This preference challenges the conventional notion that human decision-makers are favoured in decisions involving a ‘moral’ component such as fairness.
A new study has revealed that people prefer Artificial Intelligence (AI) over humans when it comes to redistributive decisions.
As technology continues to integrate into various aspects of public and private decision-making, understanding public perception and satisfaction and ensuring the transparency and accountability of algorithms will be key to their acceptance and effectiveness.
The study, conducted by researchers from the СƵ and the , looked into public attitudes towards algorithmic versus human decision-making and examined the impact of potential discrimination on these preferences.
An online decision experiment was used to study the preference for human or AI decision makers, where the earnings of two people could be redistributed between them after a series of tasks were performed. Over 200 participants from the UK and Germany were asked to vote on whether they wanted a human or an algorithm (AI) to make the decision that would determine how much money they earned.
Contrary to previous findings, over 60 per cent of participants chose AI over a human to decide how the earnings were redistributed. Participants favoured the algorithm, irrespective of potential discrimination. This preference challenges the conventional notion that human decision-makers are favoured in decisions involving a ‘moral’ component such as fairness.
However, despite the preference for algorithms, when rating the decisions taken participants were less satisfied with the decision of the AI and found it less ‘fair’ than the one taken by humans.
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.
Subjective ratings of the decisions are mainly driven by participants’ own material interests and fairness ideals. Participants could tolerate any reasonable deviation between the actual decision and their ideals but reacted very strongly and negatively to redistribution decisions that were not consistent with any of the established fairness principles.
Dr Wolfgang Luhan, Associate Professor of Behavioural Economics in the School of Accounting, Economics and Finance and corresponding author of the study, said: “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.”
The study is published in the journal .
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