Events

Professor Adelle Xue Yang
Assistant Professor of Marketing
NUS Business School
National University of Singapore

ABSTRACT

The reduction of decision speed is a central goal in the development of AI (artificial intelligence) applications. However, do people always prefer a faster AI decision-maker? Across twelve pre-registered experiments (N = 6,971), we find that people have greater appreciation for an AI decision-maker when it is slower at resolving moral tradeoffs than structurally identical non-moral tradeoffs. The effect was replicated across a variety of classic moral dilemmas (e.g., trolley problem) as well as generic resource-allocation problems. The effect shows insensitivity to decision consequences, and holds even when slower moral decision-making produces non-adaptive outcomes. Critically, the effect no longer emerges when either the “moral” or “tradeoff” component is removed from the slower decision. Results from moderation studies and measured process variables consistently suggest that the effect is attributable primarily to overgeneralized moral intuitions about “good” moral decision-makers, rather than specific inferences about the AI decision-makers’ “mind” or decision quality per se. Additional analyses of text responses using a large language model (LLM) corroborate these mechanism insights. Theoretical and practical implications are discussed.