Paper Details

Abstract: The fast progression of artificial intelligence (AI) and algorithmic decision-making has prompted urgent ethical enquiries on responsibility, equity, and moral accountability. As AI systems progressively impact human decisions, government, healthcare, education, and combat, the ethical implications have reached unprecedented levels. The moral responsibility of artificial intelligence is investigated in this study via the lens of a multidisciplinary approach, including ideas from the fields of philosophy, computer science, law, sociology, and cognitive science. It investigates the ways in which conventional ethical theories, including as deontology, utilitarianism, and virtue ethics, connect with modern difficulties in algorithmic design, data bias, and autonomous decision-making. The article also examines the conflict between human supervision and machine independence, highlighting the need for institutions, developers, and politicians to manage accountability in an era characterized by opaque and incomprehensible algorithms. This paper rigorously analyses the prevailing ethical frameworks of deontological and utilitarian viewpoints, focussing particularly on the implications of data bias within algorithmic systems. The conclusion presents a framework for the governance of ethical AI, emphasising the principles of transparency, accountability, and collaboration across various sectors. The paper finally presents a definitive set of ethical standards for assessing and improving moral accountability in AI systems, advocating for the incorporation of multidisciplinary perspectives to more effectively traverse the ethical terrain in the era of algorithms.

Keywords: Artificial Intelligence Ethics, Algorithmic Accountability, Deontological Ethics, Utilitarianism, Virtue Ethics, Algorithmic Bias, Human-in-the-Loop, Transparency in AI