I study decision-making processes assisted by AI. Right now that means the micro scale: a person has a decision to make, an AI suggests an answer, and the person has to decide whether to follow it. Next, I want to understand what that adds up to in a macro scale: how AI is reshaping hospitals and research institutions, and what policy should do about it.
PhD candidate, IST, University of Lisbon & INESC-ID · Lisbon, Portugal
AI recommendations and explanations can enhance medical performance, but do not consistently improve efficiency. In complex clinical cases, AI explanations significantly improved diagnostic accuracy but also led to higher resource use, with participants ordering more unnecessary exams.
The impact of XAI is more pronounced in decision-making with groups. Groups rely less on incorrect AI recommendations when explanations are available, but they rely more on incorrect AI recommendations when explanations are absent, compared to individual decision-makers.
The presence of explanations in AI-Assisted Decision-Making increases AI trust but only in certain conditions. When the AI system performance is not guaranteed, the use of explanations may lead to over-reliance.