Author Archives: Carl Shulman

The SAEE: who was right?

Bryan Caplan argues that economists mostly agree with one another, compared to the general public, and reports results from the Survey of Americans and Economists on the Economy (SAEE):

The leading correlates of economists’ disagreement are political-ideology and, to a lesser extent, party affiliation. Liberal Democratic and conservative Republican economists disagree in expected ways about taxes, regulation, excessive profits and executive pay, and some employment-related issues. Conservative economists are also markedly more optimistic about the country’s economic future. Note, however, that there is little evidence of an ideological divide over the economy’s past or present performance. Economists
across the political spectrum can largely agree about the path of inequality, real income, and real wages over the past two decades.

I don’t find agreement about the past very comforting: the point of economic advice is to deliver good consequences in the future. However, I would point out that disagreements about predictions are an opportunity for retrospective assessment. Indeed, when Bryan’s paper was published, in 2002, the 5 year timeline of the predictions had already come and gone. But there’s nothing stopping us from checking now. [Note, I prepared this post up until this point with the intention of posting it before peeking at the data.] Results below the fold.

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Future Filter Fatalism

One of the more colorful vignettes in philosophy is Gibbard and Harper’s “Death in Damascus” case:

Consider the story of the man who met Death in Damascus. Death looked surprised, but then recovered his ghastly composure and said, ‘I am coming for you tomorrow’. The terrified man that night bought a camel and rode to Aleppo. The next day, Death knocked on the door of the room where he was hiding, and said I have come for you’.

‘But I thought you would be looking for me in Damascus’, said the man.

‘Not at all’, said Death ‘that is why I was surprised to see you yesterday. I knew that today I was to find you in Aleppo’.

That is, Death’s foresight takes into account any reactions to Death’s activities.

Now suppose you think that a large portion of the Great Filter lies ahead, so that almost all civilizations like ours fail to colonize the stars. This implies that civilizations almost never adopt strategies that effectively avert doom and allow colonization. Thus the mere fact that we adopt any purported Filter-avoiding strategy S is strong evidence that S won’t work, just as the fact that you adopt any particular plan to escape Death indicates that it will fail.

To expect S to work we would have to be very confident that we were highly unusual in adopting S (or any strategy as good as S), in addition to thinking S very good on the merits. This burden might be met if it was only through some bizarre fluke that S became possible, and a strategy might improve our chances even though we would remain almost certain to fail, but common features, such as awareness of the Great Filter, would not suffice to avoid future filters.

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Breeding happier livestock: no futuristic tech required

[Edited to remove insensitive framing. Also, the possibility of reducing the misery in factory farming with such technology does not and would not justify factory farming.]

I have spoken with a lot of people who are enthusiastic about the possibility that advanced genetic engineering technologies will improve animal welfare.

But would it really take radical new technologies to produce genetics reducing animal suffering?

Modern animal breeding is able to shape almost any quantitative trait with significant heritable variation in a population. One carefully measures the trait in different animals, and selects sperm for the next generation on that basis. So far this has not been done to reduce animals’ capacity for pain as such, or to increase their capacity for pleasure, but it has been applied to great effect elsewhere on productivity (with some positive but overall negative effects on welfare).

One could test varied behavioral measures of fear response, and physiological measures like cortisol levels, and select for them. As long as the measurements in aggregate tracked one’s conception of animal welfare closely enough, breeders could generate increases in farmed animal welfare, potentially initially at low marginal cost in other traits.

Just how powerful are ordinary animal breeding techniques? Consider cattle:

In 1942, when my father was born, the average dairy cow produced less than 5,000 pounds of milk in its lifetime. Now, the average cow produces over 21,000 pounds of milk. At the same time, the number of dairy cows has decreased from a high of 25 million around the end of World War II to fewer than nine million today. This is an indisputable environmental win as fewer cows create less methane, a potent greenhouse gas, and require less land.

 Wired has an impressive chart of turkey weight over time:


Anderson, who has bred the birds for 26 years, said the key technical advance was artificial insemination, which came into widespread use in the 1960s, right around the time that turkey size starts to skyrocket…

This process, compounded over dozens of generations, has yielded turkeys with genes that make them very big. In one study in the journal Poultry Science, turkeys genetically representative of old birds from 1966 and modern turkeys were each fed the exact same old-school diet. The 2003 birds grew to 39 pounds while the legacy birds only made it to 21 pounds. Other researchers have estimated that 90 percent of the changes in turkey size are genetic.

Moreover, breeders are able to improve complex weighted mixtures of diverse traits:

The bull market (heh) can be reduced to one key statistic, lifetime net merit, though there are many nuances that the single number cannot capture. Net merit denotes the likely additive value of a bull’s genetics. The number is actually denominated in dollars because it is an estimate of how much a bull’s genetic material will likely improve the revenue from a given cow. A very complicated equation weights all of the factors that go into dairy breeding and — voila — you come out with this single number. For example, a bull that could help a cow make an extra 1000 pounds of milk over her lifetime only gets an increase of $1 in net merit while a bull who will help that same cow produce a pound more protein will get $3.41 more in net merit. An increase of a single month of predicted productive life yields $35 more.

No futuristic technologies are needed to make progress, although they would expedite the process: just feed accurate enough measurements of animal welfare into the net merit equation and similar progress could begin on the new trait.

Added December 8th:

Gaverick Matheny reports that some breeds have been selected in part for welfare. However, because breeders have not yet finished optimizing farm animals for productivity, the opportunity cost of not increasing productivity even further instead has been too high, given weak market and other pressures for welfare improvement, for this to take off.

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Nuclear winter and human extinction: Q&A with Luke Oman

In Reasons and Persons, philosopher Derek Parfit wrote:

I believe that if we destroy mankind, as we now can, this outcome will be much worse than most people think. Compare three outcomes:

1. Peace

2. A nuclear war that kills 99% of the world’s existing population.

3. A nuclear war that kills 100%

2 would be worse than 1, and 3 would be worse than 2. Which is the greater of these two differences? Most people believe that the greater difference is between 1 and 2. I believe that the difference between 2 and 3 is very much greater… If we do not destroy mankind, these thousand years may be only a tiny fraction of the whole of civilized human history.

The ethical questions raised by the example have been much discussed, but almost nothing has been written on the empirical question: given nuclear war, how likely is scenario 3?

The most obvious path from nuclear war to human extinction is nuclear winter: past posts on Overcoming Bias have bemoaned neglect of nuclear winter, and high-lighted recent research. Particularly important is a 2007 paper by Alan Robock, Luke Oman, and Georgiy Stenchikov:  “Nuclear winter revisited with a modern climate model and current nuclear arsenals: Still catastrophic consequences.” Their model shows severe falls in temperature and insolation that would devastate agriculture and humanity’s food supply, with the potential for billions of deaths from famine in addition to the direct damage.

So I asked Luke Oman for his estimate of the risk that nuclear winter would cause human extinction, in addition to its other terrible effects. He gave the following estimate:

The probability I would estimate for the global human population of zero resulting from the 150 Tg of black carbon scenario in our 2007 paper would be in the range of 1 in 10,000 to 1 in 100,000.

I tried to base this estimate on the closest rapid climate change impact analog that I know of, the Toba supervolcanic eruption approximately 70,000 years ago.  There is some suggestion that around the time of Toba there was a population bottleneck in which the global population was severely reduced.  Climate anomalies could be similar in magnitude and duration.  Biggest population impacts would likely be Northern Hemisphere interior continental regions with relatively smaller impacts possible over Southern Hemisphere island nations like New Zealand.

Luke also graciously gave a short Q & A to clarify his reasoning:

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Alms is not about alms experts

In September Robin suggested that there might be an Alms Expert Opening:

Today the three spending categories of medicine, school, and alms make up ~40% of US GDP, a far larger fraction than in 1800. …

Today, two of these three classic charities have very powerful associated “professions”: doctors and teachers. These professions are powerful because they are seen as representing the good in those causes – doctors are our official authorities on what is good for patients, and teachers are our official authorities on what is good for students…

The missing group here is alms experts: we have no strong profession of those who specialize in helping the poor, crippled, etc.

Are alms experts punching below their weight, given the large fraction of GDP spent on alms? I think not, because alms spending mostly bypasses the work of alms experts.

Medical spending mostly goes to pay doctors, nurses, and other medical professionals, or to provide facilities and equipment that supports their work: there were over 7.5 million technically skilled healthcare workers in 2011. In education elementary schoolhigh school, and post-secondary teachers added up to over 4.4 million people, with other spending going to school buildings, principals, utilities, libraries, and so forth.

But consider the largest alms program in the United States, the Social Security Administration, which makes cash payments to the elderly, the disabled, and surviving family members of certain deceased. Its budget request projects that in 2013 it will pay out some $873 billion to beneficiaries while spending less than $12 billion for operations, with only 80,000 state and federal employees.

The relatively small role for administration recurs elsewhere, e.g. the food voucher program SNAP disbursed $76 billion in 2011 with administrative costs of $6.9 billion and the Earned Income Tax Credit disbursed $59.5 billion with direct administrative costs of less than one percent. Staffing can be higher for programs involving social workers and foreign assistance, but less is spent on these than the large formula-driven programs.

Since alms employees are relatively scarce, they can directly deliver fewer votes or political contributions than teachers or medical workers. And since their role in the provision of alms is so much less central, it is harder for others to see them as “representing the good in those causes.” Instead, organizations of recipients can take on the role of defenders of the alms they receive. For alms influence and status, look to the 38 million members of the AARP, not 80,000 Social Security workers.

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“Evicting” brain emulations

Follow up to: Brain Emulation and Hard Takeoff

Suppose that Robin’s Crack of a Future Dawn scenario occurs: whole brain emulations (’ems’) are developed, diverse producers create ems of many different human brains, which are reproduced extensively until the marginal productivity of em labor approaches marginal cost, i.e. Malthusian near-subsistence wages. Ems that hold capital could use it to increase their wealth by investing, e.g. by creating improved ems and collecting the fruits of their increased productivity, by investing in hardware to rent to ems, or otherwise. However, an em would not be able to earn higher returns on its capital than any other investor, and ems with no capital would not be able to earn more than subsistence (including rental or licensing payments). In Robin’s preferred scenario, free ems would borrow or rent bodies, devoting their wages to rental costs, and would be subject to "eviction" or "repossession" for nonpayment.

In this intensely competitive environment, even small differences in productivity between em templates will result in great differences in market share, as an em template with higher productivity can outbid less productive templates for scarce hardware resources in the rental market, resulting in their "eviction" until the new template fully supplants them in the labor market. Initially, the flow of more productive templates and competitive niche exclusion might be driven by the scanning of additional brains with varying skills, abilities, temperament, and values, but later on em education and changes in productive skill profiles would matter more.

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Brain Emulation and Hard Takeoff

The construction of a working brain emulation would require, aside from brain scanning equipment and computer hardware to test and run emulations on, highly intelligent and skilled scientists and engineers to develop and improve the emulation software. How many such researchers? A billion dollar project might employ thousands, of widely varying quality and expertise, who would acquire additional expertise over the course of a successful project that results in a working prototype. Now, as Robin says:

They would try multitudes of ways to cut corners on the emulation implementation, checking to see that their bot stayed sane.  I expect several orders of magnitude of efficiency gains to be found easily at first, but that such gains would quickly get hard to find.  While a few key insights would allow large gains, most gains would come from many small improvements.   

Some project would start selling bots when their bot cost fell substantially below the (speedup-adjusted) wages of a profession with humans available to scan.  Even if this risked more leaks, the vast revenue would likely be irresistible.   

To make further improvements they would need skilled workers up-to-speed on relevant fields and the specific workings of the project’s design. But the project above can now run an emulation at a cost substantially less than the wages it can bring in. In other words, it is now cheaper for the project to run an instance of one of its brain emulation engineers than it is to hire outside staff or collaborate with competitors. This is especially so because an emulation can be run at high speeds to catch up on areas it does not know well, faster than humans could be hired and brought up to speed, and then duplicated many times. The limiting resource for further advances is no longer the supply of expert humans, but simply computing hardware on which to run emulations.

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Sick of Textbook Errors

One of the most well-worn examples in introductions to Bayesian reasoning is testing for rare diseases: if the prior probability that a patient has a disease is sufficiently low, the probability that the patient has the disease conditional on a positive diagnostic test result may also be low, even for very accurate tests. One might hope that every epidemiologist would be familiar with this textbook problem, but this New York Times story suggests otherwise:

For months, nearly everyone involved thought the medical center had had a huge whooping cough outbreak, with extensive ramifications. […]

Then, about eight months later, health care workers were dumbfounded to receive an e-mail message from the hospital administration informing them that the whole thing was a false alarm.

Now, as they look back on the episode, epidemiologists and infectious disease specialists say the problem was that they placed too much faith in a quick and highly sensitive molecular test that led them astray.

While medical professionals can modestly improve their performance on inventories of cognitive bias when coached, we should not overestimate the extent to which formal instruction such as statistics or epidemiology classes will improve actual behavior in the field.

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Should we Defer to Secret Evidence?

At the Volokh Conspiracy,  Stuart Benjamin raises an important question, asking:

whether we can articulate any useful metrics for when we should defer to self-serving statements by those with access to more information, and when we should not. In the two instances above, the doubters were vindicated. There are other examples in this vein. LBJ had access to greater information about the Gulf of Tonkin incident than did the doubters, but the latter were right, as the Pentagon and LBJ misrepresented what happened…

But there are counter-examples. Many people believed that Julius Rosenberg was innocent, but it is now clear the government really did have the goods on him, and that he was guilty. Same for Alger Hiss. Indeed, the airstrikes that President Clinton ordered at the height of the Lewinsky imbroglio – which were widely criticized as trumped up attempts at diverting attention, with little deference to the information asymmetry favoring the President – look quite different after September 11, 2001.

Two strategies for dealing with such asymmetries come to mind. One is an ex ante strategy, working to place unusually trustworthy individuals and groups in such positions (life-tenured judges, bipartisan committees, etc) or in positions where they can provide credible signals about justification (as Auditor-General, for instance). The other relies on the shadow of ex post punishment, which could be increased in inverse proportion to the probability of eventual detection.

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A Christmas Gift for Rationalists

Charitable donations are ripe with what seem to be irrationalities: door-to-door charitable contributions can be doubled when the donations are solicited by women 1 SD above the norm in attractiveness, we divide our contributions among multiple targets rather than putting 100% in the area with the highest marginal impact, and do very little to investigate charitable efficiency in the first place. At the same time, Christmas gifts are subject to staggering deadweight losses. In both cases, the failure to efficiently realize the supposed objective of benefitting the recipient can be explained by attributing the decision to a ‘purchase of identity,’ or signalling function. Someone who will tithe 10% of her income to Habitat for Humanity to build house for plump, but relatively poor, Westerners demonstrates her generosity just as well as someone who saves dozens of children from death by malaria by purchasing nets and DDT for an African village, even though the latter does more good.

My three-for-one proposal: rationalist types should ask for charitable gift certificates (the charity signs up as a project, and then recipients can allocate the value of their gift cards at will) this Christmas, and then donate the proceeds to some  high-impact but unconventional charity. (What’s the third bias addressed, you ask? The self-serving bias that keeps our charitable contributions so low!)

Some questions:
1. Will this bring in a smaller total in gift expenditures? Do weddings that request donations to a named charity take in less than those that use a gift registry?
2. Would an exchange of two $100 charitable gift certificates between friends really feel less silly than the exchange of two $100 bills because of the public commitment function?
3. Would this work for weddings or bar mitzvahs?

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