No Radar, No Rudder: Fiscal & Monetary Destabilization

31 Wednesday May 2023

Posted by Nuetzel in Fiscal policy, Monetary Policy

Tags

budget deficits, Credible Committments, crowding out, David Beckworth, David Henderson, Discretionary Spending, economic stimulus, Federal Reserve, Great Depression, Housing Bubble, Inflation Reduction Act, Long and Variable Lags, Lucas Critique, Mortgage Crisis, Pandemic Relief, Rational Expectations, Robert Lucas, Shovel-Ready Projects, Spending Multipliers, Stabilization policy, Tyler Cowen

Policy activists have long maintained that manipulating government policy can stabilize the economy. In other words, big spending initiatives, tax cuts, and money growth can lift the economy out of recessions, or budget cuts and monetary contraction can prevent overheating and inflation. However, this activist mirage burned away under the light of experience. It’s not that fiscal and monetary policy are powerless. It’s a matter of practical limitations that often cause these tools to be either impotent or destabilizing to the economy, rather than smoothing fluctuations in the business cycle.

The macroeconomics classes seem like yesterday: Keynesian professors lauded the promise of wise government stabilization efforts: policymakers could, at least in principle, counter economic shocks, particularly on the demand side. That optimistic narrative didn’t end after my grad school days. I endured many client meetings sponsored by macro forecasters touting the fine-tuning of fiscal and monetary policy actions. Some of those economists were working with (and collecting revenue from) government policymakers, who are always eager to validate their pretensions as planners (and saviors). However, seldom if ever do forecasters conduct ex post reviews of their model-spun policy scenarios. In fairness, that might be hard to do because all sorts of things change from initial conditions, but it definitely would not be in their interests to emphasize the record.

In this post I attempt to explain why you should be skeptical of government stabilization efforts. It’s sort of a lengthy post, so I’ve listed section headings below in case readers wish to scroll to points of most interest. Pick and choose, if necessary, though some context might get lost in the process.

Expectations Change the World
Fiscal Extravagance
Multipliers In the Real World
Delays
Crowding Out
Other Peoples’ Money
Tax Policy
Monetary Policy
Boom and Bust
Inflation Targeting
Via Rate Targeting
Policy Coordination
Who Calls the Tune?
Stable Policy, Stable Economy

Expectations Change the World

There were always some realists in the economics community. In May we saw the passing of one such individual: Robert Lucas was a giant intellect within the economics community, and one from whom I had the pleasure of taking a class as a graduate student. He was awarded the Nobel Prize in Economic Science in 1995 for his applications of rational expectations theory and completely transforming macro research. As Tyler Cowen notes, Keynesians were often hostile to Lucas’ ideas. I remember a smug classmate, in class, telling the esteemed Lucas that an important assumption was “fatuous”. Lucas fired back, “You bastard!”, but proceeded to explain the underlying logic. Cowen uses the word “charming” to describe the way Lucas disarmed his critics, but he could react strongly to rude ignorance.

Lucas gained professional fame in the 1970s for identifying a significant vulnerability of activist macro policy. David Henderson explains the famous “Lucas Critique” in the Wall Street Journal:

“… because these models were from periods when people had one set of expectations, the models would be useless for later periods when expectations had changed. While this might sound disheartening for policy makers, there was a silver lining. It meant, as Lucas’s colleague Thomas Sargent pointed out, that if a government could credibly commit to cutting inflation, it could do so without a large increase in unemployment. Why? Because people would quickly adjust their expectations to match the promised lower inflation rate. To be sure, the key is government credibility, often in short supply.”

Non-credibility is a major pitfall of activist macro stabilization policies that renders them unreliable and frequently counterproductive. And there are a number of elements that go toward establishing non-credibility. We’ll distinguish here between fiscal and monetary policy, focusing on the fiscal side in the next several sections.

Fiscal Extravagance

We’ve seen federal spending and budget deficits balloon in recent years. Chronic and growing budget deficits make it difficult to deliver meaningful stimulus, both practically and politically.

The next chart is from the most recent Congressional Budget Office (CBO) report. It shows the growing contribution of interest payments to deficit spending. Ever-larger deficits mean ever-larger amounts of debt on which interest is owed, putting an ever-greater squeeze on government finances going forward. This is particularly onerous when interest rates rise, as they have over the past few years. Both new debt is issued and existing debt is rolled over at higher cost.

Relief payments made a large contribution to the deficits during the pandemic, but more recent legislation (like the deceitfully-named Inflation Reduction Act) piled-on billions of new subsidies for private investments of questionable value, not to mention outright handouts. These expenditures had nothing to do with economic stabilization and no prayer of reducing inflation. Pissing away money and resources only hastens the debt and interest-cost squeeze that is ultimately unsustainable without massive inflation.

Hardly anyone with future political ambitions wants to address the growing entitlements deficit … but it will catch up with them. Social Security and Medicare are projected to exhaust their respective trust funds in the early- to mid-2030s, which will lead to mandatory benefit cuts in the absence of reform.

If it still isn’t obvious, the real problem driving the budget imbalance is spending, not revenue, as the next CBO chart demonstrates. The “emergency” pandemic measures helped precipitate our current stabilization dilemma. David Beckworth tweets that the relief measures “spurred a rapid recovery”, though I’d hasten to add that a wave of private and public rejection of extreme precautions in some regions helped as well. And after all, the pandemic downturn was exaggerated by misdirected policies including closures and lockdowns that constrained both the demand and supply sides. Beckworth acknowledges the relief measures “propelled inflation”, but the pandemic also seemed to leave us on a permanently higher spending path. Again, see the first chart below.

The second chart below shows that non-discretionary spending (largely entitlements) and interest outlays are how we got on that path. The only avenue for countercyclical spending is discretionary expenditures, which constitute an ever-smaller share of the overall budget.

We’ve had chronic deficits for years, but we’ve shifted to a much larger and continuing imbalance. With more deficits come higher interest costs, especially when interest rates follow a typical upward cyclical pattern. This creates a potentially explosive situation that is best avoided via fiscal restraint.

Putting other doubts about fiscal efficacy aside, it’s all but impossible to stimulate real economic activity when you’ve already tapped yourself out and overshot in the midst of a post-pandemic economic expansion.

Multipliers In the Real World

So-called spending multipliers are deeply beloved by Keynesians and pork-barrel spenders. These multipliers tell us that every dollar of extra spending ultimately raises income by some multiple of that dollar. This assumes that a portion of every dollar spent by government is re-spent by the recipient, and a portion of that is re-spent again by another recipient. But spending multipliers are never what they’re cracked up to be for a variety of reasons. (I covered these in “Multipliers Are For Politicians”, and also see this post.) There are leakages out of the re-spending process (income taxes, saving, imports), which trim the ultimate impact of new spending on income. When supply constraints bind on economic activity, fiscal stimulus will be of limited power in real terms.

If stimulus is truly expected to be counter-cyclical and transitory, as is generally claimed, then much of each dollar of extra government spending will be saved rather than spent. This is the lesson of the permanent income hypothesis. It means greater leakages from the re-spending stream and a lower multiplier. We saw this with the bulge in personal savings in the aftermath of pandemic relief payments.

Another side of this coin, however, is that cutting checks might be the government’s single-most efficient activity in execution, but it can create massive incentive problems. Some recipients are happy to forego labor market participation as long as the government keeps sending them checks, but at least they spend some of the income.

Delays

Another unappreciated and destabilizing downside of fiscal stimulus is that it often comes too late, just when the economy doesn’t need stimulus. That’s because a variety of delays are inherent in many spending initiatives: legislative, regulatory, legal challenges, planning and design, distribution to various spending authorities, and final disbursement. As I noted here:

“Even government infrastructure projects, heralded as great enhancers of American productivity, are often subject to lengthy delays and cost overruns due to regulatory and environmental rules. Is there any such thing as a federal ‘shovel-ready’ infrastructure project?”

Crowding Out

The supply of savings is limited, but when government borrows to fund deficits, it directly competes with private industry for those savings. Thus, funds that might otherwise pay for new plant, equipment, and even R&D are diverted to uses that should qualify as government consumption rather than long-term investment. Government competition for funds “crowds-out” private activity and impedes growth in the economy’s productive capacity. Thus, the effort to stimulate economic activity is self-defeating in some respects.

Other Peoples’ Money

Government doesn’t respond to price signals the way self-interested private actors do. This indifference leads to mis-allocated resources and waste. It extends to the creation of opportunities for graft and corruption, typically involving diversion of resources into uses that are of questionable productivity (corn ethanol, solar and wind subsidies).

Consider one other type of policy action perceived as counter-cyclical: federal bailouts of failing financial institutions or other troubled businesses. These rescues prop up unproductive enterprises rather than allowing waste to be flushed from the system, which should be viewed as a beneficial aspect of recession. The upshot is that too many efforts at economic stabilization are misdirected, wasteful, ill-timed, and pro-cyclical in impact.

Tax Policy

Like stabilization efforts on the spending side, tax changes may be badly timed. Tax legislation is often complex and can take time for consumers and businesses to adjust. In terms of traditional multiplier analysis, the initial impact of a tax change on spending is smaller than for expenditures, so tax multipliers are smaller. And to the extent that a tax change is perceived as temporary, it is made less effective. Thus, while changes in tax policy can have powerful real effects, they suffer from some of the same practical shortcomings for stabilization as changes in spending.

However, stimulative tax cuts, if well crafted, can boost disposable incomes and improve investment and work incentives. As temporary measures, that might mean an acceleration of certain kinds of activity. Tax increases reduce disposable incomes and may blunt incentives, or prompt delays in planned activities. Thus, tax policy may bear on the demand side as well as the timing of shifts in the economy’s productive potential or supply side.

Monetary Policy

Monetary policy is subject to problems of its own. Again, I refer to practical issues that are seemingly impossible for policy activists to overcome. Monetary policy is conducted by the nation’s central bank, the Federal Reserve (aka, the Fed). It is theoretically independent of the federal government, but the Fed operates under a dual mandate established by Congress to maintain price stability and full employment. Therein lies a basic problem: trying to achieve two goals that are often in conflict with a single policy tool.

Make no mistake: variations in money supply growth can have powerful effects. Nevertheless, they are difficult to calibrate due to “long and variable lags” as well as changes in money “velocity” (or turnover) often prompted by interest rate movements. Excessively loose money can lead to economic excesses and an overshooting of capacity constraints, malinvestment, and inflation. Swinging to a tight policy stance in order to correct excesses often leads to “hard landings”, or recession.

Boom and Bust

The Fed fumbled its way into engineering the Great Depression via excessively tight monetary policy. “Stop and go” policies in the 1970s led to recurring economic instability. Loose policy contributed to the housing bubble in the 2000s, and subsequent maladjustments led to a mortgage crisis (also see here). Don’t look now, but the inflationary consequences of the Fed’s profligacy during the pandemic prompted it to raise short-term interest rates in the spring of 2022. It then acted with unprecedented speed in raising rates over the past year. While raising rates is not always synonymous with tightening monetary conditions, money growth has slowed sharply. These changes might well lead to recession. Thus, the Fed seems given to a pathology of policy shifts that lead to unintentional booms and busts.

Inflation Targeting

The Fed claims to follow a so-called flexible inflation targeting policy. In reality, it has reacted asymmetrically to departures from its inflation targets. It took way too long for the Fed to react to the post-pandemic surge in inflation, dithering for months over whether the surge was “transitory”. It wasn’t, but the Fed was reluctant to raise its target rates in response to supply disruptions. At the same time, the Fed’s own policy actions contributed massively to demand-side price pressures. Also neglected is the reality that higher inflation expectations propel inflation on the demand side, even when it originates on the supply side.

Via Rate Targeting

At a more nuts and bolts level, today the Fed’s operating approach is to control money growth by setting target levels for several key short-term interest rates (eschewing a more direct approach to the problem). This relies on price controls (short-term interest rates being the price of liquidity) rather than allowing market participants to determine the rates at which available liquidity is allocated. Thus, in the short run, the Fed puts itself into the position of supplying whatever liquidity is demanded at the rates it targets. The Fed makes periodic adjustments to these rate targets in an effort to loosen or tighten money, but it can be misdirected in a world of high debt ratios in which rates themselves drive the growth of government borrowing. For example, if higher rates are intended to reduce money growth and inflation, but also force greater debt issuance by the Treasury, the approach might backfire.

Policy Coordination

While nominally independent, the Fed knows that a particular monetary policy stance is more likely to achieve its objectives if fiscal policy is not working at cross purposes. For example, tight monetary policy is more likely to succeed in slowing inflation if the federal government avoids adding to budget deficits. Bond investors know that explosive increases in federal debt are unlikely to be repaid out of future surpluses, so some other mechanism must come into play to achieve real long-term balance in the valuation of debt with debt payments. Only inflation can bring the real value of outstanding Treasury debt into line. Continuing to pile on new debt simply makes the Fed’s mandate for price stability harder to achieve.

Who Calls the Tune?

The Fed has often succumbed to pressure to monetize federal deficits in order to keep interest rates from rising. This obviously undermines perceptions of Fed independence. A willingness to purchase large amounts of Treasury bills and bonds from the public while fiscal deficits run rampant gives every appearance that the Fed simply serves as the Treasury’s printing press, monetizing government deficits. A central bank that is a slave to the spending proclivities of politicians cannot make credible inflation commitments, and cannot effectively conduct counter-cyclical policy.

Stable Policy, Stable Economy

Activist policies for economic stabilization are often perversely destabilizing for a variety of reasons. Good timing requires good forecasts, but economic forecasting is notoriously difficult. The magnitude and timing of fiscal initiatives are usually wrong, and this is compounded by wasteful planning, allocative dysfunction, and a general absence of restraint among political leaders as well as the federal bureaucracy..

Predicting the effects of monetary policy is equally difficult and, more often than not, leads to episodes of over- and under-adjustment. In addition, the wrong targets, the wrong operating approach, and occasional displays of subservience to fiscal pressure undermine successful stabilization. All of these issues lead to doubts about the credibility of policy commitments. Stated intentions are looked upon with doubt, increasing uncertainty and setting in motion behaviors that lead to undesirable economic consequences.

The best policies are those that can be relied upon by private actors, both as a matter of fulfilling expectations and avoiding destabilization. Federal budget policy should promote stability, but that’s not achievable institutions unable to constrain growth in spending and deficits. Budget balance would promote stability and should be the norm over business cycles, or perhaps over periods as long as typical 10-year budget horizons. Stimulus and restraint on the fiscal side should be limited to the effects of so-called automatic stabilizers, such as tax rates and unemployment compensation. On the monetary side, the Fed would do more to stabilize the economy by adopting formal rules, whether a constant rate of money growth or symmetric targeting of nominal GDP.

The Scary Progress and Hairy Promise of AI

18 Tuesday Apr 2023

Posted by Nuetzel in Artificial Intelligence, Existential Threats, Growth

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Agentic Behavior, AI Bias, AI Capital, AI Risks, Alignment, Artificial Intelligence, Ben Hayum, Bill Gates, Bryan Caplan, ChatGPT, Clearview AI, Dumbing Down, Eliezer Yudkowsky, Encryption, Existential Risk, Extinction, Foom, Fraud, Generative Intelligence, Greta Thunberg, Human capital, Identity Theft, James Pethokoukis, Jim Jones, Kill Switch, Labor Participation Insurance, Learning Language Models, Lesswrong, Longtermism, Luddites, Mercatus Center, Metaculus, Nassim Taleb, Open AI, Over-Employment, Paul Ehrlich, Pause Letter, Precautionary Principle, Privacy, Robert Louis Stevenson, Robin Hanson, Seth Herd, Synthetic Media, TechCrunch, TruthGPT, Tyler Cowen, Universal Basic Income

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 the chart 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.

Imagining AI 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, but writing 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.

Everything’s Big In Texas Except Surge Capacity

01 Monday Mar 2021

Posted by Nuetzel in Electric Power, Price Mechanism, Shortage

≈ 3 Comments

Tags

Austin Vernon, Blackouts, Climate Change, Coal Power, Dolar Power, Electric Reliability Council of Texas, ERCOT, Gas Power, Green Energy, H. Sterling Burnett, Heartland Institute, Judith Curry, Lynn Kiesling, Nuclear power, Renewables, Surge Capacity, Texas, Tyler Cowen, Variable-Rate Pricing, Vernon L. Smith, Wind Power

The February cold snap left millions of Texas utility customers without power. I provide a bit of a timeline at the bottom of this post. What happened? Well, first, don’t waste your time arguing with alarmists about whether “climate change” caused the plunge in temperatures. Whether it was climate change (it wasn’t) or anything else, the power shortage had very nuts-and-bolts causes and was avoidable.

Texas has transitioned to producing a significant share of its power with renewables: primarily wind and solar, which is fine across a range of weather conditions, though almost certainly uneconomic in a strict sense. The problem in February was that the state lacks adequate capacity to meet surges under extreme weather conditions. But it wasn’t just that the demand for power surged during the cold snap: renewables were not able to maintain output due to frozen wind turbines and snow-covered solar panels, and even some of the gas- and coal-fired generators had mechanical issues. The reliability problem is typical of many renewables, however, which is why counting on it to provide base loads is extremely risky.

Judith Curry’s web site featured an informative article by a planning engineer this week: “Assigning Blame for the Blackouts in Texas”. The Electric Reliability Council of Texas (ERCOT) is the independent, non-profit operator of the state’s electric grid, with membership that includes utilities, electric cooperatives, other sellers, and consumers. Apparently ERCOT failed to prepare for such an extreme weather event and the power demand it engendered:

“… unlike utilities under traditional models, they don’t ensure that the resources can deliver power under adverse conditions, they don’t require that generators have secured firm fuel supplies, and they don’t make sure the resources will be ready and available to operate.”

ERCOT’s emphasis on renewables was costly, draining resources that otherwise might have been used to provide an adequate level of peak capacity and winterization of existing capacity. Moreover, it was paired with a desire to keep the price of power low. ERCOT has essentially “devalued capacity”:

“Texas has stacked the deck to make wind and solar more competitive than they could be in a system that better recognizes the value of dependable resources which can supply capacity benefits. … capacity value is a real value. Ignoring that, as Texas did, comes with real perils. … In Texas now we are seeing the extreme shortages and market price spikes that can result from devaluing capacity. “

Lest there be any doubt about the reliance on renewables in Texas, the Heartland Institutes’s H. Sterling Burnett notes that ERCOT data:

“… shows that five days before the first snowflake fell, wind and solar provided 58% of the electric power in Texas. But clouds formed, temperatures dropped and winds temporarily stalled, resulting in more than half the wind and solar power going offline in three days never to return during the storm, when the problems got worse and turbines froze and snow and ice covered solar panels.”

Power prices must cover the cost of meeting “normal” energy needs as well as the cost of providing for peak loads. That means investment in contracts that guarantee fuel supplies as well as peak generating units. It also means inter-connectivity to other power grids. Instead, ERCOT sought to subsidize costly renewable power in part by skimping on risk-mitigating assets.

Retail pricing can also help avert crises of this kind. Texas customers on fixed-rate plans had no incentive to conserve as temperatures fell. Consumers can be induced to lower their thermostats with variable-rate plans, and turning it down by even a degree can have a significant impact on usage under extreme conditions. The huge spike in bills for variable-rate customers during the crisis has much to do with the fact that too few customers are on these plans to begin with. Among other things, Lynne Kiesling and Vernon L. Smith discuss the use of digital devices to exchange information on scarcity with customers or their heating systems in real time, allowing quick adjustment to changing incentives. And if a customer demands a fixed-rate plan, the rate must be high enough to pay the customer’s share of the cost of peak capacity.

Price incentives make a big difference, but there are other technological advances that might one day allow renewables to provide more reliable power, as discussed in Tyler Cowen’s post on the “energy optimism” of Austin Vernon”. I find Vernon far too optimistic about the near-term prospects for battery technology. I am also skeptical of wind and solar due to drawbacks like land use and other (often ignored) environmental costs, especially given the advantages of nuclear power to provide “green energy” (if only our governments would catch on). The main thing is that sufficient capacity must be maintained to meet surges in demand under adverse conditions, and economic efficiency dictates that that it is a risk against which ratepayers cannot be shielded.

Note: For context on the chart at the top of this post, temperatures in much of Texas fell on the 9th of February, and then really took a dive on the 14th before recovering on the 19th. Wind generation fell immediately, and solar power diminished a day or two later. Gas and coal helped to offset the early reductions, but it took several days for gas to ramp up. Even then there were shortages. Then, on the 16th, there were problems maintaining gas and coal generation. Gas was still carrying a higher than normal load, but not enough to meet demand.

Fauci Flubs Herd Immunity

03 Sunday Jan 2021

Posted by Nuetzel in Coronavirus, Herd Immunity, Public Health, Vaccinations

≈ 2 Comments

Tags

Acquired Immunity, Anthony Fauci, Covid-19, Herd Immunity, Hererogeneity, HIT, Masks, Max Planck Institute, Measles, MMR Vaccine, R0, Reproduction Rate, T-Cells. Pre-Immunity, Tyler Cowen, Vaccinations. Fragile Immunity

Anthony Fauci has repeatedly increased his estimate of how much of the population must be vaccinated to achieve what he calls herd immunity, and he did it again in late December. This series of changes, and other mixed messages he’s delivered in the past, reveal Fauci to be a “public servant” who feels no obligation to level with the public. Instead, he crafts messages based on what he believes the public will accept, or on his sense of how the public must be manipulated. For example, by his own admission, his estimates of herd immunity have been sensitive to polling data! He reasoned that if more people reported a willingness to take a vaccine, he’d have flexibility to increase his “public” estimate of the percentage that must be vaccinated for herd immunity. Even worse, Fauci appears to lack a solid understanding of the very concept of herd immunity.

Manipulation

There is so much wrong with his reasoning on this point that it’s hard to know where to start. In the first place, why in the world would anyone think that if more people willingly vaccinate it would imply that even more must vaccinate? And if he felt that way all along it demonstrates an earlier willingness to be dishonest with the public. Of course, there was nothing scientific about it: the series of estimates was purely manipulative. It’s almost painful to consider the sort of public servant who’d engage in such mental machinations.

Immunity Is Multi-Faceted

Second, Fauci seemingly wants to convince us that herd immunity is solely dependent on vaccination. Far from it, and I’m sure he knows that, so perhaps this too was manipulative. Fauci intimates that COVID herd immunity must look something like herd immunity to the measles, which is laughable. Measles is a viral infection primarily in children, among whom there is little if any pre-immunity. The measles vaccine (MMR) is administered to young children along with occasional boosters for some individuals. Believe it or not, Fauci claims that he rationalized a requirement of 85% vaccination for COVID by discounting a 90% requirement for the measles! Really???

In fact, there is substantial acquired pre-immunity to COVID. A meaningful share of the population has long-memory, cross-reactive T-cells from earlier exposure to coronaviruses such as the common cold. Estimates range from 10% to as much as 50%. So if we stick with Fauci’s 85% herd immunity “guesstimate”, 25% pre-immunity implies that vaccinating only 60% of the population would get us to Fauci’s herd immunity goal. (Two qualifications: 1) the vaccines aren’t 100% effective, so it would take more than 60% vaccinated to offset the failure rate; 2) the pre-immune might not be identifiable at low cost, so there might be significant overlap between the pre-immune and those vaccinated.)

Conceptual Confusion

Vaccinations approaching 85% would be an extremely ambitious goal, especially if it is recommended annually or semi-annually. It would be virtually impossible without coercion. While more than 91% of children are vaccinated for measles in the U.S., it is not annual. Thus, measles does not offer an appropriate model for thinking about herd immunity to COVID. Less than half of adults get a flu shot each year, and somewhat more children.

Fauci’s reference to 85% – 90% total immunity is different from the concept of the herd immunity threshold (HIT) in standard epidemiological models. The HIT, often placed in the range of 60% – 70%, is the point at which new infections begin to decline. More infections occur above the HIT but at a diminishing rate. In the end, the total share of individuals who become immune due to exposure, pre-immunity or vaccination will be greater than the HIT. The point is, however, that reaching the HIT is a sufficient condition for cases to taper and an end to a contagion. If we use 65% as the HIT and pre-immunity of 25%, only 40% must be vaccinated to reach the HIT.

Heterogeneity

A recent innovation in epidemiological models is the recognition that there are tremendous differences between individuals in terms of transmissibility, pre-immunity, and other factors that influence the spread of a particular virus, including social and business arrangements. This kind of heterogeneity tends to reduce the effective HIT. We’ve already discussed the effect of pre-immunity. Suppose that certain individuals are much more likely to transmit the virus than others, like so-called super-spreaders. They spur the initial exponential growth of a contagion, but there are only so many of them. Once infected, no one else among the still-susceptible can spread the virus with the same force.

Researchers at the Max Planck Institute (and a number of others) have gauged the effect of introducing heterogeneity to standard epidemiological models. It is dramatic, as the following chart shows. The curves simulate a pandemic under different assumptions about the degree of heterogeneity. The peak of these curves correspond to the HIT under each assumption (R0 refers to the initial reproduction number from infected individuals to others).

Moderate heterogeneity implies a HIT of only 37%. Given pre-immunity of 25%, only an additional 12% of the population would have to be infected or vaccinated to prevent a contagion from gaining a foothold for the initial exponential stage of growth. Fauci’s herd immunity figure obviously fails to consider the effect of heterogeneity.

How Close To the HIT?

We’re not as far from HITs as Fauci might think, and a vaccination goal of 85% is absurd and unnecessary. The seasonal COVID waves we’ve experienced thus far have faded over a period of 10-12 weeks. Estimates of seroprevalence in many localities reached a range of 15% – 25% after those episodes, which probably includes some share of those with pre-immunity. To reach the likely range of a HIT, either some additional pre-immunity must have existed or the degree of heterogeneity must have been large in these populations.

But if that’s true, why did secondary waves occur in the fall? There are a few possibilities. Of course, some areas like the upper Midwest did not experience the springtime wave. But in areas that suffered a recurrance, perhaps the antibodies acquired from infections did not remain active for as long as six months. However, other immune cells have longer memories, and re-infections have been fairly rare. Another possibility is that those having some level of pre-immunity were still able to pass live virus along to new hosts. But this vector of transmission would probably have been quite limited. Pre-immunity almost surely varies from region to region, so some areas were not as firmly above their HITs as others. It’s also possible that infections from super-spreaders were concentrated within subsets of the population even within a given region, in certain neighborhoods or among some, but not all, social or business circles. Therefore, some subsets or “sub-herds” achieved a HIT in the first wave, but it was unnecessary for other groups. In other words, sub-herds spared in the first wave might have suffered a contagion in a subsequent wave. And again, reinfections seem to have been rare. Finally, there is the possibility of a reset in the HIT in the presence of a new, more transmissible variant of the virus, as has become prevalent in the UK, but that was not the case in the fall.

Fragility

Tyler Cowen has mentioned another possible explanation: so-called “fragile” herd immunity. The idea is that any particular HIT is dependent on the structure of social relations. When social distancing is widely practiced, for example, the HIT will be lower. But if, after a contagion recedes, social distancing is relaxed, it’s possible that the HIT will take a higher value at the onset of the next seasonal wave. Perhaps this played a role in the resurgence in infections in the fall, but the HIT can be reduced via voluntary distancing. Eventually, acquired immunity and vaccinations will achieve a HIT under which distancing should be unnecessary, and heterogeneity suggests that shouldn’t be far out of reach.

Conclusion

Anthony Fauci has too often changed his public pronouncements on critical issues related to management of the COVID pandemic. Last February he said cruises were fine for the healthy and that most people should live their lives normally. Oops! Then came his opinion on the limited effectiveness of masks, then a shift to their necessity. His first position on masks has been called a “noble lie” intended to preserve supplies for health care workers. However, Fauci was probably repeating the standing consensus at that point (and still the truth) that masks are of limited value in containing airborne pathogens.

This time, Fauci admitted to changing his estimate of “herd immunity” in response to public opinion, a pathetic approach to matters of public health. What he called herd immunity was really an opinion about adequate levels of vaccination. Furthermore, he neglected to consider other forms of immunity: pre-existing and already acquired. He did not distinguish between total immunity and the herd immunity threshold that should guide any discussion of pandemic management. He also neglected the significant advances in epidemiological modeling that recognize the reality of heterogeneity in reducing the herd immunity threshold. The upshot is that far fewer vaccinations are needed to contain future waves of the pandemic than Fauci suggests.

On COVID, NPIs, and “Human” Data Points

24 Tuesday Nov 2020

Posted by Nuetzel in Lockdowns, Pandemic, Public Health

≈ 1 Comment

Tags

Alzheimer's, Anthony Fauci, Asymptomatic Carriers, Cancer, CDC, Centers for Disease Control, Covid-19, Dementia, Domestic Abuse, Education, HIV, Human Costs, Journal of the American Medical Association, Lancet, Lockdowns, Malaria, Malignant Neoplasms, Mandates, Masks, Public Health, Robert Redfield, SAAAD, SARS-CoV-2, Starvation, Suicide, The Ethical Skeptic, Tuberculoosis, Tyler Cowen, United Nations, Vitamin D

The other day a friend told me “your data points always seem to miss the people points.” He imagines a failure on my part to appreciate the human cost of the coronavirus. Evidently, he feels that I treat data on cases, hospitalizations, and deaths as mere accounting issues, all while emphasizing the negative aspects of government interventions.

This fellow reads my posts very selectively, hampered in part by his own mood affiliation. Indeed, he seems to lack an appreciation for the nuance and zeitgeist of my body of blogging on the topic… my oeuvre! This despite his past comments on the very things he claims I haven’t mentioned. His responses usually rely on anecdotes relayed to him by nurses or doctors he knows. Anecdotes can be important, of course. But I know nurses and doctors too, and they are not of the same mind as his nurses and doctors. Anecdotes! We’re talking about the determination of optimal policy here, and you know what Dr. Fauci says about relying on anecdotes!

Incremental Costs and Benefits

My friend must first understand that my views are based on an economic argument, one emphasizing the benefits and costs of particular actions, including human costs. COVID is dangerous, but primarily to the elderly, and no approach to managing the virus is free. Here are two rather disparate choices:

Mandated minimization of economic and social interactions throughout society over some time interval in the hope of reducing the spread of the virus;
Laissez faire for the general population while minimizing dangers to high-risk individuals, subject to free choice for mentally competent, high-risk individuals.

To be clear, #2 entails all voluntary actions taken by individuals to mitigate risks. Therefore, #1 implies a set of incremental binding restrictions on behavior beyond those voluntary actions. However, I also include in #1 the behavioral effects of scare mongering by public officials, who regularly issue pronouncements having no empirical basis.

The first option above entails so-called non-pharmaceutical interventions (NPIs) by government. These are the elements of so-called lockdowns, such as quarantines and other restrictions on mobility, business and consumer activity, social activities, health care activities, school closures, and mask mandates. NPIs carry costs that are increasing in the severity of constraints they impose on society.

And before I proceed, remember this: tallying all fatal COVID cases is really irrelevant to the policy exercise. Nothing we do, or could have done, would save all those lives. We should compare what lives can be saved from COVID via lockdowns, if any, with the cost of those lockdowns in terms of human life and human misery, including economic costs.

Economic Losses

NPIs involve a loss of economic output that can never be recovered… it is gone forever, and a loss is likely to continue for some time to come. That sounds so very anodyne, despite the tremendous magnitude of the loss involved. But let’s stay with it for just a second. The loss of U.S. output in 2020 due to COVID has been estimated at $2.5 trillion. As Don Boudreaux and Tyler Cowen have noted, what we normally spend on safety and precautionary measures (willingness-to-pay), together with the probabilities of losses, implies that we value our lives at less than $4 million on average. Let’s say the COVID death toll reaches 300,000 by year-end (that’s incremental in this case— but it might be a bit high). That equates to a total loss of $1.2 trillion in life-value if we ignore distinctions in life-years lost. Now ask this: if our $2.5 trillion output loss could have saved every one of those 300,000 lives, would it have been worth it? Not even close, and the truth is that the sacrifice will not have saved even a small fraction of those lives. I grant, however, that the economic losses are partly attributable to voluntary decisions, but goaded to a great extent by the alarmist commentary of public health officials.

The full depth of losses is far worse than the dollars and cents comparison above might sound. Output losses are always matched by (and, in value, are exactly the same as) income losses. That involves lost jobs, lost hours, failed businesses, and destroyed careers. Ah, now we’re getting a bit more “human”, aren’t we! It’s nothing short of callous to discount these costs. Unfortunately, the burden falls disproportionately on low-income workers. Our elites can mostly stay home and do their jobs remotely, and earn handsome incomes. The working poor spend their time in line at food banks.

Yes, government checks can help those with a loss of income compete with elites for the available supply of goods, but of course that doesn’t replace the lost supply of goods! Government aid of this kind is a palliative measure; it doesn’t offset the real losses during a suspension of economic activity.

Decimated Public Health

The strain of the losses has been massive in the U.S. and nearly everywhere in the world. People are struggling financially, making do with less on the table, depleting their savings, and seeking forbearance on debts. The emotional strains are no less real. Anxiety is rampant, drug overdoses have increased, calls to suicide hotlines have exploded, and the permanence of the economic losses may add to suicide rates for some time to come. Dr. Robert Redfield of the CDC says more teenagers will commit suicide this year than will die from COVID (also see here). There’s also been a terrifying escalation in domestic abuse during the pandemic, including domestic homicide. The despair caused by economic losses is all too real and should be viewed as a multiplier on the total cost of severe NPIs.

More on human costs: a health care disaster has befallen locked-down populations, including avoidance of care on account of panic fomented by so-called public health experts, the media, and government. Some of the consequences are listed here. But to name just a few, we have huge numbers of delayed cancer diagnoses, which sharply decrease survival time; mass avoidance of emergency room visits, including undiagnosed heart attacks and strokes; and unacceptable delays in cardiac treatments. Moreover, lockdowns worldwide have severely damaged efforts to deal with scourges like HIV, tuberculosis, and malaria.

The CDC reports that excess mortality among 25-44 year-olds this year was up more than 26%, and the vast bulk of these were non-COVID deaths. A Lancet study indicates that a measles outbreak is likely in 2021 due to skipped vaccinations caused by lockdowns. The WHO estimates that 130,000,000 people are starving worldwide due to lockdowns. That is roughly the population of the U.S. east coast. Again, the callousness with which people willfully ignore these repercussions is stunning, selfish and inhumane, or just stupid.

Excess Deaths

Can we quantify all this? Yes we can, as a matter of fact. I’ve offered estimates in the past, and I already mentioned that excess deaths, COVID and non-COVID, are reported on the CDC’s web site. The Ethical Skeptic (TES) does a good job of summarizing these statistics, though the last full set of estimates was from October 31. Here is the graphic from the TES Twitter feed:

Note particularly the huge number of excess deaths attributable to SAAAD (Suicide, Addiction Abandonment, Abuse and Despair): over 50,000! The estimate of life-years lost due to non-COVID excess deaths is almost double that of COVID deaths because of the difference in the age distributions of those deaths.

Here are a few supporting charts on selected categories of excess deaths, though they are a week behind the counts from above. The first is all non-COVID, natural-cause excess deaths (the vertical gap between the two lines), followed by excess deaths from Alzheimer’s and dementia, other respiratory diseases, and malignant neoplasms (cancer):

The clearest visual gap in these charts is the excess Alzheimer’s and dementia deaths. Note the increase corresponding to the start of the pandemic, when these patients were suddenly shut off from loved ones and the company of other patients. I also believe some of these deaths were (and are) due to overwhelmed staff at care homes struck by COVID, but even discounting this category of excess deaths leaves us with a huge number of non-COVD deaths that could have been avoided without lockdowns. This represents a human cost over and above those tied to the economic losses discussed earlier.

Degraded Education and Health

Lockdowns have also been destructive to the education of children. The United Nations has estimated that 24 million children may drop out of school permanently as a result of lockdowns and school closures. This a burden that falls disproportionately on impoverished children. This article in the Journal of the American Medical Association Network notes the destructive impact of primary school closures on educational attainment. Its conclusions should make advocates of school closures reconsider their position, but it won’t:

“… missed instruction during 2020 could be associated with an estimated 5.53 million years of life lost. This loss in life expectancy was likely to be greater than would have been observed if leaving primary schools open had led to an expansion of the first wave of the pandemic.“

Lockdown Inefficacy

Lockdowns just don’t work. There was never any scientific evidence that they did. For one thing, they are difficult to enforce and compliance is not a given. Of course, Sweden offers a prime example that draconian lockdowns are unnecessary, and deaths remain low there. This Lancet study, published in July, found no association between lockdowns and country mortality, though early border closures were associated with lower COVID caseloads. A French research paper concludes that public decisions had no impact on COVID mortality across 188 countries, U.S. states, and Chinese states. A paper by a group of Irish physicians and scientists stated the following:

“Lockdown has not previously been employed as a strategy in pandemic management, in fact it was ruled out in 2019 WHO and Irish pandemic guidelines, and as expected, it has proven a poor mitigator of morbidity and mortality.”

One of the chief arguments in favor of lockdowns is the fear that asymptomatic individuals circulating in the community (and there are many) would spread the virus. However, there is no evidence that they do. In part, that’s because the window during which an individual with the virus is infectious is narrow, but tests may detect tiny fragments of the virus over a much longer span of time. And there is even some evidence that lockdown measures may increase the spread of the virus!

Lockdown decisions are invariably arbitrary in their impact as well. The crackdown on gyms is one noteworthy example, but gyms are safe. Restaurants don’t turn up in many contact traces either, and yet restaurants have been repeatedly implicated as danger zones. And think of the many small retailers shut down by government, while giant competitors like Wal-Mart continue to operate with little restriction. This is manifest corporatism!

Then there is the matter of mask mandates. As readers of this blog know, I think masks probably help reduce transmission from droplets issued by a carrier, that is, at close range. However, this recent Danish study in the Annals of Internal Medicine found that cloth masks are ineffective in protecting the wearer. They do not stop aerosols, which seem to be the primary source of transmission. They might reduce viral loads, at least if worn properly and either cleaned often or replaced. Those are big “ifs”.

To the extent that masks offer any protection, I’m happy to wear them within indoor public accommodations, at least for the time being. To the extent that people are “scared”, I’m happy to observe the courtesy of wearing a mask, but not outside in uncrowded conditions. To the extent that masks are required under private “house rules”, of course I comply. Public mask mandates outside of government buildings are over the line, however. The evidence that those mandates work is too tenuous and our liberties are too precious too allow that kind of coercion. And private facilities should be subject to private rules only.

QED

So my poor friend is quite correct that COVID is especially deadly to certain cohorts and challenging for the health care community. But he must come to grips with a few realities:

The virus won’t be defeated with NPIs; they don’t work!
NPIs inflict massive harm to human well-being.
Lockdowns or NPIs are little or no gain, high-pain propositions.

The rejection of NPI’s, or lockdowns, is based on compelling “human” data points. As Don Boudreaux says:

“The lockdowns and other restrictions on economic and social activities are astronomically costly – in a direct economic sense, in an emotional and spiritual sense, and in a ‘what-the-hell-do-these-arbitrary-diktats-portend-for-our-freedom?’ sense.”

This doctor has a message for the those denizens of social media with an honest wish to dispense helpful public health advice:

“Americans have admitted that they will meet for Thanksgiving. Scolding and shaming them for wanting this is unlikely to slow the spread of SARS-CoV-2, though it may earn you likes and retweets. Starting with compassion, and thinking of ways they can meet, but as safely as possible, is the task of real public health. Now is the time to save public health from social media.”

And take some Vitamin D!

Union Control, Shuttered Schools, COVID Risk

07 Monday Sep 2020

Posted by Nuetzel in Coronavirus, Education, Unions

≈ Leave a comment

Tags

Christos Makridis, Corey DeAngelis, Covid-19, K-12 education, Public Employee Unions, Public Schools, Right to Work, School Closures, Teachers Unions, Tyler Cowen, Virtual Classrooms

Public schools are closed in favor of virtual classrooms in some areas. Elsewhere, however, schools have physically reopened to the children of willing parents. It should be no surprise that the varying strength of teachers’ unions has a lot to do with these decisions. One cannot claim that the pattern of closures is a response to varying levels of COVID risk, as there is no geographic association between the closures and COVID cases or deaths. The shame of it is that closures compromise learning and also have destructive effects on local labor markets and the ability of parents to earn incomes.

That unions play this role, often decisively, is shown in a new paper entitled “Are School Reopening Decisions Related to Union Influence?“, by Corey DeAngelis and Christos Makridis (HT: Tyler Cowen). The authors examine the fall reopening decisions of 835 school districts and find that “… districts in locations with stronger teachers’ unions are less likely to reopen in person…“. The authors test four different measures of union strength with similar findings. They also rule out potential confounding influences like voting patterns.

Shall we defend the unions for protecting their members from excessive risk? Well, another important finding reported by the authors won’t surprise anyone having the least familiarity with data on C19 risks:

“We also do not find evidence to suggest that measures of COVID-19 risk are correlated with school reopening decisions.”

Few children catch the virus and children are not effective at transmitting C19 to their peers, teachers, and parents. Furthermore, schools closed to in-person learning are not located in areas at elevated risk relative to those remaining open.

The role of teachers’ unions in school reopening decisions is a textbook case of the inadvisability of unionized public employees. Most obviously, it is in their interests to encourage greater funding and taxes. This is but one of many dimensions of the political agendas that teachers’ unions may advance, and to which member dues are put. These are not always representative of members’ views, which is especially problematic in states without right-to-work laws.

The very nature of public service means that the work of public employees (or its absence) has profound external influences on the community at large. The unions are not shy about using this power as leverage in negotiations. Thus, teachers’ unions often act as adversaries not only to taxpayers, but to parents, children, and the business community.

Do public school administrators and elected school board members belong on the list of union adversaries as well? Perhaps: the unions have bullied school districts and have made them less attractive as educational institutions in a cost-benefit sense. In the present case, the unions have successfully lobbied for ongoing payments of income and benefits to their members despite the degraded effectiveness of on-line instruction for many K-12 students. Meanwhile, many parents are learning to exercise choice in the matter by abandoning public schools in favor of private alternatives.

Risk Realism, COVID Hysteria

29 Wednesday Jul 2020

Posted by Nuetzel in Uncategorized

≈ 1 Comment

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All-Cause Mortality, American Academy of Pediatrics, American Association of Sciences, Asian Flu, Covid-19, David Zaruk, Engineering and Medicine, Hydroxychloraquine, Infection Fatality Rate, Mollie Hemingway, Precautionary Principle, Spanish Flu, The Risk Monger, Tyler Cowen, Wired

Perhaps life in a prosperous society has sapped our ability and willingness to face risks. This tendency undermines that very prosperity, however. If we ever needed an illustration, the hysteria surrounding COVID-19 surely provides it. Do we really know how to exist in a world with risk anymore? During this episode, the media, public officials, and much of the public have completely lost their bearings with respect to the evaluation of risk, acting as if they are entitled to a zero-risk existence. Of course, COVID-19 is highly transmissible and dangerous for certain segments of the population, but it is rather benign for most people.

Perspective On C19 Risks

Just for starters, the table at the top of this post (admittedly not particularly well organized) shows calculations of odds from the CDC. These odds might well overstate the risks of both C19 and the flu, as they probably don’t account well for the huge number of asymptomatic cases of both viruses.

Another glimpse of reality is offered by a recent Swiss study showing the C19 infection mortality rate (IFR) by age, shown below. You can find a number of other charts on-line that show the same pattern: If you’re less than 50 years old, your risk of death from C19 is quite slim. Even those 50-64 years of age don’t face a substantial mortality risk, though it’s obviously higher for individuals having co-morbidities. These IFRs are lower than all-cause mortality for younger cohorts, but higher for older cohorts.

And here are a few other facts to put the risks of C19 in perspective:

The current pandemic is relatively benign: thus far, the U.S. has suffered a total of about 145,000 deaths, or 440 per million of population;
the Asian Flu of 1957-58 took 116,000, according to the CDC, or 674 per million;
the Spanish Flu of 1917-18 took 675,000 U.S lives, or 6,553 per million.

It should be obvious that these risks, while new and elevated for some, are not of such outrageous magnitude that they can’t be managed without bringing life to a grinding halt. That’s especially true when so-called safety measures entail substantial health risks of their own, as I have emphasized elsewhere (and here).

The Schools

Nothing illustrates our inability to assess risks better than the debate over reopening schools. This article in Wired is well-balanced on the safety issue. It emphasizes that there is little risk to teachers, students, or their families from opening schools if reasonable safety measures are taken.

Children of pre-school and elementary school age do not contract the virus readily, do not transmit the virus readily, and do not readily succumb to its effects. This German study on elementary schools demonstrates the safety of reopening. It is similar to the experience of other EU countries that have reopened schools. This article reinforces that point, but it emphasizes measures to limit any flare-ups that might arise. And while it singles out Israel as an example of poor execution, it fails to offer any evidence on the severity of infections.

Furthermore, we should not overlook the destructive effects of denying in-classroom learning to children. They simply don’t learn as well on-line, especially students who struggle. There are also the devastating social-psychological effects of the isolation experienced by many elementary school children during extended school closures. This is of a piece with the significant risks of lockdowns to well being. Perhaps not well known is that schooling is positively correlated with life expectancy: this study found that a one-year reduction in years of schooling is associated with a reduction in life expectancy of 0.6 years!

It’s true that children older than 10 might pose somewhat greater risks for C19 contagion, but those risks are manageable via hygiene, distancing, and other mitigations including hydroxychloraquine or other prophylaxes against infection for teachers who desire it. Capacity limitations might well require a temporary mix of online and in-school learning, but at least part-time attendance at brick-and-mortar schools should remain the centerpiece.

As Tyler Cowen points out, teenagers are less likely to remain isolated from others during school closures, so their behavior might be more difficult to manage. It’s quite possible they could be more heavily exposed outside of school, hanging out with friends, than in the classroom. This illustrates how our readiness to demure from absolute risk often ignores the pertinent question of relative risk.

Judging by reactions on social media, people are so frightened out of their wits that they cannot put these manageable risks in perspective. But here is a statement from the American Academy of Pediatrics. And here is a statement from the American Association of Sciences, Engineering and Medicine. They speak for themselves.

Excessive Precautionary Putzery

Our reaction to C19 amounts to a misapplication of the precautionary principle (PP), which states, quite reasonably, that precautionary measures must be invoked when faced with a risk that is not well understood. Risk must be managed! But what are those precautions and on what basis should benefits we forego via mitigation be balanced against quantifiable risks. That was one theme of my post “Precaution Forbids Your Rewards” several years back. Ralph B. Alexander discusses the PP, noting that the construct is vulnerable to political manipulation. It is, unfortunately, a wonderful devise for opportunistic interest groups and interventionist politicians. See something you don’t like? Identify a risk you can use to frighten the public. Use any anecdotal evidence you can scrape together. Start a movement and put a stop to it!

That really doesn’t help us deal with risk in a productive way. Do we understand that well being generally is enhanced by our willingness to incur and manage risks? As David Zaruk, aka, the Risk Monger, says, “our reliance of the precautionary principle has ruined our ability to manage risk.”:

“Two decades of the precautionary principle as the key policy tool for managing uncertainties has neutered risk management capacities by offering, as the only approach, the systematic removal of any exposure to any hazard. As the risk-averse precautionary mindset cements itself, more and more of us have become passive docilians waiting to be nannied. We no longer trust and are no longer trusted with risk-benefit choices as we are channelled down over-engineered preventative paths. While it is important to reduce exposure to risks, our excessively-protective risk managers have, in their zeal, removed our capacity to manage risks ourselves. Precaution over information, safety over autonomy, dictation over accountability.”

To quote Mollie Hemingway, in the case of the coronavirus, Americans are “reacting like a bunch of hysterics“.

Central Planning With AI Will Still Suck

23 Sunday Feb 2020

Posted by Nuetzel in Artificial Intelligence, Central Planning, Free markets

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Artificial Intelligence, central planning, Common Law, Data Science, Digital Socialism, Friedrich Hayek, Jesús Fernández-Villaverde, Machine Learning, Marginal Revolution, Property Rights, Robert Lucas, Roman Law, Scientism, The Invisible Hand, The Knowledge Problem, The Lucas Critique, Tyler Cowen

Artificial intelligence (AI) or machine learning (ML) will never make central economic planning a successful reality. Jesús Fernández-Villaverde of the University of Pennsylvania has written a strong disavowal of AI’s promise in central planning, and on the general difficulty of using ML to design social and economic policies. His paper, “Simple Rules for a Complex World with Artificial Intelligence“, was linked last week by Tyler Cowen at Marginal Revolution. Note that the author isn’t saying “digital socialism” won’t be attempted. Judging by the attention it’s getting, and given the widespread acceptance of the scientism of central planning, there is no question that future efforts to collectivize will involve “data science” to one degree or another. But Fernández-Villaverde, who is otherwise an expert and proponent of ML in certain applications, is simply saying it won’t work as a curative for the failings of central economic planning — that the “simple rules” of the market will aways produce superior social outcomes.

The connection between central planning and socialism should be obvious. Central planning implies control over the use of resources, and therefore ownership by a central authority, whether or not certain rents are paid as a buy-off to the erstwhile owners of those resources. By “digital socialism”, Fernández-Villaverde means the use of ML to perform the complex tasks of central planning. The hope among its cheerleaders is that adaptive algorithms can discern the optimal allocation of resources within some “big data” representation of resource availability and demands, and that this is possible on an ongoing, dynamic basis.

Fernández-Villaverde makes the case against this fantasy on three fronts or barriers to the use of AI in policy applications: data requirements; the endogeneity of expectations and behavior; and the knowledge problem.

The Data Problem: ML requires large data sets to do anything. And impossibly large data sets are required for ML to perform the task of planning economic activity, even for a small portion of the economy. Today, those data sets do not exist except in certain lines of business. Can they exist more generally, capturing the details of all economic transactions? Can the data remain current? Only at great expense, and ML must be trained to recognize whether data should be discarded as it becomes stale over time due to shifting demographics, tastes, technologies, and other changes in the social and physical environment.

Policy Change Often Makes the Past Irrelevant: Planning algorithms are subject to the so-called Lucas Critique, a well known principle in macroeconomics named after Nobel Prize winner Robert Lucas. The idea is that policy decisions based on observed behavior will change expectations, prompting responses that differ from the earlier observations under the former policy regime. A classic case involves the historical tradeoff between inflation and unemployment. Can this tradeoff be exploited by policy? That is, can unemployment be reduced by a policy that increases the rate of inflation (by printing money at a faster rate)? In this case, the Lucas Critique is that once agents expect a higher rate of inflation, they are unlikely to confuse higher prices with a more profitable business environment, so higher employment will not be sustained. If ML is used to “plan” certain outcomes desired by some authority, based on past relationships and transactions, the Lucas Critique implies that things are unlikely to go as planned.

The Knowledge Problem: Not only are impossibly large data sets required for economic planning with ML, as noted above. To achieve the success of markets in satisfying unlimited wants given scarce resources, the required information is impossible to collect or even to know. This is what Friedrich Hayek called the “knowledge problem”. Just imagine the difficulty of arranging a data feed on the shifting preferences of many different individuals across a huge number of products, services and they way preference orderings will change across the range of possible prices. The data must have immediacy, not simply a historical record. Add to this the required information on shifting supplies and opportunity costs of resources needed to produce those things. And the detailed technological relationships between production inputs and outputs, including time requirements, and the dynamics of investment in future productive capacity. And don’t forget to consider the variety of risks agents face, their degree of risk aversion, and the ways in which risks can be mitigated or hedged. Many of these things are simply unknowable to a central authority. The information is hopelessly dispersed. The task of collecting even the knowable pieces is massive beyond comprehension.

The market system, however, is able to process all of this information in real time, the knowable and the unknowable, in ways that balance preferences with the true scarcity of resources. No one actor or authority need know it all. It is the invisible hand. Among many other things, it ensures the deployment of ML only where it makes economic sense. Here is Fernández-Villaverde:

“The only reliable method we have found to aggregate those preferences, abilities, and efforts is the market because it aligns, through the price system, incentives with information revelation. The method is not perfect, and the outcomes that come from it are often unsatisfactory. Nevertheless, like democracy, all the other alternatives, including ‘digital socialism,’ are worse.”

Later, he says:

“… markets work when we implement simple rules, such as first possession, voluntary exchange, and pacta sunt servanda. This result is not a surprise. We did not come up with these simple rules thanks to an enlightened legislator (or nowadays, a blue-ribbon committee of academics ‘with a plan’). … The simple rules were the product of an evolutionary process. Roman law, the Common law, and Lex mercatoria were bodies of norms that appeared over centuries thanks to the decisions of thousands and thousands of agents.”

These simple rules represent good private governance. Beyond reputational enforcement, the rules require only trust in the system of property rights and a private or public judicial authority. Successfully replacing private arrangements in favor of a central plan, however intricately calculated via ML, will remain a pipe dream. At best, it would suspend many economic relationships in amber, foregoing the rational adjustments private agents would make as conditions change. And ultimately, the relationships and activities that planning would sanction would be shaped by political whim. It’s a monstrous thing to contemplate — both fruitless and authoritarian.

3 Cheers, No Tears for Strike on Master of Iranian Terror

08 Wednesday Jan 2020

Posted by Nuetzel in Middle East, War

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AL Monitor, Al-Quds, Anderson Cooper, Avi Melamed, Bloomberg, Charles De Gaulle, Decapitation, Deterrence, Donald Trump, Iran, Iranian Mullah Regime, Iraq, Kataeb Hezbollah, Politico, Qassim Soleimani, Regime Change, Retaliation, Reuters, Saudi Arabia, Self-Defense, Syria, Terrorism, Tyler Cowen, Victor Davis Hanson, World War III

Note: As I finish this post, Iran has fired missiles at U.S. bases in Iraq, so we know a bit more about their response to the killing of Qassim Soleimani. Tonight’s response by Iran looks to have been impotent. There are risks of other kinds of action, of course. We shall see.

Last week’s killing of Iranian General Qassim Soleimani was not prompted solely by the attack on the U.S. embassy in Iraq by Kataeb Hezbollah, the Iranian-backed militia. Iran, perhaps the largest state-sponsor of terrorism in the world, has been guilty of provocation and aggression in Iraq, Syria, Saudi Arabia and elsewhere under Soleimani’s direction for many years. And he was reviled for his ruthless treatment of protestors within Iran’s borders. In recent weeks there had been a series of rocket attacks on U.S. bases, and there was “chatter” that much more was planned. It’s been noted that the presence of so-many high-level officials in one place at the time of the attack on Soleimani indicated that something big was in the works. This Reuters article gives some insight into Soleimani’s suspicious activities in the weeks prior to his death, of which the U.S. was surely aware. While the attack on the U.S. embassy provided additional pretext (as if it was needed), all of this indicates that Soleimani’s assassination was not an impulsive decision, but deliberated, contrary to assertions by critics of President Trump’s decision to act. It was both retaliatory and preemptive. Soleimani’s travels and whereabouts were well known, and it’s highly likely that a “decapitation” had been planned as a contingency for some time. This report in Politico provides details of the decision making leading up to the strike. The attack was executed brilliantly by all accounts.

The U.S. had retaliated to earlier rocket attacks with strikes against Kataeb Hezbollah positions. That the strike on Soleimani was more than retaliation and an act of self-defense against additional threats is, I believe, the flaw in arguments against the strike like the one Tyler Cowen seemed to make in Bloomerg (though his main point was different). The value of the strike goes far beyond retaliation. This was not intended to be another volley in an ongoing series of “tits-for-tats”.

In addition to Soleimani, several other high-level Iranian military personnel were killed. This undoubtedly disrupted plans that would have threatened U.S. soldiers and assets, yet some describe the strike as an “impulsive” act on Trump’s part, and an “act of war”, as if unprovoked. And as if Iran had not been warring on the U.S. for the past 40 years. What to make of those who take this position? Of course, most are reflexively anti-Trump, refusing to evaluate the decision on it’s own merits. They pretend that Soleimani and the Iranian overseers of the stooge government in Iraq have legitimacy. Anderson Cooper actually compared Soleimani to Charles De Gaulle. It would be more accurate to compare him to the murderous Che Guevara, but then again, many on the Left worship Che’s memory as well! These fools will tell you that Soleimani was “worshipped” in Iran. In fact, there are a great many Iranians who are quietly celebrating his death.

Middle East analyst Avi Melamed does not mince words in describing the impact Soleimani has had on the Middle East (emphasis his):

“Some argue that the assassination of Soleimani will increase tensions in the Middle East. This outlook confuses cause and effect: Tensions in the Middle East have intensified over the past decade because of the violent Iranian aggression which Soleimani spearheaded. Aggression which has led to Syria’s destruction and the disintegration of Lebanon and Iraq. Aggression that threatens maritime routes and safe passage in the Arab (Persian) Gulf and the Red Sea, a direct attack on Saudi Arabia’s oil facilities that spiked oil prices and compromised the world’s oil supply. Aggression that has fueled and intensified tensions – including direct military confrontations – between Iran and its proxies and Israel.

General Soleimani and the Al-Quds force led the escalation in the region in the service of the hegemonic vision of the Iranian Mullah regime. Their actions have so far claimed the lives of hundreds of thousands of people, led to the destruction of states, the disintegration of cities, and caused a wave of millions of refugees. Killing Soleimani is not the cause of the escalation – but the result.”

Malamed expected Iran to take retaliatory actions in Iraq, where it already has a strong military presence and good reconnaissance. Missiles have now been fired at U.S. bases from Iran (as of tonight), but with few or no casualties. It remains to be seen how effective a response the Iranians can mount. Any short-term U.S. casualties should probably not be viewed as incremental, given the high likelihood of casualties had Soleimani lived. Perhaps Iran will fire missiles at Israel from western Iraq or Syria, or at Saudi Arabian oil assets, as it did last September. Or it might make a bold military intervention in Iraq to strengthen its control there, which Iran considers crucial to its own security.

Al Monitor believes the assassination “leaves Iran with very few options to retaliate” with any strength, at least in the short-run:

“… the economic hardship in Iran — in addition to the challenges the government is facing internally — would not allow Tehran to increase the tension. Iran’s past conduct against Israel strikes on Iranian bases in Syria also shows it will not seek revenge if its national security and interests are in danger. … This all indicates that Iran and its proxies in the region most likely would not seek revenge in the near future and — in regard to Iraq, in particular — would not lead Iraq to fall into a civil war or mass destruction, because it would lose even more in Iraq if it takes such a risk.”

So despite the brash talk, Iran is weak and spread thin across commitments outside its borders, and the regime has real fear of retaliation by its enemies that can only have been reinforced by the strike against Soleimani. Of what other retaliatory actions is Iran capable, assuming the regime can survive in the longer run? And assuming the Mullah regime itself is willing to take existential risks? It has threatened actions against civilians in the West. Can it bring down planes? Can it bomb targets in the U.S.? Can it develop or buy a small nuclear device? It can try any of those things, of course, but with uncertain odds and with risks it might not want to take. Survival is of the utmost importance to the regime, and it is already on shaky ground.

Trump’s critics claim that he authorized the “decapitation” without a plan for its aftermath. Trump has made clear his intent to “punch back twice as hard”, as it were, in response to any additional force from Iran. This is, first and foremost, a game of deterrence. Beyond that, however, and despite talk of “changing the Iranian regime’s behavior”, it appears that the larger plan pursued by Trump is to continue undermining the regime with sanctions and targeted strikes, if necessary. “Maximum pressure”. But there will be no World War III. The markets seem pretty comfortable about that as well, including the oil market.

I do take issue with Trump’s mention of the possibility of striking “cultural sites” in Iran, though he seems to have retracted it. On that point, however, I fully agree with Tyler Cowan (linked above). The only plausible rationale for such a statement is to frighten Iran’s leadership, especially if it has located military and intelligence functions within cultural sites.

Trump still maintains that our ultimate goal should be withdrawal from Iraq. That assumes stabilization in the region and fair elections, which would be well-served by a weaker Iran or a regime change there. As Victor Davis Hanson explains, the Middle East is of declining importance in world energy markets and trade generally. That’s one reason we’re unlikely to ever again send a huge ground force to the region, and it’s a good reason to scale back our presence in the Middle East generally.

Jordan Peterson Is Not Complacent

23 Tuesday Jan 2018

Posted by Nuetzel in Identity Politics, Individualism

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Dan Sanchez, Freedom of Expression, Human Action, Identity Politics, Individualism, Jordan Peterson, Noah Smith, rent seeking, Tyler Cowen, University of Toronto, White Privilege

It’s a hoot to watch Jordan Peterson ‘s videos — he stands before crowds doing … crisply-articulated philosophy, seemingly on the fly. He is an outspoken psychologist at the University of Toronto who covers a lot of intellectual ground with an impactful delivery. One of Peterson’s primary messages is so simple as to seem trite: take control of yourself, because you can and you should for your own sake and those around you! But his treatment is an empowering tonic for both men and women, and many are listening. He has toiled away as a professional psychologist, a professor, an author and a philosopher for many years; his ascent to notoriety has been recent and fairly meteoric. Luminaries like Tyler Cowen and Noah Smith now call Peterson one of the top public intellectuals in the western world.

However, Peterson takes positions that are seemingly hard for the Left to swallow: he believes in the power of individual action; that freedom of expression is the basis of personal and academic freedom; that identity politics is destructive (whether on the Right or the Left); and that white privilege is a lie.

Predictably, the Left has attacked Peterson and attempted to characterize him as a spokesman for the far-right. He meets challenges of this kind with a kind of charged equanimity, exposing falsehoods with quick-footed logic, empirics, and honest reflection. Dan Sanchez has written a nice summary of the attacks on Peterson and shows them to be wholly without foundation. He has critics in both ends of the political spectrum, as Sanchez observes:

“[Far right] critics don’t understand what Peterson is saying, because they are mired in the mindsets of politics and war. The way of politics and war is to confront an enemy horde by amassing your own horde: whether it be on the battlefield, in street demonstrations, or in voting booths. It is to fight tribal barbarism by tending toward the tribal and the barbaric yourself. But the way of the heroic, civilized individual is to lead by example and to lead by appealing to the interests of those whose behavior you want to influence.”

And in Peterson’s own words, quoted by Sanchez, tribal barbarism is the way to social ruin:

“…where we’re making your group identity the most important thing about you. I think that’s reprehensible. I think it’s devastating. I think it’s genocidal in its ultimate expression. I think it will bring down our civilization if we pursue it. We shouldn’t be playing that game.“

On those assertions, Sanchez notes the following:

“… Peterson’s claim that identity politics is ‘genocidal in its ultimate expression’ is no exaggeration. Hitler’s military invasions and death camps were the ultimate expression of the racialist and nationalist identity politics that spiritually drove Nazism. And Stalin’s weaponized famines and ‘gulag archipelago’ were the ultimate expression of the class warfare identity politics that spiritually drove Soviet communism.”

So Peterson clearly condemns groupthink on both the Left and Right. He celebrates the value of people as individuals, and he urges us all to realize our value through individual responsibility and productive effort. Help yourself, help those you love, and help others. That’s a call to real human action, as distinct from the seeking of rents through the political process. Peterson is both a fascinating personality and thinker. His ideas and passion can be a powerful antidote to the complacency that plagues so many today. I hope he continues to gain prominence.

Sacred Cow Chips

Tag Archives: Tyler Cowen

No Radar, No Rudder: Fiscal & Monetary Destabilization

The Scary Progress and Hairy Promise of AI

Everything’s Big In Texas Except Surge Capacity

Fauci Flubs Herd Immunity

On COVID, NPIs, and “Human” Data Points

Union Control, Shuttered Schools, COVID Risk

Risk Realism, COVID Hysteria

Central Planning With AI Will Still Suck

3 Cheers, No Tears for Strike on Master of Iranian Terror

Jordan Peterson Is Not Complacent