LEGAL LIABILITY AND ACCOUNTABILITY IN AI DECISION-  MAKING: CHALLENGES AND SOLUTIONS

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Dr Priyadarshi Nagda

LEGAL LIABILITY AND ACCOUNTABILITY IN AI DECISION- MAKING: CHALLENGES AND SOLUTIONS

Authors: Dr Priyadarshi Nagda

Unique Paper ID: 174899
Volume: 11
Issue: 11
PageNo: 1789-1799

Keywords: AI Decision-Making Legal Liability Accountability Ethical Guidelines Transparency and Explainability.

Abstract:
Artificial intelligence (AI) has fast become part of many businesses, enabling significant advances in healthcare, finance, and transportation. Our rising reliance on AI decision-making systems raises severe legal responsibility and accountability concerns. This research paper examines legal duty and accountability in AI decision-making to bridge gaps and satisfy future expectations. The article defines artificial intelligence, how it works, and how it makes judgments. It investigates the intricate operations of AI systems using examples from diverse sectors to explain how these technologies work and their legal implications. We will then examine AI control laws, regulations, and case law. As part of our research, we evaluated global laws to discover where they agreed and diverged. By revealing how courts have addressed accountability and liability in AI situations, historical decisions may illuminate the current law. The paper focuses on AI decision-making challenges to accountability and legal responsibility. These include explainability, transparency, AI system complexity, and legal definitions. The “black box” nature of many AI systems makes it hard to trace decision-making processes and assign blame. The essay also discusses AI system prejudice and bias, which might lead to immoral or unlawful behavior. The global deployment of AI has made defining jurisdiction difficult, complicating the legal liability structure. It will take several approaches to tackle these challenges. The paper suggests developing explainable AI (XAI) techniques to make AI systems more transparent. New regulatory sandboxes and testing environments are being proposed to promote ethical AI development and deployment. In these controlled contexts, we may test and evaluate AI systems to identify and resolve ethical and legal issues before they impact the market. Ethical standards and best practices are necessary to navigate AI law. The essay discusses AI ethics and the importance of interdisciplinary cooperation between lawyers, technologists, and ethicists. This collaboration is essential for crafting robust policies that balance innovation, accountability, and public safety. The paper proposes accountability and legal system changes as feasible alternatives. This includes specific legal amendments to better define AI and its roles and 1 Binns, R. (2018). “Fairness in Machine Learning: Lessons from Political Philosophy.” Proceedings of responsibilities. Auditors, impact evaluations, and liability insurance help ensure AI systems follow the regulations. Technology for monitoring and grading AI systems helps with compliance, according to the report. The paper concludes by emphasizing AI legislative harmonization and international cooperation. Legal framework differences threaten global AI deployment. We propose worldwide collaboration and harmonization to improve AI regulation. An extensive analysis of AI decision-making's legal responsibility and accountability issues and remedies ends this paper. It gives a framework that considers recent and future AI developments. This article gives results and proposals to help policymakers, developers, and consumers navigate AI's complex legal environment to responsibly and ethically utilize these powerful technologies. This article's extensive investigation contributes to AI law and governance discussions by providing insights and practical ideas for a secure and responsible AI ecosystem.

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ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 1789-1799

LEGAL LIABILITY AND ACCOUNTABILITY IN AI DECISION- MAKING: CHALLENGES AND SOLUTIONS

Available:https://ijirt.org/article?manuscript=174899

01 Apr, 2025

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