The rapid evolution of Artificial Intelligence (AI) has left legal frameworks struggling to keep up. With AI generative models now deeply embedded in various aspects of daily life, litigation is on the rise, making the development of AI law an urgent necessity.

 Compliance and oversight remain complex due to conflicting interests, tangled regulations, and significant legal gaps.

Emergence of AI Law

The AI Foundation Model Transparency Act was introduced in response to several high-profile copyright lawsuits, including Doe v. GitHub, Inc., Getty Images, Inc. v. Stability AI, and Andersen v. Stability AI.

 Stability AI, a defendant in two of these cases, spent $160,000 on lobbying in 2023 to influence AI-related legislation. 

As the 2024 presidential election approaches, many organizations are lobbying for the Protect Elections from Deceptive AI Act.  This bill aims to amend the Federal Election Campaign Act aka FECA, prohibiting the distribution of “materially deceptive AI-generated audio or visual media” about candidates before the election.

The Laws of Robotics

Science fiction has long explored the ethical and moral dilemmas of AI, from Isaac Asimov's writings to TV shows like Star Trek. Asimov's famous laws of robotics illustrate foundational ethical principles for AI:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey orders given by humans except where such orders would conflict with the First Law.
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

These fictional guidelines highlight enduring concerns that are now being addressed in real-world AI legislation.

AI Legislation in the U.S.

In 2023, Microsoft faced a lawsuit from the New York Times over allegations of using copyrighted content to train its machine learning models. Microsoft responded by emphasizing the importance of democratic, law-making processes in creating principled and actionable norms for AI development and deployment.

 The AI governance landscape in the U.S. is marked by diverse perspectives: some organizations, like the Center for AI Policy and the Center for AI Safety Action Fund, advocate for stringent regulations, while others support a more hands-off approach.

The Brennan Center reported that over 90 AI-related bills with bi-partisan sponsorship were introduced in the 118th Congress by June 2024. Despite differing approaches, there is a shared acknowledgment that federal legislation is struggling to keep pace with AI industry advancements.

Global AI Governance

Similar to the U.S., countries worldwide are racing to establish principles and legal frameworks for AI, particularly generative models.

 Proposals are emerging from various bodies, including the White House, the European Union, the United Nations, and the G20. 

This proliferation has led to numerous workshops, journals, and collaborative efforts focused on ethical AI. While there is widespread agreement on the importance of ethical AI, there is no consensus on its precise definition or implementation.

The U.S. currently employs a sectoral, self-regulatory approach to AI, while the European Union favors a centralized, risk-based framework. 

Despite extensive interest and research, the implications of AI remain contentious and challenging to define. Legal experts and governmental bodies stress the importance of balancing innovation with regulatory safeguards in AI development.

AI Law is thriving academically, with increasing research, conferences, and collaborations dedicated to the intersection of law and technology. However, there is still no consensus on the broader implications of AI, highlighting the complexity of integrating these technologies into existing legal systems.