Governance research program
Effective AI Governance to mitigate existential risk
A research program by Convergence evaluating critical & neglected policy recommendations in AI governance
What is AI governance?
Why is it important?
Unlike more established industries, where safeguards and regulations have evolved over time, the breakneck development of frontier AI models unfolds in a near-total regulatory void. These AI systems possess staggering capabilities, fundamentally altering the world we know.
Examples of AI model capabilities
In all of these cases, there are practically no regulations governing who can develop this technology or how it can be used. With such a power vacuum, it’s essentially up to the AI labs to independently decide how they want to distribute such tremendous abilities and to whom, leaving the safety of society in private hands.
As a result, AI governance is a critical and rapidly growing field intended to manage the potential negative externalities of AI development.
examples of current AI governance initiatives
We believe that effective AI governance is the most important approach to mitigate the likelihood of a catastrophic global outcome in the next ten years.
Governance Research
What are Governance Recommendations?
For the vast majority of proposed AI governance, there is a lack of detailed analysis regarding the feasibility, implementation, effectiveness at reducing risk, or negative externalities of such a proposal.
As a result, we're launching a research agenda focused on generating comprehensive reports to analyze specific recommendations that we’ve identified to be critical & neglected.
Governance Policies we are researching:
KEY CRITERIA WE WILL CONSIDER:
Feasibility
Effectiveness
Negative Externalities
In our Governance Recommendations program, we’re creating a foundational corpus of reports of key governance recommendations we believe are feasible and worth advocating for, starting with the most critical and neglected.
For each of these recommendations, we are evaluating the current societal landscape, providing a detailed proposal for the best course of implementation, and considering key evaluative criteria on the overall viability of the proposal.
We'll be launching a State of the AI Regulatory Landscape Report and a series of technical analyses on specific AI policies in early 2024.
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