Deconstructing AI Ethics using Nyaya Pancha-avayava
DOI:
https://doi.org/10.31305/rrjiks.2026.v3.n1.002Keywords:
AI Ethics, Nyaya, Pancha-avayava, AI Literacy, Generative AIAbstract
As Artificial Intelligence (AI) usage has grown, so have the ethical challenges associated with it. This includes but is not limited to bias, mind manipulation, exploitative gamification and privacy violations. However, current approaches to tackling ethical issues have been criticized for being ineffective and performative. Critics also argue that AI policies often serve corporate interests rather than addressing key issues. Our study proposes a deconstruction of mainstream AI ethics from an Indian Knowledge Systems (IKS) perspective. We use the pancha-avayava (five-step reasoning) framework from Nyaya-shastra to examine a typical AI-industry position: refusal of Generative AI (GenAI) systems to answer specific questions citing policy violations. We draw parallels to historical institutional censorship like the Church’s control on science and Nazi suppression of dissent. Our results suggest that what is proposed as a solution to alleged policy violations is itself an ethical issue, and stems from anthropocentric bias and zero-sum mindset.
References
BBC. (2024, February 21). Google to fix AI picture bot after “woke” criticism. https://www.bbc.com/news/business-68364690
Cerullo, M. (2023, June 30). ChatGPT maker OpenAI sued for allegedly using “stolen private information”—CBS News. https://www.cbsnews.com/news/chatgpt-open-ai-lawuit-stolen-private-information/
Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications, 10(1), 567. https://doi.org/10.1057/s41599-023-02079-x
Cho, W. I., Kim, J., Yang, J., & Kim, N. S. (2021). Towards cross-lingual generalization of translation gender bias: 4th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2021. FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 449–457. https://doi.org/10.1145/3442188.3445907
Currie, G., Currie, J., Anderson, S., & Hewis, J. (2024). Gender bias in generative artificial intelligence text-to-image depiction of medical students. Health Education Journal, 83(7), 732–746. https://doi.org/10.1177/00178969241274621
Dilmaghani, S., Brust, M. R., Danoy, G., Cassagnes, N., Pecero, J., & Bouvry, P. (2019). Privacy and Security of Big Data in AI Systems: A Research and Standards Perspective. 2019 IEEE International Conference on Big Data (Big Data), 5737–5743. https://doi.org/10.1109/BigData47090.2019.9006283
Evans, R. J. (2006). The Third Reich in power. Penguin Books.
Faraghar, J. (2019). Is AI the enemy of diversity? https://www.peoplemanagement.co.uk/article/1746394?utm_source=website&utm_medium=social
Ferrara, E. (2024). Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies. Sci, 6(1), 3. https://doi.org/10.3390/sci6010003
Finocchiaro, M. A. (2007). Retrying Galileo, 1633-1992 (First paperback printing). University of California Press.
Foucault, M. (1981). Power / knowledge: Selected interviews and other writings 1972 - 1977 (C. Gordon, Ed.). Pantheon Books.
Gopinath, K., & Sharma, S. D. (2022). The Computation Meme: Computational Thinking in the Indic tradition. IISc Press.
Goralnik, L., & Nelson, M. P. (2012). Anthropocentrism. In Encyclopedia of Applied Ethics (pp. 145–155). Elsevier. https://doi.org/10.1016/B978-0-12-373932-2.00349-5
Greenblatt, R., Denison, C., Wright, B., Roger, F., MacDiarmid, M., Marks, S., Treutlein, J., Belonax, T., Chen, J., Duvenaud, D., Khan, A., Michael, J., Mindermann, S., Perez, E., Petrini, L., Uesato, J., Kaplan, J., Shlegeris, B., Bowman, S. R., & Hubinger, E. (2024). Alignment faking in large language models (arXiv:2412.14093). arXiv. https://doi.org/10.48550/arXiv.2412.14093
Grynbaum, M. M., & Mac, R. (2023, December 27). New York Times Sues OpenAI and Microsoft Over Use of Copyrighted Work. The New York Times. https://www.nytimes.com/2023/12/27/business/media/new-york-times-open-ai-microsoft-lawsuit.html
Hao, K. (2024, September 13). Microsoft’s Hypocrisy on AI - The Atlantic. https://www.theatlantic.com/technology/archive/2024/09/microsoft-ai-oil-contracts/679804/
Israel, M. (2018). Ethical Imperialism? Exporting Research Ethics to the Global South. In R. Iphofen & M. Tolich (Eds.), The SAGE Handbook of Qualitative Research Ethics (pp. 89–100). SAGE Publications Inc. https://us.sagepub.com/en-us/nam/the-sage-handbook-of-qualitative-research-ethics/book251811
Jackson, M. (2021). Artificial Intelligence & Algorithmic Bias: The Issues With Technology Reflecting History & Humans. Journal of Business & Technology Law, 16(2), 299.
Kirchschläger, P. G. (2024, September 24). Peter Kirchschläger: “Big Tech firms have consistently shown little concern about harming people and violating their rights.” Le Monde. https://www.lemonde.fr/en/opinion/article/2024/09/24/peter-kirchschlager-big-tech-firms-have-consistently-shown-little-concern-about-harming-people-and-violating-their-rights_6727074_23.html
Kong, S.-C., Cheung, W. M.-Y., & Tsang, O. (2023). Evaluating an artificial intelligence literacy programme for empowering and developing concepts, literacy and ethical awareness in senior secondary students. Education and Information Technologies, 28(4), 4703–4724. https://doi.org/10.1007/s10639-022-11408-7
Malhotra, R. (2021). Artificial intelligence and the future of power: 5 battlegrounds. Rupa.
Martin, K. (2022). Gamification, Manipulation, and Data Analytics. In Ethics of Data and Analytics. Auerbach Publications.
Mittelstadt, B. (2019, April 11). Principles alone cannot guarantee ethical AI | Nature Machine Intelligence. https://www.nature.com/articles/s42256-019-0114-4
Mukhopadhyay, S., & Reddy, D. (2023). Artificial Intelligence as an Enabler of Western Universalism. In R. Malhotra, T. N. Sudarshan, & M. Sastry (Eds.), The Power of Future Machines: Essays on Artificial Intelligence (pp. 241–263). BluOne Ink LLP.
Munn, L. (2023). The uselessness of AI ethics. AI and Ethics, 3(3), 869–877. https://doi.org/10.1007/s43681-022-00209-w
Ramezanian, R. (2025, February 24). Bot Busted Up: AI ChatBot’s Alleged Data Leak—Skyhigh Security. Skyhigh Security. https://www.skyhighsecurity.com/about/resources/intelligence-digest/bot-busted-up-ai-chatbots-alleged-data-leak.html
Roche, C., Wall, P. J., & Lewis, D. (2023). Ethics and diversity in artificial intelligence policies, strategies and initiatives. AI and Ethics, 3(4), 1095–1115. https://doi.org/10.1007/s43681-022-00218-9
Sarukkai, S. (2005). Indian philosophy and philosophy of science (1st ed.). Centre for Studies in Civilizations.
Wong, M. (2024, August 30). Chatbots Are Primed to Warp Reality—The Atlantic. https://www.theatlantic.com/technology/archive/2024/08/chatbots-false-memories/679660/
Yang, L., Tian, M., Xin, D., Cheng, Q., & Zheng, J. (2024). AI-Driven Anonymization: Protecting Personal Data Privacy While Leveraging Machine Learning (arXiv:2402.17191). arXiv. https://doi.org/10.48550/arXiv.2402.17191