There has been a recent resurgence in fears about AI. A range of voices, from Sen. Bernie Sanders and Steve Bannon to former engineers and leaders of various AI labs, have been calling for a pause in AI development. Many of these calls are accompanied by science fiction-esque doomsday scenarios about the worst that could happen. Yet a rush to regulate out of fear could have longer-term negative consequences than the risk it claims to address.

The last week has focused a lot on the potential risks of AI, distracting from the ways this broad-purpose technology is already transforming our lives in ways we don’t think about or see. We no longer think of autocomplete or text-to-speech as AI, even though they are. We often don’t see the remarkable medical research that is being powered by AI until it directly impacts us or a loved one. AI is opening new doors for entrepreneurship and creating fresh opportunities in skilled trades. Any conversation about how to govern this technology should consider two truths: yes, the risks could be real and worth taking seriously, but so are the benefits already showing up in people’s lives and livelihoods.

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On September 3, Senator Bernie Sanders (I‑VT) and Representative Greg Casar (D‑TX) announced their Ban Artificial Superintelligence Act, which would pause the development of “advanced AI” until a new federal regulatory body is set up and, as its name indicates, ban what they define as “superintelligent” artificial intelligence (AI) systems. To those companies or individuals who attempt to develop or deploy these systems, the punishment could go from a “corporate death penalty” to up to 20 years in prison. 

Sanders’s idea is not exactly new, but that does not make it less wrong. There are reasonable guardrails to tackle the risks related to frontier AI development, but criminalizing AI development will do little to make us safer. 

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September 11 marks one of the darkest days in US history. Terrorists murdered thousands of people on American soil, put countless people in fear for their safety, and left a scar in American history that can still be felt to this day. Yet what is less known is the financial surveillance that was expanded in the wake of the attack.

The Bank Secrecy Act already required banks and other financial institutions to report their customers to the government, but Congress decided that it wanted more. In the near blink of an eye, the USA PATRIOT Act was signed into law. At the time, the Cato Institute’s Robert A. Levy wrote that the law “zipped through in six weeks—gutting much of the Fourth Amendment in far less time than Congress typically expends on routine bills that raise no constitutional concerns.”

The damage to civil liberties caused by the PATRIOT Act is far-reaching. For just financial surveillance, the law mandated stricter customer identification (better known as know your customer, or KYC, requirements), expanded the list of financial institutions that must surveil customers, scrutinized foreign relations, created channels for more government officials to access this surveillance system, and made much of the system confidential from the broader public.

Many innovators find the growing uncertainty, frequent changes, and secret frameworks in the AI regulatory space as barriers to investment in the research, development, and deployment of new technology. At the same time, there’s broad recognition that laws such as the EU AI Act risk being out of date by their effective date, representing a different constraint on the AI ecosystem. The frustrating reality is that there’s no “right” way to govern AI. Existing laws, including consumer protection statutes, already address many of the most common harms associated with AI. Yet frontier issues and edge cases will require new paradigms and regulatory certainty to allow innovators to fully pursue possibilities while resolving the public’s and policymakers’ concerns about legitimate risks, such as cybersecurity threats.

New governance efforts should be tailored to address cases where clear market failures underpinning broader AI adoption and ongoing AI research occur or where the lack of regulatory certainty prevents important development of the technology. Three examples of such failures include: Inadequate information about model capabilities and values is hindering the ability of consumers to make knowledgeable decisions; insufficient supply of independent AI auditors threatens to prevent the timely and thorough investigation of company practices; and ineffective initiatives to increase the talent pipeline of AI experts may hinder the nation’s long-term tech ambitions.

Senate Finance Committee Ranking Member Ron Wyden (D‑OR) recently proposed a new federal tax on data centers. The proposal would tax gross data center revenue “at a low single-digit rate.” Because it taxes revenue rather than net profits, the proposal risks imposing effective tax rates exceeding 100 percent.

Such a tax could end new data center development and risk stripping the US of its status as the global leader in AI and other cloud-based technologies. 

The fundamental problem with taxing revenue rather than profits is that the tax ignores whether a firm can pay the tax. Revenue tells policymakers nothing about profitability. Grocery stores, for example, generate hundreds of billions of dollars in sales each year while typically earning profit margins of only 1 to 3 percent.

Everyone wants to know the “right” answer on AI in schools. Should it be banned? Required? Left up to teachers? Locked down with strict rules? The reality is that there isn’t one right answer. In this, as in much of life, economist Thomas Sowell’s brilliant insight rings true: “There are no solutions, only trade-offs.”

When it comes to AI in education, different families have different preferences. And the effects of decisions made today may not be known for years. Given the diverse views among parents and the ever-changing nature of AI, it’s crucial that we embrace freedom rather than mandates.

As we continue our special “AI in Education” series, it’s time to consider the funding side. On Tuesday, my colleague Jennifer Huddleston examined why AI in the classroom matters and the importance of parents and teachers deciding how kids use it. Yesterday, she and Christopher Gardner looked at how teachers can benefit from AI. 

School choice is an important element that relates to both topics. It’s easy enough to say parents should decide how much their children interact with AI in school. But how realistic is that in practice? In our current system, parents are generally mandated to send their children to assigned public schools. If they want something different, they must pay twice for education—once in taxes and again in tuition or homeschooling costs. Similarly, as public schools have a near monopoly on education in most areas, that’s where the vast majority of teachers work.