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Trustworthy artificial intelligence (AI) in education: Promises and challenges

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  • Stéphan Vincent-Lancrin

    (OECD)

  • Reyer van der Vlies

    (OECD)

Abstract

This paper was written to support the G20 artificial intelligence (AI) dialogue. With the rise of artificial intelligence (AI), education faces two challenges: reaping the benefits of AI to improve education processes, both in the classroom and at the system level; and preparing students for new skillsets for increasingly automated economies and societies. AI applications are often still nascent, but there are many examples of promising uses that foreshadow how AI might transform education. With regard to the classroom, this paper highlights how AI can accelerate personalised learning, the support of students with special needs. At the system level, promising uses include predictive analysis to reduce dropout, and assessing new skillsets. A new demand for complex skills that are less easy to automate (e.g. higher cognitive skills like creativity and critical thinking) is also the consequence of AI and digitalisation. Reaching the full potential of AI requires that stakeholders trust not only the technology, but also its use by humans. This raises new policy challenges around “trustworthy AI”, encompassing the privacy and security of data, but also possible wrongful uses of data leading to biases against individuals or groups.

Suggested Citation

  • Stéphan Vincent-Lancrin & Reyer van der Vlies, 2020. "Trustworthy artificial intelligence (AI) in education: Promises and challenges," OECD Education Working Papers 218, OECD Publishing.
    • Handle: RePEc:oec:eduaab:218-en
    DOI: 10.1787/a6c90fa9-en
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    Cited by:

    1. Raval, Khushi Jatinkumar & Jadav, Nilesh Kumar & Rathod, Tejal & Tanwar, Sudeep & Vimal, Vrince & Yamsani, Nagendar, 2024. "A survey on safeguarding critical infrastructures: Attacks, AI security, and future directions," International Journal of Critical Infrastructure Protection, Elsevier, vol. 44(C).
    2. Schiavo, Gianluca & Businaro, Stefano & Zancanaro, Massimo, 2024. "Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial Intelligence," Technology in Society, Elsevier, vol. 77(C).
    3. Nadine Bachmann & Shailesh Tripathi & Manuel Brunner & Herbert Jodlbauer, 2022. "The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals," Sustainability, MDPI, vol. 14(5), pages 1-33, February.
    4. Rocsana Bucea-Manea-Țoniş & Valentin Kuleto & Simona Corina Dobre Gudei & Costin Lianu & Cosmin Lianu & Milena P. Ilić & Dan Păun, 2022. "Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    5. Wei, Xinyi & Chu, Xiaoyuan & Geng, Jingyu & Wang, Yuhui & Wang, Pengcheng & Wang, HongXia & Wang, Caiyu & Lei, Li, 2024. "Societal impacts of chatbot and mitigation strategies for negative impacts: A large-scale qualitative survey of ChatGPT users," Technology in Society, Elsevier, vol. 77(C).

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