Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Workers Through Explainable Artificial Intelligence

Schemmer, Max
Kühl, Niklas
Satzger, Gerhard
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While recent advances in AI-based automated decision-making have shown many benefits for businesses and society, they also come at a cost. It has long been known that a high level of automation of decisions can lead to various drawbacks, such as automation bias and deskilling. In particular, the deskilling of knowledge workers is a major issue, as they are the same people who should also train, challenge, and evolve AI. To address this issue, we conceptualize a new class of DSS, namely Intelligent Decision Assistance (IDA) based on a literature review of two different research streams---DSS and automation. IDA supports knowledge workers without influencing them through automated decision-making. Specifically, we propose to use techniques of Explainable AI (XAI) while withholding concrete AI recommendations. To test this conceptualization, we develop hypotheses on the impacts of IDA and provide the first evidence for their validity based on empirical studies in the literature.
Explainable Artificial Intelligence (XAI), automation, decision support, explainable artificial intelligence, explanations, xai
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