All Issue

2026 Vol.19 Preview Page

특집

From Artificial Wisdom to Wisdom Education: An Exploration from the Perspective of Prajñā

인공지혜에서 지혜교육으로 : 반야(般若) 관점의 탐색

Gil WanJe

길완제*

Adjunct Professor, AI Convergence Education, Dongguk University
*동국대학교 교육대학원 AI융합교육전공 겸임교수, 한국로봇사용자협회 전략기획본부장, jaygil8755@gmail.com
31 August 2026. pp. 27-55
PDF Citation
Abstract
인공지능이 판단의 영역으로 확장되면서 책임의 귀속, 판단능력의 형성, 판단 근거의 투명성과 다양성이 함께 문제로 제기되었다. 이 연구는 세 문제를 인공지혜 논의와 지혜교육의 연결점에서 검토한다. 먼저 인공지혜 선행연구를 지혜를 식별 가능한 내용이나 속성으로 이해하는 관점과 판단의 기능이나 절차로 이해하는 관점으로 구분하고, 두 관점이 지혜를 명세하여 다른 체계로 옮길 수 있는 요소로 다룬다는 공통 전제를 확인한다. 이어 인공지능과 교육 연구가 차용한 반야에 주목한다. 이 문헌들에서 반야는 처리하는 지식의 양이나 절차의 정교함이 아니라 판단하는 쪽의 조건을 다시 보게 하는 방향으로 사용된다. 이 글은 반야 전체를 정의하지 않고 조견오온개공에 나타나는 자기성찰적 국면, 곧 인식 주체 또한 조건 지어진 구성임을 보는 작동만을 분석 관점으로 취한다. 두 생성형 인공지능에 동일한 질문을 제시한 예시적 문답은 이들이 오온개공을 유창하게 설명할 수 있음을 보여 주는 동시에, 설명의 산출과 판단 주체의 형성이 구별되어야 함을 드러낸다. 이 구별은 인공지능의 앞으로도 판단능력을 갖출 수 없다고 단정하는 것은 아니며 인간 교사와 학습자에게도 동일하게 적용된다. 이를 바탕으로 반야 기반 지혜교육의 잠정적 목표를 제시하고, 판단의 보류, 근거의 가시화, 관점의 전환과 비교, 판단의 인수라는 네 조건과 그 안에서 인공지능이 담당할 수 있는 역할 및 한계를 탐색하였다.
키워드
지혜교육
인공지혜
반야
조견오온개공
프로네시스
인식적 주도성
판단능력의 형성
생성형 인공지능
개념 연구
불교교육
As artificial intelligence extends into the domain of judgment, three problems arise together: the attribution of responsibility, the formation of the human capacity for judgment, and the transparency and plurality of the grounds on which judgments rest. This conceptual study examines these problems at the point where research on artificial wisdom meets the question of wisdom education. It first distinguishes two ideal types in the existing literature on artificial wisdom. The first treats wisdom as a combination of identifiable contents or attributes, such as prosociality, emotional regulation, self-reflection, and decisiveness, and seeks to implement them as system capacities. The second treats wisdom as a function or procedure of judgment, drawing on Aristotelian phronesis and, more recently, on machine metacognition. Although the two appear opposed, both share the premise that wisdom can be specified and transferred to another system. The study then turns to prajñā as it has been borrowed in research on AI and education. There prajñā is not offered as one more attribute to be added to a system; it redirects attention to the conditions of the one who judges and to the relation among human beings, technology, and world. Rather than defining prajñā as a whole, the study isolates a single analytic feature expressed in seeing that the five aggregates are empty: the knower, too, is seen as conditionally constituted. An illustrative exchange in which identical questions were posed to two generative AI systems shows that such systems can articulate this doctrine fluently, and for that very reason it shows that producing an accurate account is not the same as forming a judging subject. This distinction asserts no permanent incapacity of AI and applies equally to human teachers and learners. On this basis the study proposes a provisional aim for prajñā-oriented wisdom education and four conditions for learning activity: suspending judgment, making the grounds of judgment visible, shifting and comparing perspectives, and assuming judgment as one's own. It also specifies the educational roles AI can play and the limits of those roles. Rather than prescribing a fixed instructional sequence, these conditions are offered as criteria against which a lesson may be examined. The study closes by indicating the observable changes through which the proposal could later be tested: how learners revise an initial judgment, how they connect evidence to their own position, how they treat counter-perspectives and uncertainty, and what quality of reliance on AI their work displays.
Keywords
Wisdom Education
Artificial Wisdom
Prajñā
Emptiness of the Five Aggregates
Phronesis
Epistemic Agency
Formation of Judgment
Generative Artificial Intelligence
Conceptual Study
Buddhist Education
References

  1. 길완제 외(2025). ｢인공지능을 바라보는 불교의 시선: 스코핑 리뷰｣, 『원불교사상과 종교문화』, 제106집. 익산: 원광대학교 원불교사상연구원. pp. 209-235.

     10.67287/WTH.2025.12.106.209

  2. 김유리ㆍ신명희(2023). ｢인공지능시대, 불교 교육 방향성 고찰을 위한 시론적 연구 ― 『금강경』에 기반한 윤리관 구축을 중심으로｣, 『한국교수불자연합학회지』, 제29권 제2호. 서울: 한국교수불자연합회. pp. 163-192.

     10.34281/KABP.29.2.8

  3. Burrell, Jenna (2016). “How the Machine ‘Thinks’: Understanding Opacity in Machine Learning Algorithms”, Big Data & Society, Vol. 3, No. 1. London: SAGE. pp. 1-12.

     10.1177/2053951715622512

  4. Casacuberta, David (2013). “The Quest for Artificial Wisdom”, AI & Society, Vol. 28, No. 2. London: Springer. pp. 199-207.

     10.1007/s00146-012-0390-6

  5. Davis, Joshua P. (2019). “Artificial Wisdom? A Potential Limit on AI in Law (and Elsewhere)”, Oklahoma Law Review, Vol. 72, No. 1. Norman: University of Oklahoma College of Law. pp. 51-84.

     10.2139/ssrn.3350600

  6. Eisikovits, Nir & Feldman, Dan (2022). “AI and Phronesis”, Moral Philosophy and Politics, Vol. 9, No. 2. Berlin: De Gruyter. pp. 181-199.

     10.1515/mopp-2021-0026

  7. Hershock, Peter D. (2020). “The Intelligence Revolution and the New Great Game: A Buddhist Reflection on the Personal and Societal Predicaments of Big Data and Artificial Intelligence”, Hualin International Journal of Buddhist Studies, Vol. 3, No. 2. Singapore: National University of Singapore. pp. 62-77.

     10.15239/hijbs.03.02.04

  8. Jeste, Dilip V. 외(2020). “Beyond Artificial Intelligence: Exploring Artificial Wisdom”, International Psychogeriatrics, Vol. 32, No. 8. Cambridge: Cambridge University Press. pp. 993-1001.

     10.1017/S1041610220000927 32583762 PMC7942180

  9. Johnson, Samuel G. B. 외(2026). “Imagining and Building Wise Machines: The Centrality of AI Metacognition”, Trends in Cognitive Sciences. Amsterdam: Elsevier. 온라인 선출간(2026. 2. 26.), https://doi.org/10.1016/j.tics.2026.01.002 2026. 9. 11. 검색.

     10.1016/j.tics.2026.01.002

  10. Koutsikouri, Dina 외(2023). “Seven Elements of Phronesis: A Framework for Understanding Judgment in Relation to Automated Decision-Making”, Proceedings of the 56th Hawaii International Conference on System Sciences. Honolulu: University of Hawai‘i at Mānoa. pp. 5292-5301.

     10.24251/HICSS.2023.646

  11. Liu, Jia (2026). “Between No-Self and the Algorithm: Buddhist Mind-Nature as Ethical Architecture for AI and Human Self-Realization”, Religions, Vol. 17, No. 3. Basel: MDPI. Article 378.

     10.3390/rel17030378

  12. McGregor, Tate (2025). “The Philosophy of Artificial Wisdom”, Philosophy & Technology, Vol. 38, No. 4. Dordrecht: Springer. Article 126.

     10.1007/s13347-025-00964-8

  13. Peschl, Markus F. 외(2025). “Can We Expect AI to Be Wise? A Wisdom, Knowledge (Management), Resonance, and Cognitive Science Perspective”, Proceedings of the 58th Hawaii International Conference on System Sciences. Honolulu: University of Hawai‘i at Mānoa. pp. 4863-4872.

     10.24251/HICSS.2025.585

  14. Peters, Michael A. & Green, Benjamin J. (2024). “Wisdom in the Age of AI Education”, Postdigital Science and Education, Vol. 6, No. 4. Cham: Springer. pp. 1173-1195.

     10.1007/s42438-024-00460-w

  15. Santoni de Sio, Filippo & Mecacci, Giulio (2021). “Four Responsibility Gaps with Artificial Intelligence: Why They Matter and How to Address Them”, Philosophy & Technology, Vol. 34, No. 4. Dordrecht: Springer. pp. 1057-1084.

     10.1007/s13347-021-00450-x

  16. Tsai, Cheng-Hung (2020). “Artificial Wisdom: A Philosophical Framework”, AI & Society, Vol. 35, No. 4. London: Springer. pp. 937-944.

     10.1007/s00146-020-00949-5

  17. Tsai, Cheng-Hung & Ku, Hsiu-Lin (2025). “Why AI May Undermine Phronesis and What to Do about It”, AI and Ethics, Vol. 5, No. 3. Cham: Springer. pp. 3079-3086.

     10.1007/s43681-024-00617-0

  18. Uttam, Jitendra (2023). “Between Buddhist ‘Self-Enlightenment’ and ‘Artificial Intelligence’: South Korea Emerging as a New Balancer”, Religions, Vol. 14, No. 2. Basel: MDPI. Article 150.

     10.3390/rel14020150

  19. Wu, Jiun-Yu 외(2025). “Strengthening Human Epistemic Agency in the Symbiotic Learning Partnership with Generative Artificial Intelligence”, Educational Researcher, Vol. 54, No. 6. Washington, D.C.: American Educational Research Association. pp. 358-368.

     10.3102/0013189X251333628

  20. Yan, Lixiang 외(2025). “Beyond Efficiency: Empirical Insights on Generative AI’s Impact on Cognition, Metacognition and Epistemic Agency in Learning”, British Journal of Educational Technology, Vol. 56, No. 5. Hoboken: Wiley. pp. 1675-1685.

     10.1111/bjet.70000

  21. Younas, Ammar & Zeng, Yi (2026). “Metric Monoculture: How AI’s Flat Intelligence Erases Cultural Wisdom”, AI & Society, Vol. 41, No. 2. London: Springer. pp. 1325-1326.

     10.1007/s00146-025-02515-3
Information
  • Publisher :불교의례문화연구소
  • Publisher(Ko) :불교의례문화연구소
  • Journal Title :Intangible Culture
  • Journal Title(Ko) :무형문화연구
  • Volume : 19
  • Pages :27-55
  • DOI :https://doi.org/10.23058/brcr.2026..19.002
Journal Informaiton Intangible Culture Intangible Culture
  • KISTI Current Status
  • KISTI Cited-by
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close