Behavioral AI

Organizations and governments around the globe are integrating Artificial Intelligence (AI) algorithms across different sectors to enhance products and services, as well as to refine governance for citizens. There is a pressing need for a research agenda focused on developing a behavioral science of AI to gain insights into how the public perceives, evaluates, decides on, and interacts with AI technologies.

Lay, professional and Artificial Intelligence perspectives all say the same – number of lives in risky medical decisions matters in gain frames but not in loss frames

The number of lives moderated risk-aversion in gain frame (people were risk-neutral for low number of lives and risk-averse for high number of lives). However, in the loss frame, risk-seeking was observed irrespective of how many lives were at stake. This pattern was consistent across laypersons and medical professionals, further extended to preferences for choices that medical professionals and artificial intelligence programmes should make. It shows how valuation of lives can be dependent on decision frames and framing biases that could impact medical decisions, which in turn could impact health and wellbeing of citizens.