precautionary approach
Accountability of Generative AI: Exploring a Precautionary Approach for "Artificially Created Nature"
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.
Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation
Everyone wants to be safe. But paradoxically, sometimes the policies we implement to guarantee our safety end up making us much worse off than if we had done nothing at all. It is counterintuitive, but this is the well-established calculus of the world of risk analysis. When we consider the future of AI and the public policies that will shape its evolution, it is vital to keep that insight in mind. While AI-enabled technologies can pose some risks that should be taken seriously, it is important that public policy not freeze the development of life-enriching innovations in this space based on speculative fears of an uncertain future.
A Precautionary Approach to Artificial Intelligence, by Maciej Kuziemski
FLORENCE – For policymakers anywhere, the best way to make decisions is to base them on evidence, however imperfect the available data may be. But what should leaders do when facts are scarce or non-existent? That is the quandary facing those who must grapple with the fallout of "advanced predictive algorithms" – the binary building blocks of machine learning and artificial intelligence (AI). In academic circles, AI-minded scholars are either "singularitarians" or "presentists." Singularitarians generally argue that while AI technologies pose an existential threat to humanity, the benefits outweigh the costs.