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While artificial intelligence (AI) holds promise for addressing societalchallenges, issues of exactly which tasks to automate and to what extent to doso remain understudied. We approach this problem of task delegability from ahuman-centered perspective by developing a framework on human perception oftask delegation to AI. We consider four high-level factors that can contributeto a delegation decision: motivation, difficulty, risk, and trust. To obtain anempirical understanding of human preferences in different tasks, we build adataset of 100 tasks from academic papers, popular media portrayal of AI, andeveryday life, and administer a survey based on our proposed framework. We findlittle preference for full AI control and a strong preference formachine-in-the-loop designs, in which humans play the leading role. Among thefour factors, trust is the most correlated with human preferences of optimalhuman-machine delegation. This framework represents a first step towardscharacterizing human preferences of AI automation across tasks. We hope thiswork encourages future efforts towards understanding such individual attitudes;our goal is to inform the public and the AI research community rather thandictating any direction in technology development.

Ask Not What AI Can Do, But What AI Should Do: Towards a Framework of Task Delegability