IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0244592.html
   My bibliography  Save this article

Mediating artificial intelligence developments through negative and positive incentives

Author

Listed:
  • The Anh Han
  • Luís Moniz Pereira
  • Tom Lenaerts
  • Francisco C Santos

Abstract

The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, business and also policy. This anxiety is further energised by an AI race narrative that makes people believe they might be missing out. Whether real or not, a belief in this narrative may be detrimental as some stake-holders will feel obliged to cut corners on safety precautions, or ignore societal consequences just to “win”. Starting from a baseline model that describes a broad class of technology races where winners draw a significant benefit compared to others (such as AI advances, patent race, pharmaceutical technologies), we investigate here how positive (rewards) and negative (punishments) incentives may beneficially influence the outcomes. We uncover conditions in which punishment is either capable of reducing the development speed of unsafe participants or has the capacity to reduce innovation through over-regulation. Alternatively, we show that, in several scenarios, rewarding those that follow safety measures may increase the development speed while ensuring safe choices. Moreover, in the latter regimes, rewards do not suffer from the issue of over-regulation as is the case for punishment. Overall, our findings provide valuable insights into the nature and kinds of regulatory actions most suitable to improve safety compliance in the contexts of both smooth and sudden technological shifts.

Suggested Citation

  • The Anh Han & Luís Moniz Pereira & Tom Lenaerts & Francisco C Santos, 2021. "Mediating artificial intelligence developments through negative and positive incentives," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-21, January.
    • Handle: RePEc:plo:pone00:0244592
    DOI: 10.1371/journal.pone.0244592
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244592
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0244592&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0244592?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
    ---><---

    References listed on IDEAS

    as
    1. Mariarosaria Taddeo & Luciano Floridi, 2018. "Regulate artificial intelligence to avert cyber arms race," Nature, Nature, vol. 556(7701), pages 296-298, April.
    2. Todd Cherry & David McEvoy, 2013. "Enforcing Compliance with Environmental Agreements in the Absence of Strong Institutions: An Experimental Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(1), pages 63-77, 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. Wang, Xianjia & Ding, Rui & Zhao, Jinhua & Chen, Wenman & Gu, Cuiling, 2022. "Competition of punishment and reward among inequity-averse individuals in spatial public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Han, The Anh & Lenaerts, Tom & Santos, Francisco C. & Pereira, Luís Moniz, 2022. "Voluntary safety commitments provide an escape from over-regulation in AI development," Technology in Society, Elsevier, vol. 68(C).
    3. Sayed Fayaz Ahmad & Muhammad Mansoor Alam & Mohd. Khairil Rahmat & Muhammad Khalil Shahid & Mahnaz Aslam & Nur Agus Salim & Mohammed Hasan Ali Al-Abyadh, 2023. "Leading Edge or Bleeding Edge: Designing a Framework for the Adoption of AI Technology in an Educational Organization," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    4. Liu, Linjie & Chen, Xiaojie, 2022. "Effects of interconnections among corruption, institutional punishment, and economic factors on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    5. Egils Ginters & Jagadeesh Chakkaravarthy Revathy, 2021. "Hidden and Latent Factors’ Influence on Digital Technology Sustainability Development," Mathematics, MDPI, vol. 9(21), pages 1-22, November.
    6. Wang, Lichen & Liu, Yuyuan & Guo, Ruqiang & Zhang, Liang & Liu, Linjie & Hua, Shijia, 2024. "Cooperation and resource sustainability in coupling social-ecological systems with dynamic growth rates," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    7. He, Jialu & Wang, Jianwei & Yu, Fengyuan & Chen, Wei & Li, Bofan, 2022. "The slow but persistent self-improvement boosts group cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(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. Han, The Anh & Lenaerts, Tom & Santos, Francisco C. & Pereira, Luís Moniz, 2022. "Voluntary safety commitments provide an escape from over-regulation in AI development," Technology in Society, Elsevier, vol. 68(C).
    2. Casari, Marco & Tavoni, Alessandro, 2024. "Climate clubs in the laboratory," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 110(C).
    3. Flores, Lucas S. & Han, The Anh, 2024. "Evolution of commitment in the spatial public goods game through institutional incentives," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    4. Stine Aakre & Leif Helland & Jon Hovi, 2016. "When Does Informal Enforcement Work?," Journal of Conflict Resolution, Peace Science Society (International), vol. 60(7), pages 1312-1340, October.
    5. Federica Alberti & Edward J. Cartwright, 2016. "Full agreement and the provision of threshold public goods," Public Choice, Springer, vol. 166(1), pages 205-233, January.
    6. Tatsuya Sasaki & Isamu Okada & Satoshi Uchida & Xiaojie Chen, 2015. "Commitment to Cooperation and Peer Punishment: Its Evolution," Games, MDPI, vol. 6(4), pages 1-14, November.
    7. Jon Truby, 2020. "Governing Artificial Intelligence to benefit the UN Sustainable Development Goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 946-959, July.
    8. Ziyuan Sun & Man Wang & Weiwei Zhang & Yanli Li & Dan Wang & Feng Dong, 2019. "How Can We Improve the Transformation Success Rate of Research Results in the Pharmaceutical Industry? The Game Theoretic Model of Technology Transfer Subjects," IJERPH, MDPI, vol. 16(9), pages 1-30, May.
    9. Christian Feige & Karl-Martin Ehrhart & Jan Krämer, 2018. "Climate Negotiations in the Lab: A Threshold Public Goods Game with Heterogeneous Contributions Costs and Non-binding Voting," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(2), pages 343-362, June.
    10. David McEvoy, 2013. "Enforcing compliance with international environmental agreements using a deposit-refund system," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 13(4), pages 481-496, November.
    11. Gersbach, Hans & Hummel, Noemi, 2016. "A development-compatible refunding scheme for a climate treaty," Resource and Energy Economics, Elsevier, vol. 44(C), pages 139-168.
    12. Goeschl, Timo & Haberl, Beatrix & Soldà, Alice, 2023. "How to Organize Monitoring and Punishment: Experimental Evidence," Working Papers 0737, University of Heidelberg, Department of Economics.
    13. Eichner, Thomas & Kollenbach, Gilbert, 2022. "Environmental agreements, research and technological spillovers," European Journal of Operational Research, Elsevier, vol. 300(1), pages 366-377.
    14. Wang, Jianwei & Chen, Wei & Yu, Fengyuan & Zhou, Siyuan & He, Jialu & Xu, Wenshu & Dai, Wenhui, 2024. "The emergence of cooperation in the context of prior agreement with threshold and posterior compensation," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    15. Jon Hovi & Hugh Ward & Frank Grundig, 2015. "Hope or Despair? Formal Models of Climate Cooperation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(4), pages 665-688, December.

    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:plo:pone00:0244592. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.