Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Challenges and opportunities in translating ethical AI principles into practice for children

Nature Machine Intelligence volume 6, pages 265–270 (2024)Cite this article

Subjects

Abstract

AI systems are becoming increasingly pervasive within children’s devices, apps and services. The concern over a world where AI systems are deployed unchecked has raised burning questions about the impact, governance and accountability of these technologies. Although recent effort on AI ethics has converged into growing consensus on a set of high-level ethical AI principles, engagement with children’s issues is still limited, and even less is known about how to effectively apply them in practice for children. This Perspective first maps the current global landscape of existing ethics guidelines for AI and analyses their correlation with children. We then critically assess the strategies and recommendations proposed by current AI ethics initiatives, identifying the critical challenges in translating such ethical AI principles into practice for children. Finally, we tentatively map out several suggestions regarding embedding ethics into the development and governance of AI for children.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Li, J.-P. O. et al. Digital technology, tele-medicine and artificial intelligence in ophthalmology: a global perspective. Progr. Retin. Eye Res. 82, 100900 (2021).

    Article  CAS  Google Scholar 

  2. Sims, A. et al. UNICEF Public Consultation on Draft Policy Guidance on AI for Children (UNICEF, 2022); https://www.unicef.org/globalinsight/media/2356/file/UNICEF-Global-Insight-policy-guidance-AI-children-2.0-2021.pdf

  3. Strengers, Y., Kennedy, J., Arcari, P., Nicholls, L. & Gregg, M. Protection, productivity and pleasure in the smart home: emerging expectations and gendered insights from Australian early adopters. In Proc. 2019 CHI Conference on Human Factors in Computing Systems 645 (ACM, 2019).

  4. Fadhil, A. & Villafiorita, A. An adaptive learning with gamification & conversational UIs: the rise of CiboPoliBot. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization 408–412 (ACM, 2017).

  5. Kumaresamoorthy, N. & Firdhous, M. An approach of filtering the content of posts in social media. In 2018 3rd International Conference on Information Technology Research 1–6 (IEEE, 2018).

  6. Corbett-Davies, S., Pierson, E., Feller, A., Goel, S. & Huq, A. Algorithmic decision making and the cost of fairness. In Proc. 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 797–806 (ACM, 2017).

  7. General Comment No. 25 (2021) on Children’s Rights in Relation to the Digital Environment (UNCRC, 2021); https://www.ohchr.org/en/documents/general-comments-and-recommendations/general-comment-no-25-2021-childrens-rights-relation

  8. Age Appropriate Design Code (ICO, 2020); https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/childrens-information/childrens-code-guidance-and-resources/age-appropriate-design-a-code-of-practice-for-online-services/

  9. Jobin, A., Ienca, M. & Vayena, E. The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1, 389–399 (2019).

    Article  Google Scholar 

  10. Leslie, D. Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector (The Alan Turing Institute, 2019).

  11. Guidance for Regulation of Artificial Intelligence Applications (The White House, 2020); https://www.whitehouse.gov/wp-content/uploads/2020/11/M-21-06.pdf

  12. Adams, C., Pente, P., Lemermeyer, G. & Rockwell, G. Artificial intelligence ethics guidelines for K-12 education: a review of the global landscape. In Artificial Intelligence in Education: 22nd International Conference Proceedings Part II, 24–28 (Springer, 2021).

  13. Adams, C., Pente, P., Lemermeyer, G. & Rockwell, G. Ethical principles for artificial intelligence in K-12 education. Comput. Educ. 4, 100131 (2023).

    Google Scholar 

  14. Artificial Intelligence and Machine Learning (Internet Society, 2017); https://www.internetsociety.org/resources/doc/2017/artificial-intelligence-and-machine-learning-policy-paper/

  15. Greene, D., Hoffmann, A. L. & Stark, L. Better, nicer, clearer, fairer: a critical assessment of the movement for ethical artificial intelligence and machine learning. In Proc. 52nd Hawaii International Conference on System Sciences (ed. Bui, T.) 2122–2131 (ScholarSpace, 2019).

  16. McCradden, M. D., Joshi, S., Mazwi, M. & Anderson, J. A. Ethical limitations of algorithmic fairness solutions in health care machine learning. Lancet Digit. Health 2, e221–e223 (2020).

    Article  PubMed  Google Scholar 

  17. Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts (European Commission, 2021); https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52021PC0206

  18. Touretzky, D., Gardner-McCune, C., Martin, F. & Seehorn, D. Envisioning AI for K-12: what should every child know about AI? In Proc. AAAI Conference on Artificial Intelligence Vol. 33, 9795–9799 (ACM, 2019).

  19. Goralski, M. A. & Tan, T. K. Artificial intelligence and sustainable development. Int. J. Manage. Educ. 18, 100330 (2020).

    Google Scholar 

  20. Ethics and Governance of Artificial Intelligence for Health: Who Guidance (World Health Organization, 2021); https://www.who.int/publications/i/item/9789240029200

  21. Roumate, F. in Ethics of Artificial Intelligence, Higher Education, and Scientific Research 129–144 (Springer). https://doi.org/10.1007/978-981-19-8641-3_10

  22. Aayog, N. Discussion Paper: National Strategy for Artificial Intelligence (Government of India, 2018).

  23. Gupta, M. & Sharma, A. Fear of missing out: a brief overview of origin, theoretical underpinnings and relationship with mental health. World J. Clin. Cases 9, 4881–4889 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Fjeld, J., Achten, N., Hilligoss, H., Nagy, A. & Srikumar, M. Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI (Berkman Klein Center, 2020).

  25. Lorenz, B., Kikkas, K. & Laanpere, M. Comparing children’s e-safety strategies with guidelines offered by adults. Electron. J. e-Learning 10, 326–338 (2012).

    Google Scholar 

  26. Online Safety Bill (UK Parliament, 2022); https://commonslibrary.parliament.uk/research-briefings/cbp-9579/

  27. Child Rights By Design (5Rights Foundation, 2023); https://childrightsbydesign.digitalfuturescommission.org.uk/page/childrens-voices

  28. Markopoulos, P., Read, J. C. & Giannakos, M. in Handbook of Human Factors and Ergonomics 1287–1304 (John Wiley & Sons, 2021).

  29. Mittelstadt, B. Principles alone cannot guarantee ethical AI. Nat. Mach. Intell. 1, 501–507 (2019).

    Article  Google Scholar 

  30. Prunkl, C. E. et al. Institutionalizing ethics in AI through broader impact requirements. Nat. Mach. Intell. 3, 104–110 (2021).

    Article  Google Scholar 

  31. Wang, G., Zhao, J., Van Kleek, M. & Shadbolt, N. Informing age-appropriate AI: examining principles and practices of AI for children. In Proc. 2022 CHI Conference on Human Factors in Computing Systems 536 (ACM, 2022).

  32. Fletcher, A. C. & Blair, B. L. Maternal authority regarding early adolescents’ social technology use. J. Family Iss. 35, 54–74 (2014).

    Article  Google Scholar 

  33. Langford, R. Critiquing child-centred pedagogy to bring children and early childhood educators into the centre of a democratic pedagogy. Contemp. Issues Early Childh. 11, 113–127 (2010).

    Article  Google Scholar 

  34. Wang, G., Zhao, J., Van Kleek, M. & Shadbolt, N. 12 ways to empower: designing for children’s digital autonomy. In Proc. 2023 CHI Conference on Human Factors in Computing Systems 91 (ACM, 2023).

  35. Wang, G., Zhao, J., Van Kleek, M. & Shadbolt, N. ‘Treat me as your friend, not a number in your database’: co-designing with children to cope with datafication online. In Proc. 2023 CHI Conference on Human Factors in Computing Systems 95 (ACM, 2023).

  36. Steen, M. Co-design as a process of joint inquiry and imagination. Des. Issues 29, 16–28 (2013).

    Article  Google Scholar 

  37. Visram, S., Leyden, D., Annesley, O., Bappa, D. & Sebire, N. J. Engaging children and young people on the potential role of artificial intelligence in medicine. Pediatr. Res. 93, 440–444 (2023).

    Article  PubMed  Google Scholar 

  38. Thai, K. et al. Perspectives of youths on the ethical use of artificial intelligence in health care research and clinical care. JAMA Netw. Open 6, e2310659 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Druga, S., Yip, J., Preston, M. & Dillon, D. The 4As: Ask, Adapt, Author, Analyze—AI Literacy Framework for Families (MIT Press, 2021).

  40. Lee, K. J. et al. The show must go on: a conceptual model of conducting synchronous participatory design with children online. In Proc. 2021 CHI Conference on Human Factors in Computing Systems 345 (ACM, 2021).

  41. Woodward, J. et al. Using co-design to examine how children conceptualize intelligent interfaces. In Proc. 2018 CHI Conference on Human Factors in Computing Systems 575 (ACM, 2018).

  42. Ekambaranathan, A., Zhao, J. & Van Kleek, M. “Money makes the world go around": identifying barriers to better privacy in children’s apps from developers’ perspectives. In Proc. 2021 CHI Conference on Human Factors in Computing Systems 46 (ACM, 2021).

  43. Kop, M. EU Artificial Intelligence Act: The European Approach to AI (EU Artificial Intelligence Act, 2021).

  44. MacCarthy, M. An Examination of the Algorithmic Accountability Act of 2019 (SSRN, 2019).

  45. Zimmerman, J. & Forlizzi, J. in Ways of Knowing in HCI 167–189 (Springer, 2014).

  46. Sandoval, W. Conjecture mapping: an approach to systematic educational design research. J. Learn. Sci. 23, 18–36 (2014).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Ethical Web and Data Architectures project (grant number EWADA).

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Oxford, Oxford, UK

    Ge Wang, Jun Zhao, Max Van Kleek & Nigel Shadbolt

Authors
  1. Ge Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Max Van Kleek
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nigel Shadbolt
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.W. conceptualized and wrote the manuscript. J.Z., M.V.K. and N.S. provided critical feedback. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ge Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Machine Intelligence thanks Ryoko Asai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, G., Zhao, J., Van Kleek, M. et al. Challenges and opportunities in translating ethical AI principles into practice for children. Nat Mach Intell 6, 265–270 (2024). https://doi.org/10.1038/s42256-024-00805-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s42256-024-00805-x

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing