Trusting AI
Abstract Here is a very popular view on what user rational trust in AI requires: the Explanation View of AI Trust, whereby user rational trust in AI requires an explanation of why the AI has reached the conclusion it has. The authors of this chapter think that the Explanation View of AI Trust is wrong. It is not true of trust in general that rational trust (even typically) requires understanding why, and it is not the case that AI communication generates any special normative requirement that there should be an explanation why that grounds rational trust. This doesn’t mean that the authors think there is nothing to be gained by explainable AI (XAI)—they prefer explainability, all else being equal! But understanding how to increase trust (when appropriate) in AI requires the right diagnosis. In order to understand how to increase trust in AI, the authors think it’s better to focus not on AI explainability but instead on AI trustworthiness. That is, in this chapter, they defend what they call the Simple View of AI Trust, whereby user rational trust in AI requires AI trustworthiness.