திருக்குறள் கூறும் அறிவுடைமை (Wisdom) மற்றும் தரவுசார் செயற்கை நுண்ணறிவு முடிவெடுத்தல்
Thirukkural’s Concept of Wisdom (Arivudaimai) and Data-Driven AI Decision-Making: A Study
DOI:
https://doi.org/10.63300/tm10sp012026.06Abstract
Thirukkural stands as a timeless ethical foundation for human life. Central to its teachings is "Wisdom" (Arivudaimai), which transcends the mere collection of factual information. It is an integrated human faculty that generates ethical decisions through experiential background, moral discernment, contextual awareness, and a sense of responsibility toward the public good. Because this faculty operates with a contextual perspective, it reflects not just rules, but the very essence of humanity.
In the modern digital era, Data-driven Artificial Intelligence (AI) has reshaped decision-making processes in sectors such as governance, healthcare, and finance. Its ability to analyze Big Data has significantly enhanced speed and precision. However, AI systems that rely entirely on data volume and statistical models carry the risk of neglecting the key components of wisdom defined by Thirukkural: ethical reasoning, humanitarianism, and social consideration. This can lead to decisions that are biased, decontextualized, and lacking in human empathy.
Against this backdrop, the primary objective of this research paper is to explain the multidimensional aspects of wisdom as prescribed by Thirukkural and perform a qualitative comparison with the strengths and limitations of data-centric AI decision-making. Furthermore, the ultimate goal of this article is to propose a new Hybrid Decision-Making Model that integrates the core strengths of both human wisdom and AI’s analytical capability. Centered on ethical clarity and social responsibility, this model will serve as a balanced guiding tool for data-driven management.
Downloads
References
1. சுப்பிரமணியன், கி. (2021). திருக்குறள் மெய்யியல்: அறிவு, அறிவுடைமை மற்றும் நெறிமுறை. சென்னை: தமிழ்ப் பல்கலைக்கழக வெளியீடு.
2. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2).
3. பாலசுப்பிரமணியன், ஆ. (2019). திருக்குறளில் அறிவியல் சிந்தனை. சென்னை: மணிவாசகர் பதிப்பகம்.
4. O'Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group. (தரவு சார்பு மற்றும் விளைவுகள் குறித்து).
5. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. (நீண்டகால விளைவுகளின் முக்கியத்துவம் குறித்து).
6. Gupta, A., & Sharma, P. (2023). Foundations of Data-Driven AI: From Theory to Practice. IEEE Transactions on Knowledge and Data Engineering.
7. பெயிஸ்ட், ரா. (2022). பெருந்தரவும் முன்கணிப்புத் தொழில்நுட்பமும். தமிழ்நாடு தொழில்நுட்ப ஆய்வு மையம்.
8. Binns, R. (2020). On the Apparent Conflict Between Individual and Group Fairness. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* '20).
9. Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1).
10. Dignum, V. (2019). Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. Springer International Publishing.
11. Gebru, T., et al. (2021). Datasheets for Datasets. Communications of the ACM, 64(12), 86-92.
12. Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy. International Journal of Human-Computer Interaction, 36(6), 495-504.
13. Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56.
14. Dreyfus, H. L., & Dreyfus, S. E. (1986). Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer. The Free Press.
15. Jobin, A., Ienca, M., & Vayena, E. (2019). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 1(9), 389-399.
16. Grosz, B. J., et al. (2019). Embedded EthiCS: Integrating Ethics Broadly Across Computer Science Education. Communications of the ACM, 62(8), 54-61.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal adopts CC BY License Creative Commons Attribution 4.0 International License http://Creativecommons.org//license/by/4.0/ . It allows using, reusing, distributing and reproducing of the original work with proper citation.