Study Shows Majority Prefer AI for Redistributive Decisions

London, UK (SPX) Jul 17, 2024 - A recent study has indicated that people favor Artificial Intelligence (AI) over humans when making redistributive decisions.

As technology increasingly becomes part of both public and private decision-making processes, it is crucial to understand public perception, satisfaction, and the need for transparency and accountability in algorithmic systems to ensure their acceptance and effectiveness.

The research, conducted by teams from the University of Portsmouth and the Max Planck Institute for Innovation and Competition, explored public attitudes towards decision-making by algorithms versus humans, focusing on potential discrimination's impact on these preferences.

An online experiment was designed where over 200 participants from the UK and Germany voted on whether a human or an AI should decide the redistribution of earnings after completing a series of tasks. The results showed that more than 60% of participants preferred AI over humans for deciding the redistribution of their earnings, regardless of potential discrimination. This finding challenges the common belief that humans are preferred for decisions involving moral considerations like fairness.

Despite the preference for AI, participants rated the AI's decisions as less satisfying and less fair compared to those made by humans. Subjective ratings were influenced primarily by participants' material interests and fairness ideals. They were tolerant of reasonable deviations from their ideals but reacted negatively to decisions that did not align with any established fairness principles.

Dr. Wolfgang Luhan, Associate Professor of Behavioural Economics at the University of Portsmouth and corresponding author of the study, explained, "Our research suggests that while people are open to the idea of algorithmic decision-makers, especially due to their potential for unbiased decisions, the actual performance and the ability to explain how they decide play crucial roles in acceptance. Especially in moral decision-making contexts, the transparency and accountability of algorithms are vital.

"Many companies are already using AI for hiring decisions and compensation planning, and public bodies are employing AI in policing and parole strategies. Our findings suggest that, with improvements in algorithm consistency, the public may increasingly support algorithmic decision makers even in morally significant areas.

"If the right AI approach is taken, this could actually improve the acceptance of policies and managerial choices such as pay rises or bonus payments."

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