ETHICAL IMPLICATIONS OF AI IN AUTONOMOUS DECISION-MAKING SYSTEMS
Keywords:
Artificial Intelligence, Ethics, Autonomous Decision-Making, Accountability, Transparency, BiasAbstract
As artificial intelligence (AI) systems become increasingly integrated into autonomous decision-making, concerns about the ethical implications of these systems have grown. This paper explores the ethical challenges associated with AI-driven autonomous decision-making, focusing on issues such as bias, accountability, transparency, and the societal impact. Through a combination of case studies and theoretical analysis, we discuss the potential risks and benefits of AI in various sectors, including healthcare, law enforcement, and finance. The paper aims to contribute to the ongoing discourse on creating ethical frameworks for AI development and deployment.
References
Binns, R. (2018). Fairness in Machine Learning: Lessons from Political Philosophy. Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency, 149-159.
Danks, D., & London, A. J. (2017). Algorithmic Bias in Autonomous Systems. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), 4691-4697.
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The Ethics of Algorithms: Mapping the Debate. Big Data & Society, 3(2), 2053951716679679.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.
Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation. International Data Privacy Law, 7(2), 76-99.
Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1
Jobin, A., Ienca, M., & Vayena, E. (2019). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
Rahwan, I. (2018). Society-in-the-Loop: Programming the Algorithmic Social Contract. Ethics and Information Technology, 20(1), 5–14. https://doi.org/10.1007/s10676-017-9430-8
Crawford, K. (2017). The Trouble with Bias. Conference on Neural Information Processing Systems (NIPS). https://www.nips.cc/Conferences/2017/Schedule?showEvent=8754
European Commission. (2020). White Paper on Artificial Intelligence: A European Approach to Excellence and Trust. https://ec.europa.eu/info/sites/default/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
