Analysis of hidden feedback loops in continuous machine learning systems

• URL: http://arxiv.org/abs/2101.05673v2
• Date: Sun, 17 Jan 2021 18:38:51 GMT
• Title: Analysis of hidden feedback loops in continuous machine learning systems
• Authors: Anton Khritankov
• Abstract summary: We signify a problem of implicit feedback loops, demonstrate how they intervene with user behavior on an exemplary housing prices prediction system. Based on a preliminary model, we highlight conditions when such feedback loops arise and discuss possible solution approaches.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this concept paper, we discuss intricacies of specifying and verifying the quality of continuous and lifelong learning artificial intelligence systems as they interact with and influence their environment causing a so-called concept drift. We signify a problem of implicit feedback loops, demonstrate how they intervene with user behavior on an exemplary housing prices prediction system. Based on a preliminary model, we highlight conditions when such feedback loops arise and discuss possible solution approaches.

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