Please, no. Let’s not get too aggressive about regulating AI development and use.
Sure, certain kinds of AI regulation are worthwhile and probably unavoidable, but those theoretically fall within the bounds of existing law: the framework in which liability issues, property rights, and claims of fraud are settled. Otherwise, there may be a role for industry self-regulation, perhaps within the kind of framework outlined here. Beyond that, broader and more intrusive government regulation and oversight of AI companies would serve to slow or retard development, and thereby hamper progress on addressing safety and security (because ongoing development will help reveal weaknesses). It would also stifle industry competition in the U.S., and cede advantages to adversaries, particularly China.
Promise and Limits
My position on AI regulation flows from optimism about what AI can accomplish as well as recognition of AI’s inherent limits. It is a powerful technology, but it does not “reason”. It is capable of real innovation, but only to the extent that it mechanically and iteratively constructs solutions based on a catalogue of past knowledge. Of course, it does the latter exceptionally well, and its solutions can be quite novel, drawing upon complex links between phenomena across many dimensions, but that is not the same as creative genius.
Those who anthropomorphize AI tend to fall for superstitions about new technology that have plagued humanity for centuries and have, at times, hindered the advancement of human well being. Yet we have prospered from new technologies in spite of this noise.
Begging For Discipline
Unfortunately, recent warnings from some AI executives and developers have been taken to heart across the political spectrum, though not particularly within the Trump Administration. While I have been critical of many of Trump’s policy positions and initiatives, deregulation has been a bright spot (if very uneven), and the promise of a light touch on AI regulation is another plus. Yet Trump has allowed the Pentagon to prohibit defense contracts with Anthropic as a security concern. In addition, the proposed “AI Force” raises questions, especially in light of Defense (War!) Secretary Pete Hegseth’s Anthropic decision. Presumably, the AI Force would be a branch of Homeland Security. AI obviously has significant military and defense applications. But could such an AI Force remain above the regulatory fray even as it designates certain applications or models to be a threat to national security? And could such a designation be contested?
The “doomers” within the AI industry are an obvious irony. They warn that their work might have “existential” consequences but continue that work under what we might call a self-compelled burden of competence. If anyone and everyone is going to do AI, then they too must do it too, if only for the good of humanity. But they insist that joining forces with the federal government to regulate or even pause development will somehow save the day, despite the global nature of the competition.
Perhaps Deeper Motives
To me, their rationale for government regulation seems implausible. The big AI companies are massive enterprises, and whether or not one believes they could “capture” a new regulatory body, they are nonetheless highly interested in shaping the future of any rules and regulation to which they and their competitors would be subject.
Alex Tabarrokinsists that regulatory capture is typically confined to mature, regulated industries in his post “What Regulatory Capture Actually Looks Like”. He not only doubts that AI doomers have designs on capturing regulators; he also believes that the doomers expressed fears are completely sincere.
As one of Tabarrok’s commenters suggests, however, the AI executives’ behavior comports with the “bootleggers and baptists” theory of public choice, whereby politicians or influential parties claim the highest motives in serving the public interest and yet stand to reap economic gains from “protective” restrictions. In the case of AI, the executives may well be playing both roles. And they might happily accept both roles even if they believe their own warnings of doom. In fact, any rents the big AI concerns gain as a result of new regulations might be viewed as deserved, or unavoidable in any case.
Another plausible explanation for the pro-regulatory (and pro-pause) position taken by some players, notably Anthropic and OpenAI, is discussed by Francis Turner. It has to do with a desperate need for cash flow. One avenue would involve an effort to:
“… wriggle out of the optimistic compute commitments they have made. … both Open AI and Anthropic have made enormous commitments to purchase compute which has been what has driven the explosive growth in data centers. Unfortunately for Big AI the demand simply doesn’t seem to be there. Or at least the demand to pay the prices Big AI wants to charge.“
Turner also notes that a regulatory push to ban Chinese models would be seen as a competitive boost for these companies. Finally, Turner believes the big AI companies employ individuals with a personal drive to control the evolution and use of AI. That’s not hard to believe! A regulatory regime would offer ample opportunities for industry insiders to step into roles in which they could do just that. Possible motives are ample, whether borne of altruism, power-seeking, or the pursuit of economic gain. We could call this mere rent seeking or political bargaining, rather than regulatory capture, but some sort of capture might well be a goal.
Fearsand Risks
Again, cries for regulation are accompanied by a stoking of fears that AI presents existential risks for humanity. One prominent example is closely associated with Noah Smith, though I’m sure he’s not the first to discuss it. That’s the idea that AI will be used to design a deadly supervirus that will wipe out most of the human race. This fear is overblown and unrealistic. A number of extremely deadly pathogens already exist, ebola being the perhaps the most contagious and deadly. Local deployments could surely be used to infect a large number of people, but that would be difficult to pull off and we are capable of containment. It is hardly an existential threat to humanity. As to the creation and spread of deadly new bugs, practical obstacles drastically reduce the likelihood of such an outcome, particularly on an existential scale, as outlined by Claus Wilke in “I’m sorry, you’re not going to die from an AI-engineered supervirus”.
Perhaps the most significant risks presented by AI fall within the realm of cybersecurity. Certain security breaches could conceivably threaten large numbers of people, but they are unlikely to approach existential levels for humanity.
The potential for plain old fraud via AI is real, including the creation and propagation of misinformation at scale. This is probably as much a human or user problem as an AI problem. AI hallucinations are an aspect of it as well, but that’s really an obstacle to adoption, so AI companies are working hard to minimize the problem. Damages under all of these categories should fall within the traditional legal bounds of liability, whether the result of intent or negligence. The latter distinction should carry less weight given that AI decisions are often shrouded within a so-called “black box”. Of course, assigning liability assumes that a responsible party can be identified, but legally defining LLMs as products helps to solve that problem.
Turner also raises the possibility of severe financial damage from an AI agent given authority over large amounts of capital, especially if assigned malicious financial objectives. This category of damage falls within the scope of existing securities laws and regulation.
Finally, some have warned of a risk that humans will suffer “cognitive atrophy” from relying on AI. In fact, it’s said to be a reality even now, and that it will become more severe as humans rely on AI to solve more problems and perform tasks. Will AI cause humans to devolve and face a more brutish existence? While I accept that AI presents a risk of cognitive atrophy, there are also ways in which AI stimulates intellectual curiosity about all manner of things. Much depends on the spirit in which AI is approached. It must be used as a tool and a complement to human intellectual pursuit, not a substitute for it, but that depends in large part on the user. I’m confident that the human spirit of inquiry will remain as strong as ever.
Summary
To sum up my general view regarding the pleadings for regulation of AI, I offer this quote from Per Byland:
“The State’s core function, in both theory and practice, is to give the ruling class a reliable way to extract wealth from society while posing as selfless public servants. It’s an ideal setup for the greedy, self‑absorbed, and unproductive.“
Except in this case we see the ownership and employees within a highly productive sector of the economy ostensibly rooting for the state to make them less productive. Or are they really? If it’s safety they want, then it’s incumbent on them to make their products safe, whatever that might entail, or face legal consequences. Continued development is likely to reveal risks as well as better ways to mitigate those risks.
If it’s economic advantage that Big AI craves, that answer too is in their very hands: they must compete in the AI marketplace to produce capable, reliable, and safe products that buyers value. Adopting a rigid government regulatory solution or a pause in development would likely bring the sacrifice of U.S. competitive advantages in AI and ultimately a centrally-planned and ineffective approach to AI.
As for designs on gaining a political advantage, we can hope that AI doomers will ultimately go the way of all Luddites before them.
I voted for Trump because I considered him to be far preferable to Kamala Harris across a range of issues. I still feel that way, but I’m appalled at a number of actions he’s taken and/or proposed in the 14 months since he took office. As a candidate, I gave Trump a “grade point average” of about 2.68, a solid C+. Here, I’ll grade him on most of the same categories, but I’ve made a few changes to the categories based on developments since his inauguration. My perspective here is generally domestic non-intervention and small government.
Yes, I realize this is tldr; I’m sure I elaborated more than necessary, but you can skip around and scroll to sections in which you might have greater interest. Here’s a list of topics:
Role of Government
Regulation
Border Policy
Antitrust
Foreign Policy
Trade
Taxes
Inflation
Federal Reserve Independence
Federal Spending and the Deficit
Entitlement Reform
Government Waste
Health and Health Care
Abortion
Housing
Energy
First Amendment Rights
Second Amendment Rights
DEI and Its Evil Financial Twin, ESG
Technology
Voting Rights
Education
Role of Government: It’s probably unfair to treat this as a separate category because it might double count specifics mentioned later, but Trump has demonstrated an unfortunate proclivity for wielding government power over private affairs when it suits him politically. On this point, “The Conspicuous Fist of Trump’s State Corporatism”, is a good read. Trump’s actions demonstrate the awful ways in which populism is often a close cousin to socialism. An example is Trump’s economic micro-management and abrogation of property rights in attacking share buybacks. Trump boasts of his efforts to strengthen the American economy by committing public resources to investments in private enterprises, and by “doing deals” with foreign governments to invest in the U.S. When it comes to limited government, candidate Trump’s C is now President Trump’s D.
Regulation: Despite the kinds of intrusions cited above, the Trump Administration has, at the same time, aggressively pursued deregulation of private activity. The goal is to achieve a 10-to-1 ratio of rule rollbacks to new regulatory rules. One can and should assess regulatory measures one-by-one, but there are plenty of rules that wouldn’t pass a reasonable cost-benefit test. On the whole the regulatory state has grown unwieldy and imposes significant costs on producers, and ultimately taxpayers and consumers, often with little compensatory benefit. I applaud the effort to untangle the regulatory state. My grade for Trump here remains an A.
Border Policy: Despite my preference for non-intervention, I support strong border enforcement along with expanded legal immigration.
Illegal entry has plummeted under Trump, a welcome development. Uncontrolled immigration entails a loss of sovereignty and is a poor fiscal proposition. Those with deeper criminal records, from either before or after entry, deserve no concessions. Strict vetting is also necessary to prevent incursions by potential terror threats.
While illegal entry is a crime, otherwise innocent illegals should be treated kindly. For example, rewards can be offered for voluntary deportation, an approach used extensively by the Trump Administration. There are difficult issues such as birthright citizenship, the constitutionality of which has been questioned on textual grounds, and the practicality of which can be shaky, even for children of parents who enter the U.S. legally. Either way, it seems clear that the promise of birthright citizenship should not serve as an incentive for illegal entry.
The Administration has certainly fumbled immigration enforcement in some instances, with cases of improperly detained individuals. Furthermore, very little has been done to advance the cause of increased legal immigration. On this topic I give Trump an overall B-.
Antitrust: This is a case of excessive government meddling with a big dose of favoritism thrown in. Early on, the Trump Administration chose to follow in the footsteps of Biden-era antitrust enforcement with a bias toward penalizing successful businesses on the pretext of “protecting” consumers.
Even worse, the Trump Administration has used the threat of antitrust as a cudgel in pursuit of a variety of objectives that are purely political. For example, in a recent executive order (EO), Trump threatened antitrust action against companies who invest in *too many* single-family homes, a counterproductive prohibition with hoped-for appeal to populist instincts. Then, under Trump, there have been missives from the FTC to tech companies about their failure to provide “balanced” news coverage, a prerogative protected by the First Amendment.
Trump has also interfered with Netflix’s now aborted acquisition of Warner Bros., in favor of a rival offer from Paramount. Trump also engineered the coercive extraction of a U.S. government “Golden Share” in approving the merger of U.S. Steel and Nippon Steel, which Trump claims gives him “total control”, in part by controlling the number of board seats. And he basically extorted a 15% cut for the government for approving a deal allowing Nvidea and AMD to sell the older H20 chip to China.
Trump’s approach to antitrust is very much entangled with the Administration’s uninhibited embrace of industrial policy and public control over private activity. He shares a fantasy common to interventionists that he can leverage the coercive power of government to create just the outcomes he would like.
The grade here is a D, which I think is generous.
Foreign Policy: I’ll try to keep this category separate from trade and tariff issues, though they are intertwined. Trump’s approach to foreign policy is nothing if not bold, and it’s been a mixed bag in terms of success. In the western hemisphere we have the so-called “Donroe Doctrine”, Trump’s effort to establish U.S. hemispheric leadership. So far: we gained a more effective partnership with Panama over the canal and diminished China’s control; decapitated the Maduro regime in Venezuela, asserting control over its oil shipments and undercutting the flow of narcotics through the country; brought the Cuban communist regime to near collapse by choking off its oil imports (but at the cost of greater human suffering in Cuba); partnered with Mexico in eliminating the head of a major drug cartel; and developed closer ties with several conservative regimes in Central and South America.
I’m troubled by the deadly force used against vessels said to be transporting drugs. We might have great intelligence on smuggling operations, but there must be less deadly ways to interdict.
For better or worse, Trump has trolled Canadian leadership in an effort to provoke dissent and gain influence there with respect to trade and security issues. His provocative stance on Greenland is primarily motivated by concerns over security in the Arctic.
Trump’s action against the repressive Iranian theocracy, its support of terror, and its nuclear ambitions has been a military success. Unfortunately, it has come at the cost of some American lives, at least a few civilian casualties in Iran, and a considerable economic cost. We can only hope for quick resolution and a transition to a more liberal regime for the people of Iran. However, Trump was patient to a fault with the mullahs, offering them an off-ramp during repeated rounds of negotiations. They refused to take it.
Of course, Trump is also pro-Israel and has rallied a coalition of nations who might contribute to a revitalized Gaza. I give Trump huge props for his support of Israel and his disgust with anti-Semitism in general.
Trump’s involvement in negotiations between Ukraine and Russia have been unsuccessful. It’s fair to wonder whether he’s cutting Putin way too much slack, as Putin has no intention of relenting. China remains a major threat to U.S. interests and our allies, but many of Trump’s foreign policy initiatives have served to undermine CCP interests.
Trump unique approach has alienated some of our traditional European allies, though he has had success in influencing policy abroad. In Venezuela, it’s worrisome that Trump acts as if he’s cultivating a relationship with Maduro’s replacements, who are probably no better than Maduro except for their eagerness to cowtow to Trump. Well, maybe, maybe not! Also troubling is the collateral damage suffered by the people of Cuba. There are signs of a willingness among Cuban leaders to negotiate with Trump, though hopes for a friendly successor regime might be foolish.
On the whole, I’ll give Trump a B on foreign policy. It’s bold, but he’s had some real successes.
Trade: I gave Trump an F on trade policy as a candidate. He’s more than justified that grade as president. He is a complete dolt when it comes to the benefits of foreign trade, the meaning of a trade deficit, the costs inflicted by tariffs, their complete inadequacy as a replacement for the income tax, and their counterproductive effect on foreign investment in the U.S. His “emergency” tariffs constituted a huge tax increase on the American people, but those were ruled unconstitutional by the Supreme Court. His latest ploy is to impose punitive tariffs under the guise of a balance of payments emergency, but the balance of payments is zero! This too will be struck down in the courts.
Some might argue that Trump’s other foreign policy achievements would not have been possible without the threat of tariffs, but the fact is Trump imposed the tariffs anyway. Yup, it’s an F.
Taxes: In terms of budget effects, the increased tariff revenue (which might not last at present levels) is much more than offset by tax provisions in the One Big Beautiful Bill Act (OBBBA) passed into law last summer. It makes permanent many of the reductions in the Tax Cuts and Jobs Act of 2017 that had been ready to expire. The standard deduction is increased and more limits are placed on itemization. The Act also creates targeted (and temporary) deductions for tips, overtime, auto loans, and seniors, which is inefficient because it treats various forms of income differently, leading to incentives for unproductive reallocations. Those changes also smack of political pandering.
The OBBBA makes permanent some tax incentives for business, such as immediate expensing of short-term asset purchases and domestic R&D investment. It also provides a temporary 100 percent deduction for certain structures and phases out tax credits for green energy production (bravo!).
To the extent that the tax package includes some pro-growth elements, I applaud it. Tax reductions generally are a good thing because they reduce distortions, but Trump has managed to introduce several distortionary elements just the same. I won’t dock Trump for deficit effects here because the deficit is fundamentally a spending problem, not a tax problem. I gave him a C+ on taxes as a candidate, but I’ll boost him to a B- for his first year.
Inflation: Trump doesn’t have real control over inflation as economists define it, but he’s managed to aggravate some price increases just the same. Unfortunately, he makes repeated claims that “prices have fallen” under his leadership, which of course is false. Egg prices perhaps, and oil prices (er… not this month). Of course, in general prices are up, including import prices. Inflation measures have been fairly steady over the past year, but remain stubbornly higher than the Federal Reserve’s target. I give Trump a grade on this topic only because he deserves a penalty for his false boasts. It’s a C, the same as candidate Trump.
Federal Reserve Independence: Trump has relentlessly badgered Jerome Powell and the Fed to somehow engineer lower interest rates. Of course, many key interest rates are market driven and outside the Fed’s direct control. Trump has gone so far as to bring lawfare to bear against Powell, accusing him of misleading Congress regarding cost overruns on the renovation of the Fed’s offices in DC. Of course, it’s not unusual for a president to jawbone the Fed, but Trump has been absurdly aggressive at a time when reducing the Fed’s rate targets would quite possibly backfire. At least Trump’s selection of the next Fed Chairman, Kevin Warsh, was more reasonable than another top candidate who would probably have been a mere punching bag. For this, I’ll lift his grade slightly, from an F to a D-.
Federal Spending and the Deficit: I discuss a few components of spending under other headings below. Beyond those points, Trump has taken every opportunity to find creative uses for taxpayer money. He has proposed a “tariff dividend” for all households funded by the revenue from import taxes. (Refunds of tariff revenue to “payers” are still in question.) At this point, the better alternative is to put extra revenue toward paying down the federal debt. The same goes for any revenue earned from the many “deals” Trump is counting on. Pay down the debt and earn an immediate, certain, and lasting return, rather than installing the government as part owner of otherwise private enterprises having uncertain returns.
Apart from that and the folly of establishing a sovereign wealth fund while the public debt is burgeoning, Trump has made no progress whatsoever on deficit reduction. Granted, he can’t count on strong legislative support despite slight majorities in both chambers of Congress.
The tax cuts in the OBBBA obviously don’t help the cause of deficit reduction. In fairness, rebuilding the military is a major priority. However, interests costs on the debt will keep rising as will discretionary non-defense outlays. At least the East-Wing Ballroom, the Arc de Trump (!), and the Kennedy Center renovation all appear to be privately funded.
Trump deserves a D here. Some of his priorities are terrible, and I can’t cut him any slack based on trends in discretionary spending.
Entitlement Reform: Trump has been silent on reforms to Social Security’s “Old Age and Survivors” programs and Medicare, except to promise no cuts in benefits under his watch. Kick the can! However, the administration has considered cuts in other entitlements, such as Social Security Disability Insurance, Medicaid and Supplemental Nutrition Assistance (SNAP). These programs have been riddled with fraud, so I applaud steps to clean them up. Nevertheless, any progress made here will still be dwarfed by the insolvency of the Retirement and Medicare programs, which Trump considers a third rail for potential reformers. I gave him an F as a candidate, but his anti-fraud efforts help him salvage a C-.
Government Waste: DOGE was short-lived as originally constituted, its execution was clumsy, and the blow-up in Trump’s relationship with Elon Musk was an embarrassment. However, DOGE was a force for stanching the flow of taxpayer dollars through politicized NGOs. The budget savings were relatively small, but the defunded programs were often egregious varieties of government waste. Subsequently, DOGE personnel had an outsized influence on downsizing the federal bureaucracy and targeting waste across various agencies. In addition, the efforts of one-time DOGE workers were put to good use in identifying entitlement fraud, which could and should result in budget savings. Trump gets a B+ on this one.
Health and Health Care: I’ll give Trump credit here for pursuing a more consumer-oriented approach to health care reform, though at least one of his initiatives is counterproductive.
His initial steps took the form of EOs reducing subsidies paid on ACA marketplace policies, ending remaining penalties for violating the ACA’s individual mandate, approving short-term coverages free of certain ACA restrictions, cutting Medicaid expansion funding, and granting more flexibility for states in defining “essential” healthcare benefits. All of these are basically good steps.
Trump issued an ill-conceived EO calling for “Most-Favored Nation” (MFN) prescription drug pricing, which should reduce Americans’ prescription costs but will dramatically undercut life-saving drug research. Hate the pharmaceutical companies all you want, but they must earn a reasonable profit to risk the massive development costs of new miracle drugs, of which they’ve brought many to market. Price controls always create more problems than they solve.
In early 2026 Trump introduced his “Great Healthcare Plan” (GHP). It would codify MFN drug pricing, fund cost-sharing reductions for ACA plans, encourage price transparency, and redirect payments to consumers and away from insurers to facilitate choice and competition. Also launched was the TrumpRx.gov platform featuring MFN pricing. Ironically, the goal here is to improve access to prescription drugs. Good luck!
Under Robert F. Kennedy, Jr., Trump’s HHS Secretary, the “Make America Healthy Again” agenda has emphasized a healthy diet and exercise, including noteworthy changes in the famous food triangle hierarchy. I can’t argue with those. However, RFK Jr. has upended research under HHS, and those actions were rash in a number cases. He wants to address chronic diseases but I’m skeptical of some of his causal claims. I also have mixed reactions to his changed guidance on vaccines. There are reports that the White House has not been comfortable with all of RFK’s pronouncements and is eager to inject more oversight.
I have varied reactions to Trump’s efforts in the health care arena. MFN price capping is a good way to destroy the advantages Americans enjoy in terms of access to innovative drugs, even if they come at a steep cost. RFK Jr. is a wild card, to be fair. Otherwise, while the GHP should help to improve healthcare affordability, it neglects other critical reforms such as ending the disparate tax treatment of health care premiums and deregulating providers. Still, Trump’s grade improved here, from a D+ as a candidate to a B- thus far in his term.
Abortion: No change here. Trump has consistently supported the right to life. He gets an A.
Housing: Build Baby Build! But aside from harping on the Fed to lower interest rates, Trump hasn’t done much to encourage housing supply.
His EO banning institutional investors from owning “too many” single-family homes won’t help affordability because so few homes are owned by large investors. But to the extent that they are, the EO will increase rents and discourage new housing supply. This is another misguided foray into central economic planning.
While I think a 50-year mortgage should be legal, it’s something I believe potential homebuyers should avoid unless they want to risk stubbornly low equity in their homes stretching into retirement. Trump shouldn’t talk this up too much.
Trump has supported the “ROAD to Housing” bill, which has garnered bipartisan support. It would codify the restrictions on ownership of single-family housing by institutional investors and restrict construction of “rent-to-own” housing by such investors. One couldn’t invent a less effective way to encourage supply and promote “affordability”. But the bill would also subsidize demand, which will increase pressure on housing prices even as the bill aims to assist particular groups (e.g., tax credits for first-time homebuyers). Despite all those downsides, the bill actually includes a few steps to boost housing supply, such as making some federal lands available for development, regulatory reform, and tax incentives for builders.
Trump has also discussed changes to government sponsored enterprises (GSEs, Fannie Mae and Freddie Mac), which purchase new mortgages from lenders, including possible privatization. He might be licking his chops for the $300 billion the GSEs owe the federal government, which could be put toward various “deals” he might like to cut. If privatization were to end the explicit government guarantee for mortgage-backed securities issued by the GSEs, mortgage interest rates would rise and it could be quite disruptive for banks.
Housing policy is another mixed bag for Trump, but I’ll give him a B on the strength of his deregulatory effort.
Energy: Drill baby drill! Despite the current disruption to oil shipments through the straight of Hormuz and the spike in oil prices, I deem Trump’s energy policies a success thus far. Largely through deregulation, Trump has opened up the spigots on domestic oil production. He has also realigned energy priorities, eliminating subsidies and mandates for intermittent renewable energy sources in favor of encouraging fossil fuels, hydroelectric, and especially a new emphasis on nuclear power. Some of these steps represent unabashed central planning, so I can’t give Trump an A on energy policy,. However, the preceding green-energy regime was central planning on steroids with the unintended consequence of instability in the power grid. I would greatly prefer a policy of complete neutrality with respect to energy sources, but at least Trump is not cowed by global warming hysteria.
And Trump is considering a temporary suspension of the Jones Act due to the energy crunch brought on by the war in Iran. That would be great except that the waiver should be permanent. The move would lower energy (and other) costs to U.S. consumers and minimize supply disruptions by allowing energy (and other goods) to flow more freely between U.S. ports.
His grade on energy policy is a B.
First Amendment Rights: Trump has not been the defender of free speech that I had hoped. On this, I gave him an A- as a candidate, but his Administration has been belligerent in attacking speech. He (and his FCC Chairman) threaten media outlets with license revocation, his Attorney General says “we will target you” for anything DOJ attorneys might define as hate speech, and Trump has called certain speech he dislikes “illegal”. I also have qualms about an EO issued last year by Trump targeting “campaigns of … radicalization”, which might, in practice, bring any sort of opposition speech under scrutiny. And there are other potentially troublesome provisions for protected speech. Trump’s pure intent might be to stop violent radicalism, which is fine in spirit but hard to bring off without mass surveillance and violations of rights. I therefore downgrade Trump to a C on free speech.
Second Amendment Rights: Trump has not been quite as consistent on gun rights as he was as a candidate. He took a number of actions to reduce burdens and restrictions on gun rights, but in other cases he let restrictions stand, including arrests for gun possession in Washington DC by federal agents and a possible proposal to restrict the gun rights of transgendered individuals. All-in-all, I’ll reduce Trump’s A on gun rights to a B+.
DEI and Its Evil Financial Twin, ESG: There is no question that Trump has done much to cut through the stranglehold that DEI doctrine had imposed on social and economic life. He issued EOs to end DEI practices in the federal government. He also threatened major universities with funding freezes and anti-discrimation actions, an approach that has met with some success. Trump’s words and actions on DEI have reverberated through the private sector as well. He has encouraged individuals who believe they’ve suffered discrimination based on DEI to file lawsuits. The thrust of the Administration’s agenda on DEI and regulatory changes has served to undermine the use of ESG measures. These are intended to draw investors to companies purporting to foster environmental and social goals, which can be at odds with creating value for shareholders. Trump has earned his A in this category.
Technology: As in other policy domains, the record here is marred by misguided industrial policies. That includes the recent snafu over the Department of Defense’s allegation of “supply chain risk” posed by Anthropic. DoD wants carte blanche access to all aspects of any AI model it adopts, including uses in autonomous weapons systems and mass public surveillance. Anthropic said it would not accept that without guardrails, so an apparently infuriated Pete Hegseth moved to designate the company a supply chain risk, an outright punishment that would obviously damage Anthropic’s economic prospects. Yet almost immediately, DoD agreed to an arrangement with OpenAI with guardrails similar to those desired by Anthropic. Now, Trump, who seems to have Hegseth’s back, is readying an EO on the topic… so we shall see. But it’s a mess. Anthropic has filed suit.
And yet Trump has generally been supportive of AI development, signing an order to prevent states from imposing a patchwork of varying, complex regulations. The White House has issued an ”AI Action Plan” to encourage AI exports, minimizing federal regulatory burdens, and “upholding free speech” on “unbiased” frontier models. Let’s hope “unbiased” has a truly neutral definition in this case. Trump has signed a series of EOs related to AI research and deployment, which are linked here.
Post-inauguration, Trump dove right into another socialist joint venture known as Stargate to build data center infrastructure. The rationale for the government’s direct involvement is national security. Of course, that’s the Administration’s rough and ready excuse for almost any kind of intervention.
Trump has helped promote the crypto industry, supporting legislation (the CLARITY Act and the GENIUS Act) enabling more widespread use of stablecoins. He even supports the payment of returns on stablecoins, a development that is unpopular with banks. Trump has also acted to promote cybersecurity and harden infrastructure against malicious actors. More recently, he initiated a program to test eVTOL technologies (electronic vertical takeoff and landing), which are expected to revolutionize local and regional transportation in coming years.
The best I can give Trump on technology is a B-, given his penchant for government control. The Anthropic controversy is a real black eye.
Voting Rights: The Trump-backed SAVE America Act would require an ID proving citizenship to vote in federal elections. It’s stalled in the Senate, seven votes short of the 60 needed to send it to Trump’s desk. GOP senators are unwilling to force a talking filibuster, let alone to use the so-called “nuclear option” to force a simple-majority vote. There is still a possibility of including a voter ID requirement in a budget reconciliation bill if anyone can convince the Senate Parliamentarian that it would have budget impacts. For his part, Trump says he’ll refuse to sign any other legislation until the SAVE Act crosses his desk, though he’s also threatened to issue an EO mandating voter ID should the Senate fail to pass the bill. The constitutionality of such an order would be challenged, of course, but for his determination on the issue, I’ll give him an A+.
Education: This is a quick addition to the list. After inserting the photo of Trump at the top, I realized that I’d completely forgotten to add education as a performance category. Trump’s effort to dismantle the wasteful and unproductive Department of Education is to be applauded. He’s also been an unwavering supporter of school choice. I’ll give him an A here.
I have to stop! That’s 22 categories and a “grade point average” of 2.55 if the categories are equally weighted. It’s a little worse than Trump’s GPA as a candidate (2.67). He could have improved his grades dramatically without his bent for economic intervention, but I’d have to vote for him again given the alternative.
As of February 2026, I’m adding this short preamble to a few older posts on the subject of AI and future prospects for human labor. In the original post below (and a few others), I overstated the case that the law of comparative advantage would assure a continued role for humans in production. I still think the case is strong, mind you, but now I’m convinced that the outcome depends on elasticities of input substitution and how those elasticities might shift given the advent of AI-augmented capital. You can read my most recent thoughts on the matter here.
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In this case, the “A” stands for Altman. Now Sam Altman is no slouch, but he’s taken a few ill-considered positions on public policy. Altman, the CEO of Open AI, wrote a blog post back in 2021 entitled “Moore’s Law For Everything” in which he predicted that AI will feed an explosion of economic growth. He also said AI will put a great many people out of work and drive down the price of certain kinds of labor. Furthermore, he fears that the accessibility of AI will be heavily skewed against the lowest socioeconomic classes. In later interviews (see here and here), Altman is somewhat demure about those predictions, but the general outline is the same: despite exceptional growth of GDP and wealth, he envisions job losses, an underclass of AI-illiterates, and a greater degree of income and wealth inequality.
Not Quite Like That
We’ve yet to see an explosion of growth, but it’s still very early in the AI revolution. The next several years will be telling. AI holds the potential to vastly increase our production possibilities over the course of the next few decades. For that and other reasons, I don’t buy the more dismal aspects of Altman’s scenario, as my last two posts make clear (here and here).
There will be plenty of jobs for people because humans will have comparative advantages in various areas of production. AI agents might have absolute advantages across most or even all jobs, but a rational deployment would have AI agents specialize only where they have a comparative advantage.
Scarcity will not be the sort of anachronism envisioned by some AI futurists, Altman included, and scarcity of AI agents (and their inputs) will necessitate their specialization in certain tasks. The demand for AI agents will be quite high, and their energy and “compute” requirements will be massive. AI agents will face extremely high opportunity costs in other tasks, leaving many occupations open for human labor, to say nothing of abundant opportunities for human-AI collaboration.
However, I don’t dismiss the likelihood of disruptions in markets for certain kinds of labor if the AI revolution proceeds as rapidly as Altman thinks it will. Many workers would be displaced, and it would take time, training, and a willingness to adapt for them to find new opportunities. But new kinds of jobs for people will emerge with time as AI is embedded throughout the economy.
Altman’s Rx
Altman’s somewhat pessimistic outlook for human employment and inequality leads him to make a couple of recommendations:
1) Ownership of capital must be more broadly distributed.
2) Capital and land must be taxed, potentially replacing income taxes, but primarily to fund equity investments for all Americans.
Here I agree with the spirit of #1. Broad ownership of capital is desirable. It allows greater participation in the capitalist system, which fosters political and economic stability. And wider access to capital, whether owned or not, allows a greater release of entrepreneurial energy. It also diversifies incomes and reduces economic dependency.
Altman proposes the creation of an American Equity Fund (AEF) to hold the proceeds of taxes on land and corporate assets for the benefit of all Americans. I’ll get to the taxes in a moment, but in discussing the importance of educating the public on the benefits of compounding, Altman seems to imply that assets in AEF would be held in individual accounts, as opposed to a single “public” account controlled by the federal government. Individual accounts would be far preferable, but it’s not clear how much control Altman would grant individuals in managing their accounts.
To Kill a Golden Goose
Taxes on capital are problematic. Capital can only be accumulated over time by saving out of income. Thus, as Michael Munger points out, as a general proposition under an income tax, all capital has already been taxed once. And we tax the income from capital at both the corporate and individual level. So corporate income is already double taxed: corporate profits are taxed along with dividend payments to shareholders.
Altman proposed in his 2021 blog post to levy a tax of 2.5% on the market value of publicly-traded corporations each year. The tax would be payable in cash or in corporate shares to be placed into the AEF. The latter would establish a kind of UnLiquidated Tax Reserve Accounts (ULTRA), which Munger discusses in the article linked above (my bracketed x% in the quote here):
“Instead of taking [x%] of the liquidated value of the wealth, the state would simply take ownership of the wealth, in place. An ULTRA is a ‘notional equity interest.’ The government literally takes a portion of the value of the asset; that value will be paid to the state when the asset is sold. Now, it is only a ‘notional’ stake, in the sense that no shared right of control or voting rights exists. But for those who advocate for ULTRAs, in any situation where tax agencies are authorized to tax an asset today, but cannot because there is no evaluation event, the taxpayer could be made to pay with an ULTRA rather than with cash.”
This solves all sorts of administrative problems associated with wealth taxes, but it is draconian nevertheless. Munger quotes an example of a successful, privately-held business subject to a 2% wealth tax every year in the form of an ULTRA. After 20 years, the government owns more than a third of the company’s value. That represents a substantial penalty for success! However, the incidence of such a tax might fall more on workers and customers and less on business owners. And Altman would tax corporations more heavily than in Munger’s example.
A tax on wealth essentially penalizes thrift, reduces capital accumulation, and diminishes productivity and real wages. But another fundamental reason that taxes on capital should be low is that the supply of capital is elastic. A tax on capital discourages saving and encourages capital flight. The use of avoidance schemes will proliferate, and there will be intense pressure to carve out special exemptions.
A Regressive Dimension
Another drawback of a wealth tax is its regressivity with respect to returns on capital. To see this, we can convert a tax on wealth to an equivalent income tax on returns. Here is Chris Edwardson that point:
“Suppose a person received a pretax return of 6 percent on corporate equities. An annual wealth tax of 2 percent would effectively reduce that return to 4 percent, which would be like a 33 percent income tax—and that would be on top of the current federal individual income tax, which has a top rate of 37 percent.”
… The effect is to impose lower effective tax rates on higher‐yielding assets, and vice versa. If equities produced returns of 8 percent, a 2 percent wealth tax would be like a 25 percent income tax. But if equities produced returns of 4 percent, the wealth tax would be like a 50 percent income tax. People with the lowest returns would get hit with the highest tax rates, and even people losing money would have to pay the wealth tax.“
Edwards notes the extreme inefficiency of wealth taxes demonstrated by the experience of a number of OECD countries. There are better ways to increase revenue and the progressivity of taxes. The best alternative is a tax on consumption, which rewards saving and capital accumulation, promoting higher wages and economic growth. Edwards dedicates a lengthy section of his paper to the superiority of a consumption tax.
Is a Wealth Tax Constitutional?
The constitutionality of a wealth tax is questionable as well. Steven Calabresi and David Schizer (C&S)contend that a federal wealth tax would qualify as a direct tax subject to the rule of apportionment, which would also apply to a federal tax on land. That is, under the U.S. Constitution, these kinds of taxes would have to be the same amount per capita in every state. Thus, higher tax rates would be necessary in less wealthy states.
C&S also note a major distinction between taxes on the value of wealth relative to income, excise, import, and consumption taxes. The latter are all triggered by transactions entered into voluntarily. They are avoidable in that sense, but not wealth taxes. Moreover, C&S believe the founders’ intent was to rely on direct taxes only as a backstop during wartime.
The recent Supreme Court decision in Moore v. United States created doubt as to whether the Court had set a precedent in favor of a potential wealth tax. According to earlier precedent, the Constitution forbade the “laying of taxes” on “unrealized” income or changes in wealth. However, in Moore, the Court ruled that undistributed profits from an ownership interest in a foreign business are taxable under the mandatory repatriation tax, signed into law by President Trump in 2017 as part of his tax overhaul package. But Justice Kavanaugh, who wrote the majority opinion, stated that the ruling was based on the foreign company’s status as a pass-through entity. The Wall Street Journalsays of the decision:
“Five Justices open the door to taxing unrealized gains in assets. Democrats will walk through it.”
In a brief post, Calabrisi laments Justice Ketanji Brown Jackson’s expansive view of the federal government’s taxing authority under the Sixteenth Amendment, which might well be shared by the Biden Administration. But the Wall Street Journal piece also describes Kavanaugh’s admonition regarding any expectation of a broader application of the Moore opinion:
“Justice Kavanaugh does issue a warning that ‘the Due Process Clause proscribes arbitrary attribution’ of undistributed income to shareholders. And he writes that his opinion should not ‘be read to authorize any hypothetical congressional effort to tax both an entity and its shareholders or partners on the same undistributed income realized by the entity.’”
Growth Is the Way, Not Taxes
AI growth will lead to rapid improvements in labor productivity and real wages in many occupations, despite a painful transition for some workers requiring occupational realignment and periods of unemployment and training. However, people will retain comparative advantages over AI agents in a number of existing occupations. Other workers will find that AI allows them to shift their efforts toward higher-value or even new aspects of their jobs. Along the same lines, there will be a huge variety of new occupations made possible by AI of which we’re only now catching the slightest glimpse. Michael Strain has emphasized this aspect of technological diffusion, noting that 60% of the jobs performed in 2018 did not exist in 1940. In fact, few of those “new” jobs could have been imagined in 1940.
AI entrepreneurs and AI investors will certainly capture a disproportionate share of gains from an AI revolution. Of course, they’ll have created a disproportionate share of that wealth. It might well skew the distribution of wealth in their favor, but that does not reflect negatively on the market process driving the outcome, especially because it will also give rise to widespread gains in living standards.
Altman goes wrong in proposing tax-funded redistribution of equity shares. Those taxes would slow AI development and deployment, reduce economic growth, and produce fewer new opportunities for workers. The surest way to effect a broader distribution of equity capital, and of equity in AI assets, is to encourage innovation, economic growth, and saving. Taxing capital more heavily is a very bad way to do that, whether from heavier taxes on income from capital, new taxes on unrealized gains, or (worst of all) from taxes on the value of capital, including ULTRA taxes.
Altman is right, however, to bemoan the narrow ownership of capital. As I mentioned above, he’s also on-target in saying that most people do not fully appreciate the benefits of thrift and the miracle of compounding. That represents both a failure of education and our calamitously high rate of time preference as a society. Perhaps the former can be fixed! However, thrift is a decision best left in private hands, especially to the extent that AI stimulates rapid income growth.
Killer Regulation
Altman also supports AI regulation, and I’ll cut him some slack by noting that his motives might not be of the usual rent-seeking variety. Maybe. Anyway, he’ll get some form of his wish, as legislators are scrambling to draft a “roadmap” for regulating AI. Some are calling for billions of federal outlays to “support” AI development, with a likely and ill-advised effort to “direct” that development as well. That is hardly necessary given the level of private investment AI is already attracting. Other “roadmap” proposals call for export controls on AI and protections for the film and recording industries.
These proposals are fueled by fears about AI, which run the gamut from widespread unemployment to existential risks to humanity. Considerable attention has been devoted to the alignment of AI agents with human interests and well being, but this has emerged largely within the AI development community itself. There are many alignment optimists, however, and still others who decry any race between tech giants to bring superhuman generative AI to market.
The Biden Administration stepped in last fall with an executive order on AI under emergency powers established by the Defense Production Act. The order ranges more broadly than national defense might necessitate, and it could have damaging consequences. Much of the order is redundant with respect to practices already followed by AI developers. It requires federal oversight over all so-called “foundation models” (e.g., ChatGPT), including safety tests and other “critical information”. These requirements are to be followed by the establishment of additional federal safety standards. This will almost certainly hamstring investment and development of AI, especially by smaller competitors.
Patrick Hedger discusses the destructive consequences of attempts to level the competitive AI playing field via regulation and antitrust actions. Traditionally, regulation tends to entrench large players who can best afford heavy compliance costs and influence regulatory decisions. Antitrust actions also impose huge costs on firms and can result in diminished value for investors in AI start-ups that might otherwise thrive as takeover targets.
Conclusion
Sam Altman’s vision of funding a redistribution of equity capital via taxes on wealth suffers from serious flaws. For one thing, it seems to view AI as a sort of exogenous boon to productivity, wholly independent of investment incentives. Taxing capital would inhibit investment in new capital (and in AI), diminish growth, and thwart the very goal of broad ownership Altman wishes to promote. Any effort to tax capital at a global level (which Altman supports) is probably doomed to failure, and that’s a good thing. The burden of taxes on capital at the corporate level would largely be shifted to workers and consumers, pushing real wages down and prices up relative to market outcomes.
Low taxes on income and especially on capital, together with light regulation, promote saving, capital investment, economic growth, higher real wages, and lower prices. For AI, like all capital investment, public policy should focus on encouraging “aligned” development and deployment of AI assets. A consumption tax would be far more efficient than wealth or capital taxes in that respect, and more effective in generating revenue. Policies that promote growth are the best prescription for broadening the distribution of capital ownership.
Artificial intelligence (AI) has become a very hot topic with incredible recent advances in AI performance. It’s very promising technology, and the expectations shown in thechart above illustrate what would be a profound economic impact. Like many new technologies, however, many find it threatening and are reacting with great alarm, There’s a movement within the tech industry itself, partly motivated by competitive self-interest, calling for a “pause”, or a six-month moratorium on certain development activities. Politicians in Washington are beginning to clamor for legislation that would subject AI to regulation. However, neither a voluntary pause nor regulatory action are likely to be successful. In fact, either would likely do more harm than good.
Leaps and Bounds
The pace of advance in AI has been breathtaking. From ChatGPT 3.5 to ChatGPT 4, in a matter of just a few months, the tool went from relatively poor performance on tests like professional and graduate entrance exams (e.g., bar exams, LSAT, GRE) to very high scores. Using these tools can be a rather startling experience, as I learned for myself recently when I allowed one to write the first draft of a post. (Despite my initial surprise, my experience with ChatGPT 3.5 was somewhat underwhelming after careful review, but I’ve seen more impressive results with ChatGPT 4). They seem to know so much and produce it almost instantly, though it’s true they sometimes “hallucinate”, reflect bias, or invent sources, so thorough review is a must.
Nevertheless, AIs can write essays and computer code, solve complex problems, create or interpret images, sounds and music, simulate speech, diagnose illnesses, render investment advice, and many other things. They can create subroutines to help themselves solve problems. And they can replicate!
As a gauge of the effectiveness of models like ChatGPT, consider that today AI is helping promote “over-employment”. That is, there are a number of ambitious individuals who, working from home, are holding down several different jobs with the help of AI models. In fact, some of these folks say AIs are doing 80% of their work. They are the best “assistants” one could possibly hire, according to a man who has four different jobs.
Economist Bryan Caplan is an inveterate skeptic of almost all claims that smack of hyperbole, and he’s won a series of bets he’s solicited against others willing to take sides in support of such claims. However, Caplan thinks he’s probably lost his bet on the speed of progress on AI development. Needless to say, it has far exceeded his expectations.
Naturally, the rapid progress has rattled lots of people, including many experts in the AI field. Already, we’re witnessing the emergence of “agency” on the part of AI Learning Language Models (LLMs), or so called “agentic” behavior. Here’s an interesting thread on agentic AI behavior. Certain models are capable of teaching themselves in pursuit of a specified goal, gathering new information and recursively optimizing their performance toward that goal. Continued gains may lead to an AI model having artificial generative intelligence (AGI), a superhuman level of intelligence that would go beyond acting upon an initial set of instructions. Some believe this will occur suddenly, which is often described as the “foom” event.
Team Uh-Oh
Concern about where this will lead runs so deep that a letter was recently signed by thousands of tech industry employees, AI experts, and other interested parties calling for a six-month worldwide pause in AI development activity so that safety protocols can be developed. One prominent researcher in machine intelligence, Eliezer Yudkowsky, goes much further: he believes that avoiding human extinction requires immediate worldwide limits on resources dedicated to AI development. Is this a severely overwrought application of the precautionary principle? That’s a matter I’ll consider at greater length below, but like Caplan, I’m congenitally skeptical of claims of impending doom, whether from the mouth of Yudkowsky, Greta Thunberg, Paul Ehrlich, or Nassim Taleb.
As I mentioned at the top, I suspect competition among AI developers played a role in motivating some of the signatories of the “AI pause” letter, and some of the non-signatories as well. Robin Hanson points out that Sam Altman, the CEO of OpenAI, did not sign the letter. OpenAI (controlled by a nonprofit foundation) owns ChatGPT and is the current leader in rolling out AI tools to the public. ChatGPT 4 can be used with the Microsoft search engine Bing, and Microsoft’s Bill Gates also did not sign the letter. Meanwhile, Google was caught flat-footed by the ChatGPT rollout, and its CEO signed. Elon Musk (who signed) wants to jump in with his own AI development: TruthGPT. Of course, the pause letter stirred up a number of members of Congress, which I suspect was the real intent. It’s reasonable to view the letter as a means of leveling the competitive landscape. Thus, it looks something like a classic rent-seeking maneuver, buttressed by the inevitable calls for regulation of AIs. However, I certainly don’t doubt that a number of signatories did so out of a sincere belief that the risks of AI must be dealt with before further development takes place.
The vast dimensions of the supposed AI “threat” may have some libertarians questioning their unequivocal opposition to public intervention. If so, they might just as well fear the potential that AI already holds for manipulation and control by central authorities in concert with their tech and media industry proxies. But realistically, broad compliance with any precautionary agreement between countries or institutions, should one ever be reached, is pretty unlikely. On that basis, a “scout’s honor” temporary moratorium or set of permanent restrictions might be comparable to something like the Paris Climate Accord. China and a few other nations are unlikely to honor the agreement, and we really won’t know whether they’re going along with it except for any traceable artifacts their models might leave in their wake. So we’ll have to hope that safeguards can be identified and implemented broadly.
Likewise, efforts to regulate by individual nations are likely to fail, and for similar reasons. One cannot count on other powers to enforce the same kinds of rules, or any rules at all. Putting our faith in that kind of cooperation with countries who are otherwise hostile is a prescription for ceding them an advantage in AI development and deployment. Regulation of the evolution of AI will likely fail. As Robert Louis Stevenson once wrote, “Thus paternal laws are made, thus they are evaded”. And if it “succeeds, it will leave us with a technology that will fall short of its potential to benefit consumers and society at large. That, unfortunately, is usually the nature of state intrusion into a process of innovation, especially when devised by a cadre of politicians with little expertise in the area.
Again, according to experts like Yudkowsky, AGI would pose serious risks. He thinks the AI Pause letter falls far short of what’s needed. For this reason, there’s been much discussion of somehow achieving an alignment between the interests of humanity and the objectives of AIs. Here is a good discussion by Seth Herd on the LessWrong blog about the difficulties of alignment issues.
Some experts feel that alignment is an impossibility, and that there are ways to “live and thrive” with unalignment (and see here). Alignment might also be achieved through incentives for AIs. Those are all hopeful opinions. Others insist that these models still have a long way to go before they become a serious threat. More on that below. Of course, the models do have their shortcomings, and current models get easily off-track into indeterminacy when attempting to optimize toward an objective.
But there’s an obvious question that hasn’t been answered in full: what exactly are all these risks?As Tyler Cowen has said, it appears that no one has comprehensively catalogued the risks or specified precise mechanisms through which those risks would present. In fact, AGI is such a conundrum that it might be impossible to know precisely what threats we’ll face. But even now, with deployment of AIs still in its infancy, it’s easy to see a few transition problems on the horizon.
White Collar Wipeout
Job losses seem like a rather mundane outcome relative to extinction. Those losses might come quickly, particularly among white collar workers like programmers, attorneys, accountants, and a variety of administrative staffers. According to a survey of 1,000 businesses conducted in February:
“Forty-eight percent of companies have replaced workers with ChatGPT since it became available in November of last year. … When asked if ChatGPT will lead to any workers being laid off by the end of 2023, 33% of business leaders say ‘definitely,’ while 26% say ‘probably.’ … Within 5 years, 63% of business leaders say ChatGPT will ‘definitely’ (32%) or ‘probably’ (31%) lead to workers being laid off.”
A rapid rate of adoption could well lead to widespread unemployment and even social upheaval. For perspective, that implies a much more rapid rate of technological diffusion than we’ve ever witnessed, so this outcome is viewed with skepticism in some quarters. But in fact, the early adoption phase of AI models is proceeding rather quickly. You can use ChatGPT 4 easily enough on the Bing platform right now!
Contrary to the doomsayers, AI will not just enhance human productivity. Like all new technologies, it will lead to opportunities for human actors that are as yet unforeseen. AI is likely to identify better ways for humans to do many things, or do wonderful things that are now unimagined. At a minimum, however, the transition will be disruptive for a large number of workers, and it will take some time for new opportunities and roles for humans to come to fruition.
Robin Hanson has a unique proposal for meeting the kind of challenge faced by white collar workers vulnerable to displacement by AI, or for blue collar workers who are vulnerable to displacement by robots (the deployment of which has been hastened by minimum wage and living wage activism). This treatment of Hanson’s idea will be inadequate, but he suggests a kind of insurance or contract sold to both workers and investors by owners of assets likely to be insensitive to AI risks. The underlying assets are paid out to workers if automation causes some defined aggregate level of job loss. Otherwise, the assets are paid out to investors taking the other side of the bet. Workers could buy these contracts themselves, or employers could do so on their workers’ behalf. The prices of the contracts would be determined by a market assessment of the probability of the defined job loss “event”. Governmental units could buy the assets for their citizens, for that matter. The “worker contracts” would be cheap if the probability of the job-loss event is low. Sounds far-fetched, but perhaps the idea is itself an entrepreneurial opportunity for creative players in the financial industry.
The threat of job losses to AI has also given new energy to advocates of widespread adoption of universal basic income payments by government. Hanson’s solution is far preferable to government dependence, but perhaps the state could serve as an enabler or conduit through which workers could acquire AI and non-AI capital.
Human Capital
Current incarnations of AI are not just a threat to employment. One might add the prospect that heavy reliance on AI could undermine the future education and critical thinking skills of the general population. Essentially allowing machines to do all the thinking, research, and planning won’t inure to the cognitive strength of the human race, especially over several generations. Already people suffer from an inability to perform what were once considered basic life skills, to say nothing of tasks that were fundamental to survival in the not too distant past. In other words, AI could exaggerate a process of “dumbing down” the populace, a rather undesirable prospect.
Fraud and Privacy
AI is responsible for still more disruptions already taking place, in particular violations of privacy, security, and trust. For example, a company called Clearview AI has scraped 30 billion photos from social media and used them to create what its CEO proudly calls a “perpetual police lineup”, which it has provided for the convenience of law enforcement and security agencies.
AI is also a threat to encryption in securing data and systems. Conceivably, AI could be of value in perpetrating identity theft and other kinds of fraud, but it can also be of value in preventing them. AI is also a potential source of misleading information. It is often biased, reflecting specific portions of the on-line terrain upon which it is trained, including skewed model weights applied to information reflecting particular points of view. Furthermore, misinformation can be spread by AIs via “synthetic media” and the propagation of “fake news”. These are fairly clear and present threats of social, economic, and political manipulation. They are all foreseeable dangers posed by AI in the hands of bad actors, and I would include certain nudge-happy and politically-motivated players in that last category.
The Sky-Already-Fell Crowd
Certain ethicists with extensive experience in AI have condemned the signatories of the “Pause Letter” for a focus on “longtermism”, or risks as yet hypothetical, rather than the dangers and wrongs attributable to AIs that are already extant:TechCrunch quotes a rebuke penned by some of these dissenting ethicists to supporters of the “Pause Letter”:
“‘Those hypothetical risks are the focus of a dangerous ideology called longtermism that ignores the actual harms resulting from the deployment of AI systems today,’ they wrote, citing worker exploitation, data theft, synthetic media that props up existing power structures and the further concentration of those power structures in fewer hands.”
So these ethicists bemoan AI’s presumed contribution to the strength and concentration of “existing power structures”. In that, I detect just a whiff of distaste for private initiative and private rewards, or perhaps against the sovereign power of states to allow a laissez faire approach to AI development (or to actively sponsor it). I have trouble taking this “rebuke” too seriously, but it will be fruitless in any case. Some form of cooperation between AI developers on safety protocols might be well advised, but competing interests also serve as a check on bad actors, and it could bring us better solutions as other dilemmas posed by AI reveal themselves.
ImaginingAI Catastrophes
What are the more consequential (and completely hypothetical) risks feared by the “pausers” and “stoppers”. Some might have to do with the possibility of widespread social upheaval and ultimately mayhem caused by some of the “mundane” risks described above. But the most noteworthy warnings are existential: the end of the human race! How might this occur when AGI is something confined to computers? Just how does the supposed destructive power of AGIs get “outside the box”? It must do so either by tricking us into doing something stupid, hacking into dangerous systems (including AI weapons systems or other robotics), and/or through the direction and assistance of bad human actors. Perhaps all three!
The first question is this: why would an AGI do anything so destructive? No matter how much we might like to anthropomorphize an “intelligent” machine, it would still be a machine. It really wouldn’t like or dislike humanity. What it would do, however, is act on its objectives. It would seek to optimize a series of objective functions toward achieving a goal or a set of goals it is given. Hence the role for bad actors. Let’s face it, there are suicidal people who might like nothing more than to take the whole world with them.
Otherwise, if humanity happens to be an obstruction to solving an AGI’s objective, then we’d have a very big problem. Humanity could be an aid to solving an AGI’s optimization problem in ways that are dangerous. As Yudkowsky says, we might represent mere “atoms it could use somewhere else.” And if an autonomous AGI were capable of setting it’s own objectives, without alignment, the danger would be greatly magnified. An example might be the goal of reducing carbon emissions to pre-industrial levels. How aggressively would an AGI act in pursuit of that goal? Would killing most humans contribute to the achievement of that goal?
Here’s one that might seem far-fetched, but the imagination runs wild: some individuals might be so taken with the power of vastly intelligent AGI as to make it an object of worship. Such an “AGI God” might be able to convert a sufficient number of human disciples to perpetrate deadly mischief on its behalf. Metaphorically speaking, the disciples might be persuaded to deliver poison kool-aid worldwide before gulping it down themselves in a Jim Jones style mass suicide. Or perhaps the devoted will survive to live in a new world mono-theocracy. Of course, these human disciples would be able to assist the “AGI God” in any number of destructive ways. And when brain-wave translation comes to fruition, they better watch out. Only the truly devoted will survive.
An AGI would be able to create the illusion of emergency, such as a nuclear launch by an adversary nation. In fact, two or many adversary nations might each be fooled into taking actions that would assure mutual destruction and a nuclear winter. If safeguards such as human intermediaries were required to authorize strikes, it might still be possible for an AGI to fool those humans. And there is no guarantee that all parties to such a manufactured conflict could be counted upon to have adequate safeguards, even if some did.
Yudkowsky offers at least one fairly concrete example of existential AGI risk:
“A sufficiently intelligent AI won’t stay confined to computers for long. In today’s world you can email DNA strings to laboratories that will produce proteins on demand, allowing an AI initially confined to the internet to build artificial life forms or bootstrap straight to postbiological molecular manufacturing.”
There are many types of physical infrastructure or systems that an AGI could conceivably compromise, especially with the aid of machinery like robots or drones to which it could pass instructions. Safeguards at nuclear power plants could be disabled before steps to trigger melt down. Water systems, rivers, and bodies of water could be poisoned. The same is true of food sources, or even the air we breathe. In any case, complete social disarray might lead to a situation in which food supply chains become completely dysfunctional. So, a super-intelligence could probably devise plenty of “imaginative” ways to rid the earth of human beings.
Back To Earth
Is all this concern overblown? Many think so. Bryan Caplan now has a $500 bet with Eliezer Yudkowsky that AI will not exterminate the human race by 2030. He’s already paid Yudkowsky, who will pay him $1,000 if we survive. Robin Hanson says “Most AI Fear Is Future Fear”, and I’m inclined to agree with that assessment. In a way, I’m inclined to view the AI doomsters as highly sophisticated, change-fearing Luddites, but Luddites nevertheless.
Ben Hayum is very concerned about the dangers of AI, butwriting at LessWrong, he recognizes some real technical barriers that must be overcome for recursive optimization to be successful. He also notes that the big AI developers are all highly focused on safety. Nevertheless, he says it might not take long before independent users are able to bootstrap their own plug-ins or modules on top of AI models to successfully optimize without running off the rails. Depending on the specified goals, he thinks that will be a scary development.
James Pethokoukis raises a point that hasn’t had enough recognition: successful innovations are usually dependent on other enablers, such as appropriate infrastructure and process adaptations. What this means is that AI, while making spectacular progress thus far, won’t have a tremendous impact on productivity for at least several years, nor will it pose a truly existential threat. The lag in the response of productivity growth would also limit the destructive potential of AGI in the near term, since installation of the “social plant” that a destructive AGI would require will take time. This also buys time for attempting to solve the AI alignment problem.
In another Robin Hanson piece, he expresses the view that the large institutions developing AI have a reputational Al stake and are liable for damages their AI’s might cause. He notes that they are monitoring and testing AIs in great detail, so he thinks the dangers are overblown.:
“So, the most likely AI scenario looks like lawful capitalism…. Many organizations supply many AIs and they are pushed by law and competition to get their AIs to behave in civil, lawful ways that give customers more of what they want compared to alternatives.”
In the longer term, the chief focus of the AI doomsters, Hanson is truly an AI optimist. He thinks AGIs will be “designed and evolved to think and act roughly like humans, in order to fit smoothly into our many roughly-human-shaped social roles.” Furthermore, he notes that AI owners will have strong incentives to monitor and “delimit” AI behavior that runs contrary to its intended purpose. Thus, a form of alignment is achieved by virtue of economic and legal incentives. In fact, Hanson believes the “foom” scenario is implausible because:
“… it stacks up too many unlikely assumptions in terms of our prior experiences with related systems. Very lumpy tech advances, techs that broadly improve abilities, and powerful techs that are long kept secret within one project are each quite rare. Making techs that meet all three criteria even more rare. In addition, it isn’t at all obvious that capable AIs naturally turn into agents, or that their values typically change radically as they grow. Finally, it seems quite unlikely that owners who heavily test and monitor their very profitable but powerful AIs would not even notice such radical changes.”
As smart as AGIs would be, Hanson asserts that the problem of AGI coordination with other AIs, robots, and systems would present insurmountable obstacles to a bloody “AI revolution”. This is broadly similar to Pethokoukis’ theme. Other AIs or AGIs are likely to have competing goals and “interests”. Conflicting objectives and competition of this kind will do much to keep AGIs honest and foil malign AGI behavior.
The kill switch is a favorite response of those who think AGI fears are exaggerated. Just shut down an AI if its behavior is at all aberrant, or if a user attempts to pair an AI model with instructions or code that might lead to a radical alteration in an AI’s level of agency. Kill switches would indeed be effective at heading off disaster if monitoring and control is incorruptible. This is the sort of idea that begs for a general solution, and one hopes that any advance of that nature will be shared broadly.
One final point about AI agency is whether autonomous AGIs might ever be treated as independent factors of production. Could they be imbued with self-ownership?Tyler Cowen asks whether an AGI created by a “parent” AGI could legitimately be considered an independent entity in law, economics, and society. And how should income “earned” by such an AGI be treated for tax purposes. I suspect it will be some time before AIs, including AIs in a lineage, are treated separately from their “controlling” human or corporate entities. Nevertheless, as Cowen says, the design of incentives and tax treatment of AI’s might hold some promise for achieving a form of alignment.
Letting It Roll
There’s plenty of time for solutions to the AGI threat to be worked out. As I write this, the consensus forecast for the advent of real AGI on the Metaculus online prediction platform is July 27, 2031. Granted, that’s more than a year sooner than it was 11 days ago, but it still allows plenty of time for advances in controlling and bounding agentic AI behavior. In the meantime, AI is presenting opportunities to enhance well being through areas like medicine, nutrition, farming practices, industrial practices, and productivity enhancement across a range of processes. Let’s not forego these opportunities. AI technology is far too promising to hamstring with a pause, moratoria, or ill-devised regulations. It’s also simply impossible to stop development work on a global scale.
Nevertheless, AI issues are complex for all private and public institutions. Without doubt, it will change our world. This AI Policy Guide from Mercatus is a helpful effort to lay out issues at a high-level.
In advanced civilizations the period loosely called Alexandrian is usually associated with flexible morals, perfunctory religion, populist standards and cosmopolitan tastes, feminism, exotic cults, and the rapid turnover of high and low fads---in short, a falling away (which is all that decadence means) from the strictness of traditional rules, embodied in character and inforced from within. -- Jacques Barzun
