Artificial Intelligence and Machine Learning for Sustainable Development: Legal Perspectives on Innovation and Regulation

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have immense potential to drive sustainable development by addressing global challenges such as climate change, resource optimization, and economic inclusion. However, their deployment raises significant legal and ethical challenges, including issues of governance, intellectual property rights, data privacy, and algorithmic bias.

This study examines the intersection of AI, ML, and sustainable development from a legal perspective, focusing on the regulatory frameworks needed to balance innovation with ethical and equitable practices. Using doctrinal legal analysis and case studies, it identifies gaps in existing laws and highlights the need for adaptive, harmonized governance to address these challenges.

Findings indicate that while AI and ML can significantly advance Sustainable Development Goals (SDGs), fragmented regulations and ethical concerns hinder their effective and fair application. The study proposes actionable legal recommendations to support responsible AI use, emphasizing international collaboration and sustainability-focused policies.

This research contributes to the legal discourse by offering a clear roadmap for aligning AI innovation with sustainable development, ensuring technology serves as a tool for equity and global progress.