Algorithmic bias
Algorithmic bias describes systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. Bias can emerge due to many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. Algorithmic bias is found across platforms, including but not limited to search engine results and social media platforms, and can have impacts ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only
academic discipline
AI biasAlgorithmic discriminationAlgorithmic fairnessArtificial intelligence biasBias in artificial intelligenceBias in facial recognitionBias in machine learningBiased algorithmsBiased artificial intelligenceBiased computer systemsMachine learning biasRacial bias in AIRacial bias in facial recognition
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ACM Conference on Fairness, Accountability, and TransparencyAI biasAP Computer Science PrinciplesAbeba BirhaneAlgorithmic Justice LeagueAlgorithmic discriminationAlgorithmic fairnessAlgorithms of OppressionAnima AnandkumarApplications of artificial intelligenceArtificial intelligenceArtificial intelligence biasArtificial intelligence in healthcareAutomation biasBanjo (application)BiasBias in artificial intelligenceBias in facial recognitionBias in machine learningBiased algorithmsBiased artificial intelligenceBiased computer systemsCOMPAS (software)Catherine TuckerCensorship of FacebookCyber racismDeborah RajiDigital divideEcho chamber (media)Ethics of artificial intelligenceEthics of technologyFairnessFairness (machine learning)Filter bubbleFreedom of informationGarbage in, garbage outGovernment by algorithmHimabindu LakkarajuImageNetInductive bias
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Algorithmic bias
Algorithmic bias describes systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. Bias can emerge due to many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. Algorithmic bias is found across platforms, including but not limited to search engine results and social media platforms, and can have impacts ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only
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Algorithmic bias describes sys ...... een users of the same service.
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Algorithmic bias describes sys ...... rimination. This bias has only
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Algorithmic bias
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