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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 11: AAAI-21 Technical Tracks 11

Debiasing Evaluations That Are Biased by Evaluations

February 1, 2023

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Authors

Jingyan Wang

Carnegie Mellon University


Ivan Stelmakh

Carnegie Mellon University


Yuting Wei

Carnegie Mellon University


Nihar B. Shah

Carnegie Mellon University


DOI:

10.1609/aaai.v35i11.17214


Abstract:

It is common to evaluate a set of items by soliciting people to rate them. For example, universities ask students to rate the teaching quality of their instructors, and conference organizers ask authors of submissions to evaluate the quality of the reviews. However, in these applications, students often give a higher rating to a course if they receive higher grades in a course, and authors often give a higher rating to the reviews if their papers are accepted to the conference. In this work, we call these external factors the "outcome" experienced by people, and consider the problem of mitigating these outcome-induced biases in the given ratings when some information about the outcome is available. We formulate the information about the outcome as a known partial ordering on the bias. We propose a debiasing method by solving a regularized optimization problem under this ordering constraint, and also provide a carefully designed cross-validation method that adaptively chooses the appropriate amount of regularization. We provide theoretical guarantees on the performance of our algorithm, as well as experimental evaluations.

Topics: AAAI

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HOW TO CITE:

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah Debiasing Evaluations That Are Biased by Evaluations Proceedings of the AAAI Conference on Artificial Intelligence (2021) 10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah Debiasing Evaluations That Are Biased by Evaluations AAAI 2021, 10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah (2021). Debiasing Evaluations That Are Biased by Evaluations. Proceedings of the AAAI Conference on Artificial Intelligence, 10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. Debiasing Evaluations That Are Biased by Evaluations. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. 2021. Debiasing Evaluations That Are Biased by Evaluations. "Proceedings of the AAAI Conference on Artificial Intelligence". 10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. (2021) "Debiasing Evaluations That Are Biased by Evaluations", Proceedings of the AAAI Conference on Artificial Intelligence, p.10120-10128

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah, "Debiasing Evaluations That Are Biased by Evaluations", AAAI, p.10120-10128, 2021.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. "Debiasing Evaluations That Are Biased by Evaluations". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. "Debiasing Evaluations That Are Biased by Evaluations". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 10120-10128.

Jingyan Wang||Ivan Stelmakh||Yuting Wei||Nihar B. Shah. Debiasing Evaluations That Are Biased by Evaluations. AAAI[Internet]. 2021[cited 2023]; 10120-10128.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
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