Filling gaps in trustworthy development of AI

Incident sharing, auditing, and other concrete mechanisms could help verify the trustworthiness of actors

An agent-based model clarifies the importance of functional and developmental integration in shaping brain evolution

Computer simulation explores brain size evolution.

Towards Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

Ten mechanisms for supporting the verification of claims made by developers of AI systems.

Exploring AI Futures Through Role Play

Exploration of AI futures and impacts through participatory role-play simulation.

Autonomy and machine learning at the interface of nuclear weapons, computers and people

Describes new threats posed by the introduction of ML at the interfaces between people and nuclear weapons systems (and related systems), and proposes policy responses.

Method Pluralism, Method Mismatch & Method Bias

Modelling different approaches to evidence gathering.

Surveying Safety-relevant AI Characteristics

Survey of known and potential safety-relevant AI characteristics, covering internal characteristics, system-environment effects, and training.

Exploring artificial intelligence futures

Reviews different methods to explore AI futures, including fiction, single-discipline studies, several multidisciplinary approches, and interactive methods.

Mavericks and Lotteries

Summarises academic arguments for funding science by lottery, and compares these to real implementations of the policy.

Beyond Brain Size: Uncovering the Neural Correlates of Behavioral and Cognitive Specialization

Limits of brain size measures in the study of brain-behavior across species, and suggestions for alternative research approaches.

Policy Considerations for Random Allocation of Research Funds

Expanding on the policy implications of the model results in my PhD thesis.

Classifying global catastrophic risks

Classifying GCRs based on critical system breached, global spread mechanism, and human prevention and mitigation failure.

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Risks and responses to near-term malicious use of AI/ML.

Centralized funding and epistemic exploration

Extension of the model developed in my PhD thesis.

Science funding is a gamble so let’s give out money by lottery

Popular version of the argument made in my PhD thesis.

Funding science by lottery

Early quick overview of the argument made in my PhD thesis.

Breaking the grant cycle: On the rational allocation of public resources to scientific research projects

Agent-based simulations of hypothetical research communities show random allocation can outperform selection by potential merit under certain conditions.

Why We Still Need Grant Peer Review

A comment on “From funding agencies to scientific agency” by Bollen et al.