Tag Archives: Personal

Wolfers Gets Loopy

Over the years I’ve not only met folks who do drugs, I’ve met folks who’ve had deep mystical experiences on drugs. They have told me that their drug experiences made them feel sure the physical world we see around us just can’t be all there is — they’ve touched something deeper and more important. When asked how exactly a weird drug experiences could possibly count as evidence on basic physics, they have little coherent to say. It seems their subconscious just told them this abstract conclusion, and they can’t not believe a cocksure subconscious. Even one on drugs.

Druggies might say such things in private, but it is much rarer to hear a professional physicist say them in public. Odd then to hear professional economist Justin Wolfers say his near-mystical parenting experience makes him doubt standard econ:

I learned economics in my twenties, before I became a dad. … Hard math and complex models … exploring the basic idea … that people are purposeful, analytic decision makers. … I had always believed in the analytic self; I was rational, calculating, and tried to make smart decisions. Of course real people don’t use math, but I figured that we’re still weighing costs and benefits just as our models say. …

Today, I’m not so sure. My feelings toward my daughter Matilda aren’t easily expressed in analytic terms. … Her laugh is the greatest joy, and it thrills me that she shares it with me. … She’s central not only to my life, but to who I am. There’s something new and strange about all this. Today, I feel the powerful force of biology. It’s visceral; it’s real; it’s hormonal, and it’s not in our economic models. I’m helpless in the face of feelings that overwhelm me.

Yes, I know that a twenty-something reader will cleverly point out that I just need to count kids as a good which yields utility, or perhaps we need to add a state variable to the utility function as in rational addiction models. But that’s not the point. I’m surprised by how little of this I’ve consciously chosen. While the economic framework accurately describes how I choose an apple over an orange, it has had surprisingly little to say about what has been the most important choice in my life.

I’m a committed neoclassical economist. … But what kind of economists would we be if we learned our economics only after we were parents? It’s an interesting thought experiment, and truth is, I don’t know the answer. … Slivers of evidence—my own introspection, conversations with other economist-parents … —all tell me that it would be different. (more)

I don’t need to speculate – I am exactly that kind of economist. I started econ grad school with two kids, ages 0 and 2, and had no undergrad econ. I’ve seen a lot of the parenting cycle – my youngest graduates from high school tomorrow. My kids are central to who I am, and I’ve known well feelings that are visceral, hormonal, and that overwhelm me.

But none of that makes me doubt the value of neoclassical econ. How could it? First, econ makes sense of a complex social world by leaving important things out, on purpose – that is the point of models, to be simple enough to understand. More important, econ models almost never say anything about consciousness or emotional mood – they don’t at all assume people choose via a cold calculating mindset, or even that they choose consciously.  As long as choices (approximately) fit certain consistency axioms, then some utility function captures them.  So how could discovering emotional and unconscious choices possibly challenge such models?

Having an emotional parenting experience is as irrelevant to the value of neoclassical econ as having a mystical drug experience is to the validity of basic physics. Your subconscious might claim otherwise, but really, you don’t have to believe it.

Added 11p: Wolfers is usually an excellent economist, and here he seems to realize he is acting a bit loopy. This suggests a “religious” scenario, where someone tries to show devotion via a willingness to believe extreme things. Wolfers feels a new strong attachment to his family, and shows it by a willingness to change related beliefs in an extreme way. Being an economist, one of the biggest beliefs he can sacrifice on this altar is his belief in the standard economic framework. So Wolfers says that his new family attachment has made him question this framework.

Added 22June: Wolfers responds here.

GD Star Rating
loading...
Tagged as: , ,

Seeking Alien Trash

I was interviewed by Seth Shostak (minutes 15:45 to 23:00 of this show) on possible observational consequences of my game theory model of interstellar colonization. (Previous posts on this here, here, here.)

The bottom line is that even if an alien colonization wave once passed this way, our astronomical theory and observation abilities are probably still just too weak to see the telltale signs of such a wave.

GD Star Rating
loading...
Tagged as: ,

First Cryonics Hour

Me two years ago:

I hereby offer to talk for one hour on any subject to anyone who can show me they’ve newly signed up for cryonics. You can record the conversation, publish it, and can sell your time to someone else.

Stuart Armstrong has signed up for cryonics, and then redeemed my offer. Congrats Stuart! We talked for an hour, and he recorded the conversation. If he does something with that recording, I’ll post a link here.

Any other takers?

GD Star Rating
loading...
Tagged as: ,

Beware Men With Sticks

menwithsticks
Credit: Tom Munnecke

GD Star Rating
loading...
Tagged as:

5 Million Visits

Today we had our five millionth visit to Overcoming Bias, at least as measured by sitemeter. Woo and hoo … :)

GD Star Rating
loading...
Tagged as: ,

How US States Vary

Ken Lee just recieved his Ph.D. in economics from GMU; I was his thesis advisor; his thesis is here. I am impressed enough with Ken’s thesis that I’ll take the next few posts to describe some of his main findings.  The first finding I’ll describe: The main way that US states vary is in their health.

Ken collected 81 features of states, 56 cultural rankings and 25 demographic variables (listed below), and did a factor an analysis on them.  A factor analysis finds a few linear combinations of features that can explain the most variance in whole set of features; the variation of all the features could result from variation in just a few behind-the-scenes factors, plus error.

The biggest factor, explaining 27% of the variance between US states, was health – some states are just healthier than others, and this fact can explain many other things about those states.  Here are the three biggest factors:

  1. (27% of variance): Top five features: “low cancer deaths, low cardiovascular deaths, low smoking rates, low levels of unnecessary medical care, low obesity rates,” Also: “high well-being index, high exercise rates, healthiest, low mortality rates for blacks and whites, higher in education (IQ Rank, Percentage of Graduates, and Smartest), higher in health (Healthiest, Exercise Frequency, and Percentage with No Insurance), and lower in crime rates (Crime Rate and Violent Crime Rate) rankings.” Map: Factor 1
  2. (15% of variance): Top five features: “low occupational death rates, high in women’s rights, high in primary care physicians per capita, high in amount of fruit eaten per capita, low in percentage on poverty.” Also: “low in teen births, high on $ spent on K-12 education, high $ for teacher salaries, smartest … a higher percentage of people in the 25-44 age group, higher income, high college graduation rate, and higher urbanization.” Map:
    Factor 2
  3. (14% of variance): Top five features: “low rates of infections (HIV, STD), high in IQ, low overall crime rates, high in graduates, low in those having no health insurance.” Also: “low in violent crime, healthiest, low in percentage urban … regular church attendance, a high regard for religion, worse overall state economic health, high manufacturing employment, and high farming output.” Map: Factor 3

To me, factor 1 seems mainly about health, factor 2 seems about left (~forager) idealism  – fruit, women’s rights, safety rules, helping the poor, and spending lots on docs and teachers — and factor 3 seems about right (~farmer) idealism — rural, religious, low crime, sexual restraint, make real stuff, finish what you start.

The fact that health is the biggest factor says that health is very important, even beyond its direct benefits. And the fact that health and a tendency to spend on docs are largely independent says that medicine isn’t very important for health, and there should be enough variation among states to study just how important it is.

Here are those 81 state features:

Continue reading "How US States Vary" »

GD Star Rating
loading...
Tagged as: , ,

Two Recent Talks

  1. On April 27, I talked at Harvard Business School on information accounting: audio, slides.
  2. On May 5, I talked in Geneva on the economics of artificial intelligence: audio, slides.
GD Star Rating
loading...
Tagged as:

My CQ Researcher OpEd

Congressional Quarterly Researcher has a new issue focused on artificial intelligence. They invited me to write short a op-ed on the question “Will artificial intelligence lead to massive unemployment?” Alas they didn’t tell me the idea was for me to say “No” opposite Martin Ford saying “Yes” – we both said “Yes.” They’d have done better to have Ford and I dispute something we disagreed on, such as how best to deal with such unemployment.  Anyway, here’s mine oped:

Artificial intelligence could indeed lead to high unemployment if, in contrast to today’s situation, most world income was paid not for human wages, but instead for income from land and capital, including machines. After all, why work if working full time doesn’t increase your income much? And this could happen if the value of human labor fell greatly, relative to machines.

Is this possible? In the near term, it is unlikely. Right now, computers and other forms of machine intelligence aren’t nearly sophisticated enough to emulate the human brain or replace human labor on a global scale. But in the long term — say, a century or two in the future, as artificial intelligence becomes far more sophisticated than it is today — the picture could be far different. For now, it would be insufficient to merely have more powerful machines, if they continued to mainly complement human labor, as machines have for centuries. When machines complement humans, better machines lead to more, not less, demand for humans.

Even if machines have so far tended to complement humans, might machines someday become actual substitutes for human workers? The key thing to understand here is that while a machine might substitute for a human on any particular task, when the division of tasks between humans and machines is stable, then cheaper and better machines raise the demand for humans.

But if machines could effectively replace humans for most tasks now performed by humans, that would be a very different story. Full-time human wages would then become small compared to humans’ income from owning machines that do the work. This isn’t the current trend, so don’t worry about it happening soon. But not only is this possible, it is likely, within a century or two, through the use of “whole brain emulations.”

Imagine that we could 1) scan some real human brains in enough detail, 2) model all standard brain cell types with enough accuracy and 3) have cheap enough computers to emulate entire human brains, using these cell models and the scan details. Such emulations would then talk and act much like the scanned humans they emulate, and so could replace humans on most tasks.

An unregulated market in cheap brain emulations would lead to a vast explosion of wealth and emulations, and to human wages falling to match machine rental costs, soon well below human subsistence levels. Humans would then have to own enough other forms of capital, or starve. Emulations, in contrast, would be fully employed.

GD Star Rating
loading...
Tagged as: ,

I Talk Wed. At Harvard

Next Wednesday I’ll talk at Harvard business school on “Toward Information Accounting“:

What gets measured, gets done. Today, organizations account in great detail for revenue and the costs of materials and time, but have only crude informal accounting of info contributed to key organizational decisions. Because info cost and value are poorly measured, info production is neglected.

Can we use prediction markets to do better? Imagine speculative betting markets on many key organizational questions, and two key changes in business practice. First, let the division responsible for each decision declare lower-bound estimates of the value of more info on each related question. A division might, for example, declare that 1% lower error in estimating 3rd quarter sales of product X is worth at least $5000. There are standard ways to calculate such info value in specialized situations, such as inventory management.

Second, let trader accounts be denominated in a new “color of money.” Instead of doing zerosum betting, the market for each question would be subsidized at a level matching its declared info value. As a result, the subsidy amounts lost to traders as prices become more accurate would on average correspond to that question’s declared info value. For example, on 3rd quarter sales of product X, its 0.7% lower error might have earned a $3500 subsidy, going to George who gained $2000, Sue who gained $1500, Sam who gained $1000, and Fred who lost $1000.

Given these two new practices, trader account gains could be interpreted as noisy estimates of the info value those accounts transmitted via their trades. Losses could be interpreted as info destruction. Simple statistics applied to the pattern of changes in an account over time could estimate its consistent gains, amid its temporary fluctuations. The total consistent gains for the accounts of a division could be credited to that division in its ordinary cost accounting, while that same amount is debited from the divisions who declared info value on those questions.

When one created an account with an initial cash deposit, and authorized an individual or team to trade that account on specific questions, one would in essence say: “Try to show us that you can consistently add info value here via your trades. We’ve started you out small, but if you can show consistent gains we may give you more to work with. At annual review time we’ll credit your account’s consistent gains (or losses) to you (and your division) as value you transmitted to this organization, to be compared with your time and other costs of participation.”

GD Star Rating
loading...
Tagged as: , ,

Longevity Film Trailer

Apparently documentary films are often funded in chunks; they make part of it, put together a trailer to show around, and then get more money to finish it. I’m included in this part-way-through trailer for David Alvarado’s slick-looking new film on longevity:

Though the trailer is 2D, much of it was actually filmed in 3D, including a wide ranging lunch discussion with myself and my GMU colleagues. Hope that makes it into a final version.

GD Star Rating
loading...
Tagged as: ,