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AI & Human Values

Inequalities, Biases, Fairness, Nudge, and Feedback Loops

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Reflections on Artificial Intelligence for Humanity

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12600))

Abstract

This chapter summarizes contributions made by Ricardo Baeza-Yates, Francesco Bonchi, Kate Crawford, Laurence Devillers and Eric Salobir in the session chaired by Françoise Fogelman-Soulié on AI & Human values at the Global Forum on AI for Humanity. It provides an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence. It then presents and discusses concrete examples of inequalities produced by AI systems, highlighting their variety and potential harmfulness. Finally, we conclude by discussing how putting human values at the core of AI requires answering many questions, still open for further research.

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Notes

  1. 1.

    https://www.wired.com/story/when-it-comes-to-gorillas-google-photos-remains-blind/.

  2. 2.

    https://www.technologyreview.com/2018/03/27/144290/microsofts-neo-nazi-sexbot-was-a-great-lesson-for-makers-of-ai-assistants/.

  3. 3.

    https://www.mic.com/articles/156286/crime-prediction-tool-pred-pol-only-amplifies-racially-biased-policing-study-shows.

  4. 4.

    https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.

  5. 5.

    See also chapter 2 of this book.

  6. 6.

    https://ec.europa.eu/info/aid-development-cooperation-fundamental-rights/your-rights-eu/eu-charter-fundamental-rights_en.

  7. 7.

    https://www.cigionline.org/internet-survey-2019.

  8. 8.

    See also chapter 3 of this book.

  9. 9.

    https://www.lexico.com/en/definition/bias.

  10. 10.

    https://en.wikipedia.org/wiki/Bias.

  11. 11.

    https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G/.

  12. 12.

    https://www.lexico.com/en/definition/fairness.

  13. 13.

    https://www.lexico.com/en/definition/discrimination.

  14. 14.

    https://vis-www.cs.umass.edu/lfw/.

  15. 15.

    https://www.carrotrewards.ca/.

  16. 16.

    https://www.acm.org/binaries/content/assets/public-policy/2017_usacm_statement_algorithms.pdf.

  17. 17.

    See also chapters 9–10-11 of this book.

  18. 18.

    See also chapters 1 and 15 of this book.

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Author information

Authors and Affiliations

  1. Sorbonne University, CNRS-LIMSI, DATA-IA, Hub France IA, CNPEN, Paris, France

    Laurence Devillers

  2. Hub France IA, 8 bis rue Charles V, 75004, Paris, France

    Françoise Fogelman-Soulié

  3. Institute for Experiential AI, Northeastern University at SV, San Jose, CA, USA

    Ricardo Baeza-Yates

Authors
  1. Laurence Devillers
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  2. Françoise Fogelman-Soulié
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  3. Ricardo Baeza-Yates
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Corresponding author

Correspondence to Françoise Fogelman-Soulié .

Editor information

Editors and Affiliations

  1. Inria, Le Chesnay, France

    Bertrand Braunschweig

  2. LAAS-CNRS, Toulouse, France

    Malik Ghallab

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Devillers, L., Fogelman-Soulié, F., Baeza-Yates, R. (2021). AI & Human Values. In: Braunschweig, B., Ghallab, M. (eds) Reflections on Artificial Intelligence for Humanity. Lecture Notes in Computer Science(), vol 12600. Springer, Cham. https://doi.org/10.1007/978-3-030-69128-8_6

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  • DOI: https://doi.org/10.1007/978-3-030-69128-8_6

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