The rise of interactive intelligent systems has surfaced the need to make system reasoning and decision-making understandable to users through means such as ...
This paper presents and discusses possible dark patterns of explainability, transparency and control building on dark UX design patterns by Grey et al.
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Dark Patterns of Explainability, Transparency, and User Control for Intelligent Systems. M. Chromik, M. Eiband, S. Völkel, and D. Buschek.
Explainability pitfalls: Beyond dark patterns in explainable AI
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Jun 14, 2024 · Explainability pitfalls (EPs) are negative effects of AI systems that arise without the intention to deceive end users.
Dark Patterns of Explainability, Transparency, and User Control for Intelligent Systems. M Chromik, M Eiband, ST Völkel, D Buschek. IUI workshops 2327, 2019.
Apr 14, 2024 · Our approach follows related work that transferred deceptive patterns to the domain of explainability, transparency, and user control in ...
Dark Patterns of Explainability, Transparency, and User Control for Intelligent Systems · Michael ChromikMalin EibandS. VölkelDaniel Buschek. Computer Science.
Sep 26, 2021 · We introduce explainability pitfalls (EPs), unanticipated negative downstream effects from AI explanations manifesting even when there is no ...
Jun 14, 2024 · We discuss design and so- cietal implications around reframing AI adoption, recalibrating stakeholder empowerment, and resisting the. ''move ...
Oct 15, 2024 · We conceptually transfer several deceptive patterns from the literature to the new context of AI writing assistants.