Originally published on Substack. 

The AI fight is hot. Politico reports that the White House is weighing stronger oversight of advanced AI models before release, even as federal officials are already testing some models through national-security reviews.

That tension matters.

Some in Washington still understand that America wins by building, competing, and innovating. Others are drifting toward the same old trap: fear first, bureaucracy second, progress last.

Too many yes-men follow the latest political mood instead of clear principles. Sometimes the White House gets it right, and its AI framework does on one key point: Congress should not create a new federal AI rulemaking body.

That is the right instinct.

AI is too broad, too fast, and too important to put behind a federal permission slip.

AI Is Already Helping People

The strongest case for AI is not theoretical. It is human.

AI is already helping doctors, teachers, workers, students, farmers, banks, and researchers do more with less. NetChoice makes this clear in health care.

One AI-assisted mammography study found 20 percent more cancers detected without increasing false positives. Other tools are improving early Parkinson’s detection. An AI sepsis tool is helping clinicians identify a deadly condition faster.

That matters because delay is not neutral. If AI can help detect cancer sooner, identify sepsis faster, or spot disease earlier, then slowing deployment has a cost. That cost is measured in time, money, and lives.
​
The Pelican Institute adds more examples.

AI-enabled tools are helping researchers detect Parkinson’s and Alzheimer’s earlier and better understand genetic mutations. That is progress. Not hype. Not science fiction. Progress.

The Jobs Panic Is Too Simple

The usual political panic says AI will wipe out work. That is easy to say. It is not what the evidence shows so far.

A recent data review notes that LinkedIn job-posting evidence found 640,000 U.S. jobs created between 2023 and 2025 tied to AI growth. The same review points to survey evidence showing little overall employment effect in 2025, not mass displacement.

That should not surprise us.

Technology changes work. It does not just erase it. Better tools reduce low-value tasks. They increase productivity. They create new services, new firms, and new jobs.

Students are proving the same point. Eighty-seven percent of college students surveyed use AI, often to understand hard material. That is not just automation. That is human enhancement. A serious country should want more people learning faster, not fewer.

AI Helps Locally, Too

AI is not just for Silicon Valley.

The Pelican Institute shows practical uses close to home: banks using AI for fraud detection, local governments improving roads, health systems reducing clinical paperwork, students building apps, and AI reading tools improving literacy.

Texas and other states should see this as a preview. AI can help doctors in Houston, manufacturers in Fort Worth, energy firms in Midland, banks in Tyler, teachers in San Antonio, and small businesses everywhere. This is not about replacing people. It is about equipping them.
​
The AI Opportunity Project by Abundance Institute shows how wide the gains can be: tools that predict 130 diseases from one night of sleep, systems that reduce pesticide use through precision weed control, and applications that personalize athletic training.

Better information means better decisions. Better decisions mean less waste, lower costs, and more opportunity.
​
An FDA for AI Would Backfire

This is where policymakers need radical candor. A broad federal pre-approval regime for AI would be a disaster.

Adam Thierer and Neil Chilson warn against the “false promise of preemptive regulation”.

They are correct. Preemptive regulation focuses on visible risks while hiding invisible costs: startups never launched, tools never deployed, patients never helped, and productivity never gained.

Joe Lonsdale made a similar point in his CNBC interview. Any national review for AI should be “as limited and targeted as possible.”

He also warned that a sprawling AI bureaucracy would slow innovation, entrench big firms, and give China room to gain ground.
​
That is the danger.

Big companies can afford lawyers, lobbyists, compliance teams, and delays. Startups cannot. A complicated federal review system would not just “protect consumers.” It would protect incumbents.

That is how regulatory capture works.

Good Rules Are Narrow

None of this means no rules.

Fraud should be punished. Theft should be punished. Cyber abuse should be punished. Real national-security threats should be addressed. But that is very different from building a broad federal gatekeeping regime for a general-purpose technology.

The better path is clear: use existing law where possible, fill real gaps carefully, and keep guardrails narrow, fast, and tied to actual harms. Pelican’s AI Toolkit gets this balance right by focusing on practical solutions that address concerns while maximizing benefits.

Markets are discovery engines. Bureaucracies are not.

AI will improve fastest when millions of people can test it, use it, reject bad tools, and scale good ones. No federal office can predict every use in medicine, education, energy, finance, agriculture, and logistics.

Three Key Takeaways for Policymakers

• AI is already delivering real benefits. It is improving cancer detection, sepsis response, fraud prevention, literacy, infrastructure management, agriculture, and scientific discovery.
• A broad pre-approval regime would punish challengers. It would raise costs, protect incumbents, and slow useful tools before they reach the public.
• Good AI policy should be narrow and harm-based. Police fraud, theft, cyber abuse, and national-security risks, but do not smother innovation with a federal permission slip.

America should choose confidence over panic.

Tell lawmakers to reject a broad AI bureaucracy. Keep guardrails narrow. Defend the freedom to build. Let markets work so AI can help people prosper.

Originally published on Substack. 

A recent debate over AI and tax policy gets at a real political tension, but it points toward a questionable policy fix.

John Arnold argued that the way to limit a coming AI backlash is to shift taxes from labor to compute so average voters see more visible benefits from AI.

I understand the concern. If workers believe AI is enriching owners of capital while government keeps taxing work, wages, and human effort more visibly, the politics could turn ugly fast.

But the policy answer still points in the wrong direction.

We should not respond to AI by taxing capital, compute, data centers, or other forms of productive investment more heavily. And we definitely should not pretend that taxing servers, chips, algorithms, or machine-intensive infrastructure solves the deeper problem. It does not. It just shifts the burden, slows innovation, and weakens the direct connection between citizens and the cost of government.

That connection matters in a constitutional republic.

Capital Cannot Pay Taxes

This is the first principle too many people skip.

Capital cannot pay taxes. Compute cannot pay taxes. AI cannot pay taxes. Data centers cannot pay taxes.

People pay taxes.

Workers pay through lower wages. Consumers pay through higher prices. Savers and investors pay through lower returns. Communities pay through weaker investment and slower productivity growth.

The Tax Foundation explains that taxes on capital gains reduce saving and investment and lower long-run output. Cato has made the same point, especially through the lock-in effect, where capital stays trapped in older uses because selling triggers a tax penalty.

That is why taxing compute is just a new version of an old mistake. It treats productive capital as if it were a bottomless source of revenue rather than the engine of higher productivity and better living standards.

If AI is going to help the economy grow, then we should want more investment in the infrastructure, software, chips, and entrepreneurial experimentation that make that possible, not less.

Taxing Inflation Isn’t Justice

This is where the moral case gets even stronger.

The current tax code often taxes inflationary phantom gains as if they were real income. If someone buys an asset at one price and sells it years later at a higher nominal price, a large chunk of that “gain” may simply reflect the dollar losing value. Yet government still taxes it as if it were real wealth creation.
That is not just inefficient. It is unfair.

The Tax Foundation has shown that inflation indexing would stop the tax code from overstating gains and improve neutrality in the treatment of investment. Cato has argued that inflation can drive the effective capital gains tax rate toward absurd levels and that indexing is a meaningful reform even short of repeal.

Congress should do that now.

If lawmakers want to move in the right direction, the first big step is simple: index capital gains for inflation. That would at least stop government from taxing fake gains created by its own inflationary monetary and fiscal disorder.

But that should not be the end point.

The North Star Is Zero

My North Star is no taxes on capital.

That means getting the tax on capital gains to zero as quickly as possible. Indexing is the right near-term step. Zero is the right destination.

Economically, that means more capital formation, more reallocation toward productive uses, more entrepreneurship, and stronger wage growth over time.

The Tax Foundation notes that lower capital gains taxes reduce the tax bias against investment and improve long-run growth.

Cato likewise argues that lower rates reduce lock-in, encourage more productive deployment of capital, and lessen the damage from inflation.

Philosophically, taxing capital is wrong because it penalizes deferred consumption, prudence, and risk-taking. We should not punish people for saving, investing, and building.

Morally, government should not get to claim a share of inflationary asset appreciation while pretending it is taxing real income. That is legalized overreach.

The Real Disease Is Spending

Still, let’s not kid ourselves. The tax base is not the deepest problem.

Government spending is the disease.

Taxes, debt, inflation, and fiscal gimmicks are symptoms of that disease. The Congressional Budget Office projects debt held by the public at about 101 percent of GDP in 2026, rising to 120 percent by 2036, while annual deficits grow from roughly $1.9 trillion to $3.1 trillion. Gross debt is much higher.

Washington is not hunting for new tax bases because labor is mistreated and compute is undertaxed. Washington is hunting for new tax bases because government spends too much and always wants more.

That is why I keep arguing that tax reform without spending restraint is a mirage. If you do not reduce the size and scope of government, politicians will always go searching for a new “fair” thing to tax next.

Today it is capital.

Tomorrow it is compute.

Next week it is AI infrastructure.

After that it is unrealized gains, wealth, land, or something else.

The target changes. The appetite does not.

End Carveouts, Not Innovation

Now, that does not mean the current tax code is fine.

If data centers are getting special exemptions and carveouts, those should be on the chopping block. Special treatment narrows the tax base, fuels cronyism, and invites backlash. Recent Texas Tribune reporting found Texas data-center sales-tax exemptions are projected to reach about $1.6 billion by 2027, with annual totals nearing $1.8 billion by 2030.

So yes, end the carveouts.

But do not replace carveouts with a new punitive tax on compute.

That is not reform. That is just a new distortion.

Keep Taxes Visible

This is why I prefer broad taxation of final consumption of goods and services over hidden taxes on capital, production, and intermediate business inputs.

If government is going to tax, the burden should be visible enough that citizens can feel the cost and discipline the politicians imposing it. That is one reason I have argued in my own work on property tax reform and why Texas can eliminate property taxes that a broader, visible tax on final consumption is more honest and less destructive than taxes on ownership, production, or capital formation.

And no, I do not mean a value-added tax (VAT). A VAT is too easy to hide, too easy to expand, and too disconnected from ordinary taxpayers.

The Better AI Politics

If policymakers really want average voters to benefit from AI, here is the better play:

Stop punishing work.

Stop punishing investment.

Stop subsidizing favored firms.

Stop taxing capital harder.

Index capital gains for inflation now.

Drive the capital gains rate to zero fast.

And reduce government spending so politicians stop hunting for ever-newer tax bases.
That is how you let more people share in growth.

The answer to AI backlash is not more political management of innovation. It is a freer economy, a cleaner tax code, stronger growth, and a government humble enough to stop treating every new productivity gain as a new fiscal target.

Three Takeaways for Policymakers

1. Don’t tax capital, compute, or AI harder.

Those taxes do not stay on machines or servers. They land on people through lower investment, weaker productivity, and slower wage growth, as the Tax Foundation and Cato have both shown.

2. Index capital gains for inflation now and reduce the rate to zero.

Indexing is the right near-term reform because it stops taxing fake gains. Zero is the right long-term destination because capital formation should not be punished. That conclusion is supported directionally by the Tax Foundation’s inflation work, the Tax Foundation’s growth analysis, and Cato’s inflation arguments.

3. Spending is still the disease.

The reason politicians keep looking for new things to tax is that government spends too much. The CBO outlook makes that painfully clear.

The coming AI backlash is real. But the answer is not to tax compute.
​
The answer is to stop taxing growth, stop taxing inflationary fiction, end the carveouts, reduce spending, and let people prosper.

Affordability is under pressure across the U.S.—and the root causes are increasingly tied to policy choices.

In this episode of This Week’s Economy, we examine how persistent inflation, excessive federal spending, weak state tax reform, regulatory burdens, and supply constraints are driving higher costs and limiting opportunity for families and businesses.

The stakes are clear: when government expands and markets are distorted, the result is higher prices, reduced investment, and slower economic growth.

This episode provides a full economic health check—from CPI and jobs data to federal budgeting, property taxes, banking regulation, lawsuit costs, and emerging risks to future growth like data center restrictions.

The payoff is a roadmap for improving affordability: restore fiscal discipline, remove barriers to supply, and allow markets to allocate resources more efficiently.

🎧 Watch the full episode at the link above. 
📖 Read the full show notes: https://vanceginn.substack.com/p/ca1a37b7-7c59-4410-ba95-faa5c8dc2eb0

Subscribe, share, and explore more at vanceginn.com to stay informed and engaged.

​Artificial intelligence is transforming the economy—but the policy response may be doing more harm than good.

In Episode 194 of the Let People Prosper Show, I sit down with Logan Kolas of the American Consumer Institute to examine the surge in state-level AI regulation and what it means for innovation, competition, and consumer welfare.

As lawmakers across the country rush to regulate AI, many are creating a fragmented patchwork of rules that risk increasing costs, slowing technological progress, and limiting opportunity. This episode explores why these policies often miss the mark and what a more effective, pro-growth framework could look like.

If the United States wants to lead in AI while protecting consumers, it will need policies grounded in sound economics—not fear-driven regulation.

👉 Learn more: ⁠https://vanceginn.com⁠
​👉 Show notes: ⁠https://vanceginn.substack.com/p/51c930fb-1357-4a44-9436-fdf915f651ad⁠
Subscribe for more conversations on economics, policy, and how to let people prosper.

Originally published on Substack. 

Texas policymakers have a critical policy choice. The Texas House State Affairs Committee hearing on Thursday, April 9, at 10 am CT, is set to discuss data centers and their influence on the state.
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This hearing is not just about electricity or water demand. It is about whether Texas will remain competitive in the industries shaping the future, including AI, cloud computing, logistics, finance, and the digital infrastructure behind daily life.

The committee’s own charge recognizes the links between data centers, economic growth, workforce needs, national security, regulatory reform, and grid reliability. The best way to secure these issues for Texans is to allow markets to work rather than top-down, big-government policies, such as moratoria, heavy regulation, taxes, government spending, and similar approaches. Stop legislating out of fear; start thinking about first principles.

Start With First Principles

Data centers are not some niche luxury for a few tech firms. They are part of the backbone of modern commerce and communication. They help power GPS, cloud services, online banking, streaming, AI tools, and real-time business operations.

They are being built in many states, with Virginia leading the way in the number of data centers in operation or under construction. Texas is close behind Virginia in second place for the number of those data centers, but is first when including the announced data center builds.

Check out this graphic provided by the Committee to Unleash Prosperity.

The real question is not whether Texas should want data centers. Of course it should. The real question is whether Texas will build the energy and water systems needed to support growth or blame demand for exposing policy failures.
​
I’ve argued before that Texas should compete for data center investment instead of regulating it away; policymakers should stop blaming data centers for failures rooted in bad utility policy; anti-innovation energy policy can short-circuit America’s future; and intervention often backfires when innovation is at stake.

Those are not separate arguments. They are the same argument from different angles: when the government blocks supply, prosperity suffers.

The Problem Is Not Demand

Let’s grant critics their best point. Data centers use electricity. Some use water. Large new facilities require planning. But that still does not make data centers the problem.

A growing economy uses more resources. That is what growth looks like. The policy issue is whether the market is free to internalize costs spontaneously and whether supply can expand. The committee itself is studying how SB 6 (bad electricity bill passed in the 2025 regular session), ERCOT’s large-load process, and co-located resources can support resilience and reliability.

Grid strain is not proof that data centers are bad. It is often proof that policy has constrained supply.

What Electricity Critics Miss

The loudest arguments against data centers usually rely on gross electricity numbers. Those numbers sound scary, but they do not tell the whole story.

What matters is the net burden on the system and whether firms can solve problems through markets. Data centers can use private contracts, co-located generation, backup systems, and flexible load strategies. And the claim that data centers automatically drive up power prices is weaker than many assume.

A recent Committee to Unleash Prosperity summary of Institute for Energy Research findings argues that rising electricity demand can spread high fixed grid costs across more kilowatt-hours, helping moderate per-unit price pressures, while state policy plays a larger role in price differences.

That does not mean costs don’t matter. It means the answer is to allow large users to bear the costs they create through market prices and allow supply to expand. That is a serious market-based answer. Blanket restrictions or heavy regulation are not.

What Water Critics Miss

Water criticism often gets even sloppier. Opponents cite headline numbers as if every facility used the most water-intensive setup under worst-case conditions. But operating reality is more nuanced.

Many facilities can reduce water use through more efficient cooling technologies, including closed-loop systems and other innovations that sharply reduce ongoing water needs. And where water is genuinely scarce, the answer is not panic from Austin. The answer is to let pricing, contracts, property rights, reuse, and innovation allow firms to internalize those costs.
That is how markets should work.

Don’t Copy Scarcity States

Texas should not import the politics of decline from states now moving toward moratoria, tighter restrictions, and anti-data-center activism. Those policies do not stop digital demand. They just move jobs, capital, tax base, and strategic advantages elsewhere. Texas became an economic powerhouse by building, not by panicking.

Three Points for Policymakers

1. Do not confuse demand with danger. Data centers are a sign of growth, productivity, and modern infrastructure needs.
2. Allow cost internalization through market prices, not regulation, taxes, or growth suppression. When power or water is scarce, structural rules mean firms bear those costs through prices, contracts, and technology rather than broad political restrictions.
3. Choose abundance over barriers. Faster permitting, more generation, better water pricing through privatization with clear property rights, and more private infrastructure solutions are better answers. As I’ve argued in my work on utility reform and innovation over intervention, the durable answer is more supply, not fear or scapegoating.

Speak Up

The committee may be avoiding oral public testimony, as only invited testimony is allowed, but Texans can still be heard in writing. The hearing notice states that electronic public comments are open to Texas residents until the hearing adjourns.
Please submit a public comment here by noon CT on Thursday, April 9, and tell lawmakers to support data centers, reject anti-growth restrictions, and focus instead on energy and water abundance.

Texas can either build the infrastructure of the future or watch other states do it instead. Texas must build for national, economic, and personal security.

Originally published on Substack.

Washington is doing that thing it always does: taking a useful policy tool and turning it into a political weapon. Antitrust used to be boring in the best way. It had a clear test, a clear purpose, and a clear restraint on government power.

Today, it’s being used like a Swiss Army knife for whatever grievance is trending, on the left and increasingly on the right. That’s bad economics, bad governance, and a great way to slow innovation at the exact moment America needs more of it.

This is the core warning in Innovation Over Intervention and it connects directly to a bigger point I’ve made elsewhere: winning the global technological race requires more competition and capacity at home, not more politicized control.

If antitrust is going to exist, it must be governed by the consumer welfare standard. Not political vibes. Not “bigness.” Not “bias.” Real evidence of consumer harm.

The only antitrust test that works

The consumer welfare standard asks four questions:

• Will it raise prices
• Reduce output or choice
• Lower quality
• Slow innovation

If the government can prove consumer harm, enforce the law. If not, get out of the way.

That standard is not a gift to big companies. It’s a restraint on government. It keeps antitrust from becoming economic central planning by lawsuit.

Antitrust is becoming a political multi-tool

The Federal Trade Commission filed an appeal in its Meta case. The point isn’t whether you like Meta. The point is the signal: structural theories and retroactive challenges remain a live strategy, which increases uncertainty for investors and competitors.

The Google search remedies fight keeps pushing antitrust toward industrial policy. DOJ is still emphasizing sweeping remedies in its remedies statement and case materials on the search case page. Even where unlawful conduct is proven, remedies still need to be tethered to consumer welfare, not “restructure the market because we can.”

And look how quickly competition policy gets pulled into cultural fights. The FTC’s debanking warning letters show how easily agencies drift into non-economic missions.

This is the bipartisan trap: the left wants to punish “big.” Parts of the right want to punish “bias.” Either way, antitrust becomes politics-first.

And politics-first antitrust is the opposite of competition.

What tech is actually doing for the U.S. economy

Now, the part Washington keeps skipping: the benefits.

America’s tech sector is driving a historically large private investment cycle in AI and data infrastructure. Projected hyperscaler spending is expected to reach roughly $610 billion in 2026 based on company guidance. Related reporting also describes the capex surge as a broad annual investment cycle across major firms.

This matters for competition because capital formation is the fuel for entry. When expected after-regulation returns fall, the first thing that dies is the marginal project. And the marginal project is often where the next competitor comes from.

Also, these firms are not just apps. They build physical assets in America. A clear example is Amazon’s Project Kuiper satellite facility producing satellites for broadband connectivity. That’s advanced manufacturing and domestic capability.
Data centers and infrastructure investments are increasingly local growth stories too, like Amazon’s planned San Antonio data center and Meta’s boosted West Texas investment to $10 billion.

When policymakers treat profitability reduction as a goal, they are not just fighting “corporate power.” They are changing incentives to build and invest in America.

Your retirement account is in this debate

Americans own these companies through retirement accounts and broad index funds, whether they follow tech policy or not. The scale of retirement assets and equity exposure is visible in retirement market data and household exposure to equities in the Financial Accounts.

So when politicians talk about reducing profitability by force or breaking up firms for political reasons, it doesn’t just punish executives. It hits retirement savers and household wealth.

That should matter to anyone who claims to care about working families.

The biggest barrier to competition in AI is not “bigness.” It’s infrastructure.

Competition in AI is increasingly constrained by infrastructure: energy, transmission, interconnection, data centers, and permitting timelines.

The energy and AI analysis and the data center electricity demand overview emphasize rising electricity demand tied to AI and data centers.

So if Washington wants more competition, it should focus on building capacity and speeding permitting. That’s why actions on removing barriers to AI leadership and updating permitting technology matter, along with the permitting technology action plan.

You can sue your way to a headline. You cannot sue your way to a power plant.

Permitting reform is competition policy.

Why “monopoly” is often a government-made problem

In a free market, durable monopoly is rare because profits attract entry. Consumers substitute. Innovators leapfrog incumbents. Competition is a process, not a snapshot.

Durable monopoly usually requires barriers markets can’t break. And those barriers are often government-made: licensing, permitting, protected markets, trade barriers, and compliance regimes only incumbents can afford.

If policymakers want more competition, the honest agenda is lowering barriers to entry and trade, not punishing success.

For policymakers

Here’s the quick checklist:

• Use the consumer welfare standard as the only guardrail
• Demand evidence of consumer harm, not narratives about “power”
• Stop using antitrust to fight cultural disputes
• Treat permitting, energy, and transmission as pro-competition policy
• Remember that stable rules are part of winning the global technological race
• Remember: uncertainty is a barrier, and barriers are the oxygen of monopoly

Closing

If antitrust exists, it must be disciplined and boring. Consumer welfare. Evidence. Predictable rules.

Because monopoly is not defeated by breaking successful firms into smaller pieces. Monopoly is defeated by making it easy to compete.

That’s the American model. Let’s stop abandoning it.

America is once again at a familiar crossroads: innovation is moving fast—and policymakers are rushing to catch up.
The latest example is the growing push for age-verification mandates on app stores and social media platforms. Framed as a way to protect children, these proposals are gaining traction across states.

But beneath the surface, the tradeoffs are significant.

In this episode of This Week’s Economy, we explore how these policies could create serious privacy risks, restrict free speech, and reduce competition—while failing to address the root causes of youth mental health challenges.

Rather than expanding government control, the better path is clear: empower parents with tools, information, and flexibility to guide their children in a digital world.

That approach strengthens families without undermining the principles of a free society.
🎧 Watch the full episode: https://youtu.be/B5SFgE3pxS0
📖 Get more insights: https://vanceginn.substack.com
​
Subscribe, share, and join the conversation about policies that truly let people prosper.

That alone is progress.

For years, the conversation around artificial intelligence has been dominated by fear—fear about jobs, kids, misinformation, and control. And when policymakers operate from fear, they tend to rush into doing something—usually something heavy-handed.

This framework is different. It leans toward innovation, growth, and leadership.

The real question now is whether lawmakers across the country will follow that lead—or regulate this opportunity away before it fully arrives.

Because make no mistake: this is not just another tech trend.This is the early stage of the next economic revolution.

More Than a Buzzword

Let’s clear something up.

AI is not some mysterious force. It’s advanced computing—the continuation of tools we’ve used for decades in search, logistics, fraud detection, finance, and medicine. What’s changing now is the scale and speed.

That matters because it means AI will touch nearly every part of the economy.

We’ve seen this kind of moment before. The agricultural revolution transformed how we produced food. The Industrial Revolution reshaped labor and production. The digital revolution changed how we communicate and exchange information.

Each time, people feared what was coming. Each time, politicians felt pressure to step in and manage the transition. And each time, the real progress came not from top-down control, but from bottom-up experimentation.

Markets didn’t get everything right—but they adapted, learned, and improved far faster than any centralized plan ever could.

That’s still true today. Markets are far better at discovery than governments are at prediction.

A Better Direction from Washington

To its credit, the Trump framework reflects that reality.
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It focuses on empowering parents, protecting children, supporting creators and intellectual property, defending free speech, and preparing workers for a more dynamic economy. It also makes clear that America should aim to lead—not slow down—the development of AI.

That’s a welcome shift.

It avoids the worst instinct in policymaking: assuming that because something is new, it must be tightly controlled.

And importantly, it does not follow the path of proposals we’ve seen elsewhere—from U.S. Senator Marsha Blackburn at the federal level to various state efforts like by Texas Senator Angela Paxton—that push toward app store mandates, platform controls, or restrictions on infrastructure like data centers.

Those ideas are built on a simple but flawed premise: that government knows better than parents, entrepreneurs, and consumers.

It doesn’t.

Where Things Go Wrong: The States

If there’s a real risk to getting AI policy wrong, it’s not coming from this framework. It’s coming from the states.

There have already been more than 1,500 AI-related bills filed across state legislatures this year. That’s not thoughtful policymaking. That’s a stampede driven by headlines and worst-case scenarios.
​
California, New York, and Colorado are leading the charge with some of the most aggressive proposals—vague “harm” standards, licensing regimes, audits, and broad oversight structures that sound reasonable in theory but would slow innovation in practice. Even “conservative” Texas has drifted in this direction. HB 149 (TRAIGA) ended up better than where it started, but it still reflects too much fear and too little evidence.

Here’s the problem: AI doesn’t stop at state lines.

Cloud systems, data flows, software deployment, and digital services operate across borders. A 50-state patchwork of rules doesn’t make the technology safer—it makes the system more fragmented, more expensive, and less competitive.
Who wins in that environment?

Not startups. Not small businesses. Not consumers.

The winners are the largest incumbents that can afford compliance costs—and foreign competitors operating under entirely different rules.

That’s not a free market. That’s regulation protecting the powerful.

Fear Has Always Been the Wrong Guide

Let’s be honest about what’s driving a lot of this.

Fear.

Fear that jobs will disappear. Fear that kids will be harmed. Fear that new tools will be misused.

Some of those concerns are real. But they are not new.

Every major innovation has brought disruption. Workers were displaced during industrialization. The internet created new risks alongside new opportunities. Social media has amplified underlying challenges that were already there.

But here’s what history shows clearly: trying to ban or overregulate innovation doesn’t solve those problems—it often makes them worse.

When government tries to shut things down, activity doesn’t disappear. It moves. It becomes harder to track, harder to manage, and often more concentrated in fewer hands.

Think prohibition. Think black markets. Think organized crime. You don’t eliminate risk. You shift it—and often amplify it.
Heavy-handed AI regulation would follow the same pattern:

• Driving innovation elsewhere
• Reducing transparency
• Concentrating power

That’s not protection. That’s unintended consequences.

What Lawmakers Should Do Now

There is a better path—and it’s simpler than many think.

1. Refuse the worst ideas. No digital ID systems tied to AI access. That’s a dangerous step toward centralized control that has nothing to do with innovation or safety.
2. Use the laws we already have. Fraud, exploitation, coercion, and abuse are already illegal. Enforce those laws instead of creating entirely new regulatory regimes.
3. Address the growing patchwork problem. AI is inherently interstate commerce. As James Madison wrote in Federalist No. 42, the Constitution empowers the federal government to prevent state actions that “embarrass the intercourse of the States.”

That’s exactly what a fragmented AI regulatory landscape would do.
​
A temporary federal pause or preemption of state AI regulations isn’t about expanding power—it’s about preserving a functioning national market.

The Stakes

China will push forward through central planning. Europe is already slowing itself with overregulation. America still has a different option. We can trust markets, empower people, and lead the next wave of innovation.

Or we can let fear drive policy—and fall behind.

The Trump AI framework is a strong start. But it will only matter if we resist the urge to overcorrect at every level of government.

Closing Thought

We live in what should be a free society.

That means accepting trial and error. It means trusting people to adapt. It means allowing innovation to move forward even when it’s imperfect.

America should not lose the AI revolution because policymakers were too afraid to let it happen.

Let parents parent.

Let entrepreneurs build.

Let workers adapt.

Let markets work.

Let People Prosper

If we get this right, America leads the next economic revolution.
​
If we get it wrong, we regulate ourselves into decline.

Originally published on Substack. 

​A fresh round of anxiety over Texas data centers is building in Austin, and lawmakers need to get this right. The noise is familiar: grid strain, water use, local disruption, and rising demand from AI. The temptation is also familiar: form a committee, write a mandate, and pretend government can centrally plan the next phase of the digital economy better than markets can.

That instinct would be a costly mistake.

The better approach is to understand what data centers actually are, why they matter to economic growth, national security, and daily life, and how Texas can meet the challenge with more supply, more transparency, and more competition instead of more bureaucracy.

The goal should not be to block growth. It should be to build abundance.

A recent Texas Policy Research explainer captures the tension well. Texas is attracting major data-center investment because it has long offered low taxes, abundant land, and a relatively competitive electricity market. But those same projects are exposing weaknesses in the state’s energy and water systems, especially when policy gets in the way of price signals and private adaptation.

Start with the basics.

A data center is not just a warehouse with computers. It is physical infrastructure that stores, processes, and transmits information for the modern economy. Every search query, cloud backup, digital payment, video stream, logistics update, telehealth session, and AI-generated response relies on this backbone.

The Goldwater Institute is right to call data centers the “industrial backbone of the modern economy.” As of March 2025, the United States had 5,426 data centers, and global investment in data-center infrastructure could approach $7 trillion by 2030, with more than 40 percent expected in the United States.

Texas is central to that future. CBS Texas reports that the state already has more than 400 data centers and could become the largest data-center market in the world. It highlights major projects from firms like Digital Realty and says Texas data-center load could more than double, accounting for roughly 30 percent of total U.S. demand by 2028.

That is not a niche trend. That is Texas sitting at the center of America’s technology race. This is why the issue is bigger than convenience. Data centers matter for national security, too.

The same infrastructure that supports commercial AI and cloud services also supports cybersecurity, defense, communications resilience, and America’s broader technological lead. If the United States wants to compete with China, secure sensitive systems, and lead in AI, then it needs the physical infrastructure to do it.

A country cannot talk tough about technological leadership while acting squeamish about building server capacity, fiber connections, and reliable power.

Lawmakers also need a clearer picture of how these facilities are built.

According to GBC Engineers, data centers must handle massive structural loads from server racks, backup generation, batteries, cable trays, transformers, and cooling equipment. They require large open spans, flexible layouts, and rapid construction to keep pace with changing technology.

That is why developers often use prefabricated systems and precast concrete. These are specialized industrial assets, not vanity projects for big tech.

Now to the hardest concern: electricity.

Yes, data centers use a lot of power. Of course they do.

They process huge amounts of information nonstop, and computing creates heat that has to be removed.

The problem is not that demand rises. The problem is when policymakers respond as if demand itself is suspicious.

Rising electricity demand is what you should expect in a growing economy with more AI, more digital commerce, more advanced manufacturing, and more connectivity.

The Cato Institute notes that U.S. electricity demand, after staying mostly flat for years, is now climbing because of data centers, AI, manufacturing, and electrification. Cato says U.S. data centers consumed about 183 terawatt-hours of electricity in 2024, roughly 4 percent of total consumption, and projects from the International Energy Agency suggest that could rise to 426 terawatt-hours by 2030.

The answer to that is not to crush data centers. The answer is to expand supply and let large users bear their own costs.
That is where a lot of current policy thinking breaks down.

The Texas Policy Research piece notes that ERCOT has documented one of the sharpest increases in projected load growth in its history, with large-load projects entering the queue faster than generation and transmission can be built. It also flags Senate Bill 6 as an example of lawmakers leaning toward more regulatory control over large-load customers rather than relying on stronger market incentives.

That is exactly the kind of drift Texas should resist.

Here is the key point policymakers need to understand: grid strain is not proof that data centers are bad. It is often proof that policy has constrained supply, delayed investment, or socialized costs through monopoly utility structures.

The Goldwater report argues that high electricity prices are largely driven by policy choices such as mandates, fuel restrictions, and barriers to reliable generation, not by the mere existence of data centers. It even notes that Virginia maintains below-average electricity rates despite hosting one of the largest data-center concentrations in the world.

If data centers automatically wrecked affordability, Virginia would be a mess. It is not.

That should sound familiar. In my earlier writing, I made the same basic argument: the deeper problem is not private innovation but government distortion through monopoly utility structures, mispriced risk, and political meddling.

Data centers are exposing weaknesses in the system. They did not create those weaknesses out of thin air.

Connection costs are a legitimate concern, but they still do not justify panic. A large new facility can require substation work, transmission upgrades, and interconnection investments. If those costs are dumped onto ordinary customers, that is a problem. But the fix is not to let government decide which projects deserve power. That means better pricing, faster approvals, more direct contracting, more private generation, and more room for microgrids or other parallel systems.

This is where the Cato paper is especially useful. It argues for private electricity grids and consumer-regulated arrangements that allow electricity-intensive users to secure power without forcing everyone else to subsidize them. That is a much better path than trying to ration demand from the Capitol.

Responsibility should follow decisions. If a company wants to build a power-hungry facility, then it should have strong incentives to contract, generate, conserve, and invest accordingly. Markets can handle that better than hearings can.

Water is the other major concern, and again, lawmakers need more light and less heat.

The Texas Policy Research explainer is fair to note that Texas still lacks complete statewide reporting and that both direct cooling use and indirect water use through power generation matter. That uncertainty is real. But uncertainty is not the same thing as a case for blanket restrictions.

The Goldwater Institute adds important context: firms are already reducing or eliminating potable-water use in many cases through closed-loop cooling, air-cooled systems, and reclaimed-water designs.

Many modern data centers do not need pristine municipal drinking water just to cool equipment, and they have strong incentives to conserve because water costs money. That is how profit and loss work. Waste is expensive. Efficiency pays.
This is the bigger lesson policymakers need to absorb.

The public conversation too often treats data centers as though they are imposed on passive communities by giant corporations. But Texas has always been strongest when it trusted property rights, voluntary exchange, and personal responsibility more than political control.

If a developer wants to buy land, risk private capital, line up power, manage cooling, and meet clear rules, who exactly should decide that project is not worth building?

In a free state, that answer should not be “a handful of politicians who are nervous about headlines.”

That does not mean no rules. It means the conditional rules.

Texas should insist on transparency and clear property-rights protections. It should avoid subsidies that pick winners and losers. It should let prices reflect scarcity. It should allow more generation, faster infrastructure expansion, and more innovation in private power arrangements.

That is what abundance looks like.

The alternative is the politics of scarcity: bottling up supply, forcing new demand through fragile systems, then blaming growth for revealing the weakness. That is not stewardship. That is surrender dressed up as caution.

Texas should be the state that shows the country how to handle this well. Not by pretending the digital economy can run without physical infrastructure. Not by demonizing electricity demand as though growth itself were irresponsible. And not by letting government decide which parts of the future are allowed to exist.

Data centers are not the enemy. They are part of the foundation of prosperity, security, and modern life. The right question is not how to stop them. It is how to make Texas abundant enough to support them.

Legislative Snapshot

• Data centers are core Texas infrastructure for AI, payments, communications, logistics, and national security, not optional tech toys.
• Electricity and water concerns are real, but they are mostly challenges of supply, pricing, and transparency, not reasons to regulate growth away.
• The best path is abundance: protect property rights, avoid subsidies and mandates, let large users pay their utility bills, and expand energy and infrastructure through market competition.

Subscribe and share this with policymakers, staff, or media who need a clearer framework than the usual panic. The state that leads on abundance will lead on technology, too.

Originally published on Substack. 

Artificial intelligence could revive competition in American banking. But not if Washington regulates it out of existence first.

Banks across the United States are pouring billions into artificial intelligence to detect fraud, analyze credit risk, automate compliance, and modernize their operations. As CNBC reports on Wall Street’s accelerating AI investment, financial institutions increasingly see AI as the next transformative technology for the industry.

This shift could expand competition across the financial system more than any regulatory reform Washington has attempted in decades.

But if policymakers follow their usual instinct—to regulate innovation before understanding it—they could slow the very revolution that might improve banking competition and financial access.

That would be a costly mistake.

The Next Financial Revolution

Artificial intelligence is not simply another financial software upgrade. It is the next major technological revolution in financial services.

AI systems can process enormous volumes of financial data in real time, allowing banks to detect fraud, evaluate lending risks, and automate regulatory compliance tasks that previously required massive administrative departments.

Financial institutions are already embedding these tools across their operations.

The Wall Street Journal reports that large banks are integrating AI deeply into core financial services as they modernize risk management and customer-facing technology.

The implications for financial competition are enormous.

Technology lowers barriers to entry. It reduces operational costs. And it allows smaller institutions and fintech firms to compete against established incumbents. That is how innovation expands opportunity.

AI Could Strengthen Community Banking

Artificial intelligence may be particularly important for smaller financial institutions.

Community banks and regional banks have faced rising regulatory costs for years. Compliance requirements have expanded while regulatory complexity has continued to grow.

Large financial institutions can spread those costs across enormous balance sheets. Smaller institutions cannot. Artificial intelligence offers a way to change that equation.

Automation can reduce administrative burdens. Machine learning can improve credit underwriting and fraud detection without requiring thousands of compliance personnel. Technology can lower barriers that previously limited competition.
If allowed to develop freely, AI could strengthen competition across the financial system. Consumers benefit when that happens.

The Real Risk Is Regulatory Overreach

Artificial intelligence itself is not the greatest threat to financial markets. Regulatory overreaction is.

Financial services are already one of the most heavily regulated sectors in the American economy. Adding sweeping new AI-specific regulatory frameworks could unintentionally entrench the largest incumbents. This pattern has played out repeatedly.

Rules intended to protect consumers often end up protecting the largest institutions that can afford the compliance burden. Startups and smaller banks often cannot.

Heavy-handed regulation risks slowing innovation and limiting competition precisely when technology could expand both.

America Must Lead the AI Race

Artificial intelligence in banking is part of a broader technological competition. The United States currently leads much of the global financial technology sector, but leadership is not guaranteed.

As The Washington Post reports on the growing global race over AI regulation and development, governments across the world are debating how aggressively to regulate emerging technologies.

Europe is leaning toward centralized regulatory frameworks. China is pursuing a state-directed model of technological development.

America’s advantage historically has been different. Entrepreneurship. Competition. Freedom to innovate.

In my research on Winning the Global Technological Race, I explain why maintaining that environment of innovation is essential if the United States wants to lead the next technological revolution.

Artificial intelligence will test whether policymakers still understand that lesson.

Financial Reform Still Matters

Artificial intelligence alone will not solve deeper structural problems in the financial system.

Over decades, regulatory accumulation and monetary policy distortions have reshaped financial markets in ways that often reduce competition rather than expand it.

In Correcting America’s Financial Future: Monetary Policy and Financial Regulation Guide, I outline how excessive regulation and distorted financial policy have weakened competition in American banking.

Artificial intelligence offers an opportunity to restore some of that competition. But only if policymakers allow markets to work.

Give Nothing a Chance

Whenever a new technology emerges, the political instinct is predictable. Government must act. New rules must be written. New regulatory frameworks must be built.

But often the best policy response is simpler: Give nothing a chance.

Markets coordinate information better than bureaucracies. Entrepreneurs adapt faster than regulators. Competition produces better outcomes than centralized mandates.

Every major economic transformation—from railroads to electricity to the internet—succeeded because innovation was allowed to develop before regulators tried to control it.

Artificial intelligence is simply the next chapter.

The Bottom Line

Artificial intelligence could dramatically expand financial competition, lower costs, and improve access to banking services.

But those gains will only materialize if policymakers resist the temptation to regulate innovation before it fully develops.
America has led every major technological revolution of the past century because entrepreneurs had the freedom to experiment and compete.

The AI banking revolution will test whether that tradition still holds.

Five Takeaways for Policymakers

1. Avoid premature regulation.
   Artificial intelligence in finance is still evolving. Overregulation now risks freezing innovation before its benefits are fully realized.
2. Encourage competition, not consolidation. Heavy regulatory frameworks often strengthen the largest institutions while limiting smaller competitors.
3. Modernize financial regulation. Decades of regulatory accumulation have already increased barriers to entry. Policymakers should focus on simplifying rules rather than layering new mandates.
4. Maintain America’s technological advantage. Innovation thrives in competitive markets. Overregulation risks pushing technological leadership elsewhere.
5. Let markets work. The best way to encourage financial innovation is often to remove barriers rather than create new ones.

Call to Action

If you are a policymaker, regulator, journalist, or financial industry leader, the choices made today about artificial intelligence will shape the future of financial competition.

Encourage innovation—or regulate the next financial revolution before it begins.
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For deeper analysis, explore my research on Winning the Global Technological Race and financial reform in Correcting America’s Financial Future.​