AI safety field *visual* impact analysis

I made a terrain style visualisation of AI safety impact of around 3,466 works organised by citation count! The data was extracted from Arxiv and LessWrong posts based on a dictionary of keywords that appear in AI safety works. Additionally, I think its important to see how the field has “evolved” over time so I added a time functionality to slide and see the hills forming. The map is based on how particular works overlap based on embedding space level clustering organised across 18 sub-fields. The height is based on the citation count for that particular area which is log-compressed and summed across the neighbourhood, so a hill is tall because of volume and impact. I have also added functionality to filter based on citation count individual researcher (shows you their works on the map to understand what work they might be doing; 3,989 named authors are on the map clicking or searching for a work zooms into it and lists the ten works nearest it, so you can see what surrounds it The terrain itself is papers only, because Semantic Scholar doesn’t index LessWrong. The forum side of the dataset feeds the researcher profiles rather than the hills. The slider runs from 2021Q1–2026Q3. Some interesting high level observations Alignment training and scalable oversight are very high citation presently (followed by adversarial robustness and Interpretability). Most of that sits in a handful of 2022–23 papers: InstructGPT (24,222), DPO (10,596), Anthropic’s helpful-and-harmless RLHF pa…