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Placing a human in the loop may abate the risks of deploying AI systems in safety-critical settings (e.g., a clinician working with a medical AI system).
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Dan Hendrycks and Thomas Dietterich · 2019
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Rafael Müller, Simon Kornblith, and Geoffrey E Hinton · 2019
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Can You Trust Your Model’s Uncertainty? Evaluating Predictive Uncertainty under Dataset Shift
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Eliciting and learning with soft labels from every annotator
Katherine M Collins, Umang Bhatt, and Adrian Weller · 2022
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Mandeep K. Dhami and David R. Mandel · 2022
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Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frederic Precioso, Stefano Melacci, Adrian Weller, Pietro Lio, and Mateja Jamnik · 2022
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Human uncertainty makes classification more robust
Joshua C Peterson, Ruairidh M Battleday, Thomas L Griffiths, and Olga Russakovsky · 2019
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Probabilistic biases meet the bayesian brain
Nick Chater, Jian-Qiao Zhu, Jake Spicer, Joakim Sundh, Pablo León-Villagrá, and Adam Sanborn · 2020
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Simple and principled uncertainty estimation with deterministic deep learning via distance awareness
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Bryan Wilder, Eric Horvitz, and Ece Kamar · 2020
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Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability
Vikram V Ramaswamy, Sunnie SY Kim, Ruth Fong, and Olga Russakovsky · 2022
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Ambiguous images with human judgments for robust visual event classification
Kate Sanders, Reno Kriz, Anqi Liu, and Benjamin Van Durme · 2022
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Claudia R Schneider, Alexandra LJ Freeman, David Spiegelhalter, and Sander van der Linden · 2022
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Learning from uncertain concepts via test time interventions
Ivaxi Sheth, Aamer Abdul Rahman, Laya Rafiee Sevyeri, Mohammad Havaei, and Samira Ebrahimi Kahou · 2022
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Human-centered AI
Ben Shneiderman · 2022
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Bayesian modeling of human–ai complementarity
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On the informativeness of supervision signals, 2022
Ilia Sucholutsky, Raja Marjieh, Nori Jacoby, and Thomas L. Griffiths · 2022
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Yue Yang, Artemis Panagopoulou, Shenghao Zhou, Daniel Jin, Chris Callison-Burch, and Mark Yatskar · 2022
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Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley Love, and Adrian Weller · 2023
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Towards robust metrics for concept representation evaluation
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Label-free concept bottleneck models
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Post-hoc concept bottleneck models, 2023
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Navigating the grey area: Expressions of overconfidence and uncertainty in language models
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