Using human-in-the-loop and explainable AI to envisage new future work practices

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Abstract

In this paper, we discuss the trends and challenges of the integration of Artificial Intelligence (AI) methods in the workplace. An important aspect towards creating positive AI futures in the workplace is the design of fair, reliable and trustworthy AI systems which aim to augment human performance and perception, instead of replacing them by acting in an automatic and non-transparent way. Research in Human-AI Interaction has proposed frameworks and guidelines to design transparent and trustworthy human-AI interactions. Considering such frameworks, we discuss the potential benefits of applying human-in-the-loop (HITL) and explainable AI (XAI) methods to define a new design space for the future of work. We illustrate how such methods can create new interactions and dynamics between human users and AI in future work practices.

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Tsiakas, K., & Murray-Rust, D. (2022). Using human-in-the-loop and explainable AI to envisage new future work practices. In ACM International Conference Proceeding Series (pp. 588–594). Association for Computing Machinery. https://doi.org/10.1145/3529190.3534779

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