SMU Law Review
Abstract
Recent advancements in artificial intelligence (AI) showcase its rapid evolution and promise, with the potential to profoundly transform decision-making, self-expression, and even the practice of law. However, AI also presents formidable challenges, including the further entrenchment of societal inequalities, widespread labor disruption, and existential threats to humanity. Modern AI systems show early signs of general intelligence, enabling them to perform a wide range of tasks beyond those of chatbots in both virtual and physical environments. Despite industry assurances of responsible AI development, these technologies are easily exploited and often exhibit troubling behaviors that even their creators struggle to understand.
This Article provides an accessible introduction to the current AI governance landscape, highlighting the intensifying AI development race alongside critical concepts such as model opacity and alignment mechanisms. It explores the novel ethical challenges introduced by generative AI, with an emphasis on societal-scale safety risks that have received minimal scholarly attention to date. The analysis further examines how judicial and regulatory systems attempt to address various AI-related issues, including discrimination, privacy, and intellectual property concerns. This Article concludes by arguing that the existing governance paradigm is inadequate to meet the unique challenges posed by advanced AI technologies. To transform the ideal of responsible AI from myth into reality, AI law and policy will need to transcend tenuous private-sector commitments and the narrow focus on model transparency.
Recommended Citation
Yussuf A. Aleem,
Socially Responsible AI in the GPT Era,
78
SMU L. Rev.
563
(2025)
