Governance

What forms of governance can we use to keep AI systems safe for personal use and advance the common good in society?

Effective governance of large language models (LLMs) and other AI systems is a multifaceted challenge that requires strategies grounded in transparency, accountability, and inclusivity. Transparency is essential in understanding how an AI system makes decisions. This includes disclosing the types and sources of data used for training, the algorithmic mechanisms, and the biases that might be embedded within the model. Implementing a standardized AI transparency reporting, similar to environmental, social, and governance (ESG) reporting for corporations, can be an effective strategy. This would help stakeholders understand how the AI system operates and inform potential areas for improvement.

Accountability is another key pillar of AI governance. AI developers should be accountable for the performance and behavior of their systems. This requires robust oversight and regulation, possibly through a dedicated body with sufficient technical expertise to assess AI systems. Accountability also implies recourse - a system must be in place for addressing harm or grievances that arise from the use of these technologies. A robust feedback mechanism would allow users and affected parties to voice concerns, which could then be addressed in a timely and efficient manner.

Lastly, governance strategies should be inclusive and respectful of a broad range of perspectives. AI does not operate in a vacuum, but in complex social systems, with diverse cultural contexts and values. Therefore, a range of voices, including those from marginalized communities, should be included in the decision-making process. This could be achieved through public consultation processes, third-party audits, or partnerships with civic organizations. By integrating diverse perspectives, we can work towards AI governance that is not only technically robust, but also ethically sound and socially beneficial.

I discuss this topic further in the chapter Risks.