Using Cognitive Models to Understand and Counteract the Effect of Self-Induced Bias on Recommendation Algorithms

Recommendation algorithms trained on a training set containing sub-optimal decisions may increase the likelihood of making more bad decisions in the future. We call this harmful effect self-induced bias, to emphasize that the bias is driven directly by the user’s past choices. In order to better und...

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Veröffentlicht in:	Journal of Artificial Intelligence and Soft Computing Research 2023-03, Vol.13 (2), p.73-94
Hauptverfasser:	Pawłowska, Justyna, Rydzewska, Klara, Wierzbicki, Adam
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Benchmarks Bias Cognitive ability Cognitive models Decision making Filtration Psychology Simulation
Online-Zugang:	Volltext
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