Sentinel Bio - Toby Webster - AIxBio

AIxBio projects on biological data, biological AI models, and their interactions with GPAIs, to directly progress the maturity of interventions and reduce strategic/technical uncertainties. Some projects may be scoped to directly inform Sentinel's AIxBio strategy and resource allocation.

Stream overview

Topic areas:

  • Securing biological data to reduce risks from biological AI models
  • Reducing risks from biological AI models
  • Reducing risks arising from the interactions between GPAIs and biological AI models

Objective types:

  • Increase policy readiness of a policy intervention (e.g. risk-based governance of bio data)
  • Increase readiness of a technical or process intervention (e.g. new bio AI model input/output classifiers)
  • Reducing uncertainties that block technical/policy progress (e.g. how bio data links to dual use capabilities, the potential role of synthetic data)
  • Increase international diffusion of progress to key jurisdictions
  • Achieve buy-in for promising interventions from new and influential stakeholders
  • Improve situational awareness (e.g. mapping future data assets, reducing blind spots like proprietary datasets)

I may update later with more specific projects.

AIxBio projects - technical or policy. Priorities include the security of new and existing biological data, the security of large biological AI models, AI creation of biological AI tools, strategy for a world with biological superintelligence.

Mentors

Toby Webster
Sentinel Bio
,
Program Director
London
Policy and Governance
Biosecurity
Capability and Propensity Evaluations

Toby Webster is a program director at Sentinel Bio, leading work on risks at the intersection of AI and engineering biology. Previously, Webster studied biological AI model security at RAND Europe.

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Mentorship style

Fellows we are looking for

A range of skill mixes is appropriate for the types of work I am interested in, including both technical and policy.

Project selection

Streams

The Winter 2027 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.

Empirical
London
Empirical
London
Empirical
Montreal
Empirical
SF Bay Area
Empirical
Theory
Founding and Field-Building
Policy and Governance
SF Bay Area
Empirical
Systems Security
London
Empirical
Washington, D.C.
Policy and Governance
Washington, D.C.
Policy and Governance
SF Bay Area
Strategy and Forecasting
Policy and Governance
SF Bay Area
Founding and Field-Building
Washington, D.C.
Biosecurity
Empirical
London
Empirical
London
Empirical