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Artificial Intelligence Can't Be Charmed: The Effects of Impartiality on Laypeople's Algorithmic Preferences
Marius C Claudy1, Karl Aquino2, Maja Graso3
1College of Business, University College Dublin, Dublin, Ireland.
Frontiers in Psychology
|July 18, 2022
Summary
People perceive artificial intelligence (AI) as more impartial than humans for resource allocation. However, they prefer human decision-makers unless human biases are highlighted, revealing a complex acceptance of AI in decision-making.
Area of Science:
- Decision-making science
- Human-computer interaction
- Artificial intelligence ethics
Background:
- Artificial intelligence (AI) offers potential for standardized and debiased decision-making.
- Little research exists on public perception of AI in resource allocation.
- Algorithmic fairness is a key concern in AI deployment.
Purpose of the Study:
- To examine laypeople's reactions to AI making resource-allocation decisions.
- To investigate the role of perceived impartiality in AI acceptance.
- To understand preferences between human and AI decision-makers.
Main Methods:
- Empirical investigation of public perception.
- Analysis of factors influencing acceptance of AI decision-makers.
- Examination of resource allocation scenarios.
Main Results:
- People value impartiality in resource allocation decisions.
- Laypeople perceive AI as more impartial than humans.
- Despite perceived impartiality, people paradoxically prefer human decision-makers.
- Preference for humans shifts when human biases are made apparent.
Conclusions:
- Impartiality is crucial for AI acceptance in decision-making.
- AI's perceived impartiality does not automatically translate to preference.
- Highlighting human biases can increase acceptance of AI decision-makers.
- Findings have implications for AI policy and design.
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