Entries Tagged "laws"

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Against the Federal Moratorium on State-Level Regulation of AI

Cast your mind back to May of this year: Congress was in the throes of debate over the massive budget bill. Amidst the many seismic provisions, Senator Ted Cruz dropped a ticking time bomb of tech policy: a ten-year moratorium on the ability of states to regulate artificial intelligence. To many, this was catastrophic. The few massive AI companies seem to be swallowing our economy whole: their energy demands are overriding household needs, their data demands are overriding creators’ copyright, and their products are triggering mass unemployment as well as new types of clinical psychoses. In a moment where Congress is seemingly unable to act to pass any meaningful consumer protections or market regulations, why would we hamstring the one entity evidently capable of doing so—the states? States that have already enacted consumer protections and other AI regulations, like California, and those actively debating them, like Massachusetts, were alarmed. Seventeen Republican governors wrote a letter decrying the idea, and it was ultimately killed in a rare vote of bipartisan near-unanimity.

The idea is back. Before Thanksgiving, a House Republican leader suggested they might slip it into the annual defense spending bill. Then, a draft document leaked outlining the Trump administration’s intent to enforce the state regulatory ban through executive powers. An outpouring of opposition (including from some Republican state leaders) beat back that notion for a few weeks, but on Monday, Trump posted on social media that the promised Executive Order is indeed coming soon. That would put a growing cohort of states, including California and New York, as well as Republican strongholds like Utah and Texas, in jeopardy.

The constellation of motivations behind this proposal is clear: conservative ideology, cash, and China.

The intellectual argument in favor of the moratorium is that “freedom“-killing state regulation on AI would create a patchwork that would be difficult for AI companies to comply with, which would slow the pace of innovation needed to win an AI arms race with China. AI companies and their investors have been aggressively peddling this narrative for years now, and are increasingly backing it with exorbitant lobbying dollars. It’s a handy argument, useful not only to kill regulatory constraints, but also—companies hope—to win federal bailouts and energy subsidies.

Citizens should parse that argument from their own point of view, not Big Tech’s. Preventing states from regulating AI means that those companies get to tell Washington what they want, but your state representatives are powerless to represent your own interests. Which freedom is more important to you: the freedom for a few near-monopolies to profit from AI, or the freedom for you and your neighbors to demand protections from its abuses?

There is an element of this that is more partisan than ideological. Vice President J.D. Vance argued that federal preemption is needed to prevent “progressive” states from controlling AI’s future. This is an indicator of creeping polarization, where Democrats decry the monopolism, bias, and harms attendant to corporate AI and Republicans reflexively take the opposite side. It doesn’t help that some in the parties also have direct financial interests in the AI supply chain.

But this does not need to be a partisan wedge issue: both Democrats and Republicans have strong reasons to support state-level AI legislation. Everyone shares an interest in protecting consumers from harm created by Big Tech companies. In leading the charge to kill Cruz’s initial AI moratorium proposal, Republican Senator Masha Blackburn explained that “This provision could allow Big Tech to continue to exploit kids, creators, and conservatives? we can’t block states from making laws that protect their citizens.” More recently, Florida Governor Ron DeSantis wants to regulate AI in his state.

The often-heard complaint that it is hard to comply with a patchwork of state regulations rings hollow. Pretty much every other consumer-facing industry has managed to deal with local regulation—automobiles, children’s toys, food, and drugs—and those regulations have been effective consumer protections. The AI industry includes some of the most valuable companies globally and has demonstrated the ability to comply with differing regulations around the world, including the EU’s AI and data privacy regulations, substantially more onerous than those so far adopted by US states. If we can’t leverage state regulatory power to shape the AI industry, to what industry could it possibly apply?

The regulatory superpower that states have here is not size and force, but rather speed and locality. We need the “laboratories of democracy” to experiment with different types of regulation that fit the specific needs and interests of their constituents and evolve responsively to the concerns they raise, especially in such a consequential and rapidly changing area such as AI.

We should embrace the ability of regulation to be a driver—not a limiter—of innovation. Regulations don’t restrict companies from building better products or making more profit; they help channel that innovation in specific ways that protect the public interest. Drug safety regulations don’t prevent pharma companies from inventing drugs; they force them to invent drugs that are safe and efficacious. States can direct private innovation to serve the public.

But, most importantly, regulations are needed to prevent the most dangerous impact of AI today: the concentration of power associated with trillion-dollar AI companies and the power-amplifying technologies they are producing. We outline the specific ways that the use of AI in governance can disrupt existing balances of power, and how to steer those applications towards more equitable balances, in our new book, Rewiring Democracy. In the nearly complete absence of Congressional action on AI over the years, it has swept the world’s attention; it has become clear that states are the only effective policy levers we have against that concentration of power.

Instead of impeding states from regulating AI, the federal government should support them to drive AI innovation. If proponents of a moratorium worry that the private sector won’t deliver what they think is needed to compete in the new global economy, then we should engage government to help generate AI innovations that serve the public and solve the problems most important to people. Following the lead of countries like Switzerland, France, and Singapore, the US could invest in developing and deploying AI models designed as public goods: transparent, open, and useful for tasks in public administration and governance.

Maybe you don’t trust the federal government to build or operate an AI tool that acts in the public interest? We don’t either. States are a much better place for this innovation to happen because they are closer to the people, they are charged with delivering most government services, they are better aligned with local political sentiments, and they have achieved greater trust. They’re where we can test, iterate, compare, and contrast regulatory approaches that could inform eventual and better federal policy. And, while the costs of training and operating performance AI tools like large language models have declined precipitously, the federal government can play a valuable role here in funding cash-strapped states to lead this kind of innovation.

This essay was written with Nathan E. Sanders, and originally appeared in Gizmodo.

EDITED TO ADD: Trump signed an executive order banning state-level AI regulations hours after this was published. This is not going to be the last word on the subject.

Posted on December 15, 2025 at 7:02 AM • View Comments

Banning VPNs

This is crazy. Lawmakers in several US states are contemplating banning VPNs, because…think of the children!

As of this writing, Wisconsin lawmakers are escalating their war on privacy by targeting VPNs in the name of “protecting children” in A.B. 105/S.B. 130. It’s an age verification bill that requires all websites distributing material that could conceivably be deemed “sexual content” to both implement an age verification system and also to block the access of users connected via VPN. The bill seeks to broadly expand the definition of materials that are “harmful to minors” beyond the type of speech that states can prohibit minors from accessing­ potentially encompassing things like depictions and discussions of human anatomy, sexuality, and reproduction.

The EFF link explains why this is a terrible idea.

Posted on December 1, 2025 at 7:59 AM • View Comments

On Hacking Back

Former DoJ attorney John Carlin writes about hackback, which he defines thus: “A hack back is a type of cyber response that incorporates a counterattack designed to proactively engage with, disable, or collect evidence about an attacker. Although hack backs can take on various forms, they are—­by definition­—not passive defensive measures.”

His conclusion:

As the law currently stands, specific forms of purely defense measures are authorized so long as they affect only the victim’s system or data.

At the other end of the spectrum, offensive measures that involve accessing or otherwise causing damage or loss to the hacker’s systems are likely prohibited, absent government oversight or authorization. And even then parties should proceed with caution in light of the heightened risks of misattribution, collateral damage, and retaliation.

As for the broad range of other hack back tactics that fall in the middle of active defense and offensive measures, private parties should continue to engage in these tactics only with government oversight or authorization. These measures exist within a legal gray area and would likely benefit from amendments to the CFAA and CISA that clarify and carve out the parameters of authorization for specific self-defense measures. But in the absence of amendments or clarification on the scope of those laws, private actors can seek governmental authorization through an array of channels, whether they be partnering with law enforcement or seeking authorization to engage in more offensive tactics from the courts in connection with private litigation.

Posted on November 12, 2025 at 7:01 AM • View Comments

The Semiconductor Industry and Regulatory Compliance

Earlier this week, the Trump administration narrowed export controls on advanced semiconductors ahead of US-China trade negotiations. The administration is increasingly relying on export licenses to allow American semiconductor firms to sell their products to Chinese customers, while keeping the most powerful of them out of the hands of our military adversaries. These are the chips that power the artificial intelligence research fueling China’s technological rise, as well as the advanced military equipment underpinning Russia’s invasion of Ukraine.

The US government relies on private-sector firms to implement those export controls. It’s not working. US-manufactured semiconductors have been found in Russian weapons. And China is skirting American export controls to accelerate AI research and development, with the explicit goal of enhancing its military capabilities.

American semiconductor firms are unwilling or unable to restrict the flow of semiconductors. Instead of investing in effective compliance mechanisms, these firms have consistently prioritized their bottom lines—a rational decision, given the fundamentally risky nature of the semiconductor industry.

We can’t afford to wait for semiconductor firms to catch up gradually. To create a robust regulatory environment in the semiconductor industry, both the US government and chip companies must take clear and decisive actions today and consistently over time.

Consider the financial services industry. Those companies are also heavily regulated, implementing US government regulations ranging from international sanctions to anti-money laundering. For decades, these companies have invested heavily in compliance technology. Large banks maintain teams of compliance employees, often numbering in the thousands.

The companies understand that by entering the financial services industry, they assume the responsibility to verify their customers’ identities and activities, refuse services to those engaged in criminal activity, and report certain activities to the authorities. They take these obligations seriously because they know they will face massive fines when they fail. Across the financial sector, the Securities and Exchange Commission imposed a whopping $6.4 billion in penalties in 2022. For example, TD Bank recently paid almost $2 billion in penalties because of its ineffective anti-money laundering efforts

An executive order issued earlier this year applied a similar regulatory model to potential “know your customer” obligations for certain cloud service providers.

If Trump’s new license-focused export controls are to be effective, the administration must increase the penalties for noncompliance. The Commerce Department’s Bureau of Industry and Security (BIS) needs to more aggressively enforce its regulations by sharply increasing penalties for export control violations.

BIS has been working to improve enforcement, as evidenced by this week’s news of a $95 million penalty against Cadence Design Systems for violating export controls on its chip design technology. Unfortunately, BIS lacks the people, technology, and funding to enforce these controls across the board.

The Trump administration should also use its bully pulpit, publicly naming companies that break the rules and encouraging American firms and consumers to do business elsewhere. Regulatory threats and bad publicity are the only ways to force the semiconductor industry to take export control regulations seriously and invest in compliance.

With those threats in place, American semiconductor firms must accept their obligation to comply with regulations and cooperate. They need to invest in strengthening their compliance teams and conduct proactive audits of their subsidiaries, their customers, and their customers’ customers.

Firms should elevate risk and compliance voices onto their executive leadership teams, similar to the chief risk officer role found in banks. Senior leaders need to devote their time to regular progress reviews focused on meaningful, proactive compliance with export controls and other critical regulations, thereby leading their organizations to make compliance a priority.

As the world becomes increasingly dangerous and America’s adversaries become more emboldened, we need to maintain stronger control over our supply of critical semiconductors. If Russia and China are allowed unfettered access to advanced American chips for their AI efforts and military equipment, we risk losing the military advantage and our ability to deter conflicts worldwide. The geopolitical importance of semiconductors will only increase as the world becomes more dangerous and more reliant on advanced technologies—American security depends on limiting their flow.

This essay was written with Andrew Kidd and Celine Lee, and originally appeared in The National Interest.

Posted on August 6, 2025 at 12:35 AM • View Comments

“Encryption Backdoors and the Fourth Amendment”

Law journal article that looks at the Dual_EC_PRNG backdoor from a US constitutional perspective:

Abstract: The National Security Agency (NSA) reportedly paid and pressured technology companies to trick their customers into using vulnerable encryption products. This Article examines whether any of three theories removed the Fourth Amendment’s requirement that this be reasonable. The first is that a challenge to the encryption backdoor might fail for want of a search or seizure. The Article rejects this both because the Amendment reaches some vulnerabilities apart from the searches and seizures they enable and because the creation of this vulnerability was itself a search or seizure. The second is that the role of the technology companies might have brought this backdoor within the private-search doctrine. The Article criticizes the doctrine­ particularly its origins in Burdeau v. McDowell­and argues that if it ever should apply, it should not here. The last is that the customers might have waived their Fourth Amendment rights under the third-party doctrine. The Article rejects this both because the customers were not on notice of the backdoor and because historical understandings of the Amendment would not have tolerated it. The Article concludes that none of these theories removed the Amendment’s reasonableness requirement.

Posted on July 22, 2025 at 7:05 AM • View Comments

AI-Generated Law

On April 14, Dubai’s ruler, Sheikh Mohammed bin Rashid Al Maktoum, announced that the United Arab Emirates would begin using artificial intelligence to help write its laws. A new Regulatory Intelligence Office would use the technology to “regularly suggest updates” to the law and “accelerate the issuance of legislation by up to 70%.” AI would create a “comprehensive legislative plan” spanning local and federal law and would be connected to public administration, the courts, and global policy trends.

The plan was widely greeted with astonishment. This sort of AI legislating would be a global “first,” with the potential to go “horribly wrong.” Skeptics fear that the AI model will make up facts or fundamentally fail to understand societal tenets such as fair treatment and justice when influencing law.

The truth is, the UAE’s idea of AI-generated law is not really a first and not necessarily terrible.

The first instance of enacted law known to have been written by AI was passed in Porto Alegre, Brazil, in 2023. It was a local ordinance about water meter replacement. Council member Ramiro Rosário was simply looking for help in generating and articulating ideas for solving a policy problem, and ChatGPT did well enough that the bill passed unanimously. We approve of AI assisting humans in this manner, although Rosário should have disclosed that the bill was written by AI before it was voted on.

Brazil was a harbinger but hardly unique. In recent years, there has been a steady stream of attention-seeking politicians at the local and national level introducing bills that they promote as being drafted by AI or letting AI write their speeches for them or even vocalize them in the chamber.

The Emirati proposal is different from those examples in important ways. It promises to be more systemic and less of a one-off stunt. The UAE has promised to spend more than $3 billion to transform into an “AI-native” government by 2027. Time will tell if it is also different in being more hype than reality.

Rather than being a true first, the UAE’s announcement is emblematic of a much wider global trend of legislative bodies integrating AI assistive tools for legislative research, drafting, translation, data processing, and much more. Individual lawmakers have begun turning to AI drafting tools as they traditionally have relied on staffers, interns, or lobbyists. The French government has gone so far as to train its own AI model to assist with legislative tasks.

Even asking AI to comprehensively review and update legislation would not be a first. In 2020, the U.S. state of Ohio began using AI to do wholesale revision of its administrative law. AI’s speed is potentially a good match to this kind of large-scale editorial project; the state’s then-lieutenant governor, Jon Husted, claims it was successful in eliminating 2.2 million words’ worth of unnecessary regulation from Ohio’s code. Now a U.S. senator, Husted has recently proposed to take the same approach to U.S. federal law, with an ideological bent promoting AI as a tool for systematic deregulation.

The dangers of confabulation and inhumanity—while legitimate—aren’t really what makes the potential of AI-generated law novel. Humans make mistakes when writing law, too. Recall that a single typo in a 900-page law nearly brought down the massive U.S. health care reforms of the Affordable Care Act in 2015, before the Supreme Court excused the error. And, distressingly, the citizens and residents of nondemocratic states are already subject to arbitrary and often inhumane laws. (The UAE is a federation of monarchies without direct elections of legislators and with a poor record on political rights and civil liberties, as evaluated by Freedom House.)

The primary concern with using AI in lawmaking is that it will be wielded as a tool by the powerful to advance their own interests. AI may not fundamentally change lawmaking, but its superhuman capabilities have the potential to exacerbate the risks of power concentration.

AI, and technology generally, is often invoked by politicians to give their project a patina of objectivity and rationality, but it doesn’t really do any such thing. As proposed, AI would simply give the UAE’s hereditary rulers new tools to express, enact, and enforce their preferred policies.

Mohammed’s emphasis that a primary benefit of AI will be to make law faster is also misguided. The machine may write the text, but humans will still propose, debate, and vote on the legislation. Drafting is rarely the bottleneck in passing new law. What takes much longer is for humans to amend, horse-trade, and ultimately come to agreement on the content of that legislation—even when that politicking is happening among a small group of monarchic elites.

Rather than expeditiousness, the more important capability offered by AI is sophistication. AI has the potential to make law more complex, tailoring it to a multitude of different scenarios. The combination of AI’s research and drafting speed makes it possible for it to outline legislation governing dozens, even thousands, of special cases for each proposed rule.

But here again, this capability of AI opens the door for the powerful to have their way. AI’s capacity to write complex law would allow the humans directing it to dictate their exacting policy preference for every special case. It could even embed those preferences surreptitiously.

Since time immemorial, legislators have carved out legal loopholes to narrowly cater to special interests. AI will be a powerful tool for authoritarians, lobbyists, and other empowered interests to do this at a greater scale. AI can help automatically produce what political scientist Amy McKay has termed “microlegislation“: loopholes that may be imperceptible to human readers on the page—until their impact is realized in the real world.

But AI can be constrained and directed to distribute power rather than concentrate it. For Emirati residents, the most intriguing possibility of the AI plan is the promise to introduce AI “interactive platforms” where the public can provide input to legislation. In experiments across locales as diverse as Kentucky, Massachusetts, France, Scotland, Taiwan, and many others, civil society within democracies are innovating and experimenting with ways to leverage AI to help listen to constituents and construct public policy in a way that best serves diverse stakeholders.

If the UAE is going to build an AI-native government, it should do so for the purpose of empowering people and not machines. AI has real potential to improve deliberation and pluralism in policymaking, and Emirati residents should hold their government accountable to delivering on this promise.

Posted on May 15, 2025 at 7:00 AM • View Comments

AI Will Write Complex Laws

Artificial intelligence (AI) is writing law today. This has required no changes in legislative procedure or the rules of legislative bodies—all it takes is one legislator, or legislative assistant, to use generative AI in the process of drafting a bill.

In fact, the use of AI by legislators is only likely to become more prevalent. There are currently projects in the US House, US Senate, and legislatures around the world to trial the use of AI in various ways: searching databases, drafting text, summarizing meetings, performing policy research and analysis, and more. A Brazilian municipality passed the first known AI-written law in 2023.

That’s not surprising; AI is being used more everywhere. What is coming into focus is how policymakers will use AI and, critically, how this use will change the balance of power between the legislative and executive branches of government. Soon, US legislators may turn to AI to help them keep pace with the increasing complexity of their lawmaking—and this will suppress the power and discretion of the executive branch to make policy.

Demand for Increasingly Complex Legislation

Legislators are writing increasingly long, intricate, and complicated laws that human legislative drafters have trouble producing. Already in the US, the multibillion-dollar lobbying industry is subsidizing lawmakers in writing baroque laws: suggesting paragraphs to add to bills, specifying benefits for some, carving out exceptions for others. Indeed, the lobbying industry is growing in complexity and influence worldwide.

Several years ago, researchers studied bills introduced into state legislatures throughout the US, looking at which bills were wholly original texts and which borrowed text from other states or from lobbyist-written model legislation. Their conclusion was not very surprising. Those who borrowed the most text were in legislatures that were less resourced. This makes sense: If you’re a part-time legislator, perhaps unpaid and without a lot of staff, you need to rely on more external support to draft legislation. When the scope of policymaking outstrips the resources of legislators, they look for help. Today, that often means lobbyists, who provide expertise, research services, and drafting labor to legislators at the local, state, and federal levels at no charge. Of course, they are not unbiased: They seek to exert influence on behalf of their clients.

Another study, at the US federal level, measured the complexity of policies proposed in legislation and tried to determine the factors that led to such growing complexity. While there are numerous ways to measure legal complexity, these authors focused on the specificity of institutional design: How exacting is Congress in laying out the relational network of branches, agencies, and officials that will share power to implement the policy?

In looking at bills enacted between 1993 and 2014, the researchers found two things. First, they concluded that ideological polarization drives complexity. The suggestion is that if a legislator is on the extreme end of the ideological spectrum, they’re more likely to introduce a complex law that constrains the discretion of, as the authors put it, “entrenched bureaucratic interests.” And second, they found that divided government drives complexity to a large degree: Significant legislation passed under divided government was found to be 65 percent more complex than similar legislation passed under unified government. Their conclusion is that, if a legislator’s party controls Congress, and the opposing party controls the White House, the legislator will want to give the executive as little wiggle room as possible. When legislators’ preferences disagree with the executive’s, the legislature is incentivized to write laws that specify all the details. This gives the agency designated to implement the law as little discretion as possible.

Because polarization and divided government are increasingly entrenched in the US, the demand for complex legislation at the federal level is likely to grow. Today, we have both the greatest ideological polarization in Congress in living memory and an increasingly divided government at the federal level. Between 1900 and 1970 (57th through 90th Congresses), we had 27 instances of unified government and only seven divided; nearly a four-to-one ratio. Since then, the trend is roughly the opposite. As of the start of the next Congress, we will have had 20 divided governments and only eight unified (nearly a three-to-one ratio). And while the incoming Trump administration will see a unified government, the extremely closely divided House may often make this Congress look and feel like a divided one (see the recent government shutdown crisis as an exemplar) and makes truly divided government a strong possibility in 2027.

Another related factor driving the complexity of legislation is the need to do it all at once. The lobbyist feeding frenzy—spurring major bills like the Affordable Care Act to be thousands of pages in length—is driven in part by gridlock in Congress. Congressional productivity has dropped so low that bills on any given policy issue seem like a once-in-a-generation opportunity for legislators—and lobbyists—to set policy.

These dynamics also impact the states. States often have divided governments, albeit less often than they used to, and their demand for drafting assistance is arguably higher due to their significantly smaller staffs. And since the productivity of Congress has cratered in recent years, significantly more policymaking is happening at the state level.

But there’s another reason, particular to the US federal government, that will likely force congressional legislation to be more complex even during unified government. In June 2024, the US Supreme Court overturned the Chevron doctrine, which gave executive agencies broad power to specify and implement legislation. Suddenly, there is a mandate from the Supreme Court for more specific legislation. Issues that have historically been left implicitly to the executive branch are now required to be either explicitly delegated to agencies or specified directly in statute. Either way, the Court’s ruling implied that law should become more complex and that Congress should increase its policymaking capacity.

This affects the balance of power between the executive and legislative branches of government. When the legislature delegates less to the executive branch, it increases its own power. Every decision made explicitly in statute is a decision the executive makes not on its own but, rather, according to the directive of the legislature. In the US system of separation of powers, administrative law is a tool for balancing power among the legislative, executive, and judicial branches. The legislature gets to decide when to delegate and when not to, and it can respond to judicial review to adjust its delegation of control as needed. The elimination of Chevron will induce the legislature to exert its control over delegation more robustly.

At the same time, there are powerful political incentives for Congress to be vague and to rely on someone else, like agency bureaucrats, to make hard decisions. That empowers third parties—the corporations, or lobbyists—that have been gifted by the overturning of Chevron a new tool in arguing against administrative regulations not specifically backed up by law. A continuing stream of Supreme Court decisions handing victories to unpopular industries could be another driver of complex law, adding political pressure to pass legislative fixes.

AI Can Supply Complex Legislation

Congress may or may not be up to the challenge of putting more policy details into law, but the external forces outlined above—lobbyists, the judiciary, and an increasingly divided and polarized government—are pushing them to do so. When Congress does take on the task of writing complex legislation, it’s quite likely it will turn to AI for help.

Two particular AI capabilities enable Congress to write laws different from laws humans tend to write. One, AI models have an enormous scope of expertise, whereas people have only a handful of specializations. Large language models (LLMs) like the one powering ChatGPT can generate legislative text on funding specialty crop harvesting mechanization equally as well as material on energy efficiency standards for street lighting. This enables a legislator to address more topics simultaneously. Two, AI models have the sophistication to work with a higher degree of complexity than people can. Modern LLM systems can instantaneously perform several simultaneous multistep reasoning tasks using information from thousands of pages of documents. This enables a legislator to fill in more baroque detail on any given topic.

That’s not to say that handing over legislative drafting to machines is easily done. Modernizing any institutional process is extremely hard, even when the technology is readily available and performant. And modern AI still has a ways to go to achieve mastery of complex legal and policy issues. But the basic tools are there.

AI can be used in each step of lawmaking, and this will bring various benefits to policymakers. It could let them work on more policies—more bills—at the same time, add more detail and specificity to each bill, or interpret and incorporate more feedback from constituents and outside groups. The addition of a single AI tool to a legislative office may have an impact similar to adding several people to their staff, but with far lower cost.

Speed sometimes matters when writing law. When there is a change of governing party, there is often a rush to change as much policy as possible to match the platform of the new regime. AI could help legislators do that kind of wholesale revision. The result could be policy that is more responsive to voters—or more political instability. Already in 2024, the US House’s Office of the Clerk has begun using AI to speed up the process of producing cost estimates for bills and understanding how new legislation relates to existing code. Ohio has used an AI tool to do wholesale revision of state administrative law since 2020.

AI can also make laws clearer and more consistent. With their superhuman attention spans, AI tools are good at enforcing syntactic and grammatical rules. They will be effective at drafting text in precise and proper legislative language, or offering detailed feedback to human drafters. Borrowing ideas from software development, where coders use tools to identify common instances of bad programming practices, an AI reviewer can highlight bad law-writing practices. For example, it can detect when significant phrasing is inconsistent across a long bill. If a bill about insurance repeatedly lists a variety of disaster categories, but leaves one out one time, AI can catch that.

Perhaps this seems like minutiae, but a small ambiguity or mistake in law can have massive consequences. In 2015, the Affordable Care Act came close to being struck down because of a typo in four words, imperiling health care services extended to more than 7 million Americans.

There’s more that AI can do in the legislative process. AI can summarize bills and answer questions about their provisions. It can highlight aspects of a bill that align with, or are contrary to, different political points of view. We can even imagine a future in which AI can be used to simulate a new law and determine whether or not it would be effective, or what the side effects would be. This means that beyond writing them, AI could help lawmakers understand laws. Congress is notorious for producing bills hundreds of pages long, and many other countries sometimes have similarly massive omnibus bills that address many issues at once. It’s impossible for any one person to understand how each of these bills’ provisions would work. Many legislatures employ human analysis in budget or fiscal offices that analyze these bills and offer reports. AI could do this kind of work at greater speed and scale, so legislators could easily query an AI tool about how a particular bill would affect their district or areas of concern.

This is a use case that the House subcommittee on modernization has urged the Library of Congress to take action on. Numerous software vendors are already marketing AI legislative analysis tools. These tools can potentially find loopholes or, like the human lobbyists of today, craft them to benefit particular private interests.

These capabilities will be attractive to legislators who are looking to expand their power and capabilities but don’t necessarily have more funding to hire human staff. We should understand the idea of AI-augmented lawmaking contextualized within the longer history of legislative technologies. To serve society at modern scales, we’ve had to come a long way from the Athenian ideals of direct democracy and sortition. Democracy no longer involves just one person and one vote to decide a policy. It involves hundreds of thousands of constituents electing one representative, who is augmented by a staff as well as subsidized by lobbyists, and who implements policy through a vast administrative state coordinated by digital technologies. Using AI to help those representatives specify and refine their policy ideas is part of a long history of transformation.

Whether all this AI augmentation is good for all of us subject to the laws they make is less clear. There are real risks to AI-written law, but those risks are not dramatically different from what we endure today. AI-written law trying to optimize for certain policy outcomes may get it wrong (just as many human-written laws are misguided). AI-written law may be manipulated to benefit one constituency over others, by the tech companies that develop the AI, or by the legislators who apply it, just as human lobbyists steer policy to benefit their clients.

Regardless of what anyone thinks of any of this, regardless of whether it will be a net positive or a net negative, AI-made legislation is coming—the growing complexity of policy demands it. It doesn’t require any changes in legislative procedures or agreement from any rules committee. All it takes is for one legislative assistant, or lobbyist, to fire up a chatbot and ask it to create a draft. When legislators voted on that Brazilian bill in 2023, they didn’t know it was AI-written; the use of ChatGPT was undisclosed. And even if they had known, it’s not clear it would have made a difference. In the future, as in the past, we won’t always know which laws will have good impacts and which will have bad effects, regardless of the words on the page, or who (or what) wrote them.

This essay was written with Nathan E. Sanders, and originally appeared in Lawfare.

Posted on January 22, 2025 at 7:04 AM • View Comments

AI and the 2024 US Elections

For years now, AI has undermined the public’s ability to trust what it sees, hears, and reads. The Republican National Committee released a provocative ad offering an “AI-generated look into the country’s possible future if Joe Biden is re-elected,” showing apocalyptic, machine-made images of ruined cityscapes and chaos at the border. Fake robocalls purporting to be from Biden urged New Hampshire residents not to vote in the 2024 primary election. This summer, the Department of Justice cracked down on a Russian bot farm that was using AI to impersonate Americans on social media, and OpenAI disrupted an Iranian group using ChatGPT to generate fake social-media comments.

It’s not altogether clear what damage AI itself may cause, though the reasons for concern are obvious—the technology makes it easier for bad actors to construct highly persuasive and misleading content. With that risk in mind, there has been some movement toward constraining the use of AI, yet progress has been painstakingly slow in the area where it may count most: the 2024 election.

Two years ago, the Biden administration issued a blueprint for an AI Bill of Rights aiming to address “unsafe or ineffective systems,” “algorithmic discrimination,” and “abusive data practices,” among other things. Then, last year, Biden built on that document when he issued his executive order on AI. Also in 2023, Senate Majority Leader Chuck Schumer held an AI summit in Washington that included the centibillionaires Bill Gates, Mark Zuckerberg, and Elon Musk. Several weeks later, the United Kingdom hosted an international AI Safety Summit that led to the serious-sounding “Bletchley Declaration,” which urged international cooperation on AI regulation. The risks of AI fakery in elections have not sneaked up on anybody.

Yet none of this has resulted in changes that would resolve the use of AI in U.S. political campaigns. Even worse, the two federal agencies with a chance to do something about it have punted the ball, very likely until after the election.

On July 25, the Federal Communications Commission issued a proposal that would require political advertisements on TV and radio to disclose if they used AI. (The FCC has no jurisdiction over streaming, social media, or web ads.) That seems like a step forward, but there are two big problems. First, the proposed rules, even if enacted, are unlikely to take effect before early voting starts in this year’s election. Second, the proposal immediately devolved into a partisan slugfest. A Republican FCC commissioner alleged that the Democratic National Committee was orchestrating the rule change because Democrats are falling behind the GOP in using AI in elections. Plus, he argued, this was the Federal Election Commission’s job to do.

Yet last month, the FEC announced that it won’t even try making new rules against using AI to impersonate candidates in campaign ads through deepfaked audio or video. The FEC also said that it lacks the statutory authority to make rules about misrepresentations using deepfaked audio or video. And it lamented that it lacks the technical expertise to do so, anyway. Then, last week, the FEC compromised, announcing that it intends to enforce its existing rules against fraudulent misrepresentation regardless of what technology it is conducted with. Advocates for stronger rules on AI in campaign ads, such as Public Citizen, did not find this nearly sufficient, characterizing it as a “wait-and-see approach” to handling “electoral chaos.”

Perhaps this is to be expected: The freedom of speech guaranteed by the First Amendment generally permits lying in political ads. But the American public has signaled that it would like some rules governing AI’s use in campaigns. In 2023, more than half of Americans polled responded that the federal government should outlaw all uses of AI-generated content in political ads. Going further, in 2024, about half of surveyed Americans said they thought that political candidates who intentionally manipulated audio, images, or video should be prevented from holding office or removed if they had won an election. Only 4 percent thought there should be no penalty at all.

The underlying problem is that Congress has not clearly given any agency the responsibility to keep political advertisements grounded in reality, whether in response to AI or old-fashioned forms of disinformation. The Federal Trade Commission has jurisdiction over truth in advertising, but political ads are largely exempt—again, part of our First Amendment tradition. The FEC’s remit is campaign finance, but the Supreme Court has progressively stripped its authorities. Even where it could act, the commission is often stymied by political deadlock. The FCC has more evident responsibility for regulating political advertising, but only in certain media: broadcast, robocalls, text messages. Worse yet, the FCC’s rules are not exactly robust. It has actually loosened rules on political spam over time, leading to the barrage of messages many receive today. (That said, in February, the FCC did unanimously rule that robocalls using AI voice-cloning technology, like the Biden ad in New Hampshire, are already illegal under a 30-year-old law.)

It’s a fragmented system, with many important activities falling victim to gaps in statutory authority and a turf war between federal agencies. And as political campaigning has gone digital, it has entered an online space with even fewer disclosure requirements or other regulations. No one seems to agree where, or whether, AI is under any of these agencies’ jurisdictions. In the absence of broad regulation, some states have made their own decisions. In 2019, California was the first state in the nation to prohibit the use of deceptively manipulated media in elections, and has strengthened these protections with a raft of newly passed laws this fall. Nineteen states have now passed laws regulating the use of deepfakes in elections.

One problem that regulators have to contend with is the wide applicability of AI: The technology can simply be used for many different things, each one demanding its own intervention. People might accept a candidate digitally airbrushing their photo to look better, but not doing the same thing to make their opponent look worse. We’re used to getting personalized campaign messages and letters signed by the candidate; is it okay to get a robocall with a voice clone of the same politician speaking our name? And what should we make of the AI-generated campaign memes now shared by figures such as Musk and Donald Trump?

Despite the gridlock in Congress, these are issues with bipartisan interest. This makes it conceivable that something might be done, but probably not until after the 2024 election and only if legislators overcome major roadblocks. One bill under consideration, the AI Transparency in Elections Act, would instruct the FEC to require disclosure when political advertising uses media generated substantially by AI. Critics say, implausibly, that the disclosure is onerous and would increase the cost of political advertising. The Honest Ads Act would modernize campaign-finance law, extending FEC authority to definitively encompass digital advertising. However, it has languished for years because of reported opposition from the tech industry. The Protect Elections From Deceptive AI Act would ban materially deceptive AI-generated content from federal elections, as in California and other states. These are promising proposals, but libertarian and civil-liberties groups are already signaling challenges to all of these on First Amendment grounds. And, vexingly, at least one FEC commissioner has directly cited congressional consideration of some of these bills as a reason for his agency not to act on AI in the meantime.

One group that benefits from all this confusion: tech platforms. When few or no evident rules govern political expenditures online and uses of new technologies like AI, tech companies have maximum latitude to sell ads, services, and personal data to campaigns. This is reflected in their lobbying efforts, as well as the voluntary policy restraints they occasionally trumpet to convince the public they don’t need greater regulation.

Big Tech has demonstrated that it will uphold these voluntary pledges only if they benefit the industry. Facebook once, briefly, banned political advertising on its platform. No longer; now it even allows ads that baselessly deny the outcome of the 2020 presidential election. OpenAI’s policies have long prohibited political campaigns from using ChatGPT, but those restrictions are trivial to evade. Several companies have volunteered to add watermarks to AI-generated content, but they are easily circumvented. Watermarks might even make disinformation worse by giving the false impression that non-watermarked images are legitimate.

This important public policy should not be left to corporations, yet Congress seems resigned not to act before the election. Schumer hinted to NBC News in August that Congress may try to attach deepfake regulations to must-pass funding or defense bills this month to ensure that they become law before the election. More recently, he has pointed to the need for action “beyond the 2024 election.”

The three bills listed above are worthwhile, but they are just a start. The FEC and FCC should not be left to snipe with each other about what territory belongs to which agency. And the FEC needs more significant, structural reform to reduce partisan gridlock and enable it to get more done. We also need transparency into and governance of the algorithmic amplification of misinformation on social-media platforms. That requires that the pervasive influence of tech companies and their billionaire investors should be limited through stronger lobbying and campaign-finance protections.

Our regulation of electioneering never caught up to AOL, let alone social media and AI. And deceiving videos harm our democratic process, whether they are created by AI or actors on a soundstage. But the urgent concern over AI should be harnessed to advance legislative reform. Congress needs to do more than stick a few fingers in the dike to control the coming tide of election disinformation. It needs to act more boldly to reshape the landscape of regulation for political campaigning.

This essay was written with Nathan E. Sanders, and originally appeared in the Atlantic.

Posted on September 30, 2024 at 7:00 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.