Monthly Archives: November 2016

A Return to Discussion

Epistemic Status: Casual

It’s taken me a long time to fully acknowledge this, but people who “come from the internet” are no longer a minority subculture.  Senators tweet and suburban moms post Minion memes. Which means that talking about trends in how people socialize on the internet is not a frivolous subject; it’s relevant to how people interact, period.

There seems to have been an overall drift towards social networks as opposed to blogs and forums, and in particular things like:

  • the drift of political commentary from personal blogs to “media” aggregators like The Atlantic, Vox, and Breitbart
  • the migration of fandom from LiveJournal to Tumblr
  • The movement of links and discussions to Facebook and Twitter as opposed to link-blogs and comment sections

At the moment I’m not empirically tracking any trends like this, and I’m not confident in what exactly the major trends are — maybe in future I’ll start looking into this more seriously. Right now, I have a sense of things from impression and hearsay.

But one thing I have noticed personally is that people have gotten intimidated by more formal and public kinds of online conversation.  I know quite a few people who used to keep a “real blog” and have become afraid to touch it, preferring instead to chat on social media.  It’s a weird kind of locus for perfectionism — nobody ever imagined that blogs were meant to be masterpieces.  But I do see people fleeing towards more ephemeral, more stream-of-consciousness types of communication, or communication that involves no words at all (reblogging, image-sharing, etc.)  There seems to be a fear of becoming too visible as a distinctive writing voice.

For one rather public and hilarious example, witness Scott Alexander’s  flight from LessWrong to LiveJournal to a personal blog to Twitter and Tumblr, in hopes that somewhere he can find a place isolated enough that nobody will notice his insight and humor. (It hasn’t been working.)

What might be going on here?

Of course, there are pragmatic concerns about reputation and preserving anonymity. People don’t want their writing to be found by judgmental bosses or family members.  But that’s always been true — and, at any rate, social networking sites are often less anonymous than forums and blogs.

It might be that people have become more afraid of trolls, or that trolling has gotten worse. Fear of being targeted by harassment or threats might make people less open and expressive.  I’ve certainly heard many writers say that they’ve shut down a lot of their internet presence out of exhaustion or literal fear.  And I’ve heard serious enough horror stories that I respect and sympathize with people who are on their guard.

But I don’t think that really explains why one would drift towards more ephemeral media. Why short-form instead of long-form?  Why streaming feeds instead of searchable archives?  Trolls are not known for their patience and rigor.  Single tweets can attract storms of trolls.  So troll-avoidance is not enough of an explanation, I think.

It’s almost as though the issue were accountability.  

A blog is almost a perfect medium for personal accountability. It belongs to you, not your employer, and not the hivemind.  The archives are easily searchable. The posts are permanently viewable. Everything embarrassing you’ve ever written is there.  If there’s a comment section, people are free to come along and poke holes in your posts. This leaves people vulnerable in a certain way. Not just to trolls, but to critics.

You can preempt embarrassment by declaring that you’re doing something shitty on purpose. That puts you in a position of safety.  You move to a space for trashy, casual, unedited talk, and you signal clearly that you don’t want to be taken seriously, in order to avoid looking pretentious and being deflated by criticism.  I think that a lot of online mannerisms, like using all-lowercase punctuation, or using really self-deprecating language, or deeply nested meta-levels of meme irony, are ways of saying “I’m cool because I’m not putting myself out there where I can be judged.  Only pompous idiots are so naive as to think their opinions are actually valuable.”

Here’s another angle on the same issue.  If you earnestly, explicitly say what you think, in essay form, and if your writing attracts attention at all, you’ll attract swarms of earnest, bright-but-not-brilliant, mostly young white male, commenters, who want to share their opinions, because (perhaps naively) they think their contributions will be welcomed. It’s basically just “oh, are we playing a game? I wanna play too!”  If you don’t want to play with them — maybe because you’re talking about a personal or highly technical topic and don’t value their input, maybe because your intention was just to talk to your friends and not the general public, whatever — you’ll find this style of interaction aversive.  You’ll read it as sealioning. Or mansplaining.  Or “well, actually”-ing.  And you’ll gravitate to forms of writing and social media where it’s clear that debate is not welcome.

I think what’s going on with these kinds of terms is something like:

Author: “Hi! I just said a thing!”

Commenter: “Ooh cool, we’re playing the Discussion game! Can I join?  Here’s my comment!”  (Or, sometimes, “Ooh cool, we’re playing the Verbal Battle game!  I wanna play! Here’s my retort!”)

Author: “Ew, no, I don’t want to play with you.”

There’s a bit of a race/gender/age/educational slant to the people playing the “commenter” role, probably because our society rewards some people more than others for playing the discussion game.  Privileged people are more likely to assume that they’re automatically welcome wherever they show up, which is why others tend to get annoyed at them and want to avoid them.

Privileged people, in other words, are more likely to think they live in a high-trust society, where they can show up to strangers and be greeted as a potential new friend, where open discussion is an important priority, where they can trust and be trusted, since everybody is playing the “let’s discuss interesting things!” game.

The unfortunate reality is that most of the world doesn’t look like that high-trust society.

On the other hand, I think the ideal of open discussion, and to some extent the past reality of internet discussion, is a lot more like a high-trust society where everyone is playing the “discuss interesting things” game, than it is like the present reality of social media.

A lot of the value generated on the 90’s and early 2000’s internet was built by people who were interested in things, sharing information about those things with like-minded individuals.  Think of the websites that were just catalogues of information about someone’s obsessions. (I remember my family happily gathering round the PC when I was a kid, to listen to all the national anthems of the world, which some helpful net denizen had collated all in one place.)  There is an enormous shared commons that is produced when people are playing the “share info about interesting stuff” game.  Wikipedia. StackExchange. It couldn’t have been motivated by pure public-spiritedness — otherwise people wouldn’t have produced so much free work.  There are ordinary, human, social motivations for this kind of engagement: the desire to show off how clever you are, the desire to be a know-it-all, the desire to correct other people — and their more positive cousins, such as obsession, fascination, and the delight of infodumping. Communication based on sharing interesting things isn’t some higher plane of civic virtue; it’s just ordinary nerd behavior.

But in ordinary nerd behavior, there are some unusual strengths.  Nerds are playing the “let’s have discussions!” game, which means that they’re unembarrassed about sharing their take on things, and unembarrassed about holding other people accountable for mistakes, and unembarrassed about being held accountable for mistakes.  It’s a sort of happy place between perfectionism and laxity.  Nobody is supposed to get everything right on the first try; but you’re supposed to respond intelligently to criticism. Things will get poked at, inevitably.  Poking is friendly behavior. (Which doesn’t mean it’s not also aggressive behavior.  Play and aggression are always intermixed.  But it doesn’t have to be understood as scary, hostile, enemy.)

The advantage of this attitude is that it’s a healthier environment for critical thinking. It’s not nearly enough to get you to a rational utopia beyond bias, of course, but it allows errors to get corrected at all, which is important in an age of abundant misinformation.  And it motivates producing interesting original content, which is how you get the raw material for a shared community knowledge repository.

Nerd-format discussions are definitely not costless. You’ll get discussions of advanced/technical topics being mobbed by clueless opinionated newbies, or discussions of deeply personal issues being overrun by clueless opinionated randos.  You’ll get endless debate over irrelevant minutiae. There are reasons why so many people flee this kind of environment.

But I would say that these disadvantages are necessary evils that, while they might be possible to mitigate somewhat, go along with having a genuinely public discourse and public accountability.

We talk a lot about social media killing privacy, but there’s also a way in which it kills publicness, by allowing people to curate their spaces by personal friend groups, and retreat from open discussions.   In a public square, any rando can ask an aristocrat to explain himself.  If people hide from public squares, they can’t be exposed to Socrates’ questions.

I suspect that, especially for people who are even minor VIPs (my level of online fame, while modest, is enough to create some of this effect), it’s tempting to become less available to the “public”, less willing to engage with strangers, even those who seem friendly and interesting.  I think it’s worth fighting this temptation.  You don’t get the gains of open discussion if you close yourself off.  You may not capture all the gains yourself, but that’s how the tragedy of the commons works; a bunch of people have to cooperate and trust if they’re going to build good stuff together.  And what that means, concretely, on the margin, is taking more time to explain yourself and engage intellectually with people who, from your perspective, look dumb, clueless, crankish, or uncool.

Some of the people I admire most, including theoretical computer scientist Scott Aaronson, are notable for taking the time to carefully debunk crackpots (and offer them the benefit of the doubt in case they are in fact correct.)  Is this activity a great ROI for a brilliant scientist, from a narrowly selfish perspective?  No. But it’s praiseworthy, because it contributes to a truly open discussion. If scientists take the time to investigate weird claims from randos, they’re doing the work of proving that science is a universal and systematic way of thinking, not just an elite club of insiders.  In the long run, it’s very important that somebody be doing that groundwork.

Talking about interesting things, with friendly strangers, in a spirit of welcoming open discussion and accountability rather than fleeing from it, seems really underappreciated today, and I think it’s time to make an explicit push towards building places online that have that quality.

In that spirit, I’d like to recommend LessWrong to my readers. For those not familiar with it, it’s a discussion forum devoted to things like cognitive science, AI, and related topics, and, back in its heyday a few years ago, it was suffused with the nerdy-discussion-nature. It had all the enthusiasm of late-night dorm-room philosophy discussions — except that some of the people you’d be having the discussions with were among the most creative people of our generation.  These days, posting and commenting is a lot sparser, and the energy is gone, but I and some other old-timers are trying to rekindle it. I’m crossposting all my blog posts there from now on, and I encourage everyone to check out and join the discussions there.

 

Industry Matters 2: Partial Retraction

Epistemic status: still tentative

Some useful comments on the last post on manufacturing have convinced me of some weaknesses in my argument.

First of all, I think I was wrong that most manufacturing job loss is due to trade. There are several economic analyses, using different methods, that come to the conclusion that a minority of manufacturing jobs are lost to trade, with most of the remainder lost to labor productivity increases.

Second of all, I want to refine my argument about productivity.

Labor productivity and multifactor productivity in manufacturing, as well as output, have grown steadily throughout the 20th century — but they are slowing down. The claim “we are making more things than ever before in America” is literally true, but there is also stagnation.

It’s also true that manufacturing employment has dropped slowly through the 70’s and 80’s until today.  This is plausibly due to improvements in labor productivity.

However, the striking, very rapid decline of manufacturing employment post-2000, in which half of all manufacturing jobs were lost in fifteen years, looks like a different phenomenon. And it does correspond temporally to a drop in output growth and productivity growth.  It also corresponds temporally to the establishment of normal trade relations with China, and there is more detailed evidence that there’s a causal link between job loss and competition with China.

My current belief is that the long-term secular decline in manufacturing employment is probably just due to the standard phenomenon where better efficiency leads to employing fewer workers in a field, the same reason that there are fewer farmers than there used to be.

However, something weird seems to have happened in 2000, something that hurt productivity growth.  It might be trade.  It might be some kind of “stickiness” effect where external shocks are hard to recover from, because there’s a lot of interdependence in industry, and if you lose one firm you might lose the whole ecosystem.  It might be some completely different thing. But I believe that there is a post-2000 phenomenon which is not adequately explained by just “higher productivity causes job loss.”

Most manufacturing job loss is due to productivity; only a minority is due to trade

David Autor‘s economic analysis concluded that trade with China contributed 16% of the US manufacturing employment decline between 1990 and 2000, 26% of the decline between 2000 and 2007, and 21% over the full period.  He came to this conclusion by looking at particular manufacturing regions in the US, looking at their exposure to Chinese imports in the local industry, and seeing how much employment declined post-2000.  Regions with more import exposure had higher job loss.

Researchers at Ball State University also concluded that trade was responsible for a minority of manufacturing job loss during the period 2000-2010: 13.4% due to trade, and 87.8% due to manufacturing productivity growth.  This was calculated using import numbers and productivity numbers from the U.S. Census and the Bureau of Labor Statistics, under the simple model that the change in employment is a linear combination of the change in domestic consumption, the change in imports, the change in exports, and the change in labor productivity.

Josh Bivens of the Economic Policy Institute, using the same model as the Ball State economists, computes that imports were responsible for 21.15% of job losses between 2000 and 2003, while productivity growth was responsible for 84.32%.

Justin Pierce and Peter Schott of the Federal Reserve Board observe that industries where the 2000 normalization of trade relations with China would have increased imports the most were those that had the most job loss. Comparing job loss in above-median impact-from-China industries vs. below-median impact-from-China industries, the difference in job loss accounts for about 29% of the drop in manufacturing employment from 2000 to 2006.

I wasn’t able to find any economic analyses that argued that trade was responsible for a majority of manufacturing job losses. It seems safe to conclude that most manufacturing job loss is due to productivity gains, not trade.

It’s also worth noting that NAFTA doesn’t seem to have cost manufacturing jobs at all.

Productivity and output are growing, but have slowed since 2000.

Real output in manufacturing is growing, and has been since the 1980’s, but there are some signs of a slowdown.

Researchers at the Economic Policy Institute claim that slowing manufacturing productivity growth and output growth around 2000 led to the sharp drop in employment.  If real value added in manufacturing had continued growing at the rate it had been in 2000, it would be 1.4x as high today.

Manufacturing output aside from computers and electronic products has been slow-growing since the 90’s.  The average annual output growth rate, 1997-2015, in manufacturing, was 12% in computers, but under 4% in all other manufacturing sectors. (The next best was motor vehicles, at 3% output growth rate.)

US motor vehicle production has been growing far more slowly than global motor vehicle production.

Here are some BLS numbers on output in selected manufacturing industries:

As an average over the time period, this growth rate represents about 2.5%-3.5% annual growth, which is roughly in line with GDP growth.  So manufacturing output growth averaged since the late 80’s isn’t unusually bad.

Labor productivity has also been rising in various industries:

However, when we look at the first and second derivatives of output and productivity, especially post-2000, the picture looks worse.

Multifactor productivity seems to have flattened in the mid-2000’s, and multifactor productivity growth has dropped sharply.  Currently, multifactor productivity is actually dropping.

Manufacturing labor productivity growth is positive, but lower than it’s been historically, at about 0.45% in 2014, and a 4-year moving average of 2.1%, compared to 3-4% growth in the 90’s.

Multifactor productivity in durable goods is down in absolute terms since about 2000 and hasn’t fully recovered.

(Multifactor productivity refers to the returns to labor and capital. If multifactor productivity isn’t growing, then while we may be investing in more capital, it’s not necessarily better capital.)

Labor productivity growth in electronics is dropping and has just become negative.

Labor productivity growth in the auto industry is staying flat at about 2%.

Manufacturing output growth has dropped very recently, post-recession, to about 0. From the 80’s to the present, it was about steady, at roughly 1%.  By contrast, global manufacturing growth is much higher: 6.5% in China, 1.9% globally.  And US GDP growth is about 2.5% on average.

In some industries, like auto parts and textiles,  raw output has dropped since 2000. (Although, arguably, these are lower-value industries and losing output there could just be a sign that the US is moving up the value chain.)

Looking back even farther, there is a slowdown in multifactor productivity growth in manufacturing, beginning in the early 70’s. Multifactor productivity grew by 1.5% annually from 1949-1973, and only by 0.3% in 1973-1983.  Multifactor productivity growth today isn’t clearly unprecedentedly low, but it’s dropping to the levels of stagnation we saw in the 1970’s, or even below.

Basically, recent labor productivity is positive but not growing and in some cases dropping; output is growing slower than GDP; and multifactor productivity is dropping. This points to there being something to worry about.

What might be going on?

Economist Jared Bernstein argues that automation doesn’t explain the whole story of manufacturing job loss. If you exclude the computer industry, manufacturing output is only about 8% higher than it was in 1997, and lower than it was before the Great Recession.  The growth in manufacturing output has been “anemic.”  He says that factory closures have large spillover effects. Shocks like the rise of China, or a global glut of steel in the 1980’s, lead to US factory closures; and then when demand recovers, the US industries don’t.

This model also fits with the fact that proximity matters a lot.  It’s valuable, for knowledge-transfer reasons, to build factories near suppliers.  So if parts manufacturing moves overseas, the factories that assemble those parts are likely to relocate as well. It’s also valuable, due to shipping costs, to locate manufacturing near to expensive-to-ship materials like steel or petroleum.  And, also as a result of shipping costs, it’s valuable to locate manufacturing in places with good transportation infrastructure. So there can be stickiness/spillover effects, where, once global trade makes it cheaper to make parts and raw materials in China, there’s incentives pushing higher-value manufacturing to relocate there as well.

It doesn’t seem to be entirely coincidence that the productivity slowdown coincided with the opening of trade with China. The industries where employment dropped most after 2000 were those where the risk of tariffs on Chinese goods dropped the most.

However, this story is still consistent with the true claim that most lost manufacturing jobs are lost to productivity, not trade. Multifactor productivity may be down and output and labor productivity may be slowing, but output is still growing, and that growth is still big enough to drive most job loss.

Vestibular Stimulation and Fat Loss

It is a strange but well replicated fact, that if you leave small animals in a centrifuge for a really long time, they lose a lot of fat.  Many of these experiments were done in the 1960’s and 1970’s as part of the study of the physiological effects of spaceflight.

Centrifugation makes animals smaller, leaner, more muscular, and denser-boned

If you put female rats in a centrifuge for 60 days, at 2.76 and 4.15 G (where G is the strength of Earth’s gravitational field), they lose 10% and 19% of their body weight, respectively, with reductions in the fat fractions of most components and increases in the water fraction of liver and gut.[1]

Female rats exposed to 3.5 or 4.7 G for one year showed “marked depletion of body-fat depots” and “significant decrease in kidney and liver lipids.”[2]

Chickens exposed to 1.75, 2.5, or 3 G for 24 weeks had significantly reduced body fat.[15]  The drop in body fat is linearly increasing in G, and also increases with body mass.[17]

Rabbits exposed to up to 2.5 G had a drop in body fat and increase in body water, even as their food consumption increased.[16]

Female rats centrifuged for 30 days at 2.76 or 3.18 G reduced body fat and fat-free body mass within the first week of centrifugation, without any difference depending on whether they were fed commercial chow, a high-fat diet, a high-protein diet, or fasted.[3]

The drop in body fat from centrifugation can be quite large; chickens went from 13% body fat to 3% body fat at 3G, and mice have a 55% drop in total body fat after 8 weeks of 2G exposure.[18]

Centrifuged mice have a drop in weight during the first few days, but slowly regain it.[10]  Hamsters born in centrifuges have a final body weight of about 30% lower than control hamsters.[13]

Female rats centrifuged for 810 days at 2.76 G grew more slowly than control rats, but had the same absolute muscle mass; they have thicker bones and larger muscles for their size than uncentrifuged rats.[4]  They also have denser bones.[6]  They have a higher proportion of slow-oxidating muscle fibers (the kind used in distance running and other endurance activities).[9]  Centrifuged dogs (subjected to 2G for 3 months) also have denser bones.[11]

Centrifuged rats also had more uptake of glucose into tissues and a stronger response to insulin than uncentrifuged rats; this is the opposite of “insulin resistance.”[5]  Centrifuged chickens also have higher glucose uptake.[14]

Centrifuged rats have a sharp decrease in body temperature at about 3 days, and a subsequent recovery of normal body temperature.[7]

Centrifuged rats have a prolonged decrease in locomotor activity and distorted circadian rhythms.[8]

Centrifugation alters the vestibular system

The vestibular system is involved in balance.

The microscopic structure of the lateral vestibular nucleus (where many vestibular nerve fibers enter the brain) is altered in chronically centrifuged rats.[12]  Centrifuged hamsters have impaired balance during swimming tests.[13]

Knockout mice that lack vestibular linear acceleration organs are known as “head-tilt mice.” They move normally, except for a head tilt, but cannot swim because they cannot orient to the gravitational force vector.  Head-tilt mice, when centrifuged at 2G, do not experience the changes that chronic centrifugation causes in wild-type mice: they do not have a drop in body temperature, body mass, or body fat percentage. While wild-type mice under 2G dropped from 16% to 8% body fat, head-tilt mice started out at 8% before centrifugation and did not change.  This implies that vestibular effects somehow cause the physiological changes associated with higher gravity.

Artificially stimulating the vestibular organs causes fat loss

A pilot study at the University of California San Diego’s Center for Brain and Cognition, one of whose authors was famed neuroscientist Vilayanur Ramachandran, tested galvanic stimulation of the vestibular nerves, a non-invasive procedure that involves passing current over the inner ear, on six overweight and obese subjects, with three controls, for a total of 40 hours, for an hour a day.  There was a significant 8.3% decrease in truncal fat and a nonsignificant decrease in total body fat.  Appetite was reduced, leptin was reduced, and insulin was increased.[19]

This is not a huge reduction in fat.  (It would be something like two pounds on me, over the course of a month.) On the other hand, this is a significantly lower “dose” of vestibular stimulation than centrifuged animals would receive. The animals that had body composition changes were centrifuged continuously over a period of months.  It may be possible to slowly increase the time spent receiving galvanic stimulation.

Vestibular stimulation may affect hormone levels

There are a few case studies from India of “controlled vestibular stimulation” (swinging on a swing) causing various changes in physiology. A college student for whom swinging resulted in significantly lower blood pressure, blood glucose, and cortisol[21], and an 83-year-old diabetic man for whom swinging resulted in significantly lower glucose and blood pressure [22].

The vestibular system modulates autonomic activity, and vestibular stimulation activates vagus nerves in the pancreas which stimulate insulin production. There seems to be a parasympathetic response to vestibular stimulation, which goes with increased insulin production and lower hunger, both of which would reduce fat.  (It also matches the intuitive observation that rocking and swinging is soothing: think of infants and rocking chairs.)

Other Vestibular Stimulation Weirdness

Galvanic vestibular stimulation also seems to reverse face blindness [23].

Conclusion

Galvanic vestibular stimulation is safe, if sometimes uncomfortable (causes motion sickness), and might have significant effects on body fat and other metabolic factors. It is probably worth investigating more on humans.

It’s trivial to set up; people who are interested in virtual reality frequently build their own vestibular stimulation rigs to increase the verisimilitude of immersive games.  This seems like something with a lot of potential for venturesome self-experimenters to try out as well as something to investigate seriously in clinical experiments.

References

[1]Pitts, G. C., L. S. Bull, and J. Oyama. “Effect of chronic centrifugation on body composition in the rat.” American Journal of Physiology–Legacy Content 223.5 (1972): 1044-1048.

[2]Oyama, J., and B. Zeitman. “Tissue composition of rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 213.5 (1967): 1305-1310.

[3]Pitts, G. C., L. S. Bull, and J. Oyama. “Regulation of body mass in rats exposed to chronic acceleration.” American Journal of Physiology–Legacy Content 228.3 (1975): 714-717.

[4]Amtmann, Eduard, and Jiro Oyama. “Effect of chronic centrifugation on the structural development of the musculoskeletal system of the rat.” Anatomy and embryology 149.1 (1976): 47-70.

[5]Daligcon, B. C., and J. Oyama. “Increased uptake and utilization of glucose by diaphragms of rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 228.3 (1975): 742-746.

[6]Jaekel, Erika, Eduard Amtmann, and Jiro Oyama. “Effect of chronic centrifugation on bone density of the rat.” Anatomy and embryology 151.2 (1977): 223-232.

[7]Oyama, J. I. R. O., WILLIAM T. Platt, and VARD B. Holland. “Deep-body temperature changes in rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 221.5 (1971): 1271-1277.

[8]Holley, Daniel C., et al. “Chronic centrifugation (hypergravity) disrupts the circadian system of the rat.” Journal of Applied Physiology 95.3 (2003): 1266-1278.

[9]Martin, W. D. “Time course of change in soleus muscle fibers of rats subjected to chronic centrifugation.” Aviation, space, and environmental medicine 49.6 (1978): 792-797.

[10]WUNDER, CHARLES C. “Survival of mice during chronic centrifugation.” Aerospace Med 33 (1962): 866-870.

[11]Amtmann, Eduard, Jiro Oyama, and Gerald L. Fisher. “Effect of chronic centrifugation on the musculoskeletal system of the dog.” Anatomy and embryology 149.1 (1976): 71-78.

[12]Johnson, J. E., W. R. Mehler, and J. Oyama. “The effects of centrifugation on the morphology of the lateral vestibular nucleus in the rat: a light and electron microscopic study.” Brain research 106.2 (1976): 205-221.

[13]Sondag, H. N. P. M., H. A. A. De Jong, and W. J. Oosterveld. “Altered behaviour in hamsters conceived and born in hypergravity.” Brain research bulletin 43.3 (1997): 289-294.

[14]Evans, J. W., and J. M. Boda. “Glucose metabolism and chronic acceleration.” American Journal of Physiology–Legacy Content 219.4 (1970): 893-896.

[15]Evans, J. W., A. H. Smith, and J. M. Boda. “Fat metabolism and chronic acceleration.” American Journal of Physiology–Legacy Content 216.6 (1969): 1468-1471.

[16]Katovich, MICHAEL J., and ARTHUR H. Smith. “Body mass, composition, and food intake in rabbits during altered acceleration fields.” Journal of Applied Physiology 45.1 (1978): 51-55.

[17]Smith, A. H., P. O. Sanchez, and R. R. Burton. “Gravitational effects on body composition in birds.” Life sciences and space research 13 (1974): 21-27.

[18]Fuller, Patrick M., et al. “Neurovestibular modulation of circadian and homeostatic regulation: vestibulohypothalamic connection?.” Proceedings of the National Academy of Sciences 99.24 (2002): 15723-15728.

[19]McGeoch, Paul D., Jason McKeown, and Vilayanur S. Ramachandran. “Modulation of Body Mass Composition using Vestibular Nerve Stimulation.” bioRxiv (2016): 087692.

[20]Yates, B. J., and A. D. Miller. “Physiological evidence that the vestibular system participates in autonomic and respiratory control.” Journal of Vestibular Research 8.1 (1998): 17-25.

[21]Sailesh, Kumar Sai, and R. Archana. “Controlled vestibular stimulation: A physiological method of stress relief.” Journal of clinical and diagnostic research: JCDR 8.12 (2014): BM01.

[22]Kumar, Sailesh Sai, R. Archana, and J. K. Mukkadan. “Controlled vestibular stimulation: Physiological intervention in diabetes care.” Asian Journal of Pharmaceutical and Clinical Research 8.4 (2015): 315-318.

[23]Wilkinson, David, et al. “Improvement of a face perception deficit via subsensory galvanic vestibular stimulation.” Journal of the International Neuropsychological Society 11.07 (2005): 925-929.

Industry Matters

Epistemic status: tentative

In the wake of the election, I’ve been thinking about the decline of manufacturing in America.

The conventional story, the one I’d been told by the news, goes as follows. Cheap labor abroad competes with US manufacturing jobs; those jobs aren’t coming back; most manufacturing jobs are lost to robots, not trade, anyhow; this is tragic for factory workers who lose their jobs, and perhaps they should be compensated with more generous social services, but overall the US’s shift towards a service economy is for the best.  Opposition to outsourcing, while perhaps an understandable emotional reaction from the hard-hit working class, is simply bad economics.  At best, the goal of keeping manufacturing jobs at home is a concession to the dignity and self-image of workers; at worst, it’s wooly-headed socialism or xenophobia.

But what if that story were not true?

Here’s an alternative story, which I think there’s some data to suggest.

Industry — as in, factories in the US making things like cars and trains — is important to long-run technological innovation, because most commercial R&D is in the manufacturing sector, and because factories and research facilities tend to physically co-locate.

High-tech, high-cost-per-unit industries in particular, like the auto industry, are like keystone species in an industrial ecosystem, because you need many different kinds of technology to support them, and because the high cost per unit makes them the first industries where it’s worth it to invest in new process improvements like robotics.  If you don’t have heavy industry at home, eventually you won’t have innovation at home.

And if you don’t have innovation at home, your economy may eventually stagnate. Foundational technologies, things like integrated circuits or metallurgy, have high fabricatory depth; better microchips give rise to more computing power which gives rise to untold multitudes of software applications. If your economy lives exclusively on the “leaves” of the tech tree, you aren’t going to be able to capture the value from a long future of continued inventions.  There may be high-paying jobs in the service economy, but an entire economy built on services will eventually flatten out.

In other words: maybe industry matters.

And, while industrial jobs may initially leave the US because they’re cheaper elsewhere, foreign labor doesn’t stay cheap forever. As countries industrialize and become wealthier, they gain expertise and advance technologically, and eventually compete on quality, not just on price.  Rich countries hope to “move up the value chain”, outsourcing cheap and crude tasks to poorer countries while focusing their own efforts on higher-tech, higher-priced tasks. The problem is that this doesn’t always work — since collocation matters, it may be that you need at least some of the basic factory work to stay at home in order to be able to do the high-tech work, especially in the long run.

“Industry matters”, if true, might be an argument in favor of tariffs, in a vaguely Hamiltonian industrial policy.  Now, the laws of economics still hold; tariffs will always cause some degree of damage.  I’m not confident that the numbers work out such that even an ideal tariff would be worth it, let alone the trade policy likely to be administered by the actually-existing USG.

“Industry matters” might also be an argument in favor of deregulation designed around making it easier to move around  “atoms not just bits.”  If environmental and labor regulations make it extremely difficult to build factories in the US, and if industry has an outsized impact on long-run growth, then the cost of regulation is even higher than previously assumed. If a factory doesn’t open, the cost is not only borne by the people today who could have worked in or profited from that factory, but by future generations who won’t be able to work at the new companies which would have been produced from innovations downstream of that factory.

If industry matters, it might be worth it to trade a bit of efficiency today for long-run growth. Not as a concession to Rust Belt voters, but as a genuine value-creating move.

The US is transitioning to a service economy

According to the Bureau of Labor Statistics’ Employment Outlook Handbook, occupations with declining employment include:

  • Agricultural workers
  • Clerks (file, correspondence, accounting, etc)
  • Cooks (fast food and short order)
  • Various manufacturing occupations like “machine tool setters” and “electronic equipment assemblers”
  • Railroad-related occupations
  • Drafters, medical transcriptionists
  • Secretaries and administrative assistants
  • Broadcasters, editors, reporters, radio and television announcers
  • Travel agents

while the jobs with the fastest growth rates include:

  • Nurses, home health aides, physician’s assistants, physical therapists
  • Financial advisors
  • Statisticians, mathematicians
  • Wind turbine service technicians, solar photovoltaic installers
  • Photogrammetry (i.e. mapping) specialists
  • Surgeons, biomedical engineers, nurse midwives, anaesthesiologists, medical sonographers
  • Athletic trainers, massage therapists, interpreters, psychological counselors
  • Bartenders, restaurant cooks, food preparers, waiters and waitresses
  • Cashiers, customer service representatives, hairdressers, childcare workers, teachers
  • Carpenters, construction laborers, electricians, rebar workers, masons

Basically, medicine, education, customer service, construction, and the “helping professions” are growing; factory work, farming, and routine office tasks are shrinking, as are industries like news and travel agents that have been disrupted by the internet.

As far as mass layoffs go, in May 2013 the largest sector by number of mass layoffs was manufacturing, where the largest number of people laid off were in “machinery” and “transportation equipment.”  Construction followed, where most layoffs were in “heavy and civil engineering” construction.

By sector, mining and manufacturing are losing employment, while construction, leisure and hospitality, education and health, and financial services, are gaining employment.

This part of the conventional story is true: manufacturing jobs really are disappearing.

US manufacturing productivity and output are stagnating

It’s not just jobs, but also productivity and output, where manufacturing in the US is weakening.  US manufacturing still produces a lot, but its growth is slowing.  We’re not getting better at making things the way we used to.

In the US, the biggest output gains per industry, in billions of dollars, between 2002 and 2012, were in the federal government, healthcare and social assistance, and professional services, at 2.6%, 2.6%, and 2.4% respectively. Manufacturing only grew by 0.2%.

Manufacturing output as a whole between 1997 and 2015 was only growing at 0.8% a year, meaning that it’s slowed down in the last 20 years.  Broken down by subsector, the highest manufacturing growth rates were in motor vehicles and other transportation equipment, at an average of about 2% yearly growth; other kinds of manufacturing, such as textiles and apparel, were stagnant or even declined in output.  By contrast, the largest output growth between 1997 and 2015 was in information tech, at an average of 5.6% yearly growth, probably coinciding with the rise of the Internet economy.

In other words, US manufacturing isn’t shedding jobs merely because it’s becoming ultra-automated and efficient. US manufacturing growth has slowed down a lot in output as well.

US manufacturing also stagnated in labor productivity and multifactor productivity. Multifactor productivity (the efficiency of labor & capital) in manufacturing has declined at an 0.5% rate from 2007-2014, while it was increasing at a 1.7% rate in 2000-2007, 1.9% in 1995-2000, and 1.1% in 1990-1995.  Manufacturing productivity was roughly flat from the 1970’s through 2000.

Manufacturing total factor productivity is still increasing, but has been leveling off.

Manufacturing output, similarly, is still increasing, but has been leveling off in recent decades.

While overall manufacturing productivity is still growing  over the period 1987-2010, manufacturing output flattened in about 2000.

While manufacturing output seems to have grown roughly steadily since the 1950s, with a slow decline or stagnation in employment from about 1970-2000, note how the output curve seems to be bending at around 2000, just as manufacturing employment plummets.

You can also see this slight bend in the curve, beginning in around 2000, in manufacturing value added.

The story of “we’re getting more efficient and thus using fewer workers” is only part true.  We’re getting more efficient, but at a slowing rate. We’re producing more output than we did in the 70’s, but that seems to have leveled off in around 2000. Yes, there’s more output and fewer workers, but it looks like recently, since about 2000, multifactor productivity and output are slowing down.

The Big Three auto manufacturers in the US, between 1987 and 2002, had dropping market share and stock price, largely due to international competition.  They lagged the competition in durability and vehicle quality, so were forced to cut prices. They also had a labor productivity disadvantage relative to Japan.  It took nearly two decades for US car manufacturers to catch up to Japanese production process improvements.

In other words, the story of the decline in US manufacturing jobs is not merely that we’re a rich country with expensive labor, or a high-tech country that uses automation in place of workers.  If that were true, output and productivity would be continuing to grow, and they’re not.  US manufacturing is stagnating in quality and efficiency.

Robots aren’t taking American jobs

The decline in US manufacturing began in the 1970’s and 1980’s, as trade liberalization made it easier to move production abroad, and new corporate governance rules made US managers focus on stock prices and short-term performance (which could be boosted by moving factories to cheaper countries.)

Manufacturing automation, by contrast, is much newer, and can’t account for anywhere near that much job loss.  There are only 1.6 million industrial robots worldwide, mostly in the auto and electronics industries; an automotive company has 10x the roboticization of the average manufacturing company.  That is to say, robots are only being used in the highest-tech sectors of the manufacturing world, and not very widely at that. Industrial robots are a rapidly growing but very recent development; there was a 15% increase in the world’s supply of robots just in 2015.

Moreover, countries with more growth in industrial robotics don’t have more job loss.  Most new robots are actually abroad rather than in the US. The largest market is in China, with 27% of global supply; the second largest market is in Europe.  The US boosted its purchases of robots by only 5% this year, at well below the global rate of robotics growth.

It is simply false that robots are causing any significant part of US manufacturing unemployment. There aren’t very many, they haven’t been around very long, they’re mostly in other countries, and they don’t hurt employment in those countries.

According to the Bureau of Labor Statistics, no US manufacturing layoffs in 2013 were due to automation.

Most of the news articles about the dangers of technological unemployment are based on projections about which jobs are in principle automatable. This is speculative, and doesn’t take into account new industries that may open up as technology improves (basically the argument from Say’s law.)  The “post-work future” is largely science fiction at this point. Lost manufacturing jobs are real — but they weren’t lost to robots.

Trade caused manufacturing job loss

The US-China Relations act in 2000 that normalized trade relations permanently was a “shock” to US manufacturing that US jobs were slow to recover from.  Not only did employment plummet, but manufacturing productivity also dropped steeply.

Only 2% of job losses are due to offshoring. But this understates the true amount: if plants close in the US while companies buy from foreign affiliates, that’s effectively “jobs moving overseas” under a different name.  Foreign affiliates now make up 37% of the total employees of US multinational companies, a figure that has been steadily rising since the 80’s; it was 26% in 1982.

Moreover, trade can also cause US job losses if foreign-owned companies outcompete US companies. The most common reason given for manufacturing layoffs in 2013 was “business demand”, mostly contract completion.  Restructuring and financial problems such as bankruptcy were also common reasons.  The main reason for manufacturing layoffs seems to be failure of US factories — poor demand or poor company performance.  Some portion of this is probably due to international competition.

In short, it’s freer trade and poor competitiveness on the international market, not automation, that has hurt American manufacturing.  It’s not the robots that are the problem — if anything, we don’t have enough robots.

Manufacturing drives the future, and location matters

A McKinsey report on manufacturing notes that while manufacturing is only 16% of US GDP, it’s a full 37% of productivity growth.  77% of commercial research and development comes from manufacturing.  Manufacturing, in other words, is where new technology comes from, and new technology drives growth.  If you care about the future economy, you care about manufacturing.

R&D, especially later-stage development rather than basic academic research, must be physically proximate to the lead factory even if some production is globalized, for reasons of communication and feedback between research and production.  You can’t outsource or trade all your manufacturing without losing your ability to innovate.

Moreover, globalized supply chains have real costs: as trade and outsourcing increase, transportation costs and supply chain risks have also been increasing. Physical proximity places some limits on how widely dispersed manufacturing can be.  Trade growth has outpaced infrastructure growth in the US, driving transportation costs up.  The cost of freight for steel and iron ore is almost as high as the material itself.

Steel production, in particular, has plummeted in industrialized countries since the 70’s and 80’s, as part of the switch to a service economy. China’s steel and cement production since the 80s seems to have grown rapidly, while its car production seems to be growing roughly linearly.  South Korea’s steel production is growing steadily. US car production, by contrast, has been shrinking (in terms of number of units), as has its steel production.  Because (due to their weight) metals have unusually high transportation costs, proximity matters an unusual amount, and so a fall in steel production might mean a fall in heavy industry output generally, which is difficult to recover from.

The main theory here is that, once you cease to be an industrial economy, it’s hard to profitably keep factories at home, which means it’s hard to innovate technologically, which means long-run GDP growth is threatened.

The largest manufacturing industries are machines, electronics, and metals

The largest manufacturing companies in China make cars (SAIC, Dongchen, China South Industries Group), chemicals (Sinochem, Chemchina), metals (Minmetals, Hesteel, Shougang, Wuhan), various engineering (Norinco, China Metallurgical group, Sinomach), electronics (Lenovo), phones (Huawei), ships (China Shipbuilding).

The US’s largest manufacturers are general engineering (GE), automotive (GM, Ford), electronics (HP, Apple, IBM, Dell, Intel), pharmaceuticals (Cardinal Health, Pfizer), consumer goods (Procter & Gamble, Johnson&Johnson), aerospace (Boeing, Lockheed Martin), food and beverage (Pepsi, Kraft, Coca-Cola), construction equipment (Caterpillar), and chemicals (Dow).

Germany’s largest manufacturing companies are automotive (Volkswagen, Daimler, BMW), chemicals (BASF), engineering (Siemens, Bosch, Heraeus), steel (ThyssenKrupp), pharmaceuticals (Bayer), and tires (Continental).

Japan’s largest manufacturers are automotive (Toyota, Nissan, Honda), engineering (Hitachi, Panasonic, Toshiba, Mitsubishi, Mitsui, Sumitomo, Denso), electronics (Sony, Fujitsu, Canon), steel (Nippon Steel, JFE), and tires (Bridgestone).

Korea’s largest manufacturers are electronics (Samsung, LG), automotive (Hyundai, Kia), and steel (POSCO).

Machinery and appliances, and electronics and parts, are by far the largest exports from Mexico.

Top exports from China, at a coarse level of granularity, are machines (48%), textiles (11%), and metals (7.8%).  At a more granular level, this involves computers, broadcasting equipment, telephones, integrated circuits, and office machine parts.

US‘s top exports are machines (24%), transportation (15%), chemicals (13%), minerals (11%), and instruments (6.3%). More granularly, this is integrated circuits, gas turbines, cars, planes and helicopters, vehicle and aircraft parts, pharmaceuticals, and refined petroleum.

Germany‘s top exports are machines (27%), transportation (23%), chemicals (13%), metals (8.1%), or in more detail: cars, vehicle parts, pharmaceuticals, and a variety of smaller machine things (valves, air pumps, gas turbines, etc).

Japan’s exports are machines (37%), transportation (22%), metals (9.8%), chemicals (8.5%), and instruments (7.8%). Or, in more detail: cars, vehicle parts, integrated circuits, and a variety of machines like industrial printers.

South Korea’s exports are machines (37%), transportation (19%), minerals (8.9%), metals (8.5%), plastics (7.1%). In more detail, integrated circuits, phones, cars, ships, vehicle parts, broadcasting equipment, and petroleum.

“Heavy industry” — that is, machines, engineering, automobiles, electronics, and metals — is the cornerstone of an industrial economy.  Integrated circuits are a true “root” of the tech tree, the foundation on which the information economy is built. Capital-intensive heavy industries like automobiles are a “keystone” which is deeply interwoven with the production of machines, parts, robots, electronics, and steel.

It’s a relevant warning sign for Americans that many current developments that seem likely to improve “heavy industry” are not concentrated in the US.

Of the top 5 semiconductor companies, only 2 are American. Some electronics innovations, like flat-screens (developed by Sony) and laser TV’s (developed by LG) were developed by Asian companies, and Mexico is the biggest exporter of flat screen TVs.  Robotics, as discussed above, is being pursued much more intensively in Asia and Europe than in the US. “Smart factories”, in which automation, sensors, and QA data analysis are integrated seamlessly, are being pioneered in Germany by Siemens.  The majority of drones worldwide are produced by Israel.  The Japanese companies Canon and Ricoh, as well as the American HP, are expected to launch 3d printers this year; meanwhile the largest manufacturer of desktop 3d printers, XYZprinting, is Taiwanese.

A positive sign, from a US-centric perspective, is that self-driving cars are being developed by American companies (Tesla and Google.)  Another positive sign is that basic research in physics and materials science — the fundamentals that make a continuation of Moore’s law possible — is still quite concentrated in American universities.

But, to have a strong industrial economy, it’s not enough to be good at software and basic research; it remains important to make machines.

Non-xenophobic, economically literate, pro-industry

Globalization has been a humanitarian triumph; Asia’s new prosperity has vastly reduced global poverty in recent decades. To acknowledge that global competition has been hard on Americans doesn’t preclude appreciating that it’s been good for foreigners, and that foreigners have equal moral worth to ourselves.

Acknowledging harms from trade also doesn’t require one to be a fan of planned economies or a believer in a “zero-sum world.” Trade is always locally a win-win; restricting it always has costs.  But it may also be true that short-term gains from trade can be counterweighted by long-term losses in productivity, especially due to loss of the gains in local skill and knowledge that come from being a manufacturing center.

If you want to live in a vibrantly growing country, you have to make sure it remains a place where things are made.

That’s not mere protectionism, and it’s certainly not Luddite.

I don’t think this is true of, say, agriculture, where vast increases in efficiency have reduced the number of farmers needed to support the global population, but where that’s not really a problem for overall growth. US farming has not lost ground — we produce more food than ever.  We are not getting worse at farming, we just need fewer people to do it.  I suspect we are getting worse at manufacturing.  And since manufacturing has so disproportionate an effect on downstream growth and innovation, that’s a problem for all of us, in a way that it’s not a problem if farmers or travel agents lose their jobs to new technologies.

Pro-Industry, Anti-Corruption

The truly obvious gains from capitalism are actually gains from industry. Cheap, varied, abundant food. Electricity and electric appliances. Fast transportation. The sort of things described in Landsailor.

Other things that show up in GDP are less obviously good for humans. If real estate prices rise, are we really better housed? If stock prices rise, do we really have more stuff?  If we spend more on medicine and education but don’t have better health outcomes or educational outcomes, are we really better cared for and better educated?

The value of firms has dramatically shifted, since 1975, towards the “dark matter” of intangibles — things like brands, customer goodwill, regulatory favoritism, company culture, and other things that can’t be easily measured or copied. US S&P 500 firms are now 5/6’ths dark matter.  How much of the growth in their value really corresponds to getting better at making stuff?  And how much of it is something more like “accounting formalism” or “corruption”?

If you are suspicious of things that cost more money but don’t create obvious Good Things for humans, then you will not consider a shift to a service economy a good outcome, even if formally it doesn’t look too bad in GDP terms. If you take a jaundiced view of medicine, education, the “helping” professions, government, and management — if you see them as frequently doing expensive but unhelpful things — then it is not good news if these sectors grow while manufacturing declines.

If your ideal vision of the future is a science-fiction one, where we cure new diseases, find new fuel sources, and colonize the solar system, then manufacturing is really important.  

The old slogans like “what’s good for GM is good for America” are not as far from the truth as you’d think.

 

On Trying Not To Be Wrong

Epistemic Status: Exhortative

I did not expect Donald Trump to become President.

I did not expect him to win, or even get very far, in the Republican primaries. Like many people, I thought the idea of Donald Trump becoming president was “weird” or “surreal” or “not a thing that happens.”  Like many people, I’ve thought 2016 was a surreal year; the Cubs won the World Series, Hillary Clinton went on television to warn people about white-supremacist memes, Elon Musk has landed rockets on ocean platforms and started an organization to develop Friendly AI.  Surreal, right?

No.

It’s real, not surreal. If reality looks weird, this means our stories about it are wrong.

Did polls and newspapers and social media fail to see this election coming? Then those sources just took a hit in credibility.

On a longer-term note, if you know there’s a replication crisis in scientific research, that should be shaking up your trust in published papers.

There may be a crisis in politics. But before we can do anything sensible about that, we need to understand that there is a crisis in credence. If the world looks weird to you and me today, that is not a matter for rueful laughter, it is a sign that we are probably badly wrong about lots of things.

And being totally wrong about how the world works is a threat to survival.

What this election brought home to me is that I don’t want to be wrong any more.

A lot of things people say and write are not really what they think is true about the world. They’re expressions of emotion or identity or solidarity. Arthur Applebee writes about “the affective center” being the prototypical use of language: gossip, relationship-building, sharing feelings.  Evolutionary biologist Geoffrey Miller thinks that language, as well as the high intelligence needed to navigate social relations, evolved in humans through sexual selection.  We are built for these “soft” uses of language and thought: to relate, to bond, to politick. Doing that feels good and intuitive and healthy. It feels “human”, because it is.

It is, of course, also not truth-seeking. We have a host of cognitive biases, particularly in these normal, social uses of speech.  Much of it is bullshit, in Harry Frankfurt’s terminology: not so much lies as not about truth in the first place.

But it is possible for language to be used in ways that do point towards truth.  Arguments where premises follow from conclusions — when people are reading to check whether premises follow from conclusions and facts are supported by evidence — actually do hold independently of shifting social contexts.

What that requires socially is for people to do something quite unnatural. Instead of going with the flow (relating, politicking, sharing feelings, bonding), it involves breaking the flow. Nitpicking. Disagreeing. Being dry and technical. Fact-checking.

The motto of the Royal Society of London was “Nullius in verba”, or “Take nobody’s word for it.”  The modern scientific tradition was founded by a small group of people defined by the fact that they would call bullshit on things unless they were demonstrated by evidence.  This is inherently disagreeable — literally, it involves disagreeing.

The contemporary flow of social media works to prevent discussion and argument, while earlier internet formats worked to promote it.

A blog and a comments section, or a forum, or an email thread, is set up to encourage discussion.  One has space to write long-form, multi-paragraph essays, which are stored permanently; and then there is ample space for other people to write long-form, multi-paragraph responses to those essays.  One can respond to specific points separately. One can respond to responses, in long nested threads.  It is good form to cite sources (links and hat-tips).  The social reward for writing is getting a response to your writing. The world of blogs and forums provided an alternative to mass media that was more discursive and more intellectual.

Newer forms of social media inhibit discussion and promote simpler affective responses.

Facebook still allows threaded discussions, but the unit of attention is the like. You get socially rewarded when lots of people agree with you; agreement, being cheaper than response, will wind up being more abundant and hence more dominant, in a sort of Gresham’s Law phenomenon.

Twitter doesn’t allow room for long-form content, of course, and the first-class actions are liking and retweeting: approval and copying.  Tumblr allows for paragraph-long posts, but has such poor threading that it’s difficult to hold a discussion, structurally prefers images and videos to text, and makes liking and reblogging first-class actions. Snapchat and Instagram are deeply unfriendly to text.

And all of the above social media platforms have an endlessly scrolling feed, which makes conversations ephemeral and difficult to reference.

The incentives are against discussion and towards response. Instant emotional readouts, approval or disapproval.  Image rather than language. Copying rather than original writing.

The medium is designed for agreement, not disagreement. People who can’t communicate in a way that will rack up “likes” or “favorites” tend to quietly withdraw.  And that feels awkward, like they’re spoiling the party, like a kind of Puritanism.

But I also suspect that these Puritans, these disagreeable people, have something to teach us. Especially now.  Especially when it’s become clear that “believing” things out of mood affiliation leads to very wrong conclusions about the world.

Humans love to socialize. One of the things that we like to do with leisure and technology is talk to each other. I’m not denigrating this normal human urge, which finds expression in social media.

What I’m saying is that one of the remarkable things that can be done with human intelligence, language, and socializing is to have discussions. Arguments. Conversations. Science is a form of conversation, as is philosophy.  Out of the natural “affective center” of gossip can come something that is a bit more unnatural but extraordinarily powerful: you can come to reliable and referenceable common knowledge.  You can refer back to “oh, yeah, on February 15th Bob did this experiment and on February 16th Alice tried it herself and got the same result, and then Carl found a flaw in the design so it turned out Alice and Bob were wrong.”

It’s not about liking a claim, it’s about being convinced by it.

I’m not talking about something that necessarily has to be high-minded and out of reach, or something that will singlehandedly fix the problems we face.

But it seems really useful now to start having discussions again. On blogs, on forums, on email, in contexts where it’s socially rewarding to disagree and pick things apart, rather than to merge into mobs of agreement.

It’s urgent to figure out what is going on in the world and how we can keep it from hurting us.  And that means our errors need to be corrected.

If this seems kind of dutiful and unpleasant, compared to the warm rush of likes and reblogs and image-sharing, consider that it’s actually kind of fun in its own right to have arguments and discussions and to dig into the nitty-gritty. It’s the nerdy kind of fun that gets a kick out of details, out of facts, out of messing around until things click into place satisfyingly.  It’s the mental equivalent of the kind of fun it is to make things with your hands, or to play games.

The Scottish Enlightenment was a little, well, Scottish.  What are the Scottish stereotypes? A little grouchy, a little ornery, a little stingy.  Hard-headedly practical.  Blunt. In other words, there’s a kind of healthy disagreeableness, that says “don’t give me bullshit”, and “don’t rip me off”, and “I’m sure as hell not going to kneel to you” and “I may not be rich or powerful, but I’m honest”, and “I built machines that work, dammit.”  In a world where liking and agreeing is the currency, I think we are likely to underappreciate the virtues that go with disagreeableness.

I’m going to lean more into disagreement and fact-checking. I’m going to try to appreciate the people who say “not exactly” instead of going with the flow. I’m going to aim to have my discussions in contexts that are actually designed for discussion.  I care about not being wrong, now, in a way I really didn’t before.  And I encourage others to consider doing the same.