Category Archives: Jason Collins is Indispensable

Will population growth rebound?

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Jason Collins and Lionel Page write,

The United Nations produces forecasts of fertility and world population every two years. As part of these forecasts, they model fertility levels in post-demographic transition countries as tending toward a long-term mean, leading to forecasts of flat or declining population in these countries. We substitute this assumption of constant long-term fertility with a dynamic model, theoretically founded in evolutionary biology, with heritable fertility. Rather than stabilizing around a long-term level for post-demographic transition countries, fertility tends to increase as children from larger families represent a larger share of the population and partly share their parents’ trait of having more offspring. Our results suggest that world population will grow larger in the future than currently anticipated.

Collins is humble about the ability of any model to project fertility, given the importance of cultural evolution. I have not seen the paper, but I would like to know whether they tested their model against actual data in any way. For example, you could “backcast” the model and see how well it “predicts” population in, say, 1980 or 1950.

Jason Collins on self-discipline

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He writes,

My iPhone is used for four main purposes: as a phone; as a train timetable; as a listening device (podcasts, audiobooks and music); and for my meditation apps (more on meditation below). It also has a few utilities such as Uber that I rarely use. I don’t use my phone for social media, as a diary, or for email. Most of the day it stays in my pocket or on my desk. All notifications, except calls and text messages, are turned off. I rarely have any reason to look at it.

The whole post is interesting.

I think that it pays to evaluate your daily habits and try to reinforce the ones that you want to keep and eliminate the ones that you want to drop. I saw a reference recently to a “stoplight” system where you give yourself a list of 10-15 desired habits and, when you keep them, give a green check and when you break them, give yourself a red check. My current list is:

1. Do serious writing first thing in the morning (that is when I am sharpest).

2. Do foot stretches twice a day (to protect against the dancer’s habit of plantar fasciitis)

3. Review one dance using YouTube.

4. Read 20 pages in a book (in practice, I tend to binge-read or read nothing)

5. Straighten up an area

6. Organize web site (I am failing at this habit)

7. Aerobic exercise at least 2 hours

8. Touch base with any friend

9. Eat an apple

10. Eat broccoli

Algorithms vs. judgment

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Jason Collins discusses the issue.

the reluctance to have our decisions and actions replaced by automated systems extends through a range of human activity and decision-making. It took nearly 50 years for people to accept automated lifts. Today, over three quarters of Americans are afraid to ride in a self-driving vehicle.

Automated systems tend to increase efficiency but at a cost of fragility. When algorithms are first introduced to a domain, humans are better at spotting circumstances that were unanticipated by the algorithm.

Amar Bhide, in A Call for Judgment, argues that the financial crisis in part reflects the fragility of a regulatory system (including internal regulations at financial institutions) that relied too much on formulas and too little on judgment.

But Collins points out that there are many situations in which humans over-ride algorithms in a harmful way. The challenge is to enable humans to distinguish situations in which the algorithm is making better calculations from situations in which the algorithm is missing something that the human sees.

Blockchain as a solution for data integrity

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From Nathan Heller’s long piece in the New Yorker about Estonia.

In a blockchain system, too, every line is contingent on what came before it. Any breach of the weave leaves a trace, and trying to cover your tracks leaves a trace, too.

. . .The blockchain makes every footprint immediately noticeable, regardless of the source. (Ruubel says that there is no possibility of a back door.) To guard secrets, K.S.I. is also able to protect information without “seeing” the information itself.

That seems like a possible use case. But my guess is that it is only practical for data records that are updated infrequently. If data is being legitimately updated multiple times a day, I would think that a blockchain ledger would be too much overhead.

But maybe I am wrong. Jason Collins points to this.

ASX is replacing the system that underpins post-trade processes of Australia’s cash equity market, known as CHESS (the Clearing House Electronic Subregister System).

ASX commenced a process of evaluating replacement options for CHESS in 2015. In January 2016, ASX selected Digital Asset as a technology partner to develop, test and demonstrate to ASX a working prototype of a post-trade platform for the cash equity market using DLT (an example of which is commonly referred to as ‘blockchain’).

That will be an interesting test to follow.

Overall, what is interesting about Estonia is the way that the leadership culture apparently revolves around knowledge of information technology. I get the impression that in the U.S. if your organization backs up its data overnight that counts as having an above-average data integrity strategy.

The Behavioral Scientist

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it is a web site that may prove interesting. For example, David Rand and Jonathan Cohen write,

Within a population, controlled processing may—rather than ensuring undeterred progress—usher in short-sighted, irrational, and detrimental behavior, ultimately leading to population collapse. This is because the innovations produced by controlled processing benefit everyone, even those who do not act with control. Thus, by making non-controlled agents better off, these innovations erode the initial advantage of controlled behavior. This results in the demise of control and the rise of lack-of-control. In turn, this eventually leads to a return to poor decision making and the breakdown of the welfare-enhancing innovations, possibly accelerated and exacerbated by the presence of the enabling technologies themselves. Our models therefore help to explain societal cycles whereby periods of rationality and forethought are followed by plunges back into irrationality and short-sightedness.

Call it the theory of mediocracy.

Elsewhere, Jason Collins writes,

Absent limiting human intervention to the right level, the pattern we will see is not humans and machines working together for enhanced decision making, but machines slowly replacing humans decision by decision. Algorithms will often be substitutes, not complements, with humans left to the (at the moment, many) places where the algorithms can’t go yet.

Jason Collins on Joseph Henrich

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Self-recommending. One excerpt:

Contrast cultural evolution with genetic natural selection. In the latter, high fidelity information is transmitted from parent to offspring in particulate form. Cultural transmission (whatever the cultural unit is) is lower-fidelity and can be in multiple directions. For genetic natural selection, selection is at the level of the gene, but the future of a gene and its vessels are typically tightly coupled within a generation. Not so with culture. As a result we shouldn’t expect to see the types of results we see in population/quantitative genetics in the cultural sphere. But can cultural evolution get even close?

Suppose that we define culture as socially communicated thought patterns and behavioral tendencies. Then cultural evolution would be the process by which the “fittest” thought patterns and behavioral tendencies survive. One can imagine that such a process could be extremely messy. There are non-linear interactions among thought patterns and behavioral tendencies. We would expect the evolutionary process to make a lot of mistakes, and indeed a little reflection would tell you that we have seen a lot of mistakes.

Weakest-Link Theory

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In a review of Garett Jones’ Hive Mind, Jason Collins writes,

Jones’s argument builds on that of Michael Kremer’s classic paper, The O-Ring Theory of Economic Development. Kremer’s insight was that if production in an economy consists of many discrete tasks and failure in any one of those tasks can ruin the final output (such as an O-ring failure on a space shuttle), small differences in skills can drive large differences in output between firms.

Let us meditate on this for a while. Toss out all of your intuition based on marginal productivity theory, and instead think of a business as undertaking a set of processes, with the overall profit constrained by its weakest process. It fails if it is great at engineering but lousy at marketing, or vice-versa. A firm that has great engineering and great marketing can be done in by poor internal controls. And so on.

First, this theory helps explain why there are firms. An engineer working by himself automatically has a lousy marketing department.

Second, it may explain why we see higher pay at highly profitable firms. These are firms that know how to identify and retain high-performing workers. That includes giving their high-performing workers appropriate compensation.

A Sentence about Tetlock’s Famous Study

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Jason Collins writes,

However – and this point is one you rarely hear in commentary about the book – the experts outperform unsophisticated forecasters (a role filled by Berkeley undergrads), whose performance is truly woeful.

Read the entire book review.

Herbert Stein wrote a memoir in which he summarized what he had learned is that economists do not know very much, but non-economists know even less.

The challenge is to get people to admit what they do not know. A non-economist who is quite ignorant is only dangerous if he or she tries to engineer the economy. Most economists, believing that they can engineer the economy, are dangerous.

Religious Fervor and Demography

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Jason Collins reviews Eric Kaufmann’s Shall the Religious Inherit the Earth?: Demography and Politics in the Twenty-First Century.

To give a sense of the power of this higher fertility, the Old Order Amish in the United States have increased from 5,000 people in 1900 to almost a quarter of a million members. In the United Kingdom, Orthodox Jews make up 17 per cent of the Jewish population but three-quarters of Jewish births.

…Kaufmann’s case worries me more than tales of government deficits due to demographic change. Even if you assign a low probability to Kaufmann’s projections, it provides another strand to the case that low fertility in the secular West is not without costs.

The numbers cited about Orthodox Jews in the UK struck me as fishy, based on what I know about the U.S. Suppose that there are 80 non-Orthodox Jewish women and they each have one child (a really low fertility rate), for a total of 80 non-Orthodox Jewish births. Then suppose you have 20 Orthodox Jewish women, and they have to account for 3/4 of all Jewish births, which means that they need to give birth to 240 children, or an average of 12 children each. There are in fact several sub-groups within Orthodox Judaism, and there are some sects in which families of that size are common, but there is no way that the average family size of all Orthodox Jews is 12 children.

There is a larger objection that I have, which is that the high growth of the fervently religious starts from a low base. Assume that non-fervent women have one child each, and fervent women have ten children each. If you start with 999 non-fervent women for every fervent woman, it is going to take quite a few generations for the fervent to “inherit the earth.” Meanwhile, much else will change.

[UPDATE: In a comment, Megan McArdle points out that the arithmetic in the above example leads to the fervent reaching parity in 3 generations, and then soaring to dominance thereafter. But as she points out, the discrepancy in fertility between the fervent and non-fervent is not as wide as in the examle. And if nothing else, I can fall back on “much else will change.” By the end of this century, we could very well see dramatic changes in medical science, including reversal of aging and cloning.

Jason Collins reviews Jonathan Last

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Collins writes,

So, if government can’t make people have children they don’t want and can’t simply ship them in, Last asks if they could help people get the children they do want. As children go on to be taxpayers, government could cut social security taxes for those with more children and make people without children pay for what they’re not supporting. (Although you’d want to make sure there was no net burden of those children across their lives, as they’ll be old people one day too. There are limits to how far you could take that Ponzi scheme.)

Keep in mind that lower birth rates are an international phenomenon, so I am reluctant to place much weight on U.S.-specific factors. My sense is that the decline in birth rates is correlated with, if not caused by, increased education of women. If that is the main causal factor, then it probably is not something that is going to be reversed.

Also, I am not convinced that there is such a down side to slower population growth and eventual decline. Yes, it messes up entitlement programs for the elderly, but that is because those programs are ill conceived, particularly in not indexing the age of government dependency to longevity. You should fix the entitlement programs to deal with the demography rather than try to fix demography to deal with entitlement programs.