Category: General

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Seth Roberts13 Comments

 

Thanks to Chuck Currie, Grace Liu, Alex Chernavsky and Dave Lull.

Two Dimensions of Economic Growth: GDP and Useful Knowledge

Seth Roberts9 Comments

Ecologists understand the exploit/explore distinction. When an animal looks for food, it can either exploit (use previous knowledge of where food is) or explore (try to learn more about where food is). With ants, the difference is visible. Trail of ants to a food source: exploit. Solitary wandering ant: explore. With other animals, the difference is more subtle. You might think that when a rat presses a bar for food, that is pure exploitation. However, my colleagues and I found that when expectation of food was lower, there was more variation — more exploration — in how the rat pressed the bar. In a wide range of domains (genetics, business), less expectation of reward leads to more exploration. In business, this is a common observation. For example, yesterday I read an article about the Washington Post that said its leaders failed to explore enough because they had a false sense of security provide by their Kaplan branch. “Thanks to Kaplan, the Post Company felt less pressure to make hard strategic choices—and less pressure to venture in new directions,” wrote Sarah Ellison.

Striking the right balance between exploitation and exploration is crucial. If an animal exploits too much, it will starve when its supply of food runs out. If it explores too much, it will starve right away. Every instance of collapse in Jared Diamond’s Collapse: How Socieities Choose to Fail or Succeed was plausibly due to too much exploitation, too little exploration (which Diamond, even though he is a biologist, fails to say). I’ve posted several times about my discovery that treadmill walking made studying Chinese more pleasant. I believe walking creates a thirst for dry knowledge. My evolutionary explanation is that this pushed prehistoric humans to explore more.

I have never heard an economist make this point: the need for proper balance between exploit and explore. It is relevant in a large fraction of discussions about how to spend money. For example, yesterday I listened to the latest EconTalk podcast, a debate between Bob Frank and Russ Roberts about whether it would be a good idea for the American government to spend $2 trillion on infrastructure projects (fix bridges, etc.). Frank said it would create jobs, and so on — the usual argument. Roberts said if fixing bridges was such a good idea, why hadn’t this choice already been made? Roberts could have said, but didn’t, that massive government shovel-ready expenditures, such as $2 trillion spent on infrastructure repair, inevitably push the exploit/explore balance toward exploit, which is dangerous. This is an argument against all Keynesian stimulus-type spending. I have heard countless arguments about such spending. I have never heard it made. If you want examples of how the American economy suffers from a profound lack of useful new ideas, look at health care. As far as I know, there are no recorded instances of a society dying because of too much exploration. The problem is always too much exploitation. People at the top — with a tiny number of exceptions, such as the Basques — overestimate the stability of their position. At the end of The Economy of Cities, Jane Jacobs says that if a spaceship landed on Earth, she would want to know how their civilization avoided overexploitation. When societies exploit too much and explore too little, said Jacobs, problems (in our society, problems such as obesity, autism, autoimmune disease, etc.) stack up unsolved. Today is China’s birthday. Due to overexploitation, I believe China is in even worse economic shape than America. Ron Unz, whom I respect, misses this.

My broad point is that a lot of economic thinking, especially about growth and development, is one-dimensional (measuring primarily growth of previously existing goods and services — exploitation) when it should be two-dimensional (measuring both (a) growth of existing stuff and (b) creation of new goods and services). Exploration (successful exploration) is inevitably tiny compared to exploitation, but it is crucial there be enough of it. If there is a textbook that makes this point, I haven’t seen it. An example of getting it right is Hugh Sinclair’s excellent new book Confessions of a Microfinance Heretic (copy sent me by publisher) that debunks microcredit. Leaving aside the very high interest rates, the use of microcredit loans to buy TVs, and so on, microcredit is still a bad idea because the money is, at best, used for a business that copies an existing business. (The higher the interest rate, the less risk a loan recipient dares take.) When a new business copies an already-existing business, you are taking an existing pie (e.g., demand for milk, if the loan has been used to buy a cow and sell its milk) and dividing it into one more piece. The pie does not get bigger. As Sinclair says, the notion that dividing existing pies into more pieces will “create a poverty-free world” is, uh, not worthy of a Nobel Prize.

Sure, it’s hard to measure growth of useful knowledge. (It is perfectly possible for a company to waste its entire R&D budget.) However, I am quite sure that realism does better than make-believe — and the notion that growth of GDP is a satisfactory metric of economic growth is make-believe. If you’ve ever been sick, or gone to college, and have a sense of history, you will have noticed the profound stagnation in two unavoidable sectors (health care and education) of our economy. That are growing really fast.

The Growth of Personal Science: Implications For Statistics

Seth Roberts2 Comments

I have just submitted a paper to Statistical Science called “The Growth of Personal Science: Implications For Statistics”. The core of the paper is examples, mostly my work (on flaxseed oil, butter, standing, and so on). There is also a section on the broad lessons of the examples — what can be learned from them in addition to the subject-matter conclusions (e.g., butter makes me faster at arithmetic). The paper grew out of a talk I gave at the Joint Statistical Meetings a few years ago, as part of a session organized by Hadley Wickham, a professor of statistics at Rice University.

I call this stuff personal science (science done to help yourself), a new term, rather than self-experimentation, the old term, partly because a large amount of self-experimentation — until recently, almost all of it — is not personal science but professional science (science done as part of a job). Now and then, professional scientists or doctors or dentists have done their job using themselves as a subject. For example, a dentist tests a new type of anesthetic on himself. That’s self-experimentation but not personal science. Moreover, plenty of personal science is not self-experimentation. An example is a mother reading the scientific literature to decide if her son should get a tonsillectomy. It is personal science, not professional self-experimentation, whose importance has been underestimated.

An old term for personal science might be amateur science. In almost all areas of human endeavor, amateur work doesn’t matter. Cars are invented, designed and built entirely by professionals. Household products are invented, designed and built entirely by professionals. The food I eat comes entirely from professionals. And so on. Adam Smith glorified this (“division of labor” — a better name is division of expertise). There are, however, two exceptions: books and science. I read a substantial number of books not by professional writers and my own personal science has had a huge effect on my life. As a culture, we understand the importance of non-professional book writers. We have yet to grasp the importance of personal scientists.

Professional science is a big enterprise. Billions of dollars in research grants, hundreds of billions of dollars of infrastructure and equipment and libraries, perhaps a few hundred thousand people with full-time jobs, working year after year for hundreds of years. Presumably they are working hard, have been working hard, to expand what we know on countless topics, including sleep, weight control, nutrition, the immune system, and so on. Given all this, the fact that one person (me) could make ten or so discoveries that make a difference (in my life) is astonishing — or, at least, hard to explain. How could an amateur (me — my personal science, e.g., about sleep is outside my professional area of expertise) possibly find something that professional scientists, with their vastly greater resources and knowledge and experience, have missed? One discovery — maybe I was lucky. Two discoveries — maybe I was very very very lucky. Three or more discoveries — how can this possibly be?

Professional scientists have several advantages over personal scientists (funding, knowledge, infrastructure, etc.). On the other hand, personal scientists have several advantages over professional scientists. They have more freedom. A personal scientist can seriously study “crazy” ideas. A professional scientist cannot. Personal scientists also have a laser-sharp focus: They care only about self-improvement. Professional scientists no doubt want to make the world a better place, but they have other goals as well: getting a raise, keeping their job, earning and keeping the respect of their colleagues, winning awards, and so on. Personal scientists also have more time: They can study a problem for as long as it takes. Professional scientists, however, must produce a steady stream of papers. To spend ten years on one paper would be to kiss their career goodbye. The broad interest of my personal science is that my success suggests the advantages of personal science may in some cases outweigh the advantages of professional science. Which most people would considered impossible.

If this sounds interesting, I invite you to read my paper and comment. I am especially interested in suggestions for improvement. There is plenty of time to improve the final product — and no doubt plenty of room for improvement.

Drug Companies Hide Unfavorable Evidence

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Ben Goldacre, a British epidemiologist and newspaper columnist (“Bad Science”), who used to attack homeopathy (trivial), has now written about something important: drug companies hide vast amounts of unfavorable evidence. I already knew this but many details were new to me.

I liked some of the comments:

We live in France and used a traditional GP for five years. Every time one of us went [to see him] he or she would come back with prescriptions for three or four medicines. Over that time he prescribed our family of five an estimated 60-80 medicines. We only ever took one, and everyone always got better without using these medicines. . . .This same GP also would refer us to thoroughly incompetent specialists. A few years ago I had a frozen shoulder. I went to see a ‘specialist’ who yanked my arm and shoulder about, clearly having no idea how an arm actually moves, and he then suggested operating. . . . Instead I looked on the Internet for info and found some exercises I could do and also underwent some Bowen technique treatment. A year later I was fine.

As a business consultant, I was approached many many years ago by a company who wanted help to set up an independent research institute evaluating farm pesticides. They’d found the doses prescribed for actual application were many times the amount actually needed (for obvious profit reasons), sometimes efficacy was in doubt, and loads of hideous ecological side effects were buried.

Speaking of “many times the amount actually needed”, I attended a talk about lighting standards in office buildings in which the speaker said the standards were too high (e.g., desks were better lit than necessary). His explanation was that the more lighting there is, the more air conditioning you need. The more air conditioning, the more cost, and architects are paid a fixed percentage of the cost. One of his slides showed that someone in the industry wrote down this rationale.

My GP often says the pharmaceutical industry wants to see everybody on prescription. He does prescribe tests, a lot of them, but drugs very rarely, and most of his recommendations are targeted at patients’ lifestyle: diet, exercise, work, relationships. When he does prescribe drugs, if it is an antibiotic or an antifungal, you have to come back after 1 week so that he can see if the treatment has worked/is working. If you need longer term treatment, for example physiotherapy and painkillers for back pains, or if you have a long term condition such as diabetes, he insists on seeing every month, to check that you are treatment compliant. . . . I have to thank him for a lot. Until fairly recently, I was stuck in a really unhealthy work environment, and could not find another job. I had done a Psychology course which had nothing but praise about antidepressants, so I asked him if he would prescribe me one of the newest tricyclic ones. He was extremely angry, told me I needed a new job, not tablets, and that if I ever got that drug elsewhere and he found out, he did not want to see me again (he would probably have found a blood test to check up I was ‘clean’). So I did not go down the tablet route, and he was right: all I needed was to change job.

Two or three years ago, I was working in Germany and went to see a German doctor. He looked at the list of daily medications my British doctor had prescribed (5 different drugs), ostensibly to help me survive middle age. He looked shocked, and told me that the British medical profession is dominated by the pharmaceutical industry, and he advised I stop taking three of the drugs prescribed. Now, having come back to the UK, every time I visit my GP, I am bullied once again to take this or that. If I try to resist, I receive very patronizing lectures about this or that risk.

Thirty years of bi-polar disorder taking virtually every possible anti-depressant over time, and at times when hospitalized, forced to take them under the duress of threatened sectioning under the Mental Health Act. Throughout those years I told the psychiatrists that the drugs didn’t work beyond an initial “placebo effect” lasting about 2 weeks, and that the side effects were often awful. Now it seems I may have been right all along. . . . Big Pharma, [you] made a difficult life a lot worse.

Maybe Goldacre will someday grasp that “evidence-based medicine”, which he often praises, also hides a vast amount of unfavorable evidence.

Last Weekend’s Quantified Self Conference

Seth Roberts2 Comments

Last Saturday and Sunday there was an international Quantified Self Conference at Stanford. I attended. In Gary Wolf’s introductory talk, he said there are 70 Quantified Self chapters (New York, London, etc.) and 10,000 members. I was especially impressed because I recently counted about 50 chapters. One new chapter is Quantified Self Beijing. It has its first meeting — in the form of a day-long conference — in nine hours and I haven’t quite finished my talk (“Brain Tracking: Why and How”). Please indulge me while I procrastinate by writing about the Stanford conference.

Here are some things that impressed me:

Office hours. A new type of participation this year was “office hour”, meaning you sit at a table for an hour. My office hour, during which two people showed up, was the most pleasant and informative hour of the whole conference for me. I thank Janet Chang for suggesting I do this.

Robin Barooah used a measure of how much he meditated, which he collected via an app he made, to measure his depression. When he was depressed, he didn’t meditate. Depression is half low mood, half inaction. It is very rare that the inactive side of it is measured. It is so much easier to ask subjects to rate their mood, but this has obvious problems. Robin inadvertently found a way to measure level of activity over long periods of time. He also found that participation in an experiment that tested a PTSD drug caused long-lasting improvement, another idea about depression I’d never heard before. At dinner, Robin told me that his partner, when they’re at a restaurant, has sometimes said “God bless Seth Roberts” for allowing her to eat butter without guilt.

Steve Jonas, from QS Portland, told me that he spent a long time (many weeks) doing some sort of mental test. During one of those weeks, he consumed butter a la Dave Asprey, in coffee. Much later he analyzed the results, computing an average for every week, and noticed that during the week with butter his performance was distinctly better than performance on other weeks. I hope to learn more about this. Steve also gave a talk about learning stuff using spaced repetition. He noticed that learning new stuff increased his curiosity. After he used spaced repetition to learn stuff about Mali, for example, he became more interested in reading news stories about Mali. I think this is an important conclusion about education, the way rote learning and encouragement of curiosity are not opposites but go together, that I have never heard before.

Larry Smarr, a computer science professor at UC San Diego, gave a talk called “Frontiers of Self-Tracking” centered on his Crohn’s disease. I was struck by what was missing from his talk. He began self-tracking before the Crohn’s diagnosis and clearly the self-tracking helped establish the diagnosis. However, you don’t need to self-track to figure out you have Crohn’s disease, roughly everyone who has gotten this diagnosis did not self-track. I couldn’t figure out how much the self-tracking helped. Crohn’s is generally associated with frequent diarrhea, which is exactly the opposite of hard to notice. Larry said nothing about this. Later he talked about massive amounts of personalized genetic data that he was getting. I couldn’t see how this data could possibly help him. Isn’t self-tracking supposed to be helpful? If I had a serious disease, I would want it to be helpful. At the same time, judging from his talk, he seemed to be ignoring the many cases where people have figured out how to better live with their Crohn’s disease. I would have liked to ask Larry about these gaps at his office hour but I had an eye problem that caused me to miss it.

I asked Nick Winter, cofounder of Skritter, what he thought of the recent Ancestral Health Symposium at Harvard (August 2012), which we both attended. He didn’t like it much, he said, but it more than justified itself because Chris Kresser’s talk about iron led him to get his iron checked. It turned out be off-the-charts high. Partly because oysters, partly because of red meat. I think he said he has since donated blood and it came down. I hadn’t previously heard of this danger of eating red meat. Again I discussed with Nick why he found that butter had a bad effect on his cognitive performance, the opposite of what I found. One possibility is that the butter slowed digestion of his lunch, thus reducing glucose in his blood at the time of the cognitive tests. But this does not explain why a certain drug eliminated the effect of butter.

In his talk, Paul Abramson, a quant-friendly San Francisco doctor, said that mainstream medicine is “riddled with undisclosed conflicts of interest”. I hope to learn more about this.

Jon Cousins contributed a neat booklet about what he had learned and not learned from starting Moodscope. What he hadn’t learned was how to make a sustainable business out of it. I suggested to him that he might be able find professors who would apply for grants with him that would use Moodscope as a research tool. The grants would pay Jon a salary and might include money for software development. Mood disorders are a huge health problem — depression is sometimes considered the most costly health problem of all, worldwide — and Moodscope is a new way to do research about them. Paying Jon a salary for a few years would cost much less than assembling a similar-sized sample (Moodscope has thousands of users) from scratch. I wonder how professors who do research on mood disorders will see it.

Benefits of Fermented Foods

Seth Roberts1 Comment

A simple story:

When Steven Kent did an internship at The Farm, a hippie commune in rural Tennessee, he had an epiphany. Eating a steady diet of sauerkraut, pickled vegetables, sourdough bread and other fermented foods, he found the digestive problems that had plagued him since college largely vanished.

There is more here about tempeh (fermented tofu) and a small Northern California company that Kent started called Alive and Healing that makes only tempeh.

Want to Track Your Brain Function?

Seth Roberts2 Comments

I am looking for people who want to try a mental test I have developed to track brain function. You do it on your laptop, once or more per day. One test session takes three minutes. For five years, I’ve been using various tests to track my brain function — first, balance, then, for a long time, arithmetic speed. The new test is better than these earlier tests, at least for me, because I find it enjoyable, which makes it easy to do several times/day. Via brain tracking, I have found that flaxseed oil and butter make my brain work considerably better. I was also able to find the best dosages. I believe that learning what foods (and dosages) make your brain work best is a good way to figure out what foods (and dosages) are best for the rest of your body. For example, after I figured out what amount of flaxseed oil was best for my brain, my gums became much healthier (less inflammation). The new test, which I do more often than the older tests, has made clear that there are all sorts of reliable yet mysterious ups and down in my brain function. I was unaware of this.

I want to find out what happens when other people use the new test. I am looking for a small number of people to do the test at least daily and send me their data at least weekly for at least 3 months. The test requires a computer running Windows 7. The test is written in R (free), but you don’t need to know R to use it. The installation requires details that I will need to handle by talking with you.

To find people to do this, I will use a bidding system. (Giving a program to those who ask for it is a waste of time, I have found.) The questions below ask for two bids: non-refundable and refundable. If you use it as promised — you set the details of how much you will use it — you get back the refundable amount.

If this interests you, please apply by sending an email to try.brain.tracking (at) gmail.com with answers to the following questions (as email text, not attachment):

  1. Name, age, sex, location, job.
  2. Computer you will use it on (e.g., Thinkpad 520), age of computer, operating system.
  3. Phone number (and Skype id, if any). I need to talk to you to set it up.
  4. Website or blog (if any).
  5. Any relevant expertise or experience? (e.g., work with computers, researcher, other self-tracking)
  6. Non-refundable amount. How much (U.S. dollars) are you willing to pay (via PayPal) to get this test?
  7. Over 3 months, on what fraction of days will you commit to doing the test at least once? at least twice?
  8. Refundable amount. This money will be refunded if you meet the goals you set in Question 7 and send me the data at least 6 times (spaced at least one week apart).
  9. Anything you want to add?

You will get an automated reply. After that, I will contact you only if I want more information or if yours is one of the winning bids.

 

 

Why Self-Track? The Possibility of Hard-to-Explain Change

Seth Roberts8 Comments

My personal science introduced me to a research method I have never seen used in research articles or described in discussions of scientific method. It might be called wait and see. You measure something repeatedly, day after day, with the hope that at some point it will change dramatically and you will be able to determine why. In other words: 1. Measure something repeatedly, day after day. 2. When you notice an outlier, test possible explanations. In most science, random (= unplanned) variation is bad. In an experiment, for example, it makes the effects of the treatment harder to see. Here it is good.

Here are examples where wait and see paid off for me:

1. Acne and benzoyl peroxide. When I was a graduate student, I started counting the number of pimples on my face every morning. One day the count improved. It was two days after I started using benzoyl peroxide more regularly. Until then, I did not think benzoyl peroxide worked well — I started using it more regularly because I had run out of tetracycline (which turned out not to work).

2. Sleep and breakfast. I changed my breakfast from oatmeal to fruit because a student told me he had lost weight eating foods with high water content (such as fruit). I did not lose weight but my sleep suddenly got worse. I started waking up early every morning instead of half the time. From this I figured out that any breakfast, if eaten early, disturbed my sleep.

3. Sleep and standing (twice). I started to stand a lot to see if it would cause weight loss. It didn’t, but I started to sleep better. Later, I discovered by accident that standing on one leg to exhaustion made me sleep better.

4. Brain function and butter. For years I measured how fast I did arithmetic. One day I was a lot faster than usual. It turned out to be due to butter.

5. Brain function and dental amalgam. My brain function, measured by an arithmetic test, improved over several months. I eventually decided that removal of two mercury-containing fillings was the likely cause.

6. Blood sugar and walking. My fasting blood sugar used to be higher than I would like — in the 90s. (Optimal is low 80s.) Even worse, it seemed to be increasing. (Above 100 is “pre-diabetic.”) One day I discovered it was much lower than expected (in the 80s). The previous day I had walked for an hour, which was unusual. I determined it was indeed cause and effect. If I walked an hour per day, my fasting blood sugar was much better.

This method and examples emphasize the point that different scientific methods are good at different things and we need all of them (in contrast to evidence-based medicine advocates who say some types of evidence are “better” than other types — implying one-dimensional evaluation). One thing we want to do is test cause-effect ideas (X causes Y). This method doesn’t do that at all. Experiments do that well, surveys are better than nothing. Another thing we want to do is assess the generality of our cause-effect ideas. This method doesn’t do that at all. Surveys do that well (it is much easier to survey a wide range of people than do an experiment with a wide range of people), multi-person experiments are better than nothing. A third thing we want to do is come up with cause-effect ideas worth testing. Most experiments are a poor way to do this, surveys are better than nothing. This method is especially good for that.

The possibility of such discoveries is a good reason to self-track. Professional scientists almost never use this method. But you can.

Lessons of SOPA: How a Slam Dunk Bill was Stopped

Seth Roberts2 Comments

Passage of SOPA (Stop Online Piracy Act) seemed inevitable. It was introduced with 40 Senate co-sponsors, including plenty of both Republicans and Democrats. (At the time it was called PIPA — Protect IP Act.) Senate passage requires 51 votes; to override a filibuster you need more. The entertainment industry (Hollywood) had spent hundreds of millions of dollars per year to pass such a bill; the people behind the lobbying felt the survival of their industry was at stake. Senator Patrick Leahy, whose office wrote the bill, is in the new Batman movie.

Yet SOPA was defeated.

The story, as I was told it, begins on a Sunday. The bill was scheduled for a vote on Wednesday, three days later. Peter Eckersley, who works at the Electronic Freedom Foundation in San Francisco, called Aaron Swartz, who lives in New York, to ask, “How are we going to defeat this?” At that point, Aaron hadn’t heard of it. Aaron’s talk about this.

It is a stunning example of David defeating Goliath. I asked Aaron what he learned from it. He told me three lessons:

1. Popular support matters. It can overcome large amounts of money. The anti-SOPA forces spent little money but got many people to tell their Congressman or Senator that they opposed the bill. The domain registrar GoDaddy reversed its position on the bill. Aaron worked with lobbyists for Google. The lobbyists believed, at least at first, that the bill could not be stopped, only weakened.

2. A little-known issue can be made a well-known issue. When SOPA was introduced, shortly before the scheduled vote, no one had heard of it. At MSNBC, and presumably other news organizations, employees were told not to cover it. When people at Google were approached to support the opposition, at first they said the bill couldn’t possibly be that bad or they would have heard of it. Without coverage by MSNBC etc., eventually everyone heard of it.

3. People will act if they can be convinced they are responsible. People at Wikipedia and Google, not to mention the originator of the GoDaddy boycott, were convinced to act, says Aaron, because they were convinced that they bore responsibility for the outcome, whatever it was. (I would put it differently. I would say they were convinced they could help determine the outcome.)

What interests me most about this story is how wrong the lobbyists were. They’re the experts in how to change/defeat legislation. They were utterly wrong. They understood the forces within their system but had no understanding of what was possible outside their system. I think healthcare experts will turn out to be equally wrong.

Assorted Links

Seth Roberts3 Comments

Thanks to Bryan Castañeda.