Towards Fair Personalization by Avoiding Feedback Loops

• URL: http://arxiv.org/abs/2012.12862v1
• Date: Sun, 20 Dec 2020 19:28:57 GMT
• Title: Towards Fair Personalization by Avoiding Feedback Loops
• Authors: G\"okhan \c{C}apan, \"Ozge Bozal, \.Ilker G\"undo\u{g}du, Ali Taylan Cemgil
• Abstract summary: Self-reinforcing feedback loops are cause and effect of over and/or under-presentation of some content in interactive recommender systems. We consider two models that explicitly incorporate, or ignore the systematic and limited exposure to alternatives.
• Score: 3.180077164673223
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Self-reinforcing feedback loops are both cause and effect of over and/or under-presentation of some content in interactive recommender systems. This leads to erroneous user preference estimates, namely, overestimation of over-presented content while violating the right to be presented of each alternative, contrary of which we define as a fair system. We consider two models that explicitly incorporate, or ignore the systematic and limited exposure to alternatives. By simulations, we demonstrate that ignoring the systematic presentations overestimates promoted options and underestimates censored alternatives. Simply conditioning on the limited exposure is a remedy for these biases.

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