Artificial Intelligence and the Future of Legal Education In Pakistan: An Analysis

Abstract

Current legal and policy approaches to artificial intelligence (AI) focus heavily on mitigating risks and preventing harms, often neglecting how law can proactively guide AI toward positive societal outcomes. This article critiques the dominant "law-of-AI-wrongs" paradigm as descriptively inaccurate and normatively flawed, arguing that it prioritizes reactive regulation over strategic governance. Through analysis of key U.S. and European initiatives—such as the FTC report, the 2022 AI Bill of Rights, and the draft EU AI Act—the article highlights a disproportionate emphasis on AI risks, often grounded in flawed comparisons to human decision-making and status quo practices. It calls for a balanced, comparative cost-benefit regulatory model that supports innovation while safeguarding rights. The article identifies key tensions in AI regulation, such as the trade-off between privacy (data minimization) and fairness (data maximization), and proposes new rights to automated decision-making and complete datasets. It advocates for policies that build public trust in AI through behavioral research, education, and collaborative governance. Ultimately, it provides a blueprint for shifting from a defensive to a proactive model of AI regulation that promotes both accountability and innovation.