Category: quantified self movement

Why Quantified Self Matters

Seth Roberts2 Comments

Why Quantified Self Matters is the title of a talk I gave yesterday at a Quantified Self conference in Beijing. I gave six examples of things I’d discovered via self-tracking and self-experiment (self-centered moi?), such as how to lose weight (the Shangri-La Diet) and be in a better mood. I said that the Quantified Self movement matters because it supports that sort of thing, i.e., personal science, which has several advantages over professional science. The Quantified Self movement supports learning from data, in contrast to trusting experts.

If I’d had more time, I would have said that personal science and professional science have different strengths. Personal science is good at both the beginning of research (when a new idea has not yet been discovered) and the end of research (when a new idea, after having been confirmed, is applied in everyday life). It is a good way to come up with plausible new ideas and a good way to develop them (assess their plausibility when they are still not very plausible, figure out the best dose, the best treatment details). That’s the beginning of research. Personal science is also a good way to take accepted ideas and apply them in everyday life (e.g., a medical treatment, an idea about deficiency disease) because it fully allows for human diversity (e.g., a medicine that works for most people doesn’t work for you, you have an allergy, whatever). That’s the end of research.

Professional science works well, better than personal science, when an idea is in a middle range of plausibility — quite plausible but not yet fully accepted. At that point it fits a professional scientist’s budget. Their research must be expensive (Veblen might have coined the term conspicuous research, in addition to “conspicuous consumption” and “conspicuous leisure”) and only quite plausible ideas are worth expensive tests. It also fits their other needs, such as avoidance of “crazy” ideas and a steady stream of publishable results (because ideas that are quite plausible are likely to produce usable results when tested). Professional science is also better than personal science for studying all sorts of “useless” topics. They aren’t actually useless but the value is too obscure and perhaps the research too expensive for people to study them on their own (e.g., I did research on how rats measure time).

In other words, the Quantified Self movement matters because it gives all of us a new scientific tool. A way to easily see where the scientific tools we already have cannot easily see.

 

 

Measuring Yourself to Improve Your Health? Want to Guest-Blog?

Seth Roberts6 Comments

What surprised me most about my self-experimental discoveries was that they were outside my area of expertise (animal learning). I discovered how to sleep better but I’m not a sleep researcher. I discovered how to improve my mood but I’m not a mood researcher. I discovered that flaxseed oil improved brain function but I’m not a nutrition researcher. And so on. This is not supposed to happen. Chemistry professors are not supposed to advance physics. Long ago, this rule was broken. Mendel was not a biologist, Wegener (continental drift) was not a geologist. It hasn’t been broken in the last 100 years. As knowledge increases, the “gains due to specialization” — the advantage of specialists over everyone else within their area of expertise — is supposed to increase. The advantage, and its growth, seem inevitable. It occurs, say economists, because specialized knowledge (e.g., what physicists know that the rest of us, including chemists, don’t know) increases. My theory of human evolution centers on the idea that humans have evolved to specialize and trade. In my life I use thousands of things made by specialists that I couldn’t begin to make myself.

Here we have two things. 1. A general rule (specialists have a big advantage, within their specialty, over the rest of us) that is overwhelmingly true. 2. An exception (my work). How can this be explained? What can we learn from it? I’ve tried to answer these questions but I can add to what I said in that paper. The power of specialization is clearly enormous. Adam Smith, who called specialization “division of labor”, was right. The existence of an exception to the general rule suggests there are forces pushing in the opposite direction (toward specialists being worse than the rest of us in their area of expertise) that can be more powerful than the power of specialization. Given the power of specialization, the countervailing forces must be remarkably strong. Can we learn more about them? Can we harness them? Can we increase them? The power of specialization has been increasing for thousands of years. How strong the countervailing forces may become is unclear.

The more you’ve read this blog, the more you know what I think the countervailing forces are. Some of them weaken specialists: 1. Professors prefer to be useless rather than useful (Veblen). 2. A large fraction (99%?) of health care workers have no interest in remedies that do not allow them to make money. 3. Medical school professors are terrible scientists. 4. Restrictions on research. Some of them strengthen the rest of us: 1. Data storage and analysis have become very cheap. 2. It is easier for non-scientists to read the scientific literature. 3. No one cares more about your health than you. These are examples. The list could be much longer. What’s interesting is not the critique of health care, which is pretty obvious, but the apparent power of these forces, which isn’t obvious at all.

I want to learn more about this. I want learn how to use these opposing forces and, if possible, increase them. One way to do this is find more exceptions to the general rule, that is, find more people who have improved their health beyond expert advice. I have found some examples. To find more, to learn more about them, and to encourage this sort of thing (DIY Health), I offer the opportunity to guest-blog here.

I think the fundamental reason you can improve on what health experts tell you is that you can gather data. Health experts have weakened their position by ignoring vast amounts of data. Three kinds of data are helpful: (a) other people’s experiences, (b) scientific papers and (c) self-measurement (combined with self-experimentation). No doubt (c) is the hardest to collect and the most powerful. I would like to offer one or more people the opportunity to guest-blog here about what happens when they try to do (c). In plain English, I am looking for people who are measuring a health problem and trying to improve on expert advice. For example, trying to lower blood pressure without taking blood pressure medicine. Or counting pimples to figure out what’s causing your acne. Or measuring your mood to test alternatives to anti-depressants. I don’t care what’s measured, so long as it is health-related. (Exception: no weight-loss stories) and you approach these measurements with an open mind (e.g., not trying to promote some product or theory). I am not trying to collect success stories. I am trying to find out what happens when people take this approach.

Guest-blogging may increase your motivation, push you to think more (“ I blog, therefore I think“) and give you access to the collective wisdom of readers of this blog (in the comments). If guest-blogging about your experiences and progress (or lack of it) might interest you, contact me with details of what you are doing or plan to do.

Assorted Links

Seth Roberts1 Comment

Thanks to Dave Lull.

Quantified Self Utopia: What Would It Look Like?

Seth Roberts1 Comment

On the QS forums, Christian Kleineidam asked:

While doing Quantified Self public relations I lately meet the challenge of explaining how our lives are going to change if everything in QS goes the way we want. A lot of what I do in quantified self is about boring details. . . . Let’s imagine a day 20 years in the future and QS is successful. How will that day be different than [now]?

Self-measurement has helped me two ways. One is simple and clear. It has helped me be healthy. Via QS, I have found new ways to sleep better, lose weight, be in a better mood, have fewer colds (due to better immune function), reduce inflammation in my body, have better balance, have a better-functioning brain, have better blood sugar, and so on. I am not an expert in any of these areas — I am not a professional sleep researcher, for example. I believe that this will be a large part of the long-term importance of QS: it will help non-experts make useful discoveries about health and it will help spread those discoveries. Non-experts have important advantages over professional researchers. The non-experts (the personal scientists) are only concerned with helping themselves, not with pleasing their colleagues or winning grants, promotions, or prizes; they can take as long as necessary; and they can test “crazy” ideas. In a QS-successful world, many non-experts would make such discoveries and what they learned would reach a wide audience. Lots of people would know about them and take them seriously. As a result, people would be a lot healthier.

Self-measurement has also helped me in a more subtle way. It made me believe I have more power over my health than I thought. This change began when I studied my acne. I did not begin with any agenda, any point I wanted to make, I just wanted to practice experimentation. I counted my pimples (the QS part) and did little experiments. My results showed that one of the drugs my dermatologist had prescribed (tetracycline, an antibiotic) didn’t work. My dermatologist hadn’t said this was possible. Either he had done nothing to learn if worked or he had reached the wrong answer. What stunned me was how easy it had been to find out something important a well-trained experienced expert didn’t know. My dermatologist was not an original thinker. He did what he was told to do by med school professors (antibiotics are a very common treatment for acne). It was the fact that I could improve on their advice that stunned me. I didn’t have a lab. I didn’t have a million-dollar grant. Yet I had learned something important about acne that dermatology professors with labs and grants had failed to learn (antibiotics may not work, be sure to check).

Skepticism about mainstream medicine is helpful, yes, but only a little bit. More useful is finding a better way. For example, it’s useful to point out that antidepressants don’t work well. It’s more useful to find new ways to combat depression. Two years ago, the psychiatrist Daniel Carlat came out with a book called Unhinged that criticized modern psychiatry: too much reliance on pills. No kidding. Carlat recommended more talk therapy, as if that worked so well. As far as I could tell, Carlat had no idea that you need better research to find better solutions and had no idea what better research might be. This is where QS comes in. By encouraging people to study themselves, it encourages study of a vast number of possible depression treatments that will never (or not any time soon) be studied by mainstream researchers. By providing a way to publicize what people learn by doing this, it helps spread encouraging results. In the case of depression, I found that seeing faces in the morning produced an oscillation in my mood (high during the day, low at night). This has obvious consequences for treating depression. This sort of thing will not be studied by mainstream researchers any time soon but it can easily be studied by someone tracking their mood.

In a QS-successful world, many people would have grasped the power that they have to improve their own health. (You can’t just measure yourself, you have to do experiments and choose your treatments wisely, but measuring yourself is a good start.) They would have also grasped the power they have to improve other people’s health because (a) they can test “crazy” solutions mainstream researchers will never test, (b) they can run more realistic tests than mainstream researchers, (c) they can run longer tests than mainstream researchers, and (d) no matter what the results, they can publicize them. In a QS-successful world, there will be a whole ecosystem that supports that sort of thing. Such an ecosystem is beginning to grow, no doubt about it.

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.

Assorted Links

Seth Roberts3 Comments

Thanks to Bryan Castañeda and Alex Chernavsky.

Assorted Links

Seth Roberts3 Comments

Thanks to Bryan Castañeda.

Assorted Links

Seth Roberts5 Comments

Thanks to Anne Weiss.

The Non-Obvious Value of Self-Tracking

Seth Roberts5 Comments

A New York doctor named Jay Parkinson is skeptical about the appeal of self-measurement:

There is a very, very small subset of people who want to document their life according to their health— the quantified selfers. But this group is tiny because it’s just data geeks who are obsessed with data. They are people who truly believe data changes behavior.

As caricatures go, this is fair. The audience and speakers at Quantified Self meetups do appear to be “data geeks who are obsessed with data” and, yes, this is a tiny subset of people. I don’t put myself in that category. I have zero interest in “documenting” my life. I record a tiny amount of stuff and only stuff I think will make a difference. For example, I stopped measuring my blood pressure after it became clear it was low enough.

Parkinson continues:

Data gets old after a while. After about a month, for those who are not obsessed, it becomes meaningless. That is, unless you have an obsession with data. . . . Good luck trying to build a viable business around that group.

Yes, and “there is a world market for about five computers”, as the president of IBM supposedly said in the 1940s. I have measured myself for so long (decades) not because I am obsessed with data but because I reaped huge benefits. In the beginning, self-measurement showed me how to reduce my acne considerably more than my dermatologist’s advice alone. Later it led to all sorts of improvements: better sleep, better mood, lower weight, fewer colds, healthier gums, better balance, better brain function. Life-changing benefits. The fraction of adults who would like to sleep better, be in a better mood, lose weight, get fewer colds, and so on is very large — perhaps 99%. Is Starbucks a “viable business”? It is built around people needing stimulants (caffeine). An enormous number of products and services are about losing weight. One of the world’s most “viable business” is illicit drugs. I believe a large fraction of illicit drug use is self-medication for depression. (More: The day I posted this, I came across this: “She said heroin helped her fight depression.”)

There is nothing obvious about how I managed to improve my sleep, mood, weight and so on. The solutions I discovered via self-measurement were exceedingly surprising, at least to me. So there is nothing obvious about how to use self-measurement to improve one’s sleep, etc. Self-measurement is needed, yes, but it’s not the only thing that’s needed. I needed: 1. Wise choice of what to measure (e.g., measure the problem, not the solution — I don’t have a FitBit for example.) 2. Wise choice of what to change. (To improve my sleep, for example, I needed a good understanding of sleep research. “Common sense” was not enough.) 3. Experimental design skill. 4. Data analysis skill. To say data is boring (to most people) is like saying tires are boring (to most people). By themselves, tires have little use, just as data alone has little use. But they are part of something very useful.

Consider literacy. For a long time, the notion that “everyone would benefit from literacy” seemed ridiculous. Books were too expensive! There were so few of them. Only a tiny fraction of people (e.g., monks) knew how to read. It was hard to learn to read. Good luck basing a business on literacy! But eventually everything changed. Right now, few quantified selfers, as far as I can tell, seem to know how to learn something useful from their measurements. (When I had been doing it for a short time, I didn’t know either.) For example, Stephen Wolfram appears to have learned nothing of use from a huge amount of self-measurement. New measurement devices, like FitBit and so on, are like books — it is as if few people know how to read. But that can change.