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AI can be sexist and racist — it’s time to make it fair

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  • James Zou
  • Londa Schiebinger

Abstract

Computer scientists must identify sources of bias, de-bias training data and develop artificial-intelligence algorithms that are robust to skews in the data, argue James Zou and Londa Schiebinger.

Suggested Citation

  • James Zou & Londa Schiebinger, 2018. "AI can be sexist and racist — it’s time to make it fair," Nature, Nature, vol. 559(7714), pages 324-326, July.
    • Handle: RePEc:nat:nature:v:559:y:2018:i:7714:d:10.1038_d41586-018-05707-8
    DOI: 10.1038/d41586-018-05707-8
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    Cited by:

    1. Alexandru Constantin Ciobanu & Gabriela Meè˜Nièšä‚, 2021. "Ai Ethics In Business €“ A Bibliometric Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 28, pages 169-202, December.
    2. Stefan Feuerriegel & Mateusz Dolata & Gerhard Schwabe, 2020. "Fair AI," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 379-384, August.
    3. Antoine Richard & Brice Mayag & François Talbot & Alexis Tsoukias & Yves Meinard, 2020. "What does it mean to provide decision support to a responsible and competent expert?," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 205-236, November.
    4. Feras A. Batarseh & Munisamy Gopinath & Anderson Monken, 2020. "Artificial Intelligence Methods for Evaluating Global Trade Flows," International Finance Discussion Papers 1296, Board of Governors of the Federal Reserve System (U.S.).
    5. Chien-Wei Chuang & Ariana Chang & Mingchih Chen & Maria John P. Selvamani & Ben-Chang Shia, 2022. "A Worldwide Bibliometric Analysis of Publications on Artificial Intelligence and Ethics in the Past Seven Decades," Sustainability, MDPI, vol. 14(18), pages 1-13, September.
    6. Charlene H. Chu & Simon Donato-Woodger & Shehroz S. Khan & Rune Nyrup & Kathleen Leslie & Alexandra Lyn & Tianyu Shi & Andria Bianchi & Samira Abbasgholizadeh Rahimi & Amanda Grenier, 2023. "Age-related bias and artificial intelligence: a scoping review," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    7. Premilla D’Cruz & Shuili Du & Ernesto Noronha & K. Praveen Parboteeah & Hannah Trittin-Ulbrich & Glen Whelan, 2022. "Technology, Megatrends and Work: Thoughts on the Future of Business Ethics," Journal of Business Ethics, Springer, vol. 180(3), pages 879-902, October.
    8. Nasir, Osama & Javed, Rana Tallal & Gupta, Shivam & Vinuesa, Ricardo & Qadir, Junaid, 2023. "Artificial intelligence and sustainable development goals nexus via four vantage points," Technology in Society, Elsevier, vol. 72(C).
    9. Marie McAuliffe & Jenna Blower & Ana Beduschi, 2021. "Digitalization and Artificial Intelligence in Migration and Mobility: Transnational Implications of the COVID-19 Pandemic," Societies, MDPI, vol. 11(4), pages 1-13, November.
    10. Neukam, Marion & Bollinger, Sophie, 2022. "Encouraging creative teams to integrate a sustainable approach to technology," Journal of Business Research, Elsevier, vol. 150(C), pages 354-364.
    11. Fleischer, Hannes, 2020. "Stereotypes in Services - A Systematic Literature Review to Move from Scattered Insights to Generalizable Knowledge," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 4(4), pages 216-236.
    12. Andrew Sudmant & Vincent Viguié & Quentin Lepetit & Lucy Oates & Abhijit Datey & Andy Gouldson & David Watling, 2021. "Fair weather forecasting? The shortcomings of big data for sustainable development, a case study from Hubballi‐Dharwad, India," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(6), pages 1237-1248, November.
    13. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    14. Chuhan Wu & Fangzhao Wu & Tao Qi & Wei-Qiang Zhang & Xing Xie & Yongfeng Huang, 2022. "Removing AI’s sentiment manipulation of personalized news delivery," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    15. Michael A. Flynn & Pietra Check & Andrea L. Steege & Jacqueline M. Sivén & Laura N. Syron, 2021. "Health Equity and a Paradigm Shift in Occupational Safety and Health," IJERPH, MDPI, vol. 19(1), pages 1-13, December.

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