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Nature Human Behavior: Understanding, Explaining, and Utilizing Medical Artificial Intelligence

Nature Human Behavior recently published a study co-researched by Chiara Longoni, Assistant Professor of Marketing, and Carey Morewedge, Professor of Marketing on their findings examining peoples’ understanding of medical AI technologies.

Chiara Longoni

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Nature Human Behavior recently published a study co-researched by Chiara Longoni, Assistant Professor of Marketing, and Carey Morewedge, Professor of Marketing on their findings examining peoples’ understanding of medical AI technologies.

The study found that people are often reluctant to be treated through medical artificial intelligence even though it is cost-effective and often outperforms human providers. The researchers found that this resistance is due to the “subjective difficulty of understanding algorithms” which in turn leads people to believe they better understand decisions made by humans. The researchers conclude that their results “suggest an egocentric bias in this illusion of understanding, that the illusion may loom largest in assessments of people – the causal systems most similar to ourselves.”

Chiara Longoni is a behavioral scientist and Assistant Professor of Marketing at Boston University Questrom School of Business. Her research explores (i) the social impact of Artificial Intelligence and technology (ii) sustainability, (iii) consumer and societal welfare. Substantively, she specializes in issues related to medical decision making, sustainability in consumer and firm behavior, and messaging to promote consumer and societal well-being. Her work has been published, among others, in the Journal of Consumer Research, the Journal of Marketing Research, the Journal of Marketing, Nature Human Behavior, and Nature Communications. Her work has also been featured in popular press outlets such as The Times, Forbes, Fortune Magazine, and Harvard Business Review, in practitioner outlets such as Infermedica and Artificial Intelligence in Medicine, and podcasts such as Man & Machine and Dividing Into Data.