Ethical Challenges and Regulatory Frameworks for Generative AI: Navigating Risks and Responsibilities

Kiran Babu Macha; Shubham Metha; Anu Rai; Sai Deepika Garikipati; Manoj Varma Lakhamraju; Nikhil Sagar Miriyala

Authors

Kiran Babu Macha Lead Developer, Maximus Inc, USA Author
Shubham Metha Software Engineer, Northwest Bank, USA Author
Anu Rai Technical Product Manager, USA. Author
Sai Deepika Garikipati Independent Researcher, USA Author
Manoj Varma Lakhamraju Workday Consultant, Teckpros LLC, USA Author
Nikhil Sagar Miriyala Senior Software Engineer, Visa Inc, USA Author

Keywords:

Generative AI, Ethical Challenges, Regulatory Framework, Bias in AI, AI accountability, Data privacy

Abstract

The use of generative AI has evolved greatly over time and has been seen as having transformative capabilities in most industries, but these capabilities bring with them significant ethical concerns and regulatory challenges. This study seeks to explore the ethical implications of generative AI; for example, it delves into bias, misinformation, data privacy, and accountability, with an examination of existing regulatory frameworks relating to its use in 2023 across different countries and organizations. The study also highlights the role of developers, policymakers, and stakeholders in ethical AI development. A comparison of the accuracy and precision of key sources shows that Kennedy S. (2023) is the most reliable source, with an accuracy of 96% and a precision of 84%, followed by Hendrycks Dan et al. (2020) with an accuracy of 80% and a precision of 78%. Kanjee Z. et al. (2023) reveal the lowest reliability with an accuracy of 64% and a precision of 54%. The above results advise choosing sources with high precision and the standardization of a regulatory approach to ensure transparency, fairness, and accountability in the applications of generative AI.

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