Algorithmic information theory
Algorithm aversion is "biased assessment of an algorithm which manifests in negative behaviours and attitudes towards the algorithm compared to a human agent." It describes a phenomenon where humans reject advice from an algorithm in a case where they would accept the same advice if they thought it was coming from another human. Algorithms, such as those employing machine learning methods or various forms of artificial intelligence, are commonly used to provide recommendations or advice to human decisionmakers. For example, recommender systems are used in E-commerce to identify products a customer might like, and artificial intelligence is used in healthcare to assist with diagnosis and treatment decisions. However, humans sometimes appear to resist or reject these algorithmic recommendations more than if the recommendation had come from a human. Notably, algorithms are often capable of outperforming humans, so rejecting algorithmic advice can result in poor performance or suboptimal outcomes. This is an emerging topic and it is not completely clear why or under what circumstances people will display algorithm aversion. In some cases, people seem to be more likely to take recommendations from an algorithm than from a human, a phenomenon called algorithm appreciation. (Wikipedia).
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