My work pictured by AI – Diana Mazzarella
"Speaker trustworthiness: Shall confidence match evidence?" - By Diana Mazzarella
What is this work about? Speakers can convey information with varying degrees of confidence, and this typically impacts the extent to which their messages are accepted as true. Confident speakers are more likely to be believed than unconfident one. Crucially, though, this benefit comes with additional risks. Confident speakers put their reputation at stake: if their message turns out to be false, they are more likely to suffer a repetitional loss than unconfident speakers. In this paper, we investigate the extent to which perceived speaker trustworthiness is affected by evidence. Our experiments show that the reputation of confident speakers is not damaged when their false claims are supported by strong evidence, but it is damaged when their true claims are based on weak evidence.
The first word that came to mind when seeing the AI-generated picture? Trust me.