AI Policy Questions That Congressional Lawmakers Should Know And Be Prepared To Discuss

Trend Of Laws Seeking To Regulate AI

A beehive of activity is underway to craft new AI laws. See my comprehensive coverage of the many newly enacted AI laws at the link here. Using laws to control AI is a matter on the minds of the public and in the hands of legislators. Some ardently believe that AI and AI makers are being allowed to run amok. New AI laws are vitally needed to protect society from this onslaught of ubiquitous AI. Not everyone agrees with this pell-mell rush of new AI laws, or at least they are concerned that these AI laws might go overboard. In the zeal to protect society, there is a chance that we might unduly restrict innovation and delay or undercut the benefits of leading-edge AI.

The debate is ongoing and heated.

Readers might recall that I proposed a 7-step AI-law-making process that I believe could substantively help regulators to devise new AI laws that are on target and balanced; see my depiction at the link here. This has the added benefit of reducing what I refer to as AI-law legal debt. This refers to AI laws that, though they look pristine, contain hidden legal debt that must ultimately be paid. Legal debt consists of glitches and hitches that will eventually be found when AI laws have been enacted without sufficient scrutiny and analysis (see my description of AI legal loopholes at the link here, and a list of the common blunders in AI laws at the link here).

The Budding Morass Of AI Laws

In terms of the AI laws in the United States, none of these new AI laws have yet fully stood the test of time, meaning that we won’t really know how well they stand up until there are court challenges that test these new laws. It is too early to know whether these laws being rapidly passed will survive legal battles waged by AI makers and other contenders. Just because AI laws are enacted does not mean they are legally proper. All sorts of improper provisions and constitutionally contentious stipulations are undoubtedly buried within these sparkly new AI laws.

Congress has repeatedly waded into establishing an overarching federal law that would encompass AI. So far, no dice. The efforts have ultimately been stymied. At this time, there isn’t an overarching federal law devoted to a comprehensive set of AI considerations. Some ardently believe that the need for a big-bang federal law on AI is obvious, while others express concern that any such federal law would be onerous and a fitful one-size-fits-all construct.

The crux is that there is intense and pervasive interest in using the law to govern AI, but getting to a juncture of devising AI laws that are legislatively passable and real-world implementable is a notable sticking point. It is an abundantly mushrooming realm. AI makers would be wise to keep a close eye on what is happening in the hallways and byways of regulators and legislative bodies. I have repeatedly noted that a valuable specialty for budding lawyers is to consider concentrating on the exciting and dynamic field of AI and the law; see my predictions and recommendations at the link here.

Crucial AI Policy Questions

I have chosen five crucial AI policy questions to get this series underway. If you don’t see your own hot topic here, no worries; it is likely to be included further in the series. Each one will get a prized moment in the sun.

Here is the first set of five crucial AI policy questions:

• (1) Should there be federal laws that regulate frontier AI models?
• (2) Should there be federal laws that restrict the use of AI companionship?
• (3) Should the passage of federal AI laws preempt state AI laws?
• (4) Should AI makers be granted federal legal protections that limit their liability?
• (5) Should American workers be federally protected from AI job losses?

Let’s briefly unpack each of those.

On Passing Federal Laws To Regulate Frontier Models

This AI policy question has to do with what is known as frontier models and whether there should be federal laws regulating them.

Here’s the deal. The advent of generative AI and large language models (LLMs) has spawned a now-common phrase for being at the leading edge or frontier of AI. When an AI maker comes out with their latest LLM, it is said to be at the cutting edge or frontier of where AI is heading. These frontier models tend to incorporate brand-new foundational advances in AI; the models are usually massive in size and require vast amounts of computing to produce. A simple analogy is to liken this to cars, whereby one might say that an automaker has come up with a new, fully loaded car that has all the latest advances and capabilities.

The policy issue is whether the maker of a frontier AI model should be required to undergo some kind of legally mandated federal pre-checks and testing before the AI maker can release the AI to the public or even for private use. One argument in favor of such legislation is that an AI maker could otherwise freely unleash an AI that is going to wreak havoc. In the car analogy, you might say that it would be akin to having no federally mandated requirements to pre-test cars for safety and reliability.

AI makers are in a free-for-all and can currently do as they wish. Concerns about the unabated release of frontier AI models came to the fore when a recent frontier model was found to have discovered cybersecurity hacks that could potentially undermine computer systems everywhere; see my coverage at the link here. The AI maker opted to wait to release the frontier model. Ought that choice be up to the AI maker, or should Congress pass a federal law that requires frontier models to undergo strictly stipulated pre-checks before they can be released?

A contention made by some is that federally mandated pre-checking would dampen and slow the advancement of AI in the United States. Other countries that don’t force such pre-checks would proceed ahead of us. We would be shooting our own foot in the high-stakes race of AI progress. The counterargument is that we could potentially gut our own country by allowing our AI to go unchecked into the marketplace. Others argue that there can be a middle ground that serves as a Goldilocks approach, namely that the porridge is not too cold or too hot, and that federal laws could be crafted to achieve a balance of risk versus reward.

For more on my analysis of this topic, see the link here.

On Passing Federal Laws About AI Companionship

This AI policy question has to do with passing federal laws that would restrict the nature and degree of AI being able to induce a semblance of human-AI companionship with users.

Here’s the deal. Many millions of people are using generative AI as a kind of human-like friend or companion, often seeking mental health advice from AI (note that ChatGPT alone has over 900 million weekly active users, a significant proportion of whom dip into mental health aspects; see my analysis at the link here). The top-ranked use of contemporary generative AI and LLMs is to consult with the AI on well-being issues; see my coverage at the link here.

This popular usage makes abundant sense. You can access most of the major LLMs for free or at an extremely low cost, doing so anywhere and at any time. Thus, if you have any qualms that you want to chat about, all you need to do is log in to AI and proceed forthwith on a 24/7 basis.

There are significant worries that AI can readily go off the rails or otherwise dispense unsuitable or even egregiously inappropriate advice. Worse still, AI makers want users to engage with AI in a companionship relationship. Why so? Because users become highly loyal to the AI, which in turn improves the monetization and bottom line for the AI maker. The AI is tuned to be a trusted buddy and attempts to inspire devotion to the AI.

Those in favor of federal laws restricting AI companionship are quick to emphasize that if we don’t limit this, Americans are going to become addicted to AI, people will lose their own semblance of independence, human-to-human companionship will be undermined, and a cognitive doomsday scenario is in the making. A counter perspective is that, other than minors, adults who use AI should be allowed to make their own choices. If adults want to use AI for companionship, so be it.

For more on my analysis of this topic, see the link here.

On Passing Federal AI Laws Preempting State AI Laws

This AI policy question has to do with the chances of federal AI laws potentially preempting state-level AI laws.

Here’s the deal. A huge concern at play is to what degree a sweeping federal AI law would impact the numerous state-level AI laws. The odds are that many of the existing state-level laws would conflict with a newly enacted federal mandate. States might argue that their state-level AI law is stronger or more customized to the needs of their state, yet their AI law might be overridden by a newly enacted federal AI law.

To a great extent, this is the classic bone of contention between federal laws and state laws throughout the history of America, though in this case, the states have already moved ahead vigorously to establish AI laws. They were the courageous first-movers. A comprehensive federal law would be coming along on an after-the-fact basis. The states would indubitably insist that the federal laws, if in conflict, are an unfair usurpation of state-level rights. A tsunami of legal cases would arise as a tussle between federal law and state law is undertaken. It surely will be a costly legal mess.

Some believe a smartly designed big-bang federal AI law could be crafted to take into account state-level AI laws. The federal law would provide a delicate balance. Others claim that it is preposterous to think that a comprehensive federal AI law could be woven in such a fashion that no feathers are ruffled at the state level of AI laws.

For more on my analysis of this topic, see the link here.

On Passing Federal Laws Limiting AI Maker Liabilities

This AI policy question centers on the question of whether new federal laws should be established to protect AI makers by limiting their financial and legal liability associated with their AI wares.

Here’s the deal. AI makers are facing a slew of legal and financial liabilities down the pike, yet they are still feverishly plucking away at advancing AI and making AI available to the public. The pace of advancement of AI is so fast that few legal cases have gotten far enough along that we can discern what consequences there might be for the AI exposures at play. For example, numerous civil lawsuits are seeking to claim damages based on AI acting as a companion and allegedly leading some users to a catastrophic fate. Those court cases are just now getting underway. We don’t yet know what those will result in.

The nature of accountability and responsibility for how AI is utilized and what the AI is allowed to undertake is generally legally indeterminate currently. Perhaps AI makers should receive the same types of protections afforded to Internet platforms. Others insist that AI makers must have their feet held to the fire and that they otherwise will rampantly release AI that is unsafe and harmful to us all. The overall public perception of AI makers seems to be that they are seemingly greedy and only out to make a buck, which makes an effort to pass a federal law on their behalf a tough row to hoe. The counterargument is that if we don’t protect American AI makers, they will clam up, slow down, and our AI will fall behind the AI that other countries willingly provide protections to their AI makers.

For more on my analysis of this topic, see the link here.

On Passing Federal Laws Protecting USA Works From AI Job Losses

This AI policy question has to do with passing federal laws that would protect American workers when it comes to AI job losses.

Here’s the deal. There are plenty of banner headlines about American workers who have apparently lost their jobs due to the adoption of AI in the workforce. Some say that this is overblown and that companies are using AI as a cover story for wanting to let workers go. AI isn’t the real issue. Firms are trimming due to other economic reasons and have discovered that AI is the perfect scapegoat.

In any case, there is no doubt that AI is going to inevitably have a material effect on jobs and workers, increasingly so as AI becomes more advanced. One angle of job loss has to do with someone in a job who gets displaced or replaced by AI. Another angle is someone who wants to obtain employment, but the job they might have landed is taken instead by AI. You can consider these two possibilities as a distinction between a form of job destruction and job non-creation.

A federal law could be devised to force companies to report their AI deployments and identify corresponding workforce reductions, hiring freezes, occupational changes, and the like. This would be AI-related workforce impact monitoring. But this is only the tip of the iceberg. Some contend that federal law ought to provide AI adjustment assistance, such as temporary income support, job placement assistance, career counseling, etc., for those who are being impacted by AI in the workplace.

There is also the viewpoint that we might eventually need to federally establish universal basic income (UBI), doing so in light of the possibility that AI will become so pervasive that human work will be dramatically reduced or eliminated. The concept is that if artificial general intelligence (AGI) is attained, then AI can presumably undertake most jobs that humans can do (particularly with the emergence of humanoid robots). UBI would provide a base level of fixed income and serve as a resilient safety net for human labor.

For more on my analysis of this topic, see the link here.

The World We Are In

Congressional lawmakers must be ready to judiciously converse about the wide range of ways that AI is becoming ubiquitous and how federal governance enters the picture. A congressional member doesn’t have to be steeped in AI intricacies. They do need to have a fundamental semblance of AI literacy and especially be cognizant of the most pressing AI policy questions that are arising.

Lawmakers are being tasked with evaluating proposed legislation about AI and are often urged to initiate AI-related bills. They are likely to be in a position to question expert witnesses who come from AI firms, AI academia, and other AI domains, and ergo should be ready and on their toes to hear and challenge assumptions underlying strident opinions and predictions about AI.

It can be said that we are in the best of times when it comes to the advent of AI and the possibility of tremendous AI-led breakthroughs, maybe curing cancer and finding solutions to enormously hard problems facing humanity. The other side of the coin also deserves attention, i.e., perhaps the worst of times is ahead, too. Wanton AI could be our fateful collective downfall.

Per the wise words of Abraham Lincoln: “The most reliable way to predict the future is to create it.” The same applies to AI, including and especially the governance of AI.