LV
L.M.B. Van der Neut
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1
Conference paper
(2026)
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Malik Khadar, Julia Cecil, Leon Van Der Neut, Nikola Banovic, Kevin Baum, Stevie Chancellor, Enrico Costanza, Ujwal Gadiraju, Harmanpreet Kaur, More Authors
As AI systems are increasingly adopted in high-stakes domains such as healthcare, autonomous driving, and criminal justice, their failures may threaten human safety and rights. Human oversight of AI systems is therefore critically important as a potential safeguard to prevent harmful consequences in high-risk AI applications. The global regulatory and policy landscape for AI governance remains understandably fragmented and diverse. While frameworks like the European AI Act require human oversight for high-risk AI systems, there is currently a lack of well-defined methodologies and conceptual clarity to operationalize such oversight effectively. Independent of policy and regulation, poorly designed oversight can create dangerous illusions of safety while obscuring accountability. This interdisciplinary workshop aims to bring together researchers from various disciplines, including AI, HCI, psychology, law, and policy, to address this critical gap. We will explore the following questions: (1) What are the greatest challenges to achieving effective human oversight of AI systems? (2) How can we design AI systems that enable meaningful human oversight? (3) How do we assign responsibilities to and support the various stakeholders involved in oversight? Through talks and interactive group discussions, participants will identify oversight challenges; examine stakeholder roles; discuss supporting tools, methods, and regulatory frameworks; and establish a collaborative research agenda. Our central goal is to further a roadmap that enables effective human oversight for the responsible deployment of AI in society.
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As AI systems are increasingly adopted in high-stakes domains such as healthcare, autonomous driving, and criminal justice, their failures may threaten human safety and rights. Human oversight of AI systems is therefore critically important as a potential safeguard to prevent harmful consequences in high-risk AI applications. The global regulatory and policy landscape for AI governance remains understandably fragmented and diverse. While frameworks like the European AI Act require human oversight for high-risk AI systems, there is currently a lack of well-defined methodologies and conceptual clarity to operationalize such oversight effectively. Independent of policy and regulation, poorly designed oversight can create dangerous illusions of safety while obscuring accountability. This interdisciplinary workshop aims to bring together researchers from various disciplines, including AI, HCI, psychology, law, and policy, to address this critical gap. We will explore the following questions: (1) What are the greatest challenges to achieving effective human oversight of AI systems? (2) How can we design AI systems that enable meaningful human oversight? (3) How do we assign responsibilities to and support the various stakeholders involved in oversight? Through talks and interactive group discussions, participants will identify oversight challenges; examine stakeholder roles; discuss supporting tools, methods, and regulatory frameworks; and establish a collaborative research agenda. Our central goal is to further a roadmap that enables effective human oversight for the responsible deployment of AI in society.