ArticleProceedings of the National Academy of Sciences of the United States of America2022
Propagation of societal gender inequality by internet search algorithms.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 91 citations in OpenAlex.
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- Navigating the light and shadow of scientific publishing faced with machine learning and generative AI.European journal of pain (London, England) · 2025Review
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- Exploring condition in which people accept AI over human judgements on justified defection.Scientific reports · 2025Article
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- Transmission of societal stereotypes to individual-level prejudice through instrumental learning.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Article
- Challenges in Understanding Human-Algorithm Entanglement During Online Information Consumption.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Article
- Algorithmic Content Recommendations on a Video-Sharing Platform Used by Children.JAMA network open · 2024Article
- Extracting intersectional stereotypes from embeddings: Developing and validating the Flexible Intersectional Stereotype Extraction procedure.PNAS nexus · 2024Article
- Online images amplify gender bias.Nature · 2024Article
- Article
- Analyzing the impact of socioeconomic indicators on gender inequality in Sri Lanka: A machine learning-based approach.PloS one · 2024Article
- Gender stereotypes embedded in natural language are stronger in more economically developed and individualistic countries.PNAS nexus · 2023Article
- Propagation of societal gender inequality by internet search algorithms.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Humans increasingly rely on artificial intelligence (AI) for efficient and objective decision-making, yet there is increasing concern that algorithms used by modern AI systems produce discriminatory outputs, presumably because they are trained on data in which societal biases are embedded. As a consequence, their use by human decision makers may result in the propagation, rather than reduction, of existing disparities. To assess this hypothesis empirically, we tested the relation between societal gender inequality and algorithmic search output and then examined the effect of this output on human decision-making. First, in two multinational samples (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.