Accountability of Generative AI: Exploring a Precautionary Approach for "Artificially Created Nature"

TL;DR

This paper discusses the accountability challenges of generative AI, emphasizing transparency limitations, proposing a precautionary approach, and advocating for citizen participation to manage AI risks.

Contribution

It introduces a precautionary principle framework for AI accountability and highlights the importance of citizen involvement in addressing generative AI risks.

Findings

Transparency alone is insufficient for AI accountability.

Generative AI can be viewed as 'artificially created nature' without full transparency.

Citizen participation is essential for managing AI risks.

Abstract

The rapid development of generative artificial intelligence (AI) technologies raises concerns about the accountability of sociotechnical systems. Current generative AI systems rely on complex mechanisms that make it difficult for even experts to fully trace the reasons behind the outputs. This paper first examines existing research on AI transparency and accountability and argues that transparency is not a sufficient condition for accountability but can contribute to its improvement. We then discuss that if it is not possible to make generative AI transparent, generative AI technology becomes ``artificially created nature'' in a metaphorical sense, and suggest using the precautionary principle approach to consider AI risks. Finally, we propose that a platform for citizen participation is needed to address the risks of generative AI.