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On the Influence of Explainable AI on Automation Bias

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arxiv 2204.08859 v1 pith:5OWL2GUR submitted 2022-04-19 cs.HC cs.AI

classification cs.HCcs.AI
keywords biasautomationdesignexplainablehoweverhumanhumansinfluence
verification ladder T0 review T1 audit T2 compute T3 formal
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Artificial intelligence (AI) is gaining momentum, and its importance for the future of work in many areas, such as medicine and banking, is continuously rising. However, insights on the effective collaboration of humans and AI are still rare. Typically, AI supports humans in decision-making by addressing human limitations. However, it may also evoke human bias, especially in the form of automation bias as an over-reliance on AI advice. We aim to shed light on the potential to influence automation bias by explainable AI (XAI). In this pre-test, we derive a research model and describe our study design. Subsequentially, we conduct an online experiment with regard to hotel review classifications and discuss first results. We expect our research to contribute to the design and development of safe hybrid intelligence systems.

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