A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities

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A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities ANDREA TOCCHETTI?, LORENZO CORTI?, AGATHE BALAYN?, MIREIA YURRITA, PHILIP LIPPMANN, MARCO BRAMBILLA, and JIE YANG? Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustness has been studied in many domains of AI, yet with different interpretations across domains and contexts. In this work, we systematically survey the recent progress to provide a reconciled terminology of concepts around AI robustness. We introduce three taxonomies to organize and describe the literature both from a fundamental and applied point of view: 1)robustness by methods and approaches in different phases of the machine learning pipeline; 2) robustness for specific model architectures, tasks, and systems; and in addition, 3) robustness assessment methodologies and insights, particularly the trade...

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• [1] https://arxiv.org/abs/2210.08906