person
Rishi Bommasani
Stanford CRFM; Foundation Model Transparency Index lead
Stanford researcher who leads the FMTI project tracking transparency across frontier developers. Argues governance must be graded on concrete, measurable criteria.
Profile
expertise
Deep technical
Sustained peer-reviewed contribution to ML, alignment, interpretability, or safety techniques. Could review a frontier paper.
Stanford CRFM. Co-author of 'Opportunities and Risks of Foundation Models' (2021), the canonical foundation-model framing paper.
recognition
Established
Reliable, recognised voice within their specific subfield. Cited and invited but not central to general AI discourse.
Recognised in foundation-models research community.
vintage
Scaling era
Worldview formed during GPT-2/3, scaling laws, Anthropic's founding. Pre-ChatGPT but post-deep-learning. The 'scale is all you need' debate is live.
Stanford CRFM. Foundation Model Index work post-2021. Career is scaling-era foundation-model evaluation.
Hand-classified. See the board for the criteria and the full grid.
Strategy positions
Evals-drivenendorses
Capability/risk evals gate deployment; evals are the load-bearing artefactPublishes the Foundation Model Transparency Index; argues measurable transparency scores are the right instrument for governance.
Without transparency, governance cannot be meaningful.
Closest strategy neighbours
by jaccard overlapOther people whose strategy tags overlap with Rishi Bommasani's. Overlap is on tag identity, not stance; opposites can show up if they reference the same tags.
Record last updated 2026-04-24.