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Towards Understanding AI Delegation: The Role of Self-Efficacy and Visual Processing Ability

Westphal, Monika; Hemmer, Patrick 1; Vössing, Michael ORCID iD icon 1; Schemmer, Max 1; Vetter, Sebastian; Satzger, Gerhard ORCID iD icon 1
1 Karlsruhe Service Research Institute (KSRI), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Recent work has proposed artificial intelligence (AI) models that can learn to decide whether to make a prediction for a task instance or to delegate it to a human by considering both parties’ capabilities. In simulations with synthetically generated or context-independent human predictions, delegation can help improve the performance of human-AI teams—compared to humans or the AI model completing the task alone. However, so far, it remains unclear how humans perform and how they perceive the task when individual instances of a task are delegated to them by an AI model. In an experimental study with 196 participants, we show that task performance and task satisfaction improve for the instances delegated by the AI model, regardless of whether humans are aware of the delegation. Additionally, we identify humans’ increased levels of self-efficacy as the underlying mechanism for these improvements in performance and satisfaction, and one dimension of cognitive ability as a moderator to this effect. In particular, AI delegation can buffer potential negative effects on task performance and task satisfaction for humans with low visual processing ability. ... mehr


Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Karlsruhe Service Research Institute (KSRI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2160-6455, 2160-6463
KITopen-ID: 1000175232
Erschienen in ACM Transactions on Interactive Intelligent Systems
Verlag Association for Computing Machinery (ACM)
Vorab online veröffentlicht am 15.10.2024
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