The AI field is still developing its understanding of policy implications, and there's a growing need for researchers to engage in policy discussions and consider the societal impact of their work. People in both AI research and civil society are often concerned about fairness, but they operate under different constraints.

There's a need for better collaboration between AI researchers and policy experts to ensure that technical developments align with societal needs and ethical considerations.

The AI industry suffers from a lack of rigorous evaluations and tests that demonstrate the frontier of model capabilities.

Expert evaluations are valuable, but they must be complemented by broader community input to avoid bias in AI assessments.

Expert evaluations are valuable, but they must be complemented by broader community input to avoid bias in AI assessments.

Open publishing in AI research is crucial for realistic public policy and understanding the current state of the field, which benefits everyone involved.

The scientific community often struggles to integrate new discoveries into existing models, preferring to fit new information into pre-existing frameworks rather than allowing the data to guide the narrative.

The diversity of opinions and expertise in the community is crucial for accurately evaluating AI models and their capabilities.

The diversity of opinions and expertise in the community is crucial for accurately evaluating AI models and their capabilities.