IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v26y2024i2d10.1007_s10796-023-10388-4.html
   My bibliography  Save this article

Data Sensitivity and Domain Specificity in Reuse of Machine Learning Applications

Author

Listed:
  • Corinna Rutschi

    (University of Bern)

  • Nicholas Berente

    (Mendoza College of Business Notre Dame)

  • Frederick Nwanganga

    (Mendoza College of Business Notre Dame)

Abstract

Data sensitivity and domain specificity challenges arise in reuse of machine learning applications. We identify four types of machine learning applications based on different reuse strategies: generic, distinctive, selective, and exclusive. We conclude with lessons for developing and deploying machine learning applications.

Suggested Citation

  • Corinna Rutschi & Nicholas Berente & Frederick Nwanganga, 2024. "Data Sensitivity and Domain Specificity in Reuse of Machine Learning Applications," Information Systems Frontiers, Springer, vol. 26(2), pages 633-640, April.
    • Handle: RePEc:spr:infosf:v:26:y:2024:i:2:d:10.1007_s10796-023-10388-4
    DOI: 10.1007/s10796-023-10388-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-023-10388-4
    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/s10796-023-10388-4?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. Karthik Panchanathan & Robert Boyd, 2004. "Indirect reciprocity can stabilize cooperation without the second-order free rider problem," Nature, Nature, vol. 432(7016), pages 499-502, November.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    2. Zhou, Chen & Zhu, Yuying & Zhao, Dawei & Xia, Chengyi, 2024. "An evolutionary trust game model with group reputation within the asymmetric population," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    3. Alexander Isakov & David Rand, 2012. "The Evolution of Coercive Institutional Punishment," Dynamic Games and Applications, Springer, vol. 2(1), pages 97-109, March.
    4. Hu, Menglong & Wang, Juan & Kong, Lingcong & An, Kang & Bi, Tao & Guo, Baohong & Dong, Enzeng, 2015. "Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 47-52.
    5. Nicole M. Baran & Paola Sapienza & Luigi Zingales, 2010. "Can we infer social preferences from the lab? Evidence from the trust game," NBER Working Papers 15654, National Bureau of Economic Research, Inc.
    6. Gilbert Roberts, 2015. "Partner Choice Drives the Evolution of Cooperation via Indirect Reciprocity," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-11, June.
    7. Martin Korndörfer & Boris Egloff & Stefan C. Schmukle, 2015. "A Large Scale Test of the Effect of Social Class on Prosocial Behavior," Working Papers 1601, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Guillaume Deffuant & Ilaria Bertazzi & Sylvie Huet, 2018. "The Dark Side Of Gossips: Hints From A Simple Opinion Dynamics Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-20, September.
    9. Hensel, Lukas & Witte, Marc & Caria, A. Stefano & Fetzer, Thiemo & Fiorin, Stefano & Götz, Friedrich M. & Gomez, Margarita & Haushofer, Johannes & Ivchenko, Andriy & Kraft-Todd, Gordon & Reutskaja, El, 2022. "Global Behaviors, Perceptions, and the Emergence of Social Norms at the Onset of the COVID-19 Pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 473-496.
    10. Paul J Zak & Angela A Stanton & Sheila Ahmadi, 2007. "Oxytocin Increases Generosity in Humans," PLOS ONE, Public Library of Science, vol. 2(11), pages 1-5, November.
    11. Joseph Henrich, 2007. "The evolution of costly displays, cooperation, and religion. Inferentially potent displays and their implications for cultural evolution," Papers on Economics and Evolution 2007-21, Philipps University Marburg, Department of Geography.
    12. Andreas Siemoneit, 2021. "Justice as a Social Bargain and Optimization Problem," Papers 2106.00830, arXiv.org.
    13. Lee, Hsuan-Wei & Cleveland, Colin & Szolnoki, Attila, 2024. "Suppressing defection by increasing temptation: The impact of smart cooperators on a social dilemma situation," Applied Mathematics and Computation, Elsevier, vol. 479(C).
    14. Quan, Ji & Nie, Jiacheng & Chen, Wenman & Wang, Xianjia, 2022. "Keeping or reversing social norms promote cooperation by enhancing indirect reciprocity," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    15. Andreas Siemoneit, 2023. "Merit first, need and equality second: hierarchies of justice," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 70(4), pages 537-567, December.
    16. Yang, Guoli & Wu, Yu'e & Cavaliere, Matteo, 2024. "Information-driven cooperation on adaptive cyber-physical systems," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    17. Wang, Zhen & Chen, Tong & Wang, Yongjie, 2017. "Leadership by example promotes the emergence of cooperation in public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 101(C), pages 100-105.
    18. Thomas Clark Durant & Michael Weintraub & Daniel Houser & Shuwen Li, 2018. "Trust in the executive," Journal of Peace Research, Peace Research Institute Oslo, vol. 55(5), pages 609-624, September.
    19. Sheen S. Levine & Robert Kurzban, 2006. "Explaining clustering in social networks: towards an evolutionary theory of cascading benefits," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 27(2-3), pages 173-187.
    20. Christian Stoff, 2004. "Establishing Cooperation between Groups: Ingroup versus Outgroup Punishment," SOI - Working Papers 0416, Socioeconomic Institute - University of Zurich, revised Feb 2006.

    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:infosf:v:26:y:2024:i:2:d:10.1007_s10796-023-10388-4. 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.