Hard Choices in Artificial Intelligence
13Tom Gilbert (Cornell University)
https://simons.berkeley.edu/talks/tbd-434
AI and Humanity
As AI systems are integrated into high stakes social domains, researchers now examine how to design and operate them in a safe and ethical manner. However, the criteria for identifying and diagnosing safety risks in complex social contexts remain unclear and contested. In this talk, I examine the vagueness in debates about the safety and ethical behavior of AI systems. I show how this vagueness cannot be resolved through mathematical formalism alone, instead requiring deliberation about the politics of development as well as the context of deployment. Drawing from a new sociotechnical lexicon, I redefine vagueness in terms of distinct design challenges at key stages in AI system development. The resulting framework of Hard Choices in Artificial Intelligence (HCAI) shows what is at stake when navigating these dilemmas by 1) specifying distinct forms of sociotechnical judgment that correspond to each stage; 2) suggesting mechanisms for feedback that ensure safety issues are exhaustively addressed. As such, HCAI contributes to a timely debate about the status of AI development in democratic societies, arguing that deliberation should be the goal of AI Safety, not just the procedure by which it is ensured.