Learning with Conflicts of Interest

Financial, social, and political factors often prevent the interests of the owners of ML systems and services and their users from being perfectly aligned. ML systems often produce biased information that can influence users to make decisions that are not in their best interest. Current solution approaches require ML systems to implement protocols to mitigate their biases. However, ML system owners usually do not have any incentive to implement these protocols and often argue that it limits thei

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ethics.ai (15 May 2026), “Learning with Conflicts of Interest,” evidence record 4292, https://ethics.ai/record/4292 (originally published by arXiv).

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