The Next Generation of Responsible AI Policies and Regulations

Carolyn Watters

doi:10.17821/srels/2024/v61i6/171623

Authors

Carolyn Watters
Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia

DOI:

https://doi.org/10.17821/srels/2024/v61i6/171623

Keywords:

AI Policy Framework, ChatGPT, Generative AI, Lare Language Models, LLMs, Responsible AI

Abstract

Responsible AI has, at its core, human-centric principles defining benefits and risks of recent generative AI applications. The purpose of this paper is to look at current and future Responsible AI policies and regulations with a focus on text-based Generative Artificial Intelligence (Gen AI) systems. Information retrieval and knowledge management research and applications provide a sound basis for the development of Gen AI. The goal is to encourage early engagement in the development of the next generation of Responsible AI policies and regulations in parallel with the emergence of the next generation of Gen AI applications, rather than as an afterthought.

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References

AIDA Artificial Intelligence and Data Act. Canada. 2024.

AI Seoul Summit. (2024). International Scientific Report on the Safety of Advanced AI. https://www.researchgate.net/publication/381277629_International_Scientific_Report_on_the_Safety_of_Advanced_AI.

Alkaissi, H., & McFarlane, S. I. (2023). Artificial hallucinations in ChatGPT: Implications in scientific writing. Cureus, 15(2), Article e35179. https://doi.org/10.7759/cureus.35179 PMid:36811129 PMCid:PMC9939079.

Barik, S. (2024). In big AI push, Cabinet clears Rs 10k cr plan to set up computing capacity. The Indian Express.

Brown, O. (2023). When AI Hallucinates. Nautilus.

CAIDP. (2024) Center for AI and Digital Policy. https://www.caidp.org/

European Commission. (2020) Critical raw materials for strategic technologies and sectors in the EU - A foresight study. https://datacentersustainability.org/data-centersandcritical-raw-materials/

European Union Agency for Fundamental Rights. (2022 Dec 8). Bias in algorithms - Artificial intelligence and discrimination. https://fra.europa.eu/sites/default/files/fra_uploads/fra2022-bias-in-algorithms_en.pdf

Global Data. (2023). Synthetic data - The master key to AI’s future. https://www.globaldata.com/store/report/syntheticdatamaster-key-to-ai-future-trend-analysis/

Grossman, S., Zerilli, T., & Nathan, J. P. (2024). Appropriateness of ChatGPT as a resource for medication-related questions. British Journal of Clinical Pharmacology, 90(10), 2691-2695. https://doi.org/10.1111/bcp.16212 PMid:39096130

McKinsey & Company. (2024a). Responsible AI (RAI) principles. https://www.mckinsey.com/capabilities/quantumblack/ how-we-help-clients/generative-ai/responsible-ai-principles.

McKinsey, & Company. (2024b). How data centers and the energy sector can sate AI’s hunger for power. https://www.mckinsey.com/industries/private-capital/our-insights/how-data-centers-and-the-energy-sector-can-sate-aishungerfor-power

Merkens, S. (2023). New York lawyers sanctioned for using fake ChatGPT cases in legal brief. Reuters. https://www.reuters.com/legal/new-york-lawyers-sanctioned-using-fakechatgptcases-legal-brief-2023-06-22/

Monserrate, S. G. (2022). The staggering ecological impacts of computation and the cloud. The MIT Reader. https://thereader.mitpress.mit.edu/the-staggering-ecologicalimpactsof-computation-and-the-cloud/

Montrealdeclaration-responsibleai. (2018). Montreal declaration for a responsible development of artificial intelligence. https://montrealdeclaration-responsibleai.com/

Mentz, C., Kang, A., Thompson, N., & Grant, G. (2024). How tech giants cut corners to harvest data. The New York Times. https://www.nytimes.com/2024/04/06/technology/techgiantsharvest-data-artificial-intelligence.html

New York Times. (2024). Report on AI Infrastructure. Ritchie, H., Mathieu, E., Roser, M., & Ortiz-Ospina, E.(2022). Internet. Our World in Data (OWID). https://ourworldindata.org/internet

Ranganathan, S. R., & Gopinath, M. A. (1967). Prolegomena to library classification. Asia Pub House.

Salton, G. (1983). Introduction to modern information retrieval. McGraw-Hill, New York.

Cahn, D. (2023). AI’s $200B question. Sequoia Capital. https:// www.sequoiacap.com/article/follow-the-gpus-perspective/

Stockle, J. (2019). AI in the hype cycle - A brief history of AI. https://www.hiig.de/en/a-brief-history-of-ai-ai-in-thehypecycle/

Toronto Declaration. (2018). Protecting the right to equality and non-discrimination in machine learning systems. https://www.torontodeclaration.org/

UNESCO. (2022). Ethics of artificial intelligence. https://www.unesco.org/en/artificial-intelligence/recommendationethics

Viswanathan, G. (2023). ChatGPT struggles to answer medical questions. CNN. https://www.cnn.com/2023/12/10/health/chatgpt-medical-questions

Watters, C. (2024a, August 12-14). Responsible AI: Next generation policies and regulations [Conference presentation]. AI and Knowledge Management: Academia-Industry Summit (AIKM), New Delhi.

Watters, C. (2024b, August 18). Responsible AI in the time of generative AI [Open Forum]. Mysore Open Forum. Mysore.

Watters, C. (2024c August 27). Responsible AI: Balancing the risks and benefits of enhanced artificial intelligence [Annual Lecture]. Informatics 20th Annual Lecture. Bengaluru.