Do you comply with AI? -- Personalized explanations of learning algorithms and their impact on employees' compliance behavior
This addresses the problem of low compliance with AI recommendations among employees, which impacts task performance, but the work appears incremental as it builds on existing concepts of personalization.
The study investigated how personalized explanations of AI learning algorithms affect employees' compliance behavior, finding preliminary evidence that such personalization is important in industry settings.
Machine Learning algorithms are technological key enablers for artificial intelligence (AI). Due to the inherent complexity, these learning algorithms represent black boxes and are difficult to comprehend, therefore influencing compliance behavior. Hence, compliance with the recommendations of such artifacts, which can impact employees' task performance significantly, is still subject to research - and personalization of AI explanations seems to be a promising concept in this regard. In our work, we hypothesize that, based on varying backgrounds like training, domain knowledge and demographic characteristics, individuals have different understandings and hence mental models about the learning algorithm. Personalization of AI explanations, related to the individuals' mental models, may thus be an instrument to affect compliance and therefore employee task performance. Our preliminary results already indicate the importance of personalized explanations in industry settings and emphasize the importance of this research endeavor.