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Auflistung nach Schlagwort "human-centered AI"

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  • Zeitschriftenartikel
    Towards Human-Centered AI: Psychological concepts as foundation for empirical XAI research
    (it - Information Technology: Vol. 64, No. 1-2, 2022) Weitz, Katharina
    Human-Centered AI is a widely requested goal for AI applications. To reach this is explainable AI promises to help humans to understand the inner workings and decisions of AI systems. While different XAI techniques have been developed to shed light on AI systems, it is still unclear how end-users with no experience in machine learning perceive these. Psychological concepts like trust, mental models, and self-efficacy can serve as instruments to evaluate XAI approaches in empirical studies with end-users. First results in applications for education, healthcare, and industry suggest that one XAI does not fit all. Instead, the design of XAI has to consider user needs, personal background, and the specific task of the AI system.
  • Konferenzbeitrag
    Towards Warranted Trust: A Model on the Relation Between Actual and Perceived System Trustworthiness
    (Mensch und Computer 2021 - Tagungsband, 2021) Schlicker, Nadine Frauke; Langer, Markus
    The public discussion about trustworthy AI is fueling research on new methods to make AI explainable and fair. However, users may incorrectly assess system trustworthiness and could consequently overtrust untrustworthy systems or undertrust trustworthy systems. In order to understand what determines accurate assessments of system trustworthiness we apply Brunswik’s Lens Model and the Realistic Accuracy Model. The assumption is that the actual trustworthiness of a system cannot be accessed directly and is therefore inferred via cues to form a user’s perceived trustworthiness. The accuracy of trustworthiness assessment then depends on: cue relevance, availability, detection, and utilization. We describe how the model can be used to systematically investigate determinants that increase the match between system’s actual trustworthiness and user’s perceived trustworthiness in order to achieve warranted trust.