We need to avoid a ‘ready, fire, aim!’ approach to AI regulation

The panic to regulate artificial intelligence (AI) came almost immediately after last fall’s release of ChatGPT popularized the technology with the public.

Some industry insiders themselves called for a pause on development, highlighting that expertise in a field doesn’t translate into proficiency in the perils of regulation. That appeal was followed by a White House AI Bill of Rights and an educational effort by Senate Majority Leader Chuck Schumer, D-N.Y. 

Fears about AI include job displacement, data security and privacy, misinformation, autonomous defense systems mistakes, discrimination and bias, and an existential threat to humanity itself.

It’s imperative to prove actual market failure before regulating and to make sure the costs of doing so don’t outweigh the benefits. (iStock)

We’ve lived with all of these threats in different contexts, but is there something new that justifies regulating AI? And, if so, what are the costs to doing so? 

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It’s imperative to prove actual market failure before regulating and to make sure the costs of doing so don’t outweigh the benefits.

Doomsday predictions are no substitute for proof of actual problems. Job displacement will certainly accompany AI integration across many industries, but so will new jobs and an elimination of current jobs’ most tedious aspects. 

Securing data and user privacy are challenges already being grappled with in the marketplace and in legislatures. Misinformation concerns likely will take center stage at the Supreme Court next term concerning the last technological wave, the rise of social media platforms. 

Autonomous defense applications of AI can likely be addressed privately with human oversight and safeguards. And we’re not yet at a point where we need to be immediately concerned about existential threats; assumedly, we’ll have learned more about safeguards by the time we are.

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The Federal Register currently lists 435 regulatory agencies. It’s hard to fathom that, among them, they lack authority to tackle any problem that might arise. Furthermore, the idea that one more for AI might have sufficient expertise to manage a technology that will be applied in so many different ways, across so many different industries. The latest edition of my colleague Wayne Crew’s Ten Thousand Commandments lists the cost of current federal regulations at $1.927 trillion, or 8% of GDP.  

So do we really need to risk the myriad benefits of AI by over-regulating at the outset?

Generally, the healthier and the wealthier a society, the better able it is to adapt to challenges and solve problems. Widespread use of AI puts us on a course to be an even more prosperous society. AI problems will certainly come, just as they have with all new technologies. But part of our nation’s recipe for success is to allow innovation, then deal with the bumps as they come.  

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Politicians and regulators are not psychic. They are not blessed with the detailed foresight of predicting the nature of every problem before it occurs. That knowledge only exists in the workings of trial and error in the marketplace. What will be a boon, a bust or reveal bona fide market failure in need of regulation can only be revealed by letting AI evolve. 

Over and early regulation risks robbing us of the benefits or AI. How many advances in efficiency, improvements in quality of life, or lives saved by medical advances are we willing to sacrifice for efforts to avoid theoretical problems that may never materialize?

That’s the sort of cost-benefit analysis that should be done before regulating. 

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It also might tip the scales against us in our global race for leadership on AI. Whatever brakes are applied here in the U.S. will not be observed by adversarial countries. Our light-touch regulatory approach has served us well in comparison to the European Union (that cannot boast one among the top 10 global tech companies, while the U.S. can claim eight) and China and Russia (where we’ve set the standard in telecommunication for the previous generations). 

Before any regulatory constraints are put on AI, we must identify actual problems, grapple with the trade-offs regulation inevitably brings, and honestly consider the probability of those laws solving the problem at hand. To do less is a disservice to Americans and to progress.