Kevin Klyman
Technology Policy Strategist
What I Do
I am a researcher who advocates for responsible uses of technology to reduce harm and advance peace. I am currently a fellow at Harvard where I study frontier AI and geopolitics. I previously helped found the U.S. AI Safety Institute, managed special projects at Stanford's Center for Research on Foundation Models, and worked on AI and privacy in the UN Secretary-General's Office. My research has been published at machine learning conferences like NeurIPS and ICML and featured by the New York Times and Washington Post. You can follow my work on Linkedin.
Coverage of My Work
Essays, Blogs, White Papers
CAISI Works with OpenAI and Anthropic to Promote Secure AI Innovation (2025) — a blog on CAISI's work with AI companies
The Future of Third-Party AI Evaluation (2024) — a workshop I hosted with colleagues from Princeton and MIT
HELM Safety v1.0 (2024) — an evaluation framework for safety of large language models using standard public benchmarks
Foundation Models Under the EU AI Act (2024) — a blog tracing the evolution of the EU AI Act over time
Transparency of AI EO Implementation (2024) — a tracker of the implementation of Biden's AI Executive Order
How to Promote Responsible Open Foundation Models (2023) — a summary of a Stanford-Princeton workshop on open AI models
Biden Takes Measured Approach on China Investment Controls (2023) — an essay in Foreign Policy on the costs and benefits of US outbound investment controls
The US Wants to Make Sure China Can't Catch Up on Quantum Computing (2023) — an essay in Foreign Policy
The Great Tech Rivalry: China vs the US (2021) — a report for Harvard on machine learning, 5G, quantum information science, semiconductors, biotech, & green tech in China and the US​​
Research
Expressing Stigma and Inapproproate Responses Prevents LLMs from Safely Replacing Mental Health Providers (2025) — a study showing LLM chatbots pose safety risks for mental health
From Symptoms to Systems (2025) — a taxonomy of risks AI poses for eating disorders based on 15 expert interviews
The Foundation Model Transparency Index (2025) — a first of its kind annual index for the transparency of foundation models
Acceptable Use Policies for Foundation Models (2024) — a mapping of 30 AI developers' acceptable use policies
Consent in Crisis (2024) — an audit of AI training datasets that showed how websites are working to resist scraping by AI firms
The Responsible Foundation Model Development Cheatsheet (2024) — best practices for developers of foundation models spanning the AI lifecycle, from data to evaluations
Considerations for Governing Open Foundation Models (2024) — an assessment of open source AI regulation
A Safe Harbor for AI Evaluation and Red Teaming (2024) — A position paper calling for protections for third party AI research
On the Societal Impact of Open Foundation Models (2024) — A position paper calling for marginal risk assessment of AI models
I'd love to hear from you
© 2026 by Kevin Klyman
My email is my kevin [dot] klyman [at] berkeley [dot] edu