IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v65y2023i2d10.1007_s12599-023-00787-x.html
   My bibliography  Save this article

Algorithmic Fairness in AI

Author

Listed:
  • Jella Pfeiffer

    (Justus Liebig University Gießen)

  • Julia Gutschow

    (Justus Liebig University Gießen)

  • Christian Haas

    (Vienna University of Economics and Business (WU))

  • Florian Möslein

    (Philipps-University Marburg)

  • Oliver Maspfuhl

    (Deutsche Bank AG)

  • Frederik Borgers

    (UNIQA Insurance Group AG)

  • Suzana Alpsancar

    (Paderborn University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Jella Pfeiffer & Julia Gutschow & Christian Haas & Florian Möslein & Oliver Maspfuhl & Frederik Borgers & Suzana Alpsancar, 2023. "Algorithmic Fairness in AI," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(2), pages 209-222, April.
    • Handle: RePEc:spr:binfse:v:65:y:2023:i:2:d:10.1007_s12599-023-00787-x
    DOI: 10.1007/s12599-023-00787-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12599-023-00787-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12599-023-00787-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. James Konow, 2009. "Is fairness in the eye of the beholder? An impartial spectator analysis of justice," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 33(1), pages 101-127, June.
    2. Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
    3. Nima Kordzadeh & Maryam Ghasemaghaei, 2022. "Algorithmic bias: review, synthesis, and future research directions," European Journal of Information Systems, Taylor & Francis Journals, vol. 31(3), pages 388-409, May.
    4. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    5. Tobias D. Krafft & Katharina A. Zweig & Pascal D. König, 2022. "How to regulate algorithmic decision‐making: A framework of regulatory requirements for different applications," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 119-136, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bar-Gil, Oshri & Ron, Tom & Czerniak, Ofir, 2024. "AI for the people? Embedding AI ethics in HR and people analytics projects," Technology in Society, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Klockmann, Victor & von Schenk, Alicia & Villeval, Marie Claire, 2022. "Artificial intelligence, ethics, and intergenerational responsibility," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 284-317.
    2. Wencheng Lu, 2024. "Inevitable challenges of autonomy: ethical concerns in personalized algorithmic decision-making," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    3. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
    4. Runshan Fu & Ginger Zhe Jin & Meng Liu, 2022. "Does Human-algorithm Feedback Loop Lead to Error Propagation? Evidence from Zillow’s Zestimate," NBER Working Papers 29880, National Bureau of Economic Research, Inc.
    5. Bauer, Kevin & Pfeuffer, Nicolas & Abdel-Karim, Benjamin M. & Hinz, Oliver & Kosfeld, Michael, 2020. "The terminator of social welfare? The economic consequences of algorithmic discrimination," SAFE Working Paper Series 287, Leibniz Institute for Financial Research SAFE.
    6. Maria De‐Arteaga & Stefan Feuerriegel & Maytal Saar‐Tsechansky, 2022. "Algorithmic fairness in business analytics: Directions for research and practice," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3749-3770, October.
    7. Marie-Pierre Dargnies & Rustamdjan Hakimov & Dorothea Kübler, 2022. "Aversion to Hiring Algorithms: Transparency, Gender Profiling, and Self-Confidence," CESifo Working Paper Series 9968, CESifo.
    8. Keding, Christoph & Meissner, Philip, 2021. "Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    9. Danielle Li & Lindsey R. Raymond & Peter Bergman, 2020. "Hiring as Exploration," NBER Working Papers 27736, National Bureau of Economic Research, Inc.
    10. Jean-Marie John-Mathews & Dominique Cardon & Christine Balagué, 2022. "From Reality to World. A Critical Perspective on AI Fairness," Journal of Business Ethics, Springer, vol. 178(4), pages 945-959, July.
    11. Bauer, Kevin & Gill, Andrej, 2021. "Mirror, mirror on the wall: Machine predictions and self-fulfilling prophecies," SAFE Working Paper Series 313, Leibniz Institute for Financial Research SAFE.
    12. Fumagalli, Elena & Rezaei, Sarah & Salomons, Anna, 2022. "OK computer: Worker perceptions of algorithmic recruitment," Research Policy, Elsevier, vol. 51(2).
    13. Aliprantis, Dionissi & Martin, Hal & Tauber, Kristen, 2024. "What determines the success of housing mobility programs?," Journal of Housing Economics, Elsevier, vol. 65(C).
    14. Cubitt, Robin P. & Drouvelis, Michalis & Gächter, Simon & Kabalin, Ruslan, 2011. "Moral judgments in social dilemmas: How bad is free riding?," Journal of Public Economics, Elsevier, vol. 95(3), pages 253-264.
    15. Daníelsson, Jón & Macrae, Robert & Uthemann, Andreas, 2022. "Artificial intelligence and systemic risk," Journal of Banking & Finance, Elsevier, vol. 140(C).
    16. Yucheng Yang & Zhong Zheng & Weinan E, 2020. "Interpretable Neural Networks for Panel Data Analysis in Economics," Papers 2010.05311, arXiv.org, revised Nov 2020.
    17. Daniel Carter & Amelia Acker & Dan Sholler, 2021. "Investigative approaches to researching information technology companies," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(6), pages 655-666, June.
    18. Robin, Stéphane & Rusinowska, Agnieszka & Villeval, Marie Claire, 2014. "Ingratiation: Experimental evidence," European Economic Review, Elsevier, vol. 66(C), pages 16-38.
    19. Ivan A Canay & Magne Mogstad & Jack Mount, 2024. "On the Use of Outcome Tests for Detecting Bias in Decision Making," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(4), pages 2135-2167.
    20. Ratzanyel Rincón, 2023. "Quarterly multidimensional poverty estimates in Mexico using machine learning algorithms/Estimaciones trimestrales de pobreza multidimensional en México mediante algoritmos de aprendizaje de máquina," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(1), pages 3-68.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:65:y:2023:i:2:d:10.1007_s12599-023-00787-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.