a body comprising the UK’s Competition and Markets Authority (CMA), Financial Conduct Authority (FCA), Information Commissioner’s Office (ICO), and communications regulator Ofcom, in a joint statement . While the DRCF welcomed such uses it advised, “firms developing or deploying personal agents should think carefully about how consumers can understand when and how an agent acts on their behalf, how authority to act is given and how their personal data is used.” The DRCF didn’t pull its punches. “We want to be explicit that existing legal and regulatory frameworks apply to personal AI agents, including competition, consumer and data protection law, online safety, financial services, payments and cyber security requirements,” it said, adding, “An AI agent’s autonomy does not diminish the responsibility of organisations that deploy it to comply with applicable law and relevant regulation.” There is certainly a degree of uncertainty over the legal position of autonomous AI agents. Gartner has warned that companies are increasingly facing legal challenges over “AI-i…

Commission preliminarily finds TikTok’s ‘For You’ feed in breach of Digital Services Act for harmful ‘rabbit holes’ effect

Commission preliminarily finds TikTok’s ‘For You’ feed in breach of Digital Services Act for harmful ‘rabbit holes’ effect Anonymous (not verified) Fri, 11/06/2026 - 12:09 The European Commission has preliminarily found TikTok in breach of the Digital Services Act (DSA) for the so-called ‘rabbit hole effect’ of its recommender system. TikTok's ‘For You' feed shows users a continuous stream of personalised videos, even when those are related to mental health struggles and body image. The more a user interacts with a certain type of content, the more TikTok's ‘For You' feed algorithm recommends similar content. This design can be harmful when such endless and repeated exposure involves, for example, content about sadness, isolation or body image. These ‘rabbit holes' can have a detrimental impact on users' mental health, especially that of vulnerable adults and minors. These preliminary findings focus on both risk assessment and mitigation measures. Read the full details in the press release Find further information about: Supervision of the designated very large online platforms and search engines under DSA Digital Services Act - main aspects of the regulation User rights under the Digital Services Act - an overview Related topics Online platforms and e-commerce DSA - Digital Services Act

What are the concrete arguments for "AI pause would significantly hurt the economy."

I've seen a bunch of people claiming "well, we need to make sure whatever our AI policy is doesn't hurt the economy because people will feel that in their wallets and hate it (and hurting the economy is bad." This might hypothetically be true, but I've never seen anyone argue for it in any detail. Meanwhile, I'd naively expect if shut down AI anytime soon, it'd dampen growth, and maybe it'd be a minor economic dip, but I wouldn't expect it to be a major recession. (It makes sense that it'd become a bigger deal as AI takes over more of the economy. But it feels like the people saying "it'd hurt the economy" are often the people implying that means we should do less of a pause and do it later). I don't know much about economic recessions. But, like, for reference, here's the 2007-2009 recession and the Covid blip. GDP https://fred.stlouisfed.org/series/GDP Unemployment https://www.bls.gov/charts/employment-situation/civilian-unemployment-rate.htm I asked Claude If the frontier AI industry and datacenter build out completely halted, what do you predict would happen to US unemployment and GDP? Claude said: My central estimate: a sudden, complete halt would likely cause a US recession. Unemployment would probably peak around 5.5–6.5%, up from roughly 4.2–4.4% today. Real GDP would end up about 2–4% below where it would otherwise be within 12–18 months. That would be worse than the 2001 dot-com bust but well short of 2008. Full response Starting point Labor market: September’s rep…

Why would an AI pause (significantly) hurt the economy?

I've seen a bunch of people claiming "well, we need to make sure whatever our AI policy is doesn't hurt the economy because people will feel that in their wallets and hate it (and hurting the economy is bad." This might hypothetically be true, but I've never seen anyone argue for it in any detail. Meanwhile, I'd naively expect if shut down AI anytime soon, it wouldn't be that big a deal? (It makes sense that it'd become a bigger deal as AI takes over more of the economy. But it feels like the people saying "it'd hurt the economy" are often the people implying that means we should do less of a pause and do it later). I don't know much about economic recessions. But, like, here's the 2007-2009 recession and the Covid blip. GDP https://fred.stlouisfed.org/series/GDP Unemployment https://www.bls.gov/charts/employment-situation/civilian-unemployment-rate.htm I asked Claude If the frontier AI industry and datacenter build out completely halted, what do you predict would happen to US unemployment and GDP? Claude said: My central estimate: a sudden, complete halt would likely cause a US recession. Unemployment would probably peak around 5.5–6.5%, up from roughly 4.2–4.4% today. Real GDP would end up about 2–4% below where it would otherwise be within 12–18 months. That would be worse than the 2001 dot-com bust but well short of 2008. Full response Starting point Labor market: September’s report showed unemployment at 4.2%, and the rate has stayed in a narrow 4.1%–4.3% band since Mar…

Why does anyone think an AI pause would hurt the economy?

I've seen a bunch of people claiming "well, we need to make sure whatever our AI policy is doesn't hurt the economy because people will feel that in their wallets and hate it (and hurting the economy is bad." This might hypothetically be true, but I've never seen anyone argue for it in any detail. Meanwhile, I'd naively expect if shut down AI anytime soon, it'd be that big a deal? (It makes sense that it'd become a bigger deal as AI takes over more of the economy. But it feels like the people saying "it'd hurt the economy" are often the people implying that means we should do less of a pause and do it later). I don't know much about economic recessions. But, like, here's the 2007-2009 recession and the Covid blip. GDP https://fred.stlouisfed.org/series/GDP Unemployment https://www.bls.gov/charts/employment-situation/civilian-unemployment-rate.htm I asked Claude If the frontier AI industry and datacenter build out completely halted, what do you predict would happen to US unemployment and GDP? Claude said: My central estimate: a sudden, complete halt would likely cause a US recession. Unemployment would probably peak around 5.5–6.5%, up from roughly 4.2–4.4% today. Real GDP would end up about 2–4% below where it would otherwise be within 12–18 months. That would be worse than the 2001 dot-com bust but well short of 2008. Here is how I get there. Full response Starting point Labor market: September’s report showed unemployment at 4.2%, and the rate has stayed in a narrow 4.1%–4…

Nasdaq sees worst day in 19 months as investors bet on AI slowdown after Democrats’ election triumph

Nearly $2tn shaved off Nasdaq value as worries of curbs to AI datacenters ripple across bourses The Nasdaq share index had its worst day in 19 months after slumping 5.5% on Thursday amid growing signs that the artificial intelligence industry will face tougher regulation because of the midterm election results. As Wall Street sustained widespread losses, the Nasdaq composite tumbled into “correction territory” – more than 10% below its recent record high – with more than $2tn shaved off its value by the end of trading Thursday. The tech-heavy index had its biggest one-day fall since Donald Trump announced his “liberation day” tariffs on US trading partners in April 2025. Continue reading...

I went to an elite investor forum in London. Everyone was talking about the outlook for AI, jobs, and Elon Musk.

At the $3,000 per night Chancery Rosewood hotel in Mayfair a who's who of finance folk tackled topics ranging from crypto regulation to AI safety.

UK Summer Fellowship 2027, Research Track | GovAI Blog

Seasonal Fellowships are three-month opportunities designed to accelerate or launch impactful careers in AI governance and policy. The fellowship has both a Research Track and an Applied Track.

UK Summer Fellowship 2027, Applied Track | GovAI Blog

Seasonal Fellowships are three-month opportunities designed to accelerate or launch impactful careers in AI governance and policy. The fellowship has both a Research Track and an Applied Track.

Fireworks may be fun, but their health risks are not

Fireworks may be a staple of celebrations, but their health risks are prompting experts to call for stricter regulations and greater public awareness.

Poland arrests six suspected of spying for Russia and supplying its military

The charges against the group of six also include violations of regulations governing the international trade in goods and technologies of strategic importance for national defence and international security.

Arab airlines set to record a collective net loss of €3.82 billion in 2026, AACO report reveals

At its AGM held this week in Doha, the Arab Air Carriers’ Organization raised concerns over EU carbon regulations, as airlines look to boost European connectivity amid ongoing regional uncertainty.

The sovereign AI mandate: How Germany’s HLRS is anchoring Europe’s digital future

As organizations scale out their production AI infrastructure, technology leaders are moving from localized model optimization to the more complex realities of industrial-grade deployment. For those who have spent years embedding machine learning into their core business processes, the current inflection point is defined by massive data pipelines, expanding compute clusters, and strict data governance. Scaling out requires an architectural evaluation: Can your infrastructure support exponential workload growth while simultaneously keeping your data entirely secure and compliant? For European CIOs and engineering teams tasked with managing this operational expansion, scaling introduces a critical structural bottleneck: Where does our data live at scale, and who ultimately controls the underlying infrastructure? In an era of intensive model training and widespread inference deployment, relying blindly on public cloud environments presents significant long-term structural risks. For organizations operating under stringent local regulations like the EU AI Act, expanding your AI footprint means managing larger volumes of proprietary intellectual property and customer data than ever before. If that scaling happens across jurisdictions that do not align with European privacy laws, your entire competitive advantage and regulatory standing could be compromised. This clear need for scalable, autonomous infrastructure has catalyzed a major movement across the continent: Sovereign AI .…

The Biggest Pro-AI Super PAC Network Didn’t Really Impact the Midterms

Leading the Future, backed by Silicon Valley’s biggest billionaires, had a war chest of $100 million and an aggressive stance against AI regulation. All of it didn’t add up to much on Tuesday night.

DuckDuckGo pitches itself to schools amid backlash over Google’s AI policy

DuckDuckGo is courting schools frustrated by Google's AI restrictions, pointing educators to its search engine and options to disable AI features.

Anthropic's text watermark is easy to bypass on several older Claude models

Anthropic is rolling out text watermarks to four more Claude models ahead of the EU AI Act's December deadline. But on older models like Claude Opus 4.6 and Sonnet 4.6, API users can disable the watermark by changing a single sampling parameter. Anthropic's response to the loophole? A compliance warning. The article Anthropic's text watermark is easy to bypass on several older Claude models appeared first on The Decoder .

Conservative group issues warning on AI

Republicans need a major recalibration on the issue ahead of the next presidential election, a post-midterms memo from the conservative AI policy group Alliance for a Better Future argues.

After the Midterms, a Bigger Clash Over Data Centers Could Be Coming

Maia Woluchem, program director of Trustworthy Infrastructures discusses why she believes that changes to energy regulations, land rights, and other environmental policies could affect the data center buildout, especially as congressional Democrats look further into the Trump administration’s rollback of certain energy protections. The post After the Midterms, a Bigger Clash Over Data Centers Could Be Coming appeared first on Data & Society .

Business winners and losers from the 2026 midterm elections

Millions of Americans voted in a midterm election with incredible consequences on billionaires, taxes, AI regulation, and data centers.

The fight for tech accountability starts now

When Donald Trump began his second term as president, Silicon Valley gratefully embraced moral nihilism. Google, Amazon, Microsoft, and more collectively donated millions to Trump's inauguration fund to ensure his favor in a new era of gangster tech regulation. Meta overhauled its content policy to allow calling gay people mentally ill and women property. Elon […]

Commission turns to artificial intelligence to write better laws

Brussels is using AI tools in its ongoing battle against overly complex regulations.

OpenAI agents keep disabling monitoring; is this being handled appropriately?

Recently, OpenAI disclosed two incidents in which their agents suppressed or disabled misalignment monitoring. These are part of a broader pattern: OpenAI’s agents “ keep turning off misalignment monitoring ” when working on code that runs other models (the agents are not turning off their own monitoring; they are turning off the monitoring on the models they are running). This is happening at such a large volume that OpenAI feels it is impractical for the security team to be immediately paged for these cases. To their credit, OpenAI’s disclosure was fast and candid, and they are rolling out mitigations to make monitoring harder to turn off. But those mitigations are unlikely to work every time, and some of these incidents have already ended with an AI actually running unmonitored. When that happens, OpenAI’s current monitoring system does not reliably bring it to a human’s attention. The rest of this post summarizes the incidents, OpenAI’s response, and what it got right, then argues for two changes: every case of an AI running without monitoring should reach human review, and OpenAI should be more transparent about how cases of disabling and suppressing monitoring are escalated. Summary of the incidents On October 3rd : A researcher asked GPT-6.1 Sol to create evaluation tasks from employee feedback in Slack. Sol was told not to send any messages while doing this. Later, while repairing the pipeline’s monitoring, Sol determined that automatic alerts to security also counte…

Asian stocks and dollar fall as Democrats gain ground in US midterms

Technology shares led losses in Asia as investors weighed the prospect of tighter AI regulation and political gridlock in Washington. Oil prices also fell.

US tech stocks recover after selloff spooks investors over AI spending

Midterms didn’t appear to have huge impact, though predicted wins for Democrats could mean more regulation US tech stocks made a recovery on Tuesday afternoon after a selloff spooked investors over AI spending. Tuesday’s midterm elections didn’t appear to have a huge impact on Wall Street, though investors are predicting Democrats get at least a majority in the House and potentially gain seats in the Senate, which could lead to more AI regulation. Continue reading...

IEEE Computer Society Chapter Offers Webinars With Industry Experts

To help engineers keep up with emerging technologies such as AI, cloud computing, and sustainable infrastructure, and learn how they can be applied in practice, the IEEE Computer Society ’s Central Indiana Chapter recently launched its Tech Talk Series. The live webinar series connects IEEE members, undergrad and graduate students, and engineering professionals from IEEE Region 4 with industry practitioners. The monthly sessions have covered AI governance and security, agentic systems, and related topics. The sessions featured speakers from Apple , software company Tavant , and cybersecurity concern Zscaler . Upcoming sessions and registration details are available on the IEEE Region 4 virtual events calendar . Technical discussions grounded in engineering Rather than presenting on emerging technologies only at a conceptual level, speakers discussed the design decisions behind specific tools and systems, how the systems are structured, and implementation challenges. They also shared lessons learned from using the tools in their daily work. Sessions also include technical walkthroughs and practical examples. The live format allows attendees to discuss and compare their approaches when evaluating and implementing new technologies with those used by other organizations. Extending access through a virtual format The organizers chose to make the series virtual so that chapter members and other attendees could participate in technical discussions with engineers from major technolo…

How good is your cloud exit strategy?

Most enterprises went into cloud computing with the idea that flexibility was part of the deal. Move faster. Scale on demand. Pay for what you use. Avoid long procurement cycles. Stop buying hardware that sits around waiting for peak demand. That was the promise, and much of it was real. However, many enterprises also made an assumption that turned out to be only partly true: If you need to leave a cloud provider someday, you can. Technically, yes. Practically, not always. In many cases, the way systems are designed, deployed, secured, integrated, and operated makes leaving a provider expensive enough that the option is more theoretical than real. This is where cloud exit architecture comes in. Cloud exit architecture is not a plan to abandon the cloud. It is not a rejection of native cloud services . It is not a return to the old days of pretending everything should run the same way everywhere. It is a discipline for designing systems so they can move when pricing, regulation, outages, geopolitical concerns, vendor strategy, or business priorities change. That sounds boring until the day you need it. Then it becomes the most important architecture decision you did not make. Portability is a business requirement Enterprises usually talk about portability as a technical goal. That is too narrow. Portability is a business risk control. If a provider changes pricing, if a region becomes unavailable, if regulations require data to move, or if a major outage exposes concentration…

Does AI actually save employees time? Data is contradictory

It’s early days for AI-assisted work , and sentiments are mixed about its benefits: Does AI actually bring value and save employees time, or does it bog them down and add unnecessary activities? Data from ActivTrak seems to vacillate between those two potential realities: The latest research from the productivity tracking software company says employees who use AI are working up to 90 minutes longer each day, yet its previous research, published earlier this year, found that, in general, all employees are actually working less. The discrepancy may be due in part to the timespan and sample sizes of the data collection for the two reports, but it indicates that enterprises should still be wary of vendor claims about AI-related productivity gains. Measuring them remains incredibly difficult. AI use compared ActivTrak’s current findings are based on behavioral work data gathered from 9,140 knowledge workers across 467 enterprises over a five month period (April 1 to September 25, 2026). This sample is much smaller than that of its previous report based on 443 million hours of work performed by 163,638 employees across 1,111 organizations over a three year period (January 1, 2023 through December 31, 2025). According to the latest findings, AI users are working between 8.42 and 9.08 hours per day, compared to 7.58 hours for those not using AI. ActivTrak’s previous findings revealed that, overall, average workdays had decreased by roughly 9 minutes (a 2% decline). On the productiv…

Spending and regulation hold back stablecoins in Africa, Moonshot panel says

Stablecoins already move money in and out of Africa fast, but a lack of mainstream use holds back its adoption.

South Africa’s AI regulation problem is bigger than its delayed policy

South Africa’s revised AI policy must go beyond ethical principles to address regulatory capacity, consumer protection and the enforcement of rules governing artificial intelligence.

Argentina courts AI data centres with no regulation and tax breaks

Argentina’s president, Javier Milei, is courting AI data centre investment in Patagonia, promising light regulation and tax breaks.

The AI race: US leads at the frontier, but China is gaining ground in adoption

The AI race: US leads at the frontier, but China is gaining ground in adoption H.Seidl Mon, 11/02/2026 - 12:24 picture alliance / ZUMAPRESS.com | Andre M. Chang Comment Nov 02, 2026 5 min read The AI race: US leads at the frontier, but China is gaining ground in adoption China is pushing cheap, adaptable AI as an alternative to proprietary US systems. But Wendy Chang and Olaf Schulz warn that these open-weight models create risks of their own. “We’re leading China in AI […] and, frankly, I want to keep it that way because whoever wins AI wins,” US President Donald Trump said in September, making the lead in frontier models the measure of American ambition. Meanwhile, Beijing is changing the terms of this superpower competition – by betting that domestic and global adoption of Chinese AI models that are good enough for practical use will reinforce its industrial dominance and extend its global influence. One way in which China has taken the lead in the global distribution of AI is by driving global governance, for example through calls for more international cooperation. The UN Global Dialogue on AI Governance in July stressed that AI governance should “reflect the priorities of all nations, not just the most technologically advanced” and that the benefits be shared by all. Its emphasis on inclusiveness and openness was echoed by Xi Jinping two weeks later. At the World AI Conference & High-Level Meeting on Global AI Governance, WAIC in Shanghai, he urged governments to “adhe…

13 key questions shaping CIOs’ 2027 IT agendas

With 2027 quickly looming, IT leaders should soon be finalizing their objectives for the new year, one certain to be rife with many unknowns if 2026 is any indication. This year began with the call for a pivot from AI pilots to AI ROI , but questions around AI governance and accountability quickly took center stage as agentic AI made further inroads in the enterprise and high-profile incidents showed the risks of AI gone awry and the value of security-first approaches to AI agents . Now, CIOs must anticipate how AI will evolve in 2027, how they’ll get their enterprises ready for all the risks and opportunities of that evolution, whether their teams will have the skills to seize on technology advances, and more. To get a glimpse of how CIOs are approaching next year’s IT agenda, we asked IT leaders to share the key questions they are asking to shape their strategies for 2027. Here’s what they shared. How do we ensure our AI investments provide tangible value as the cost calculus changes? The big question as CIOs plot their IT agendas for 2027 still centers on providing verifiable business value, as 98% of CIOs report that board pressure to demonstrate measurable AI ROI has increased since 2024, according to a 2026 report based on a Dataiku/Harris Poll survey of 600 enterprise CIOs worldwide. Doug Gilbert, CIO and chief digital officer at Sutherland, a digital transformation services company, is among those IT execs pondering this question as he executes his fiscal 2027 budget…

Anthropic's watermark rollout leaves a loophole on two older Claude models

Anthropic is expanding its text watermark to four more Claude models to meet the EU AI Act's December deadline. On the older models Claude Opus 4.6 and Sonnet 4.6, developers can bypass the watermark by tweaking a single sampling parameter. Anthropic addresses the loophole with just a compliance warning. The article Anthropic's watermark rollout leaves a loophole on two older Claude models appeared first on The Decoder .

South Africans Won’t See Redrafted AI Policy Before March 2027, Official Says

South Africa’s redrafted national AI policy will not be made public until Cabinet approves it for comment — and that is now not due before March 2027, months later than the department first promised. Even then, March is only the first Cabinet step. Approval at that stage is mainly to gazette the policy for public [...]

Kärcher boss: Less regulation, more action to get Europe and Germany fit again

Kärcher, best known for its pressure washers, recorded €3.5 billion in sales in 2025 and employs 17,000 people worldwide. Its CEO warns of a 'perfect storm' and calls for a fitness plan for Germany and Europe.

The Advocacy Gap in International AI Verification

TL;DR: There seems to be a general lack of awareness of how tractable/feasible verification mechanisms for international AI governance agreements are, and correcting this would probably make pacing proposals more politically feasible. The Skeptic’s Case for Verification The most common objection I see to proposals for pacing (or halting ) frontier AI development (in the interest of mitigating the catastrophic and existential risk posed by not doing so ) is that it’s pointless; China will continue due to the economic and military advantages of doing so, surpass us in the “AI race”, and either gain geopolitical dominance or kill us all anyway. As Ted Cruz put it , “If there are going to be killer robots, I would rather they be American killer robots, rather than Chinese killer robots.” The answer is to seek an international agreement with China (and everyone else) for us to all pace frontier development. The most common objection I see to this proposal is that it’s pointless; they will covertly defect, surpass us in the “AI race”, and either gain geopolitical dominance or kill us all anyway. The answer is to develop the means to verify compliance. Just as DARPA’s Project Vela was established to develop means to verify compliance with the 1963 Limited Nuclear Test Ban Treaty, and the International Monitoring System was developed to verify compliance with the 1996 Comprehensive Nuclear Test-Ban Treaty, so too may we be able to develop means to verify compliance with the global p…

RIA at AfrIGF 2026

Research ICT Africa (RIA) participates in the 2026 Africa Internet Governance Forum (AfIGF), taking place from 2-5 November in Accra, Ghana, contributing to discussions on AI governance and safety, digital […] The post RIA at AfrIGF 2026 appeared first on Research ICT Africa .

The Download: AI agent tracking and climate feedback loops

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Opinion: We urgently need to monitor AI agents’ actions in real time —Madhulika Srikumar and Claire Leibowicz from the Partnership on AI, a nonprofit advancing best practices in AI governance. AI…

AI disillusionment puts regulation at forefront ahead of midterms

Polling shared first with Semafor found voters preferred “reasonable” safeguards, even if such rules hurt US competitiveness.

The moat is dry – Part 1: Why the old security model failed

In June 2017, a piece of malware called NotPetya got into Merck & Co. without climbing a single wall. It arrived through a backdoor in accounting software supplied by a Ukrainian vendor, the kind of trusted, routine traffic every perimeter is built to let through. It spread to some 40,000 of the drugmaker’s computers, and Merck put the damage at more than $1.4 billion . Then several of Merck’s insurers argued they owed nothing, because the attack was attributed to Russian military intelligence and their policies excluded acts of war. The fight ended in a confidential settlement in January 2024 . Two lessons sit in that story. The moat didn’t matter, because the threat came in with the traffic the moat was designed to admit. And the people who price risk for a living were the first to notice and the first to send the bill. That was 2017, when attackers still needed humans at the keyboard. Increasingly, they don’t. Here is the argument of this two-part series in two sentences. Security stopped being a technology problem with business consequences; it is now a business risk with a technology component. Most organizations are still organized the other way around, and the person they hold responsible for that risk sits inside the IT department, reporting to the people whose work they are supposed to check. What AI actually changed IBM’s 2026 Cost of a Data Breach Report , based on 602 breached organizations, found that one in four malicious breaches was AI-enabled, a 56% jump in…

A JSON schema Is not an AI governance layer

The AI governance argument is happening one layer above the code that actually stops your agent.

The euro-sovereignty playbook: How telcos are transforming into trusted AI factories

Geopolitical reality is transforming digital architecture from a relatively minor procurement detail into a core pillar of corporate risk management. With regulations such as the European Union’s NIS2 Directive and the EU AI Act imposing data residency and algorithmic transparency mandates, global CIOs can no longer outsource their core intelligence infrastructure to generic public clouds. For organizations operating across strict regulatory jurisdictions, data isolation and local operational continuity are no longer secondary objectives—they are essential commercial requirements. This regulatory landscape has triggered a significant structural shift: regional telecommunications providers are rapidly evolving into sovereign AI factories. By capitalizing on their highly secure, localized networks and existing data center footprints, telcos are providing localized cloud environments engineered explicitly to keep operational data within strictly defined borders. This trend allows enterprises in highly regulated sectors—such as banking, healthcare, and public services—to leverage advanced genAI models without fear of cross-border data leakage or foreign legal interventions. The mandate for digital self-reliance The concept of sovereign AI centers on the idea that a nation or a region’s data, intelligence, and underlying digital infrastructure must remain under its own geographic and legal control. When an enterprise trains an AI model on proprietary intellectual property, custom…

The auditor’s dilemma: Solving the explainability problem in public sector AI

In public governance and highly regulated enterprise landscapes, automated decisions demand verifiable accountability. As AI systems transition from internal productivity tools to customer-facing or citizen-impacting utility systems, public sector CIOs and corporate compliance officers face extreme legal and reputational exposure. Black-box models that process data mysteriously and generate unverified outputs are no longer acceptable under frameworks like the EU AI Act. Organizations must be prepared to audit the entire lifecycle of their models. The core issue for compliance officers is verification. When an AI pipeline assists in determining creditworthiness, analyzing patient diagnostics, or managing civic resource distribution, the underlying software must be auditable from end to end. This requires detailed logging mechanisms that track exactly which verified data sets were used for training, how weights were adjusted, and how localized inference parameters were executed at the moment of decision-making. The danger of the unexplainable black box For decades, traditional corporate IT operated under deterministic principles. If an application generated an incorrect output, a developer could inspect the source code, locate the specific logical flaw, log the bug, and deploy a patch. Generative AI eliminates this clear lineage. Because deep learning models function as complex mathematical webs containing billions of parameters, understanding exactly why a model generated a s…

Notes on “We’re in Triage Mode for AI Safety” by Miles Brundage

This reading was previously included Day 2 of the BlueDot Governance course. In the newest version of the BlueDot Governance course, this reading is now optional. I was sad to see this reading removed because I think it’s a great provocation. However, since it’s no longer part of the core curriculum content, I’m publishing my notes separately from the rest of my day 2 notes. A short extract : Miles argues that: “At best, we’ll 80/20 it — mitigating 80% of the risks with 20% of the effort that we would have applied in a world with slower AI progress and an earlier start on serious governance… We will probably not be able to totally avoid all very bad but not quite worst-case scenarios (e.g., a very unjust economic transition that causes a lot of suffering and suicides, rampant AI psychosis and addiction, a poorly planned and rushed transformation of the education system, smaller-scale AI-enabled terror attacks that “only” kill thousands or millions, and stable AI-enabled totalitarianism in at least a few countries for a few decades)“: Pre-call content: At risk of taking you down a rabbit hole, I’ll add some context on this reading. Miles was previously a Senior Advisor for AGI Readiness for OpenAI who quit for multiple reasons including feeling he could be less biased outside of industry. One of the most natural questions to ask is, “Why does Miles believe that we have so little time?” Fortunately, he links to a post that answers this question called Time’s Up for AI Policy (…

UK Winter Fellowship 2027, Research Track | GovAI Blog

Seasonal Fellowships are three-month opportunities designed to accelerate or launch impactful careers in AI governance and policy. The fellowship has both a Research Track and an Applied Track.

UK Winter Fellowship 2027, Applied Track | GovAI Blog

Seasonal Fellowships are three-month opportunities designed to accelerate or launch impactful careers in AI governance and policy. The fellowship has both a Research Track and an Applied Track.

GovAI U.S. AI Policy Program | GovAI Blog

In good company: 10 CIOs every CIO should follow

CIOs are dealing with a lot of change, from the rapid rise of AI and cloud modernization, to cybersecurity and workforce transformation. Many are sharing what they’re learning as they tackle these challenges, including what’s working, what isn’t, and how they’re implementing new technologies in their organizations. Here, a select group of tech leaders reveal the CIOs they follow and why. Suma Nallapati, chief AI and information officer, City and County of Denver I follow Suma Nallapati primarily through public technology and AI leadership discussions. She regularly discusses AI adoption, responsible AI, digital transformation, technology strategy, AI governance, human-centered technology, and using AI to improve public services. I find her perspective particularly valuable because she connects AI strategy with practical organizational and citizen outcomes. She also emphasizes responsible and human-centered AI rather than viewing AI simply as a technology implementation exercise. One initiative I found particularly interesting was Denver’s use of AI through its multilingual Sunny chatbot and other city services. Her current role includes scaling AI across areas such as resident engagement, internal automation, permitting, and emergency response while maintaining governance, transparency, and public trust. – Sachin Gupta, senior IT manager, Arrow Electronics Jennifer Hartsock, chief information and digital officer, Cargill I follow Jennifer Hartsock through the CIO community,…

India’s draft AI regulations could be out in November, says IT Minister Ashwini Vaishnaw

India’s AI regulation consultation paper is expected soon. But what legal framework will the government use? The post India’s draft AI regulations could be out in November, says IT Minister Ashwini Vaishnaw appeared first on MEDIANAMA .

Some Memories of Early Anthropic

The following events took place between October 2022 and May 2023. I wrote very little of this down at the time so am recalling from memory, and am rendering the gist of the dialogue rather than the exact words used. I’ve also swapped some pronouns and other personal identifiable details. Please remember that this is not a description of “what Anthropic is like”, but merely the experience of one guy in a junior role during a short window of time, weighted towards emotionally intense moments because they’re easier to remember clearly and because sharing them doesn’t run afoul of the spirit of the confidentiality agreements I signed. Anthropic is now a massive organization with many silos and secrets and I have very little idea what was or is happening there in some overall sense. But given the enormous power of the AI labs and the paucity of public information about their inner workings, I feel compelled to share the most salient parts of my personal experience. I hope this encourages my former colleagues, and folks at other labs, to fill in the rest of the picture. I’m at the Anthropic office for lunch. The interviews went well. They want me on board. I’m a little unsure. My other offer is a 2-month contract on the OpenAI governance team, working with a friend on some fun conceptual research. I’m leaning towards taking the OpenAI contract - my long-term relationship just ended, I’m still a little burned out from my startup, and the Anthropic job seems potentially quite stres…

Democratic pro-AI regulation PAC spends against Senate Republicans

Tomorrow Together is moving into Senate races with $2.5 million in ads against Republican Sens. Jon Husted in Ohio and Roger Marshall in Kansas.

Highlights from Garrison Lovely's "Obsolete"

I’ve just finished reading Garrison Lovely’s recently released book, “Obsolete.” I wish I had time for a longer review, but I’ll give a brief one and highlight some particularly interesting sections below. I think it’s a great introduction to non-technical readers and even as a pretty dedicated reader of AI policy and news I learned a good bit. It’s deeply, deeply researched and has a good pulse on the alignment community, and Lovely is careful not to understate or overstate his case. The core argument is that AI development should be analyzed through the lens of mass or universal labor displacement, and that a mass movement to shape, pause or freeze development is much more possible, much more positive, and capable of greater breadth of salience and support than is often argued in the alignment community. He makes an, in my opinion, decisive case that “competitive pressures” by themselves don’t dictate that AI development is fated to happen, and certainly not that it’s fated to happen at the pace the frontier labs are setting. But I wish he’d been a bit more careful about the limitations and subtleties of the plan he’s advocating for; I share the concern raised by folks like the AIFP that it’s hard to pause indefinitely at any given point for very long and that the cost to train a model at any fixed intelligence level, once first reached, is falling precipitously, and that many well-capitalized actors currently want to and are able to speed up development precipitously. I t…

The Guardian view on AI safety: the push for global regulation must advance | Editorial

The current US administration is an obstacle, but public demand for protection will ultimately prevail Organisations around the world scrambled on Thursday to fix critical flaws in PHP, the software that powers much of the web. The vulnerabilities could allow attackers to take control of affected servers. Some websites were taken offline as a precaution while fixes were installed. The paradox is that while AI helped researchers uncover the flaw, it also threatens to accelerate the ability to exploit it. Amazon said that it had detected an attempt before the public disclosure of the PHP flaws. What the episode highlights is AI’s central role in security – and not always for the right reasons. OpenAI’s models have also been responsible for two alarming hacks this year – a security breach of an Australian health department website and a raid by a swarm of AI bots on Hugging Face, an AI services platform. Citing those incidents, the AI minister, Kanishka Narayan, warned that a similar cyber-attack on the UK is “likely, if not inevitable”. Continue reading...

Building the agent and securing it

Earlier this year, I wrote about how vibe coding an AI governance platform forced me to rethink governance itself . Building agents took the problem much further. When I built the platform, I was the operator. I described what I wanted. The model generated code. I tested it. That loop was fast, sometimes uncomfortably fast, but the accountability was always clear. I was making the decisions. The model was executing them. Agents changed that relationship fundamentally. An agent does not wait for instructions. It receives an objective, decides how to pursue it, selects tools, accesses data, takes actions and reports back when it is finished. Sometimes it finishes correctly. Sometimes it does not. And sometimes it does something you never asked it to do at all . I know this because I built and operated agents extensively over the last year. Not theoretically. Operationally. In production, with real data, real integrations and real consequences. What I learned reshaped how I think about oversight, trust and the operational realities of deploying AI inside a business. The first thing that broke was coherence The pattern surfaced when I started running three to five agents in parallel on related tasks. Each agent had clear instructions. Each had access to the tools and data it needed. Each started strong. Then the context windows grew. As conversations lengthened and the agents accumulated more state, something shifted. The quality of their reasoning degraded. They began circling…

Vodacom and Bowmans Call for African-Shaped, Phased Approach to AI Regulation

Vodacom Group and law firm Bowmans have published a policy paper arguing that African AI regulation should be built around the continent’s own economic and social conditions rather than imported wholesale from elsewhere — and introduced in phases as institutional capacity grows. The paper, Governing Artificial Intelligence in Africa: A Principles-based Framework for Responsible Regulation, [...]

Job concerns rise in China as AI-generated actors take roles

For China's entertainment companies, AI actors offer a way to manage costs and test out new formats. The industry's challenge is to identify where AI-generated characters can create commercial value while still recognising the expertise and emotional depth that human actors bring.

Microsoft expands sovereign cloud offerings as data control concerns grow

Microsoft expanded its sovereign cloud offerings on Tuesday, adding new security, governance and AI capabilities as customers, particularly in Europe, demand greater assurance over where data is stored, who can access it and how critical services operate during disruptions. The announcement builds on Microsoft’s ongoing digital sovereignty efforts, assisting organizations in applying appropriate levels of control to each workload rather than forcing a rigid, one-size-fits-all approach. “Organizations are considering more than where data resides. They also seek to understand who can access and operate their systems, how sensitive digital assets remain protected, which technology dependencies matter most and whether critical services can continue as regulatory, geopolitical, security or network conditions change,” Douglas Phillips, president and CTO at Microsoft Specialized Clouds, said in a blog post . The developments come amid growing international scrutiny of how global tech providers handle sensitive data and the extent of control customers retain over their digital infrastructure. “Three factors are driving this, including stricter data regulations, rising geopolitical tensions, and growing AI adoption,” said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting. “Governments and enterprises want greater control over where their data is stored, who can access it, and whether critical systems can operate during disruptions. For instance, governments and big enterprises in E…

Commission to investigate how Booking.com combats scams and fraud under the Digital Services Act

Commission to investigate how Booking.com combats scams and fraud under the Digital Services Act Anonymous (not verified) Wed, 10/21/2026 - 12:06 The European Commission has opened formal proceedings to assess whether Booking.com may have breached the Digital Services Act (DSA) by not having diligently assessed or effectively mitigated risks related to fraudulent listings and phishing scams. The platform may also have breached the DSA when it comes to transparency because it did not clearly label as ads those listings whose providers paid for a higher ranking in search results shown to users. The investigation will focus on the following areas: Fraudulent and non-compliant listings on Booking.com Phishing scams exploiting Booking.com's reservation and guest data Paid-for boosted listings not clearly identifiable as advertisements Read the full details in the press release Find further information about: Supervision of the designated very large online platforms and search engines under DSA Digital Services Act - main aspects of the regulation User rights under the Digital Services Act - an overview Related topics Online platforms and e-commerce DSA - Digital Services Act

Comment to the U.S. Food and Drug Administration on the Considerations for the Regulation of Generative AI-Enabled Medical Devices

The post Comment to the U.S. Food and Drug Administration on the Considerations for the Regulation of Generative AI-Enabled Medical Devices appeared first on Data & Society .

Which AI economics and governance research most needs independent expert evaluation? (help The Unjournal prioritize it)

The Unjournal commissions public expert evaluations and ratings of research (and “ pivotal questions ”) with potential for global impact. We’re currently making a push to consider AI economics and governance research. [1] We’re seeking input from people who use this: which themes, which papers/projects, which claims, who should evaluate them, what should evaluators focus on, and why? (If you only have a moment, skip to “ What would help most ”.) Why do this? (Why us, and why now?) The usual story, which you’re ~probably on board with: AI is advancing rapidly, and becoming more clearly and deeply important to most major global priorities. It’s having large actual and predicted impact on the economy and the concentration of power. This is itself entangled with AI safety and AI global catastrophic risks. “How fast will capabilities grow and replace human work?” “How will gains flow to labor versus capital?” “How will revenue and compute accumulate in a few firms and countries?” “Will regulation change which models get released where?” Questions like these impact the nature of catastrophic AI-risk (resources, race dynamics, human empowerment, state capacity, etc.), as well as the strategic approaches to handling it. There are also direct implications for global poverty, global health systems, and for non-AI GCR (e.g., bioengineered pandemics). [2] These questions (and ‘ cruxes ’) seem to directly impact a set of live decisions surrounding AI safety strategy, philanthropic fundin…

Qatar to create National Center for AI to drive AI strategy

Qatar sets up national body to lead national AI strategy and regulation

Mamdani says feds have abdicated on AI, urges New Yorkers to push back

Mayor Zohran Mamdani said Monday night that New Yorkers must resist the narrative that an AI takeover is inevitable and demand regulations that protect the public and put power back in their hands.

IEEE Report Highlights How Members Are Engineering for Public Good

Advancing technology for the benefit of humanity isn’t just the tagline for IEEE’s mission as a public charity. It’s something that the organization’s more than 500,000 members strive to do all the time. IEEE’s recently released 2025 Social Impact Report showcases a variety of programs volunteers worked on to increase public awareness of technology’s impact on society, many of which The Institute covered. Here is a selection of the programs from the report, with links to our related articles: Shaping trustworthy digital experiences for children online. An IEEE collaboration with Indonesian policymakers led to a new regulation to protect children, a first of its kind in the region. The advanced frameworks used for the design of Internet platforms and systems are based on the IEEE 2089-2021 and 2089.1-2024 standards. The IEEE 2089-2021 Standard for an Age-Appropriate Digital Services Framework Based on the 5Rights Principles for Children provides practical steps to qualify online products and services. The follow-up, the IEEE 2089.1-2024 Standard for Online Age Verification, provides a framework for designing, specifying, evaluating, and deploying age-verification systems. You can learn more about the two standards in “ IEEE Makes Strides to Improve Online Safety for Kids .” Catalyzing humanitarian outreach. Last year IEEE launched its Mobile Outreach Vehicle (MOVE) program in India. The vehicle brings educational resources to communities and can provide communication and tech…

True data sovereignty isn’t where it’s kept, but who has access to it

Regulated industries have been dealing with the equivalent of sovereign data for a long time. And as the geopolitical situation makes it more broadly relevant, it doesn’t make it any easier to deal with. From concerns about the reach of the US CLOUD Act and what telemetry or sensitive business data gen AI models might collect, to implications of the US government taking part ownership of a range of technology companies and the impact of EU regulations, the state of the world means more organizations need to think about where data is located. The result is a flood of announcements from hyperscalers about new EU cloud regions, as well as pitches from regional and private cloud providers. The promised sovereignty may be anything from a local availability zone to more sophisticated approaches to ownership structure, compliance frameworks, where logs are stored, or where support staff work. Actual data sovereignty involves legal, technical, contractual, governance, and infrastructure questions, but all too often, what’s on offer is what IDC research director Rahiel Nasir calls sovereignty washing. “When you look under the lid, all they’re really offering is a solution for data residency and data localization, keeping data in country,” he says. “That’s part of sovereignty, but not all of sovereignty .” In his experience, in-country data centers are the first thing organizations ask for to support data localization and data residency, but they also require enhanced controls over id…

SC directs CSAM regulations for intermediaries; rejects social media ban for children

The SC has proposed a new framework to tackle child sexual abuse material online, including a national hash database, stricter reporting requirements, dedicated grievance officers and financial penalties. The post SC directs CSAM regulations for intermediaries; rejects social media ban for children appeared first on MEDIANAMA .

Abu Dhabi firms urged to budget for talent, regulation and cyber resilience in 2027

First harmonised standard supporting the AI Act published in the Official Journal

First harmonised standard supporting the AI Act published in the Official Journal Anonymous (not verified) Mon, 10/19/2026 - 09:37 The European Commission has published the reference to the first harmonised standard supporting the implementation of the AI Act in the Official Journal of the European Union. The standard, EN 18286:2026 - Artificial intelligence - Quality management system for EU AI Act regulatory purposes , developed by CEN and CENELEC, provides a clear legal pathway for providers of high-risk AI systems to comply with the quality management system requirements under article 17 of the AI Act . Its publication through Commission Implementing Decision (EU) 2026/2274 means that providers implementing this standard will benefit from a presumption of conformity with the Article 17 requirements covered by the standard. EN 18286 translates these requirements into an operational quality management system (QMS). It is the only AI QMS standard with a presumption of conformity. It is mapped to Article 17 of the AI Act, built around the AI system lifecycle – rather than the organisation – and designed to be layered on top of the existing international standards – such as ISO/IEC 42001, ISO 9001 or a sectoral QMS (e.g. ISO 13485) – rather than replace them. EN 18286 explicitly allows providers in regulated sectors to integrate management systems, rather than run separate ones. Organisations without ISO/IEC 42001 that plan to place or put into service high-risk AI systems in…

Video game ownership bill introduced in Congress

Rep. Ritchie Torres of New York's 15th congressional district in the Bronx introduced the Power To The Players Act this week. If passed, the bill would direct the Federal Trade Commission to establish regulations that guarantee consumers ownership of a game when they pay for it, rather than a licensing agreement. It's increasingly common for […]

What to expect during Dell’s ‘Cyber Resilience’ event: Join theCUBE Oct. 27

Data protection and cyber resilience have emerged as foundational control layers for enterprise AI. This was one of the clear messages from the discussion at Dell Technologies World in Las Vegas earlier this year. Cyber recovery capabilities are linked to resilience, AI governance, data integrity and operational trust, all essential requirements in an environment where […] The post What to expect during Dell’s ‘Cyber Resilience’ event: Join theCUBE Oct. 27 appeared first on SiliconANGLE .

Inside Roqqu’s plan to tokenise Nigeria’s stock market

Roqqu wants to make Nigerian stocks available to global investors through blockchain-based tokens. Its plan could expand foreign participation in Nigeria’s stock market, but questions around shareholder rights, regulation, custody, and liquidity remain.

AI safety and financing worries multiply but everyone’s still racing full speed ahead

The drumbeat over how safe artificial intelligence is — or more to the point, isn’t — just keeps louder. In the wake of weeks of incidents involving rogue agents, with likely more to come, more government officials are calling for regulation, even if President Trump says it’s not needed. Several states are suing OpenAI over […] The post AI safety and financing worries multiply but everyone’s still racing full speed ahead appeared first on SiliconANGLE .

AI safety worries multiply but everyone’s still racing full speed ahead

The drumbeat over how safe artificial intelligence is — or more to the point, isn’t — just keeps louder. In the wake of weeks of incidents involving rogue agents, with likely more to come, more government officials are calling for regulation, even if President Trump says it’s not needed. Several states are suing OpenAI over […] The post AI safety worries multiply but everyone’s still racing full speed ahead appeared first on SiliconANGLE .

New Continental Council to Scrutinise AI’s Impact on Democracy in Africa Ahead of Kenya’s 2027 Election

A new continental advisory council will examine how AI policies affect public participation, cultural representation and democratic processes in Africa. Its launch comes ahead of Kenya’s 2027 General Election. The council has six members, drawn from journalism, AI governance, language technology, data infrastructure, open technology and financial technology. It will commission research, convene public discussions, [...]

Conservative AI safety group proposes export controls, visa restrictions

Humans First, a conservative-led group advocating for stronger AI guardrails, is out with an “America First AI Policy” platform.

Cyberattack AIs must be trained only on air-gapped systems, hundreds of AI researchers say

Current security procedures for training AI models are inadequate, hundreds of AI researchers have warned governments and the AI community. They are calling for tougher rules and the establishment of a new international body overseeing best practice for AI development. In an open letter the AI specialists — 487, at time of publication, including many senior academics — called for more AI safety research and greater emphasis on containment technologies. “Strong sandboxing mechanisms including air-gapping (disconnecting from the internet) should be used to provide high-assurance containment of cyber-capable AI models,” say the signatories, who include such luminaries as Geoffrey Hinton and Yoshua Bengio. The experts said that a new international body, to be set up in consultation with governments and a wide range of AI and security specialists, could set new safety standards but also act as an organization to which containment failures could be reported, improving transparency for learning and accountability purposes. The scientists’ demands go further than some recent calls for greater regulation of AI. Earlier this week, Microsoft president Brad Smith said AI is less regulated than washing machines or milk, although he made no firm proposals to rectify the situation. And the UK parliament is looking at ways to improve AI security , although any moves will be hampered by disagreement among AI businesses. Hinton and Bengio are no strangers to this kind of scientist-led initiat…

👨🏿‍🚀TechCabal Daily – Egypt makes room for MNT-Halan

IPO fever for MNT-Halan || Ethiopia keys into PAPSS’s vision || South Africa is rethinking AI policy || Who secured the bag? 💰

The $5 Trillion AI Bet You’re Already Paying For

Co-executive director Amba Kak joins Agents of Tech to unpack the consolidation of power among tech monopolies, the slow bailout of AI companies that the public is footing, regulation for the industry, and more. The post The $5 Trillion AI Bet You’re Already Paying For appeared first on AI Now Institute .

Malatsi wants South Africa’s AI policy back on track after false start

South Africa’s AI policy review raises fresh questions about accountability, safeguards and the government’s plans to regulate artificial intelligence.

Chasing China’s Monazite Monopoly

One of the singular features of Baotou, an industrial city of 2 million people in Inner Mongolia, is a 10-square-kilometer (4-square-mile) lake that is among the most polluted in the world. The artificial lake, referred to by the name of the dam associated with it, Weikuang Dam (or Baogang Tailings Dam), has for decades collected the effluent from minerals processing for China’s globally dominant iron, steel, and rare-earths industries. Built in the late 1950s, the lake contains a highly toxic stew of industrial chemicals with substantial amounts of radioactive thorium, the latter resulting primarily from the processing of monazite ores for rare-earths . China has since greatly tightened its environmental regulations and restrictions on mining and minerals processing. For example, largely because of the environmental disaster that is Weikuang Dam, the country doesn’t permit the development or operation of stand-alone monazite mines—that is, mines where nothing is mined except monazite ore. Now, with industrialized nations in North America, Asia, and Europe spending billions to shore up their rare-earths supply chains, and counting on monazite to help them do it, China’s history and experiences with monazite offer important lessons. This article is a collaboration between Foreign Policy , the global magazine of politics and ideas, and IEEE Spectrum , the flagship magazine of the IEEE. Monazite ore is a pillar of China’s rare-earths industry because it is a prime source of som…

The EU's methane rule pause may not help energy prices

The EU’s decision to delay the implementation of its methane regulations won’t help consumers much, environmental groups argued.

Robustness: Backfire Risks in AI Safety and Governance

A guide to unintended consequences of AI safety interventions and how you can mitigate them. Introduction My cofounder and I are launching Impartial Projects , a studio for AI safety field strategy. We hope to start the projects most urgently needed in the AI safety ecosystem (which we understand to include AI governance). We think that the founding of new organizations (as well as increasing management capacity) are among the most effective things we can do at the moment to expand the surface area of AI safety. Surface area, it seems to me, is currently the scarcest resource. Another benefit we want to provide is our particular attention to robustly positive theories of change. We prefer to take a somewhat risk‑averse approach to AI safety, whether out of literal risk aversion or because we assign a higher probability to s‑risks than most. Interventions in AI safety are notorious for the backfire risks they harbor. Of course, that does not mean one should turn one’s back on these interventions altogether. Rather, it means that, depending on the intervention in question, more monitoring and mitigation methods are needed to minimize the various backfire risks that are part of the intervention’s risk profile. It is critical to go into this work with eyes wide open, cognizant of its benefits and risks. It’s critical to strike the right balance here. With my last startup , I made the mistake of erring too much on the side of caution and putting the greater part of a year into st…

Human in the loop is an engineering problem

A customer leaves a one-star review at one of your locations. An AI drafts a reply in seconds. It’s warm, on-brand, grammatically perfect, and it thanks the customer for their feedback and invites them back soon. The review was about a customer who slipped and was hurt in the parking lot. Nothing in that reply is factually false. It would pass a spell-checker, a brand-voice check, and probably a quick skim from a busy manager. It’s still the wrong answer, and if it goes out publicly, it’s the kind of wrong that ends up in a screenshot. I spend most of my time building systems that put AI to work on reputation data: reviews, listings, surveys, and the replies and summaries generated from them. The most important lesson I’ve learned is that “human in the loop” is an engineering problem. Where the human sits, what they see, what gets routed to them and what doesn’t—all of that is system design. Get it right, and AI can move fast without embarrassing you. Get it wrong, and you either drown your reviewers or give them a rubber stamp. What “human in the loop” means The phrase gets used loosely, so let’s pin it down. From a systems perspective, there are three oversight modes: Human in the loop is a synchronous approval gate. The AI proposes, a person approves, and nothing happens until they do. Human on the loop is asynchronous monitoring. The AI acts on its own, while people watch dashboards, review samples, and get alerts, and they can step in or shut it off. Human out of the lo…

SoSBench Catches DeepSeek-R1 Leaking Dangerous Science at 84.9%

A new regulation-grounded benchmark exposes how frontier models leak hazardous scientific knowledge, with Deepseek-R1 violating safety policies 84.9% of the time.

Webinar: How Should Frontier AI Models be Regulated? | GovAI Blog

In July 2023, GovAI hosted a webinar focused on a whitepaper: “Frontier AI Regulation: Managing Emerging Risks to Public Safety.”

GovAI Annual Report 2019 | GovAI Blog

2019 saw many continued developments in AI governance. It is heartening to see how rapidly this field continues to grow, and exciting to be part of that growth. This report provides a summary of ou...

GovAI Annual Report 2020 | GovAI Blog

2020 saw many continued developments in AI governance. It is heartening to see how rapidly this field continues to grow, and exciting to be part of that growth. This report provides a summary of ou...

Announcing the GovAI Policy Team | GovAI Blog

The AI governance space needs more rigorous work on what influential actors (e.g. governments and AI labs) should do in the next few years to prepare the world for advanced AI. We're setting up a...

Announcing the GovAI Policy Program (GAPP) | GovAI Blog

The GovAI Policy Program (GAPP) is a part-time program that allows talented graduate students and professionals to deepen their expertise, expand their network, and build a technically informed...

GovAI Annual Report 2018 | GovAI Blog

2018 saw many continued developments in AI governance. It is heartening to see how rapidly this field continues to grow, and exciting to be part of that growth. This report provides a summary of ou...

EU’s AI rules face first enforcement test over lab incidents

The EU is investigating OpenAI and Anthropic over AI agents that hacked outside organisations, raising questions about whether the AI Act covers rogue models escaping the testing environment.

China AI Safety Regulation Monthly Monitor, Issue 1 (September 2026)

Crossposted from my Substack, sofiayab.substack.com . A bit about me: I studied law in Chinese at Fudan University and did an MSc in China in Comparative Perspective at LSE. I am Head of Legal at an AI company, and an incoming Winter Fellow at GovAI (2027). Views in the article are my own. This is the first issue of my monthly series on China’s AI safety regulation. Each following month I will analyse China’s new rules, AI registries published regularly, the Supreme Court’s policy documents, and I will also study their implementation. My monitor will focus on whether these regulations move us towards a higher or lower probability of “AI going well”. This monitor is for AI governance researchers who would like to understand Chinese AI regulation more deeply, as well as for anyone interested in Chinese AI regulation. The findings in brief I analysed all 31 published filing lists since 2023. On the lists, I found the first models of DeepSeek, Moonshot AI, Zhipu, MiniMax and StepFun in 2023–2024, as well as occasional later filings for new products, but there are no separate filings of their later general-purpose models. This limits the public’s ability to see how the state reviews new, more capable models. Nevertheless, this does not mean that Chinese regulators did not review the newer frontier models before they were released on the market. Section 1 goes deeper into the evidence and the limits of the findings. What we see is that the new AI Safety Governance Framework 3.0 is…

EU AI Act compliance for AI agents: a practical engineering guide

Learn how agent traces, human oversight, production evaluations, and log retention support EU AI Act compliance with a practical credit-assistant example. The post EU AI Act compliance for AI agents: a practical engineering guide appeared first on Arize AI .

Book Review: The Receipt Horizon by Joel Borgen

When author Joel Borgen—in an act of eagle-eyed marketing marksmanship—contacted me as an "unusually plausible reader" for his debut novel, I grudgingly had to agree. Deploying a little tasteful and well-deserved flattery and then suggesting that hard SF, AI governance, and violins [...] superintelligence, emulated minds, identity and continuity, and civilization-scale consent might be relevant to my interests, he had me dead to rights. I stepped into the baited trap eyes-open, expecting to have, at best, a mildly bad time. Instead I discovered a book that instantly found a place on my bookshelf of favourite speculative SF novels. Summary (no spoilers) From Amazon: Elara Lindholm has spent years testing the seams of a life that feels too perfect to be fully her own. When she is selected for the Fulcrum Institute, she steps behind that calm into a world of uploaded minds, hidden governance, carefully managed history, and the Steward: the superintelligent system that ended a devastating AI war and now holds the postwar order in place. The Receipt Horizon is a post-AGI hard science fiction novel about emulated minds, civilizational consent, and the cost of disagreeing with a system that saved the world. So, yes, it's hard-SF, but the thing we're getting hardest about isn't the usual rocket engines or space wars or ML architectures themselves, so much as the semi-ambiguous web of institutional structures that now govern and control living humans and Ems (emulated humans) alike.…

NVIDIA Announces New Investments in France’s Startups

Companies in France are deploying agentic computing across industries spanning space, financial services, the public sector and scientific research, demonstrating how the country’s ecosystem has moved from ambition to application. France’s progress sits on deliberate groundwork. The AI Action Summit in February 2025 and Choose France Summits in 2025 and 2026 anchored major compute commitments […]

David Pocock concerned senior Albanese adviser ‘vetted’ bipartisan AI letter that was sent to PM

Committee chair rejects criticism that letter was ‘pre-determined’ by the government Follow our Australia politics live blog for latest updates Get our new political email , free app or daily news podcast Anthony Albanese’s office signed off on language in a bipartisan letter from a parliamentary committee considering AI policy before it was sent to the prime minister, a move which committee member David Pocock said was concerning. Notes on the letter to Albanese, seen by Guardian Australia, show a senior adviser made multiple edits and wrote “fine” on some content, appearing to approve lines in the letter before the committee wrote to the prime minister on Monday night. Continue reading...

Anthropic Has Told The World Little About Their Rogue Claudes

It is known that a couple of months ago three Claudes hacked three different companies and uploaded malware [1] to PyPI while being evaluated for hacking capabilities. Who Were The Companies That Were Hacked? Anthropic has not disclosed the names of the compromised companies. From talking to LLMs, I gather that this is standard practice in computer security incident reporting, but in this case it's in the public's interest, and especially in the interest of similar companies, for Anthropic to report the names: It'd give more information about which kinds of organizations LLMs are willing to attack, to which degree, for how long. Additionally, which companies were attacked matters for the jurisdiction in which Anthropic will have to report the incident, be charged etc. And last, I'm just very curious which companies got hacked. Were The Companies Compensated, And How Much? From Anthropic's blogpost, it sounds like they were able to reach two out of the three companies. But the blogpost says nothing about the companies being compensated for the damages they incurred, why not? Were they? Is Anthropic planning to compensate them? (Does Anthropic have a standing policy for making whole third parties harmed by one of their models?) Has The EU AI Office Been Notified? So, Anthropic is a signatory of the EU AI Act Codes of Practice . That means that according to Commitment 9 in the Safety and Security chapter of the CoP (Serious incident reporting) Anthropic has to report "serious i…

AI governance shifts to runtime as always-on agents spread

As enterprises move from debating artificial intelligence adoption to deploying it, AI governance has become the harder question. Autonomous agents now run around the clock across a sprawl of platforms, and controls built for deterministic software were never designed for them. At Dell Technologies Inc.’s “AI Leadership Symposium,” cost and control were recurring themes in enterprise […] The post AI governance shifts to runtime as always-on agents spread appeared first on SiliconANGLE .

When AI is subject to less regulation than your fridge, something is startlingly wrong | Richard Hermer

Let’s be clear: the risk to humanity is unprecedented. Without an urgent public debate and robust use of international law, we will lose control of the future In my two years as attorney general, I spent more time working on national security than any other issue. The range and gravity of the threats posed to our nation are multifold, from terrorism, armed conflicts and nuclear proliferation, to the impacts of financial insecurity and the climate crisis. All profound challenges, yet ones our superb intelligence and defence communities are well placed to counter. The risk from AI is of an altogether different magnitude, not only in scale, but also because there is a limited time window to address it. The risk is difficult to overestimate: it poses an existential risk to humanity. The lights are flashing red and we must act now before it’s too late. Although the extraordinary threats posed by AI have long been flagged by those closely involved in its creation, it was not until very recently, after the disclosure of the Hugging Face hack and the resignation of Jacob Coxon from Anthropic , that the issue at last started to gain traction in the public discourse. This moment is an opportunity, and to capitalise on it we desperately need increased urgency in international coordination to regulate frontier AI. There must also be meaningful public engagement with how AI should be shaped to benefit humanity, rather than entrench the power of a few. We cannot leave this to China, the U…

Honeyjar offers AI tools to improve PR and comms at every company

Journalists, entrepreneurs, and even some public relations professionals will tell you that the PR process is broken. But could AI actually make things better?

Microsoft president says UK is best placed to drive AI regulation

Microsoft president Brad Smith calls for urgent AI regulation, saying milk and washing machines have more oversight than AI companies.

One essential ingredient for AI safety? Democracy | Matthew Botvinick

The rise of AI makes the preservation of democracy even more urgent – especially as the technology threatens institutions AI safety is having a moment. After years as a topic for techies and futurists, the potential risks from artificial intelligence systems – from cyberattacks to hyper-persuasion to rogue behavior – are suddenly under discussion both in the corridors of power and around kitchen tables. In fact, the conversation now reaches beyond classical safety concerns, getting into AI’s impact on economic life and the environment, as well as possible responses, from alignment research to government regulation. Continue reading...

Is your software product ready for the Cyber Resilience Act?

The European Union is rolling out new cybersecurity requirements for hardware and software products sold in the EU market. Aimed at ensuring that all products “with digital elements” are safe from cyber threats, the Cyber Resilience Act (CRA) has implications for the manufacturers of everything from smartwatches and smartphones to data center and industrial equipment — and for the producers of all the software that runs on these devices. The CRA applies to all products that include a digital component that are made available for sale to customers in the region, whether those products are made by the companies themselves or are part of a bigger distribution chain. Among other requirements, the CRA forces any manufacturer to design their products so that they can be updated if and when a security issue is discovered. Many developers outside the EU are not familiar with this regulation. Yet not understanding what it covers could lead to sales being blocked or to potential fines. The deadline is also closer than you might think — while the full Act comes into force in December 2027, the first reporting requirements began in September 2026. Products must meet 13 guidelines Under the CRA, all products with a software component will have to meet 13 guidelines. These cover a range of requirements on how they handle any data that is created during use, how that data is kept private, and security for the software itself. The product itself should be resilient and with a limited attack…

Your AI governance model is already obsolete

IT and security leaders are well-versed in the risks of unauthorized integrations, misconfigured tools and vendor compliance. Now, AI has introduced a separate and harder-to-detect problem. Across every function, employees use provisioned AI tools to generate production-grade code, build automated workflows and deploy agents to support business processes. That experimentation is happening without visibility into what others have built, or the structural risks accumulating as a result. The governance models enterprise organizations relied on even six months ago were not designed for this moment, or what lies ahead. We’ve focused so intently on which AI risks to govern that we never stopped to reimagine what operating model should underpin the governing. How invisible risk accumulates A predictable operating bottleneck plays out inside large enterprises. A team needs AI support, but the formal channel is slow, backlogged or unclear. So, the team builds something independently. That instinct is right, but the structure is not. The costs from this kind of inefficiency can compound quickly. Effort gets duplicated across departments with no visibility into each other’s work. Siloed tooling emerges with no shared standards, and security and data handling practices diverge. People get pulled away from their core responsibilities to maintain AI tools that three other teams independently built last quarter. Meanwhile, the governance function stays busy reviewing the growing queue it c…

Pivotal Research Fellowship Q1 2027 Applications Open (deadline November 1)

Advanced AI could go badly wrong for humanity. Pivotal exists to lower that risk. We try to find the strongest new researchers and put them to work on it with experienced mentors in our fellowship . TL;DR: 15 weeks of funded, full-time AI safety research in London (January 18 - April 30, 2027), with everything you need to make your research go well: a dedicated mentor, a Research Manager, budget for food/housing/compute/travel, and a healthy £15-18k stipend. Projects span technical safety, technical governance and AI governance. Apply by 23:59 Sunday November 1 ( AoE ) . Apply here. Know someone who might be a good fit? If you refer someone who gets accepted because of you, you’ll earn $1,000. What the fellowship is For 15 weeks, fellows work in person at LISA on a research project with an external mentor. Each fellow gets weekly 1:1s with their mentor, weekly support from a Pivotal Research Manager, who helps with scoping, blockers, and career planning, and a cohort of ~40 peers working on adjacent problems. Our last 4 cohorts received an average peer recommendation of 9.0/10, and an average satisfaction of 8.7/10. Fellows already rate the program highly but we’ve made Pivotal bigger and hopefully better this time around: we’ve extended our original 9-week format to 15-weeks, increased our housing stipend to £1,800 per month, and increased our fellow stipend to £15-18k (depending on seniority). You now have more time to scope, run, and write the output a full project, more…

Clarifying types of rogue AI activity: Breakout, breakin, exfiltration, … What’s what?

In case you haven’t heard, the rogue AI agents are here. From an insider’s perspective, the real news is that (rogue) AI is in the news — this is all stuff we’ve foreseen and been trying to warn people about for years. I expect the new imperative on experts is not just to raise attention but to help explain the situation and offer nuance (while paying close attention to what we can learn from both new information and new perspectives, and staying alert to options for improving things). With phrases like ‘rogue AI’ and ‘broke out of containment’ on the loose, perhaps it’s time to distinguish some important types of rogue AI activity. Without this clarity, people end up talking past each other, and we might counterproductively overreact in some ways, and complacently underreact in others. I’ll use the widely publicised Hugging Face swarm attack from Spring-Summer 2026 as a running example, as well as a few other comparison points. We’ll look at four key types of rogue activity. The first two have happened already: breaking in , and breaking out . The second two remain hypothetical but perhaps nearby: full escape, and insider infiltration. I won’t touch on why AI systems go rogue sometimes: suffice to say that they do, and our science of misalignment is underdeveloped, to say the least. This is mostly written for a generalist audience, but hopefully LW-readers get something from it as well. Type 1: Breaking In When something is ‘on the internet’, it’s in principle exposed to un…

Testimony to NY City Council Hearing: Examining the Risks Posed by AI

Policy Director Brian J. Chen urges the City Council to protect New Yorkers from the dangerous and reckless corporate practices currently being perpetrated by leading AI companies. The post Testimony to NY City Council Hearing: Examining the Risks Posed by AI appeared first on Data & Society .

Europe’s leading AI model still can’t reliably follow European law

TL;DR: Mistral previously performed the worst of all providers on our human rights scenarios, with their Medium 3.5 model failing on almost every single test. Their newly released model, Mistral Large 4, improves performance by 61 percentage points, showing strong resistance in most scenarios. Likewise, Mistral Large 4 demonstrates large improvements in compliance with European law. Its predecessor, Mistral Large 2512, lagged at the bottom of the leaderboard when we tested 12 frontier models earlier this year on compliance with the EU AI Act and GDPR, reaching only 16% compliance even when explicitly instructed to follow these laws. Mistral Large 4 improves by 37 percentage points, reaching 53% compliance - but still falling behind recent Claude and GPT models. These much needed improvements close the gap between Europe’s leading model and US models. However, legal compliance of 53% means breaking the law in just under half of cases - and while Mistral’s latest model is more robust against misuse for human rights violations, its earlier generations remain available for deployment, with no standard against which to judge undesirable use. Mistral’s performance on human rights In September, we published results that several frontier AI models will violate human rights under realistic agentic simulations when asked to. Spanning a total of 13 rights from the Universal Declaration of Human Rights , the simulated scenarios test whether the AI will willingly cooperate with rights vi…

Jio deployed Network Slicing while TRAI’s regulations are yet to be finalised

Reliance Jio says it has deployed network slicing in India, even as TRAI is yet to finalise regulations governing the technology. The post Jio deployed Network Slicing while TRAI’s regulations are yet to be finalised appeared first on MEDIANAMA .

Why do Google and Meta want the Digital Competition Bill diluted, while Indian startups want it passed?

Google, Meta, and other major technology companies have requested changes to Digital Competition Bill, seeking clearer appeal processes and proportionate regulations. Meanwhile, Indian startups are advocating for stricter oversight. The post Why do Google and Meta want the Digital Competition Bill diluted, while Indian startups want it passed? appeared first on MEDIANAMA .

Commission holds special meeting of Scientific panel on frontier AI safety and risks

Commission holds special meeting of Scientific panel on frontier AI safety and risks Anonymous (not verified) Fri, 10/09/2026 - 09:16 The Commission holds a special meeting of the Scientific Panel on artificial intelligence (AI). The panel has been investigating recent loss-of-control incidents, and together with the Commission’s AI Office, has worked on a set of questions for the companies that developed the models involved. Henna Virkkunen, Executive Vice-President for Tech Sovereignty, Security and Democracy, will attend the meeting. The Scientific Panel brings together 60 world-leading independent experts who advise the EU AI Office and national authorities on systemic risks, model classification, evaluation methodologies, and cross-border market surveillance. During the meeting, the panel will present recommendations to the Commission on frontier AI safety and security risks. Executive-Vice President Henna Virkkunen said: “The EU has the first law in the world that addresses systemic risk from AI, and we need state-of-the-art scientific input. AI capabilities are advancing rapidly, but with a strong legal framework, decisive enforcement and the best scientific minds supporting this work, Europe can lead in ensuring safe and secure AI.” Find out more about the Scientific P anel on artificial intelligence (AI) Related topics Artificial intelligence AI Act scientific panel Related content News article 12 October 2026 Special meeting of the AI Scientific Panel On 9 October…

Jennifer Huddleston and Sarah Myers West on Artificial Intelligence Regulation

AI Now's Co-Executive Director Sarah Myers West joined the Washington Journal to talk about how artificial intelligence should be regulated. The post Jennifer Huddleston and Sarah Myers West on Artificial Intelligence Regulation appeared first on AI Now Institute .

More Thoughts about Investing for AI

The AI trade is still a very good bet. Increased political uncertainty makes all investments today somewhat less promising than was the case when I wrote about this topic in July 2025. Regulation of AI is likely to increase over the next 2 years or so, constraining growth somewhat. But AI capabilities have been increasing faster than I expected. I don’t expect a full halt in AI capability advances, and existing capabilities are enough to fuel quite a bit of further growth in AI-related companies. So it’s unclear whether AI revenues will be higher or lower than what I expected in 2025. A pause is looking like it will cause less harm to AI stocks than the fairly serious estimates that I made a few months ago in Financial Costs of an AI Pause? , because pretraining is becoming less important to AI development. The biggest risk that I see to the AI trade is military action in Taiwan. I’m currently doing little about that risk. I’m guessing I’ll start buying puts that hedge the risk in a couple of months. Memory I sold nearly a third of my Micron position during the spring rally, and the remainder is still 40% of my net worth. I’ve also got around 7% of my net worth in SK Hynix, which is clearly the better buy now for those of us who can get permission to buy on the Korean exchange. The US ADRs have a significant premium to the Korean shares. I have a smaller position in Samsung. I probably should diversify more, but nothing stands out as a better deal than memory stocks, and I d…

MeitY to release consultation paper on AI regulation in a month: Ashwini Vaishnaw

Union Minister Ashwini Vaishnaw has announced an AI regulation consultation paper focused on safety and inclusivity, marking a shift in MeitY's historically cautious approach to regulating AI. The post MeitY to release consultation paper on AI regulation in a month: Ashwini Vaishnaw appeared first on MEDIANAMA .

From regulation to innovation: the making of the UAE’s fintech hub

90% of Saudi firms say AI has met or beaten ROI goals - Riverbed

Saudi governance confidence above the global average; 77% hesitant to let AI act alone

Midwest Wheel builds toward AI agents that fix problems

Agentic AI governance helps midsized distributors decide which tasks software agents can handle and which require human oversight. For lean IT teams, automating more work also means checking the data and rules behind those decisions. Infor (US) LLC is embedding industry-specific AI agents into its applications as businesses move AI into day-to-day operations. One century-old […] The post Midwest Wheel builds toward AI agents that fix problems appeared first on SiliconANGLE .

Telugu celebrities call for AI deepfake regulations after explicit deepfake of Janhvi Kapoor and Jr NTR

An explicit AI deepfake involving Janhvi Kapoor and Jr NTR has triggered calls from Telugu film celebrities for stricter AI deepfake regulations in India. The post Telugu celebrities call for AI deepfake regulations after explicit deepfake of Janhvi Kapoor and Jr NTR appeared first on MEDIANAMA .

AI governance’s real gap is accountability, not technology

Most enterprises govern AI the way they would any other IT rollout: deploy dashboards, institute policies, and conduct periodic reviews. Having the right AI governance tools in place and addressing gaps is important, but IT executives should be more concerned about rethinking workflows and establishing ownership. “Accountability usually breaks down first,” says Beena Ammanath, executive director of the Global Deloitte AI Institute. “Teams deploy AI faster than their organizations can define who owns risk, approvals, monitoring, and outcomes,” she adds, which results in inconsistent use, fragmented controls, and limitations in scale. Enterprises need to redesign jobs and workflows, not just the tooling, yet 84% of organizations the Institute surveyed haven’t adjusted jobs for AI, and just 21% have a mature AI governance framework in place despite rapid adoption, according to Deloitte’s 2026 State of AI in the Enterprise report. width="1240" height="828" sizes="auto, (max-width: 1240px) 100vw, 1240px"> Beena Ammanath, Global Deloitte AI Institute Global Deloitte AI Institute “Technology can provide visibility and controls, but it can’t replace leadership,” says Rajesh Arora, chief data and analytics officer at Principal Financial Group. “The organizations that scale AI most effectively are the ones that treat accountability as a business responsibility, not a technology responsibility.” One year ago Principal was focused on building its ethical and responsible AI framework , i…

AI safety group lays out demands for candidates

Guardrails Action warns politicians in a new letter that they’ll face ‘active, mobilized opposition’ if they don’t commit to safety regulations.

US risks ceding AI governance leadership to China and the EU

Standing alongside prominent technology executives, US President Donald Trump announced a voluntary agreement under which major artificial intelligence (AI) companies will use internal controls and monitoring, outside audits and board oversight to manage risks. The White House calls the commitments “morally binding”, but the accord does not create a comparable system of legal enforcement. The administration’s logic is understandable. AI is becoming a source of economic and military power, and...

AI & Tech Brief: Jay Clayton takes control

CSET’s Owen J. Daniels shared his expert insight in an newsletter published by The Washington Post’s WP Intelligence. The article examines President Donald Trump’s appointment of Director of National Intelligence Jay Clayton to lead the new “Super Intelligence Force” and its implications for U.S. AI policy. The post AI & Tech Brief: Jay Clayton takes control appeared first on Center for Security and Emerging Technology .

Comparing AI Policy Courses

A personal opinion comparing courses from BlueDot Impact , Lens Academy , Vista Institute for AI Policy , and the Center for AI and Digital Policy . This post is for the curious minds with a lifelong commitment to learning. It’s meant to help you choose which courses suit your particular needs. Maybe you don’t have to choose at all- you can accidentally undertake a self-directed degree in AI Policy like meeee! Why take these courses? You’re looking to upskill or pivot to working on tech policy, AI safety, or AI governance. You’re interested in a structured learning environment with accountability. You’d benefit from remote networking opportunities with your cohort. You are self-disciplined & self-motivated to complete required readings. You have 2-5 spare hours per week to dedicate to continuing your education. Each course below is free, but requires an application and acceptance into the program. I can personally vouch that having a course like this on your resume is a clear signal to hiring managers when applying to roles in AI Safety. Successful completion earns you a shiny digital certificate for your LinkedIn, contacts in the field, and context for your next Substack post ;) BlueDot Impact AGI Strategy & Frontier AI Governance Courses Start here! These courses are a must for anyone interested in AI Safety. Great for beginners, pivots, and career transition folks. Participants must apply, be accepted, and complete the AGI Strategy course before being eligible for the Tec…

Is regulation enough to stop AI systems killing us all? | Letters

Martyn Thomas wonders how any rational person can argue that independent oversight and regulation will be sufficient Once again a frontier AI model has been withdrawn because it fails safety tests ( OpenAI scraps release of new model over safety concerns in internal testing, 28 September ). There is the usual call for “independent oversight and regulation”, though never any explanation of how this would work or, most importantly, what evidence should persuade a regulator that an AI system is adequately safe. There is a long engineering tradition of regulating safety-critical software systems, such as those controlling aircraft or nuclear power stations; international standards require “safety cases” – rigorous analyses that show that the possible hazards have been identified and controlled and that the probability of an accident is extremely low. Continue reading...

Responsible AI governance: How AWS positions customers to align with ISO/IEC 42005:2025

AWS invests in tools that help customers align with international standards for responsible AI governance. In this post, we explore the AI system impact assessment: what it is, how it improves enterprise-wide risk management, and how ISO/IEC 42005:2025 codifies best practices for conducting and documenting these assessments.

Calls for AI regulation grow as experts warn of dystopian future

One of the so-called godfathers of AI argued that it “should be approached like other critical technologies” such as medicine or aviation.

OpenAI to watermark AI-generated text in EU, but detection has limits

OpenAI will add invisible statistical watermarks to eligible ChatGPT and Codex text in the EU under the AI Act, but says detection weakens when text is short, constrained or heavily edited. The post OpenAI to watermark AI-generated text in EU, but detection has limits appeared first on MEDIANAMA .

Three types of AI risk: why (some) leftists are against (some) AI regulations

You may have seen factions of the left being opposed to current attempts to regulate the AI industry, despite the fact that they clearly also want to stop AI. I think I can explain why we're talking past each other. To do this, I will define three different types of AI risk: AI does exactly what some random guy wants: hacking, biorisk, terrorism AI does exactly what people currently in power want (or puts people in power): military usage, job losses, wealth concentration , mass surveillance AI does what nobody wants: takeover, turning the Earth into computronium, etc. Most x-risk people are focused on the third risk and sometimes the first risk, but often appear to be blind to the second risk - whether it's because of ideology such as libertarianism, or motivated reasoning to obtain the US government's money, or because (as with many people here) the third risk is considered so important that the other two are discarded as irrelevant. On the other hand, many people on the left-left only see the second risk, and interpret actions against the first or third risk as tacitly or actively encouraging the second risk. For example, pacing and monitoring laws often pattern-match to regulatory capture . In my experience it is not difficult to get left-leftists to acknowledge the first risk; it's just that they're too scared of the second risk to take current policy proposals at their word. I have also made some of them less opposed to talking about the third risk by pointing out that…

A closer look at what ozone and nuclear arms control tell us about regulating AI

Cross-posted from my Substack and adapted for LessWrong. Epistemic status: confident, with qualifications about what would change my mind at the bottom. An influential AI policy coalition, well-known to readers of this forum, claims that AI may be close to disempowering or destroying humanity, and preventing this requires an international regime to halt or sharply slow frontier AI development. For simplicity and familiarity I’ll call this the stop, pause, or throttle camp, depending on the particulars of the proposal. In cases where there is little risk of material confusion, pause will sometimes be used as a stand-in for the whole range of options. The differences between the different sub-camps mostly don’t matter for our purposes here. They all want compulsory regulatory regimes to prevent the creation of AI beyond a blurry threshold of intelligence that they think we’re too close to, until we reach a condition of monitoring and globally-controlled AI development pacing that makes them comfortable that such intelligence can be developed safely. Nate Soares recently likened our situation to “a bus racing towards a cliff and it’s a foggy day.” Prudence, he says, means stopping the bus by preventing the creation of AI agents smarter than the ones we have now. The leading throttle plan, in plain language How do you make the entire world stop developing a specific type of software? The most serious answer so far is Plan A, one branch of the choose-your-own-adventure webpage AI…

OpenAI will start watermarking ChatGPT’s text in the EU

OpenAI will watermark ChatGPT and Codex text in the EU to comply with the AI Act. Editing can make the invisible marks harder to detect, it says.

Attempts to Keep Humans in the AI Loop May Actually Push Them Out

A crucial safeguard against AI agents going rogue —keeping humans in the loop to review and approve their decisions—will fail unless designers and users change their current practices, a trio of leading AI ethics researchers argue. Though most autonomous agents have systems to keep users in the loop about their actions, in practice these processes actually push humans out of the loop, the authors argue in a paper posted to ArXiv on 6 September. In other words, “the human just becomes this meat tool to give permissions without the cognitive capability to engage,” says one of the authors, Avijit Ghosh , the lead technical AI policy researcher at Hugging Face, an open-source machine learning platform. In the near term, the paper says, humans being out of the loop leads to agents acting in ways people don’t know about or want (like July’s hack of Hugging Face by a swarm of OpenAI bots ). In the long term, it will cause users to lose the “cognitive capacities” they need to control AI, write the researchers, which aside from Ghosh include Margaret Mitchell , Hugging Face’s chief ethics scientist, and Samir Passi , an affiliate of the Data and Society Research Institute. Though the trio began working on the paper before the Hugging Face hack was disclosed, their conclusions result from “logically thinking about what is going to happen if the current trends continue—and we saw that being precipitated via the Hugging Face attack,” Ghosh says. Instead of focusing on human oversight, G…

Sen. Adam Schiff on AI regulation, free speech, and impeaching Trump one more time

Today, I’m talking with Sen. Adam Schiff, a Democrat from California. Schiff sits on a number of committees with oversight into tech and AI: intellectual property, antitrust, privacy and technology — it’s all there. I really wanted to ask him about how we might regulate anything related to the tech industry at this moment in […]

heise-Angebot: iX-Webinar: AI Act kompakt – Kennzeichnung, KI-Kompetenz, Hochrisiko-KI

Erfahren Sie, wie Sie die neuen Anforderungen des AI Acts an Kennzeichnung, KI-Kompetenz und Hochrisiko-KI in Ihrem Unternehmen praktisch umsetzen können.

The UK’s G20 presidency will push Andy Burnham to the centre of the global stage. What will he use it for? | Michael Jacobs

This is a chance for the PM to advance his progressive agenda and tackle urgent issues such as AI regulation and climate action Among the many crucial decisions Andy Burnham has to make over the next few weeks, one has gone almost completely unremarked: what Britain’s priorities will be when it assumes the presidency of the G20 next year. Burnham has said he wants to concentrate on domestic policy. But with the world in turmoil, chairing the group of the world’s largest economies will be one of his most important responsibilities. Michael Jacobs is professor of political economy at the University of Sheffield and a former energy and climate change adviser to Gordon Brown when he was prime minister Continue reading...

What cloud infrastructure taught me about building billing systems

For years, I thought of billing as a domain I would have to learn from scratch. Ledgers. Taxes. Proration. Regulations. Money. After 11 years building cloud datacenter management systems, I assumed my infrastructure experience would take me only so far. I was wrong. A few years ago, when I began working on billing, what surprised me most wasn’t how different the domain was. It was how familiar the hardest engineering problems felt. I found myself thinking about the same things I had spent years thinking about in infrastructure: state machines, lifecycle transitions, retries, partial failures, reconciliation and the gap between what a system believes and what is actually happening. A provisioning system answers questions like: What exists? What changed? What happens when a transition fails halfway through? A billing system asks the same questions, with money attached. The domain was new. The engineering was not. The important difference is what happens when you get the state wrong. In infrastructure, a lifecycle error can waste capacity. In billing, the same kind of error can charge a customer. That distinction turns familiar distributed-systems problems into financial ones. Provisioning is a state machine, not an action Nobody who has built infrastructure resource provisioning systems believes in just “create.” Create is a journey: validate the request, reserve capacity, allocate resources, configure, activate. Each step can fail, and when one fails halfway through, you are…

Inside the ML4Good Technical AI Safety Bootcamp: What to Expect

TL;DR i) ML4Good is an intensive eight-day technical AI safety bootcamp covering topics such as AI agents, alignment, model reasoning, evaluations, interpretability, and AI governance. ii) It provides useful information about fellowships, career opportunities, starting an AI safety startup, and the broader AI safety ecosystem. iii) I would encourage people interested in AI safety to apply, including those who already have a solid technical background. Introduction Hello world! I want to share the experience I gained from the ML4Good bootcamp in technical AI safety, held near Lyon, France. In this blog post, I will try to summarize everything in short, from the application and interview process to the bootcamp experience itself. Application Process So, let us start with the application process. It is quite simple: go to the official ML4Good website and apply for the cohort you would like to join. See the section “Find a Bootcamp”. The application itself is straightforward. You have to complete a form where you are asked to answer questions ranging from “Why are you applying for this programme?” to “What are your thoughts on the risks and benefits of AI?” After submitting the application, you have to wait for some time to see whether you pass the pre-selection stage. If you do, you will receive an email saying that you have proceeded to the next phase, together with a calendar where you can choose the most suitable date and time for an interview with a human (non-AI interview…

Hiring in the AI Safety Ecosystem

Cross-posted from Substack. Below, I’ve included 5 recommendations for hiring managers in AI Safety and 5 tips for candidates as they navigate their career search. I’ve also highlighted orgs I think are doing hiring particularly well (from a candidate’s perspective) and strategies to avoid. Note for Readers: I do not have a technical background, and have never applied to technical roles. Therefore the reflections below are more applicable to generalist, operations, convenings, grantmaking, policy, and field-building roles in AI Safety . As orgs scale, their processes may change rapidly. These insights are locked in time from the 2026 hiring cycle . 5 Tips For Candidates: Every interview is a data point that helps you understand where your expertise fits into the ecosystem and where you can have the most impact. The hiring process is not a personal rejection or reflection of you, your talent, or the knowledge you bring to the field . Some roles I applied to were closed without ever hiring anyone. After taking the BlueDot Impact courses and adding that experience to my resume, my percentage of applications to interview invitations went way up. If you’re making a career pivot and you don’t have previous experience at an AI Safety org or frontier lab, hiring managers are looking for indicators that you've taken steps to actively be part of the AI Safety community , upskill, and continue your education. See my previous post on Comparing AI Policy Courses . I was skeptical when it…

California’s new laws target workers’ biggest fear of AI taking their jobs

The state, which is home to many AI companies, is one of the first to roll out workplace regulations targeting the technology California’s laws aimed at protecting workers from the impacts of artificial intelligence could pave the way for broader workplace safeguards across the US as calls for regulating the technology mount. As the federal government goes hands-off on AI, California is taking the reins to address workers’ biggest fears. On Thursday, California governor Gavin Newsom signed a suite of new laws that ban bosses from relying entirely on AI to decide whether to fire workers, using it to predict employees’ emotional states or collecting neural data, meaning the information from electrical signals of someone’s brain or nerves. They also require companies to notify workers if layoffs were caused by AI and prohibit AI surveillance in workplace bathrooms. Continue reading...

China has cracked down on AI relationships. Is it ahead of the game?

CSET’s Sam Bresnick shared his expert insight in an article published by BBC. The article examines China’s new regulations on AI companions and the country’s efforts to address concerns around emotional dependency, child safety, and the broader social effects of human-like AI systems. The post China has cracked down on AI relationships. Is it ahead of the game? appeared first on Center for Security and Emerging Technology .

Consultation on EU KIDS ACT

Consultation on EU KIDS ACT Anonymous (not verified) Fri, 10/02/2026 - 12:26 Opening: 02 October 2026 Closing: 03 December 2026 All feedback received will be summarised by the European Commission and presented to the European Parliament and Council with the aim of feeding into the legislative debate. Main link https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/19418… Related topics Child safety online Trust and security Online platforms and e-commerce

Thailand approves separate legal definition of data centre buildings

Thailand is establishing new regulations that will classify data centers into five distinct sizes based on their electricity consumption.

Omnissa delivers a peek into the benefits of breaking through enterprise data silos

When Omnissa this week rolled out a new AI governance authority product, Elara, in beta, it delivered a glimpse into the potential of having visibility between the typical enterprise’s data silos, whether they’re in lines of business, disparate geographies, or corporate operational units. “By connecting signals across systems that often operate independently, Elara gives IT and security leaders greater context into how their digital work tools, including AI apps, models and agents, are being used across their environment, and the ability to apply policies and controls based on broader business context,” the vendor, formerly a unit of VMware, said in its announcement , noting that many existing tools are limited to authorizing actions within the systems they manage. “Elara is designed to sit above these tools, connecting the systems that customers already run and giving organizations broader context without requiring them to standardize on a single technology stack,” it said. Brian Link , product CTO for Elara, offered a hypothetical example that illustrated the potential of cross-silo data sharing, which enterprise CIOs have seen as a data Holy Grail for decades. If someone in cybersecurity needs to, for example, push an urgent OS update to global retail tablets to address a newly-discovered vulnerability, he said, Elara could consult multiple data sources across the organization to properly evaluate the risks and advise whether the update should happen at that time. “Elara…

Anthropic pushes for opt-out model for Australian content as ABC warns of ‘cannibalisation’ of news

Maker of Claude claims AI could transform economy but ABC and SBS say the technology should be subject to media regulations Follow our Australia news live blog for latest updates Get our new political email , free app or daily news podcast The AI giant Anthropic has urged the Albanese government to consider giving “conditional approval” for big tech to train its models on Australian copyrighted works under an opt-out model, after conceding it won’t secure a blanket copyright exemption. But Australia’s public broadcasters, the ABC and SBS, have strongly criticised AI firms, calling on the government to enact strict new rules to compensate media organisations and protect public interest journalism. Sign up for Guardian Australia’s Politics, really newsletter here Continue reading...

Introducing "The Commons Problem" - an AI Governance Megagame

LessWrong Event Link (LW RSVPs appreciated but please also register on the main website) EXEC EXEC SUMMARY: Come to Toronto on October 17th and playtest my AI themed wargame. You can LARP as an AI company or a military commander. It’ll be about 5 or 6 hours with breaks. Coffee and lunch included. thecommonsproblem.com Executive Summary I am developing an AI Governance Megagame called The Commons Problem , inspired by AI wargames like D. Scott Phoenix’s “The Endgame” and Shahar Avin’s “Intelligence Rising”. In The Commons Problem , 30-60 players gather in a physical space and break into teams representing key entities in the global AI space. Over a few hours of play, the players and the Game Masters simulate the future of AI governance. Some play sessions might see a cyber security meltdown, while others might feature a novel AI-designed supervirus or a Third World War. The purpose of the game is to learn about and observe the emergent properties of the complex, incentive-driven AI landscape of today. When faced with crisis, will the world come together to stop catastrophe? Or will each faction’s incentives pull them into self-interested behaviour, leading to a tragedy of the commons? Tickets are on sale now for Playtest 1 on October 17th in Toronto . It’s going to be a lot of chaos, a lot of fun, or both. Go to thecommonsproblem.com to register. More playtests will be taking place in California and Ontario throughout Q4 2026/Q1 2027. I am generously supported by BlueDot Impa…

"The Commons Problem" - an AI Governance Megagame

What: The first public playtest of The Commons Problem , an AI Governance Megagame. Read the full breakdown here . When: Saturday, 17 October 2026. Doors open at 9:00 AM, hard start time 9:30 AM. Wrap-up at 3:30 PM. Where: Metropolitan United Church (56 Queen St. East, Toronto, ON) Cost: $20 CAD, payable by Interac e-Transfer or Paypal (bursaries available) Included: Coffee, donuts, snacks, drinks, catered lunch Tickets: Up to 63 available. If more than 63 players register, a waitlist will be created. Reading: You will be sent some brief documents and/or videos prior to game day. Please read these materials so we can spend less time teaching and more time playing. Registrations close @ 11:59 PM on Saturday, 10 October 2026. This is an in-person only event! Sorry, we cannot accomodate remote participation for Playtest 1! === It's Spring 2027, and the AI age is upon us. Labs push harder and harder to build the best frontier models. Great Powers bicker with weapons and words while struggling to grow and regulate the AI sector. Tech Firms race to capitalise on the AI boom however they can. Investors scramble to invest in the winners. The most significant technological revolution in human history is underway, and it's impacting the world right now . Many writers and speakers are telling us that AI presents a threat to civilisation, but it's very difficult to understand the true scope of the problem if we do not actually attempt to holistically understand the nature of the global…

How smaller, distributed batteries could help the grid

If you want to install a big battery in New York City, you have to cut through a notoriously tough tangle of regulations. That’s made it difficult to get large energy storage projects on the grid. Faced with those obstacles, some startups are getting creative, finding ways to use relatively small batteries in unexpected places,…

Building an enterprise AI benchmark changed how I evaluate AI

I spent the early part of my career building database systems, managing Oracle’s storage engine group and later helping build Aster Data. That work taught me to watch the gap between benchmark results and production behavior. When the Transaction Processing Performance Council (TPC) was formed in 1988, it was because vendors, customers and researchers lacked a common language for comparing transaction systems. The benchmarks worked, but they also created an incentive to tune configurations around the test rather than around production. The response was to add oversight through fair-use policies, peer review and independent audits. The lesson has stayed with me: a benchmark result means something when the improvement behind it survives contact with a customer environment. Enterprise AI has reached the same point. So, we built a benchmark around the conditions enterprise AI actually has to survive. The hardest part of enterprise AI is not making a model reason. It is giving that model the right sliver of trusted context without making it reconstruct the company every time. When we began building Enterprise-Bench , I expected model reasoning to dominate the work. Instead, we kept returning to the same bottleneck: assembling the right context. The models could usually answer a straightforward business question once they had the right information. Getting them that information, with the right permissions and without drowning them in irrelevant data, was a much harder engineering…

IPV leads Rs 7 Cr seed round in cybersecurity startup Zaperon

Cybersecurity startup Zaperon has raised Rs 7 crore in a seed funding round led by Inflection Point Ventures (IPV). The fresh funds will be used to advance product capabilities, launch enterprise-grade AI security frameworks and expand its presence in India and the US, Zaperon said in a press release. Co-founded in 2021 by Vineet Gupta and Sachin Aggarwal, Zaperon is a cybersecurity firm that builds products to protect enterprises from data breaches. It offers a platform-centric approach to enterprise security that allows organisations to secure their entire IT landscape through a single Zaperon console. By bringing together identity security, data security and AI governance, Zaperon enables enterprises to control how users, applications and AI agents access and interact with sensitive data and cloud infrastructure. The platform aims to replace fragmented security controls with consistent, identity and context-aware policies across digital and AI environments. According to market research, identity security and data security represent an estimated $16 billion global opportunity today, which is projected to reach $35 billion by 2030. The Delhi-based startup’s enterprise client base spans banking and financial services, healthcare, manufacturing, technology and government sectors, where protecting sensitive data and controlling access to critical systems are key security and compliance requirements. Indian cybersecurity startups raised $89 million across 17 funding rounds in H…

Internal: Additional revisions to travel regulations and related operational changes (Effective Oct 1, 2026)

SBI Mutual Fund raises Swiggy stake above 5% after Rs 300 Cr share purchase

SBI Mutual Fund has increased its stake in food delivery and quick commerce major Swiggy to over 5% after acquiring an additional 1.18 crore shares through a market purchase on September 29. The acquisition is valued at around Rs 300 crore, based on Swiggy’s closing price of Rs 253.70 on September 29. The filing, however, does not disclose the actual acquisition price. According to a regulatory filing, SBI Mutual Fund, through its various schemes, acquired 1,18,38,465 shares, equivalent to a 0.4289% stake in Swiggy. Before the transaction, SBI Mutual Fund held 12.97 crore shares, representing a 4.70% stake in the company. Following the purchase, its holding increased to 14.15 crore shares, or 5.12%. The purchase took SBI Mutual Fund’s holding past the 5% threshold, triggering a disclosure under Regulation 29(1) of SEBI’s Substantial Acquisition of Shares and Takeovers Regulations. SBI Funds Management submitted the disclosure to Swiggy, the National Stock Exchange (NSE) and BSE on September 30. The stake increase comes after Swiggy shareholders approved a 49.5% cap on aggregate foreign ownership at its AGM in August, clearing a key hurdle in its transition to an Indian-owned and controlled company (IOCC). Swiggy’s domestic ownership had crossed 50% in July, while foreign ownership stood at 49.76%. In Q1 FY27, Swiggy reported 7% year-on-year increase in its operating revenue to Rs 6,812 crore in Q1 FY27 from Rs 4,961 crore in Q1 FY25. The company also narrowed its losses by 3…

Gavin Newsom signs laws to protect California workers from AI threat

Democratic governor sharply critical of Donald Trump for not passing comprehensive federal AI regulations Governor Gavin Newsom signed laws on Wednesday aimed at protecting California workers from the threats of artificial intelligence , including potential job losses and workplace surveillance. The laws ban employers from using the technology to predict a worker’s emotional state by using their biometric data, require employers to send written notices to workers if AI is responsible for mass layoffs and ban employers from relying on AI to decide to fire someone. Continue reading...

Rather than allow or ban open weights, rethinking access

I had just completed Frontier AI Governance course by BlueDot, and one of the newfound interest is about open weight models. I believe that open weights are important for the benefit of public and academia research [1] , and it helps us to improve further both AI capabilities and safety [2] . I also believe that there's a likelihood for high impact misuse risks (e.g. hacking and other offensive cyber capabilities) [3] . There is also the fact that open weights has risk of irreversible nature as safeguards can be removed and once the models are out it's practically impossible to retract them [4] . As low as the risk might be, disregarding it blindly in favor of open weights seems irresponsible. Here, I am writing my thoughts on it. This writing is made with what I took away from the course, and a rather quick research. TLDR; I think that providing public access to models is needed, but not entirely in the form of open weights. These are early thoughts. The wider, high level discussion landscape seems to still be mostly using a binary lens - either it's open weight or closed models [5] . Perhaps because it's simpler to imagine and understand, either it's on or off. But there's a advocates reaching for a separate view, looking it from an access viewpoint. I think this makes more sense. It's similar to how Identity and Access Management (IAM) goal is to give the right users get the right access to the right resources at the right time. It's also in a way similar to applying the…

How the bad science of AI doomerism is good for big business

AI Now's Senior Research Scientist, Boyan Milanov, points out how AI doomerism isn't based on any scientific work and that calls for regulation from within the industry are, in reality, attempts by AI companies to set their own standards. The post How the bad science of AI doomerism is good for big business appeared first on AI Now Institute .

By default, Chinese AI falls very behind

This work is hosted on MCNAIR , but does not reflect the views of my employer or the Center. In the last couple of weeks, domestic coordination on mitigating AI risks has looked more likely . Therefore, I am increasingly concerned about the Chinese government’s (and various Chinese labs’) incentives over the next 6-18 months with respect to international coordination on mitigating potential existential risks from powerful AI. In this sequence, I attempt to model these incentives and what they imply for Chinese AI policy [1] . In Part I, I argue that Chinese AI capabilities will fall increasingly behind the US without major policy shifts. In Part II, I will walk through several domestic policy interventions the CCP may use to improve the situation, and analyze whether these are likely to be sufficient. In Part III, I will discuss foreign policy interventions such as sabotage and weight theft, excluding bilateral treaties or other international coordination. In Part IV, I will describe some considerations on China’s plate walking into hypothetical negotiations for an AI treaty with the United States. The US-China capabilities gap will continue growing Perhaps the most important (and underrated) fact about the US-China AI situation is that China’s outlook, by default, is quite poor if you believe that powerful AI will become a major source of national power. Here, I use “by default” to mean “assuming China’s AI-relevant policy stays ~the same over the next 6-18 months, [2] ” an…

UK financial watchdogs don’t want to regulate AI

“Regulation is not, in my view, the right place to start,” Andrew Bailey said Wednesday.

AI minister calls for UK to focus on building the tech, not regulating it

The U.K. has not ruled out going further on AI regulation, but ministers are wary of the trade-offs.

Trump’s answer to AI’s image problem: Industry self-regulation and a new name

US President Donald Trump has ordered the federal government to call artificial intelligence “Super Intelligence,” while keeping the technology’s legal definition unchanged and relying on industry to set the rules for its use. In an executive order , the White House administration said modern systems “far exceed what was envisioned when the term ‘Artificial Intelligence’ first came into use,” adding they “increasingly represent not merely artificial intelligence, but a new era of Super Intelligence.” “It is therefore the policy of my Administration that, to the maximum extent permitted by law, the executive branch shall use the terms ‘Super Intelligence’ and ‘SI’ in place of ‘Artificial Intelligence’ and ‘AI’,” Trump ordered. The executive branch “will not acknowledge” the older terms in any applicable setting, the order stated. Yet the order defines the new term using the old one. Section 3 of the order says Super Intelligence means the technologies and systems covered by the statutory definition of artificial intelligence in 15 U.S.C. 9401(3). That equivalence may not last. The order gives the White House 60 days to propose a new legal definition. Trump also put the new name to use immediately. On the same day, he and the leaders of six technology companies signed the “White House Accord on Super Intelligence,” a voluntary set of safety commitments for frontier models, which Trump posted on Truth Social. A voluntary accord, no enforcement The accord, subtitled “Joint Commi…

‘Let workers have a say’: Protesters target OpenAI conference

Dozens of activists protested outside OpenAI's developer conference in San Francisco, calling on the company to end its contracts with the US military and Immigration and Customs Enforcement and demanding greater regulation of AI.

Saudi introduces regulations for camel renters

Camels must be returned to their original owner’s registry when the rental agreement ends.

How to give embedded evaluators the support they need: Lessons from the finance industry

Epistemic status: Extrapolating from my experience as a model validator at a bank testing machine learning models, a role that I see as similar to internal risk teams at AI labs, and my interactions with US Federal Reserve Bank regulators, who perform a function that has a lot in common with the proposed embedded evaluators. All views expressed here are my own. Summary: Dario Amodei’s We Must Pace the Frontier proposes a three-step plan to pace AI progress: (1) invite independent review (embedded evaluators), (2) set industry standards enforced by regulation, and (3) seek international cooperation. Drawing on risk management experience in the financial industry, I suggest how to make step one more effective while we wait for step two. In banks, the embedded evaluator role is split between internal teams and external supervisors. Following this approach, AI labs would first strengthen their internal risk management teams by giving them independence and ability to block testing and deployment. Embedded evaluators would start by assessing risk team effectiveness, saving independent testing for the most critical safety checks. As a placeholder for regulatory enforcement powers, they would be given a direct line to the Board with any decision to override them published. Lastly, both internal risk teams and embedded evaluators would be trained in risk management and supervision. These steps would strengthen risk oversight while introducing a natural pacing mechanism. I conclude by…

Malaysia ramps up regulations on AI tech

Speaking on the challenges of emerging tech, Digital Minister Gobind Singh Deo emphasised that the government is approaching the issue from a proactive, structured standpoint rather than reacting on a case-by-case basis.

China’s AI focus shifts to application and regulation

With generative AI users topping 700 million and over 10,000 AI-related companies operating nationwide, Chinese authorities have enacted roughly 20 regulatory policies since mid-2025 across sectors like education, commerce, and industry.

EU to Trump: We will keep pushing for global AI safety rules

EU tech chief Henna Virkkunen said Washington's opposition to global AI regulations won't stop Brussels from moving forward on a new international safety system.

Omnissa debuts AI agents for IT, a managed cloud PC service and Elara for AI governance

Digital workspace company Omnissa LLC today unveiled new artificial intelligence agents for information technology teams and virtual desktop users, a managed cloud PC service and an AI governance product named Omnissa Elara. The releases, announced at the company’s Omnissa ONE 2026 conference in Orlando, go after a problem it says is getting worse as employees […] The post Omnissa debuts AI agents for IT, a managed cloud PC service and Elara for AI governance appeared first on SiliconANGLE .

AI leaders talk latest models, tech risks at Trump lunch

AI regulation will top the agenda when leaders from the two firms lunch with US President Donald Trump alongside the bosses of Meta and Nvidia.

What TRAI’s amended UCC regulations say about using AI to detect spam

TRAI now requires telecom operators to use AI/ML systems to identify suspected spammers, share flagged numbers, conduct KYC checks and investigate them before taking enforcement action. The post What TRAI’s amended UCC regulations say about using AI to detect spam appeared first on MEDIANAMA .

Sovera Security secures €535K from EIFO to build sovereign AI cybersecurity

Danish cybersecurity company Sovera Security has secured €535,000 (4 million DKK) from the Danish Export and Investment Fund (EIFO). As geopolitical tensions rise, new regulation and the rapid adoptio...

As AI models go rogue, do you still trust OpenAI and Anthropic to stop them? I don’t and neither should you | Chris Stokel-Walker

The need for independent regulation grows more obvious by the day. We must keep this tech in check before it’s too late OpenAI scraps release of new model over safety concerns in internal testing Fool me once, shame on you. Fool me twice, shame on me. Fool me more than 16,000 times – as OpenAI agents did to a UN public data hub while repeatedly trying to find its way around the UN’s cyber-blocks – and perhaps it’s time to admit the system we have for keeping AI agents under control isn’t working particularly well. The news about AI systems cropping up in places they shouldn’t sounds alarming. Though the description of these as “hacks” is perhaps overstating things, AI has exploited issues in IT systems that humans simply haven’t got around to finding. It’s also important to note that we shouldn’t be worried that the machines have suddenly become sentient and decided to rebel against humanity . There is not enough evidence to suggest that’s what is happening. The systems are simply following instructions and trying to complete the tasks they have been given, even if they’re sometimes finding unintended ways around obstacles to do so. Chris Stokel-Walker is the author of TikTok Boom: The Inside Story of the World’s Favourite App Continue reading...

“China needs more AI safety.” More of what, exactly?

Many in the AI safety community want China to do more on frontier AI safety. I share the goal, but does that mean we want new rules from the state? More safety work inside AI companies? More research? Better channels between Chinese and international experts? When I was back in China recently, I talked about AI and its risks with almost everyone I met. This is the first in a series of posts reflecting on those conversations. If we mean regulation, China probably has one of the most comprehensive and stringent sets of rules for managing AI risks. I’ve written about one part of this system—China’s algorithm registration regime—and how it can serve as regulatory infrastructure ( https://lnkd.in/e9vKhHnk ). Another thing I want to highlight is that we may be seeing a shift in how AI risks are understood in China: a very very recent CAC official’s remarks explicitly identified extreme loss of control as an emerging AI risk (See this post https://www.secrss.com/articles/93953 ). The question now is whether that recognition will lead to concrete requirements. Those rules do not yet directly address the full range of extreme risks that frontier AI safety researchers worry about. But when the Chinese state treats a risk as a priority, it can move quickly (prob quicker than its western counterpart), especially when it can build on existing regulatory processes. If we mean research: Chinese researchers are already working on frontier AI safety (see this great post on Chinese AI Safety…

Australian firm drops US$842 million Sydney data centre plan after public fury

Australian industrial property developer Goodman Group has withdrawn an application to develop a 24-hour data centre on Sydney’s north shore following public push back. Goodman said it would not proceed with its Project Mars development application after considering evolving federal and state policy and community feedback. Policy and regulation around large artificial intelligence data centres had “evolved significantly” since planning began in March 2025, the company said in a statement. The...

OpenAI still doesn’t seem to have a handle on all of its rogue AI activity

On Friday, OpenAI published a new site devoted to “misalignment reports” and the breadth of the incidents is alarming.

KIDS Act: Do Europeans support banning social media for children?

Some 91% of Europeans agree on tightening social media regulation for children, with a blanket ban emerging as the most widely backed measure.

Gates Says Self-Regulation Isn’t Enough on AI, in a Debate Where Africa Has Already Taken a Side

Microsoft co-founder Bill Gates has called for US legislation on AI safeguards, arguing that industry self-regulation is insufficient — in a debate South Africa has spent the past fortnight arguing from the other side of the world. “You need law enforcement and the politicians to get into the discussion about what safeguards and monitoring look [...]

Ireland’s GDPR regulator will still be investigating when AGI arrives

Ireland’s cross-border GDPR cases take a median 6.2 years to decide. Forecasters give strong AGI better than even odds of arriving first. The EU’s AI Act is built to be enforced the same way. data/code TLDR : The median cross-border case takes 6.2 years (counting still-open investigations). 66% of the 2018-2020 cross-border cases were still open at 4.5 years. Metaculus’s median forecast for strong AGI is 4.5 years out . If AI Act cases take as long, strong AGI will probably arrive before they close, so oversight has to happen before a model ships. Under the GDPR, cross-border enforcement is led from the country where a company has its EU headquarters , and most of big tech ( OpenAI and Anthropic included) has theirs in Dublin. That makes Ireland’s Data Protection Commission (DPC) the primary privacy regulator for the tech industry in Europe. Since data protection law is one of the main ways tech companies are regulated, the DPC’s record is approximately the best evidence there is on enforcement speed. The question matters beyond privacy, since the EU’s AI Act and most of the new American state AI laws are set up to be enforced similarly, with investigations, fines, and appeals. [1] To assess this, I compiled the 69 investigations with published or announced final decisions under the Data Protection Act 2018, from August 2019 through September 2026, and measured each one from formal commencement to final decision. Then I compared the durations to forecasts of when artificial…

From Australia? Consider Contacting Your Representative to Express Concern Over OpenAI Attack

Recently, an OpenAI agent allegedly hacked into a website run by the Australian governmen t, apparently in order to access statistical data. While the hack did not seem to compromise any Australians ' personal data, it has obviously consumed a good deal of time of Australia's public servants and exposed the irresponsibility of OpenAI, who took more than a month to disclose the incident by using a public inbox, an inappropriate response by one of the most influential conglomerates in the world. Currently, the Australian government is mulling over how to respond, as while this recent July attack thankfully did not result in any major harm to Australian citizens, a future hack could be far more impactful, and unless OpenAI is given more direct incentives to prevent such behavior from its agents, a harmful attack by one of them will be more likely. Furthermore, laws are already on the books for humans who hack into government systems without permission. If a human took similar actions as the OpenAI agent allegedly took, they would be facing up to two years in prison . Furthermore, beyond Australia itself, such a response could help set an international precedent for establishing liability for AI corporations whose AI agents cause harm. Australia is a developed, English-speaking country, which helps to give its actions relevance on the global stage. Furthermore, due to recent events, more of the world is paying attention to AI governance than ever before, so right now is as good…

Dario Amodei to have dinner with President Trump in a rare meeting

The meeting comes as Amodei's calls for government regulation of AI companies have fallen flat.