Machado, J.; Sousa, R.; Peixoto, H.; Abelha, A. Ethical Decision-Making in Artificial Intelligence: A Logic
Programming Approach. Preprints2024, 2024102406. https://doi.org/10.20944/preprints202410.2406.v1
APA Style
Machado, J., Sousa, R., Peixoto, H., & Abelha, A. (2024). Ethical Decision-Making in Artificial Intelligence: A Logic
Programming Approach. Preprints. https://doi.org/10.20944/preprints202410.2406.v1
Chicago/Turabian Style
Machado, J., Hugo Peixoto and António Abelha. 2024 "Ethical Decision-Making in Artificial Intelligence: A Logic
Programming Approach" Preprints. https://doi.org/10.20944/preprints202410.2406.v1
Abstract
This article proposes a framework for integrating ethical reasoning into AI systems through Continuous Logic Programming (CLP), emphasizing the improvement of transparency and accountability in automated decision-making. The study highlights requirements for AI that respects to human values and societal norms by examining concerns such as algorithmic bias, data privacy, and ethical dilemmas in fields like healthcare and autonomous systems. The proposed CLP-based methodology offers a systematic, elucidative framework for ethical decision-making, allowing AI systems to balance operational efficiency with ethical principles. Important contributions include strategies for the integration of ethical frameworks, stakeholder engagement, and transparency, as well as discussion on Artificial Moral Agents and their function in addressing ethical dilemmas in AI. The paper presents practical examples that illustrate the application of CLP in ethical reasoning, highlighting its ability to bring together AI performance with responsible AI practices.
Keywords
n/a; Computational Ethics; Logic Programming; Artificial Moral Ethics; Moral Agents
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.