Understanding the Implications and Processes of Artificial Intelligence

3min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

The chapter explores the necessity of discussing the openness and comprehension of artificial intelligence (AI) in various contexts, likening it to testing a drug. It emphasizes the importance of understanding the underlying processes of AI and highlights the potential value of augmenting human decision-making with AI, while stressing the need for thorough comprehension of its implications before widespread use.

Many AIs are 'black box' in nature, meaning that part of all of the underlying structure is obfuscated, either intentionally to protect proprietary information, due to the sheer complexity of the model, or both. This can be problematic in situations where people are harmed by decisions made by AI but left without recourse to challenge them.

Many researchers in search of solutions have coalesced around a concept called Explainable AI, but this too has its issues. Notably, that there is no real consensus on what it is or how it should be achieved. So how do we deal with these black boxes? In this podcast, we try to find out.

Subscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.

Hosted on Acast. See acast.com/privacy for more information.