AI regulation in the U.S. and EU | Carta

Artificial intelligence regulation

Author:

The Carta Policy Team

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Read time:

8 minutes

Published date:

July 25, 2024

AI regulation is happening at different speeds in the EU and in the U.S. Here’s a guide to where things stand.


Regulating artificial intelligence: key concerns

Technologists, economists, and business leaders expect AI will have a far-reaching impact across industries and sectors.

Policymakers and critics of AI have raised concerns over numerous possible applications of the AI systems. Thus far, these concerns are largely concentrated in a few areas:


Existing AI regulations

Creating AI regulation that protects against the risks while promoting innovation is a top priority for policymakers in both the United States and Europe, but their approaches and progress have varied.

EU AI regulations

So far, Europe has taken the lead in writing legislation to regulate AI.

In May 2024, the EU Council approved its landmark EU AI Act following its approval by the European Parliament in March. The EU’s new AI policy is the first law in the world to regulate general-purpose AI systems, and will apply to companies that operate in the 27 EU member states regardless of where the company is headquartered.

Although the law fully comes into effect in May 2026, several parts of the EU AI Act come into effect in December 2024. These sections focus primarily on privacy, including provisions that govern predictive policing (using AI algorithms to predict potential future crime) and the scraping of facial images from the internet or CCTV footage for use by AI systems.

U.S. AI regulations

In the United States, progress on AI policy has been slower and more fragmented. To date, Congress has not enacted legislation to regulate the use of AI in the United States.

The primary driver of federal AI policy is the Biden Administration’s Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence from October 2023. The executive order (EO) primarily focuses on guidance to federal government agencies on how to utilize AI to achieve more efficient outcomes. The EO asserts the federal government’s intent to foster an environment for innovation in the AI sector while finding ways to ensure AI doesn't introduce new biases or security concerns into public-sector work.

The EO articulates over 100 required actions for federal agencies to undertake over the next year, ranging from streamlining the visa process for applicants using AI to the creation of National AI Research Institutes.


AI regulation: EU vs. U.S

Comparing the two primary policies governing AI in Europe and the U.S. so far, there are some key differences between the two approaches:

EU AI Act Biden Executive Order
Coverage Directly applies to any provider of general-purpose AI models operating in the EU. Instructs federal agencies but doesn't impose regulation.
Legal status Can only be repealed by the EU parliament or struck down by a court. Can be revoked by another president or found unconstitutional by a court.
Threshold for risk A lower computing threshold means the Act covers a broader range of AI models, likely including some already in use by Google and Microsoft. A higher computing threshold means that no existing AI model is known to exceed the threshold.
Ambition Aims to be the global standard. Focused on domestic agencies.

While the current state of federal AI policy in the U.S. is less comprehensive than the EU AI Act, particularly with regard to the applicability to the private sector, AI policy continues to develop at all levels of government in the U.S.:


AI liability in the states

While the federal government continues to stall on artificial intelligence (AI) policy, the states have begun to step in, particularly as it relates to increasing AI safety through increased liability for developers of AI.

AI researchers and practitioners agree that AI poses risk—but the exact extent of the risk posed by AI is an area of debate. Although some cite catastrophic risks posed by AI as a serious concern, others in the industry argue that the large-scale risks are blown out of proportion and are concerned that over-indexing for these risks will negatively impact AI innovation.

And while regulating AI will require a swath of new policies, increasing liability for those who develop AI systems has been a focus by state policymakers looking for a way to mitigate AI-related risks.

Current AI liability landscape

Neither the courts nor Congress have provided reliable legal guidance on generative AI in the United States. Currently, AI companies operate under traditional product liability law, which falls under state jurisdiction. Notably, traditional product liability law does not account for specific unique characteristics of AI, including complexity, autonomy, and opacity; this will make it extremely difficult to assign liability using the current legal frameworks in each state.

In previous case law at the state level, many courts found that if the software was “ reasonably safe when designed and installed,” the defendants were not liable for plaintiff’s damages. These cases implied that creators of AI software or hardware were not liable for any harm as long as these products were non-defective when made. This has largely remained the standard in state courts. However, if legal liability hinges only on AI systems being “non-defective” when developed, AI developers avoid responsibility. Moreover, many AI systems are open-source and unsecured, meaning that bad actors can alter these systems and disable safety features, make their own custom versions, and abuse them for a wide variety of tasks.

In May 2024, the Senate AI Working Group released a legislative roadmap advocating for the “enforcement of existing laws” with respect to AI. However, as outlined above, there are no clear laws in the United States regarding liability surrounding AI, leaving many decisions up to the courts to decide.

SB 1047

With these gaps in the product legal liability framework concerning AI, states are beginning to step in and legislate. California is leading the way with SB 1047, a bill making its way through the California state legislature.

On July 2, the California State Assembly Judiciary Committee passed  SB 1047 (the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act), following its passage by a bipartisan vote in the California State Senate on May 21. The bill mandates specific safety testing for AI models  that cost more than $100 million in computing power to train and that use a specific, high level of computing power. If they fail to do so, they will be held liable if their AI system leads to a “mass casualty event” or more than $500 million in damages in a single incident or set of closely linked incidents. As of July 2024, there were no AI models that meet the threshold for required safety training. The bill also creates whistleblower protections for employees of frontier AI laboratories and establishes an advisory council to support safe and secure open-source AI.

The bill is opposed by venture capital firms and tech companies, including Meta. Opponents say the regulations take aim at developers and instead should be focused on those who use and exploit the AI systems for harm. Meta’s chief AI scientist Yann LeCun has argued that SB 1047 will “ destroy California’s fantastic history of technological innovation” and ultimately discourage companies from developing large AI systems, and from keeping their technology open-source, which would stifle the efforts of small startups and open source developers.

While industry fiercely pushes against SB 1047, the American public seems to agree with leading AI safety scientists: a September 2023 poll found that 73% of voters believe AI companies should be held liable for harms from technology they create compared to just 11% that believe they should not.

Next steps

The bill will be up for a final vote in August. If it passes, it still remains unclear if Governor Newsom will sign the bill into law as he has not yet provided any public feedback on it.

Looking at the larger picture, states stepping in and  building their own liability regimes for AI will eventually lead to a patchwork of regulation that will become increasingly complex and untenable. The continued development of liability regimes at the state level will result in regulatory fragmentation, leading to vastly increased regulatory complexity and costs for AI companies active throughout the United States.