Accountability in AI and the Responsibility for AI-Driven Decisions

Abstract

As Artificial Intelligence (AI) continues to permeate various sectors, the question of accountability for AI-driven decisions has become a central ethical issue. AI systems are increasingly used in critical decision-making processes across industries such as healthcare, finance, criminal justice, and employment. While AI offers potential benefits in terms of efficiency, accuracy, and cost-effectiveness, it also raises significant ethical and legal concerns regarding accountability for the outcomes of AI-driven decisions. This paper explores the issue of accountability in AI, specifically examining who is responsible when AI systems make biased, inaccurate, or harmful decisions. By reviewing existing frameworks for AI accountability, exploring case studies, and analyzing legal perspectives, the paper aims to clarify the roles and responsibilities of developers, users, and organizations in ensuring ethical AI practices. The paper argues that shared responsibility and transparent governance are key to addressing accountability concerns and ensuring AI systems serve the public good.