A Comparative Analysis of Legal Frameworks for ensuring Quality and Accuracy of AI – Generated Data: A Study of USA and Sri Lanka

Abstract

This study focuses at the changing legislative frameworks in Sri Lanka and the United States (USA) that control the reliability and quality of AI-generated data. As artificial intelligence is progressively included into diverse industries, it is imperative to guarantee the dependability and equity of outputs produced by AI. In order to protect data integrity, the paper compares the regulatory frameworks in the two nations, highlighting significant laws, case law, and enforcement strategies. The Federal Trade Commission Act and the Fair Credit Reporting Act, two US federal statutes that have an impact on consumer protection regulations and data accuracy, are examined in this paper. They have influenced how algorithmic responsibility and the use of AI to decision-making processes are seen by the law. Similarly, in Sri Lanka, the examination is concentrated on the laws and regulations that control technology governance and data protection. Examining the effects of the Data Protection Act and other pertinent laws on guaranteeing the accuracy and dependability of data generated by artificial intelligence is part of this. This article attempts to identify opportunities, problems, and gaps in the current regulatory frameworks by a thorough examination statutory provisions, and comparative legal research. In the conclusion, it aims to provide suggestions for improving existing frameworks to handle new problems pertaining to the accuracy and quality of AI-generated data in a global setting.