Bias on the web

255 citations recorded by the source corpus.

How researchers see this paper

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A Survey on Bias and Fairness in Machine Learning (2019, background): “sented [8]. For example, on the Web everything seen by the user can get clicks, while everything else gets no click. And it could be the case that the user does not see all the information on the Web [8]. Ranking Bias. The top-ranked result will attract more clicks than the others because it is both”
Bias in data‐driven artificial intelligence systems—An introductory survey (2020, background): “By Web Scientists.”
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation (2023, background): “As has been shown in the previous dimension, bias is not only algorithmic, but extends beyond the limits of models in a vicious cycle: starting with human activity bias, data bias, leads to sampling bias on the web (specially to be considered in the use of data to learn generative models), algorithm”
Bridging the Gap Between Ethics and Practice (2020, background): “Baeza-Yates [5] described additional forms of bias, such as geography, language, and culture, which were embedded in web-based algorithms, databases, and user interfaces.”
Generative artificial intelligence (2023, background): “Furthermore, social bias as a form of data bias can cause distorted views in generated texts or images and should be considered as well as mitigated (Baeza-Yates, 2018).”