Peter Wildeford

I am hoping to get more help developing policy ideas for future policy windows.

Stream overview

I lead policy development at the AI Policy Network. We do advocacy around AI safety, especially in DC. I am hoping to get more help developing policy ideas for future policy windows.

Mentors

Peter Wildeford
AI Policy Network
,
Head of AI Policy
Washington, D.C.
Policy and Governance
Forecasting and Strategy
Technical AI Governance

Peter Wildeford is the Head of Policy at The AI Policy Network, an organization building bipartisan support for policies that prepare America for AI superintelligence. He has spoken about AI on Good Morning America, the Daily Show, TIME, Politico, The Information, TechCrunch, and Transformer. Previously, he co-founded the Institute for AI Policy and Strategy and before that he was a data scientist and software engineer for five years. He is also a top-20 forecaster on Metaculus and has placed highly in multiple forecasting tournaments.

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Mentorship style

Fellows we are looking for

Project selection

Streams

The Winter 2026 cohort offers a wide range of research streams led by experts across AI alignment, interpretability, governance, and safety. Each stream provides its own research agenda, methodology, and mentorship focus.

SF Bay Area
Dangerous Capability Evals
Boston
Policy and Governance
Adversarial Robustness, Policy & Governance, Red-Teaming, Safeguards
New York City
Control, Scalable Oversight, Red-Teaming, Model Organisms, Monitoring
SF Bay Area
Policy and Governance
Policy & Governance
SF Bay Area
Control, Monitoring, Dangerous Capability Evals
SF Bay Area
Security, Compute Infrastructure
London
Theory
Interpretability
London
Scheming & Deception, Dangerous Capability Evals, Control, Red-Teaming
SF Bay Area
Dangerous Capability Evals, Red-Teaming, Model Organisms, Control, Monitoring
Toronto
Interpretability
London
Control, Monitoring, Safeguards, Dangerous Capability Evals, Scheming & Deception
Chicago
Biorisk, Security, Safeguards
SF Bay Area
Interpretability, Agent Foundations
London
Empirical
Interpretability
London
Interpretability, Red-Teaming, Monitoring
London
Monitoring, Adversarial Robustness, Control, Model Organisms, Red-Teaming, Dangerous Capability Evals, Safeguards
New York City
Policy and Governance
Dangerous Capability Evals, Control, Strategy & Forecasting, Policy & Governance, Scalable Oversight, Agent Foundations
SF Bay Area
Empirical
Theory
Dangerous Capability Evals, Adversarial Robustness, Security, Red-Teaming, Scalable Oversight
London
Control, Scheming & Deception, Dangerous Capability Evals, Monitoring
Washington, D.C.
Policy and Governance
Policy & Governance, Strategy & Forecasting