A philosophically-minded MR reader writes to me:

Tenure ought to be an occasion to explore radically new intellectual paths, ones not pre-approved by one’s field and ones that could, perhaps, do something to bridge the chasm between academic and non-academic intellectual life–and yet as a matter of fact what seems to happen is that people either stop working altogether or continue barreling down the groove they wore themselves into to get tenure.  (You mentioned this issue in a post last year:  But I want to hear more.

So: why does this happen, how can we prevent it at the University/ departmental level, and, most of all, how can we prevent it at the personal level?  (Keeping in mind that most of us are not cognitively capable of processing information at the speed to go your route!)   The idea that we are incentivized to keep working by the prospect of being promoted to full Professor seems silly, given the increased administrative responsibilities.

Related problem: as one moves up the tenure hierarchy, the administrative responsibilities tend to fall disproportionately on fewer and fewer people,  b/c there are lots of deadbeats. I repeatedly see the few responsible people overwhelmed with administrative tasks which they refuse to delegate to those they know will not take them seriously.  (And I observe these responsible people are disproportionately women, even in a field–like mine–that is disproportionately male.)

I have a few suggestions, all feasible but only a few are practical:

1. All schools should copy the committee obligations policy of the school, within their quality tier, that has the fewest committee assignments for faculty.  Yes this can be done.

2. I don’t know how to operationalize this one, but on average give women half the committee assignments that men have.  That still won’t equalize the total work burden (women on average work harder per committee assignment), but it is a start.

3. Study your lecture preparation, and experiment with cutting parts of it out.  See if that matters.

4. Each year take at least one trip to a place you didn’t think you wanted to visit.

5. Go to some Liberty Fund conferences.

6. Refuse to have colleague lunches based around local politics, politics, small talk, sports (unless of the analytic variety), and campus gossip.  Just don’t do it.  Also avoid lunches with too many people attending.

7. Of the five or so smartest people you hang out with (family aside), try to ensure that no more than half of them are in your department.

8. Change the ratio of foreign-to-domestic TV shows you watch, in favor of the foreign.

9. Hang at least one piece of non-cheery art on your wall that will remind yourself of an ever-pending death.  Change its angle every now and then, or better yet change the picture, so you don’t get too used to it and stop noticing it altogether.  If need be, supplement this with Brahms’s German Requiem.

10. Write a periodic blog post, if only a secret and non-published one.  If you don’t find this process is going well, ask yourself what is wrong.

11. Worry if no one thinks you are crazy.  Supplement this with actually being crazy.

12. What else?

I wanted to like this book, as I am keen to discover new perspectives on the arts, even if I don’t agree with them.  “False” books on the arts often illuminate the artworks themselves, sometimes more than do the “true” treatments.  Yet this work I had a tough time making sense of.  I will confess to having read only about a third of it, and browsed some more.  As I understand the book’s thesis, the plasticity of the brain, as it changes across historical eras, helps explain changes in the content of the visual arts.  But I view brain plasticity as a generally overrated idea, evidence for such claims about the arts is hard to come by (how much do we know about differences in brains in ancient Athens for instance? And how good is our theory linking brain differences to artistic content?), and most of all neuroscience itself so often disappears during the book’s exposition.  Even the Amazon summary indicates the rather mysterious nature of the book’s main argument.  It is a beautifully produced volume, and it feels important, and maybe there is finally scope for a book of this kind, but…

Here is a (very) negative review by Matthew Rampley.  Some of you may nonetheless find this interesting.  It is a big ideas book, and perhaps it can prompt you to write a more clearly defined big ideas book in response.

He is from Brown University, we met at a tacqueria, here is the interview, here is one bit from it, from me:

Popular culture is not nearly pro-science enough…. It should be much higher status to be in science. This would boost the rate of innovation. I think people privately can just choose to respect science more. In a sense it’s a free lunch! You don’t have to spend money, people just have to actually believe science is really good. So that’s what I advocate. And that’s a question of role models and exposure when you’re young. I think TV shows are very important… Star Trek and even Gilligan’s Island I think made science cool to a lot of people. I think President Obama actually has done a pretty good job of being a pro-science role model and how he talks about science. His powers are limited but I think he actually gets this pretty well, because he’s made a real concerted attempt rhetorically to work that into what he’s about. I think historically, America has not been all that pro-science, but we invented the atomic bomb, we industrialized in this fantastic manner. In a bunch of ways pro-science and nationalism should overlap. Being the first country to put a man on the moon gave a huge boost to science. That boost has proven temporary, much to my dismay.

Here are bits and pieces on the very smart Noah Cowan, who was a Jeopardy champion at a very young age.

Both male and female scientists felt that female scientists (light bars) were more objective, intelligent, etc. than male ones (dark bars), although the differences were larger when it was female scientists making the ratings.

I found this interesting too:

Strikingly, though, early-career scientists were rated as having less objectivity, integrity and open-mindedness than PhD students – or so thought the senior scientists.

Junior researchers, however, saw themselves as being slightly superior to PhD students…

Here is more, via the excellent Samir Varma.

A Yoruba tongue twister

by on December 26, 2016 at 3:06 am in Books, Science | Permalink

Opolopo opolo ni ko mo pe opolopo eniyan l’opolo l’opolopo

That means “many frogs do not know that many people are intelligent.”

That is from Teju Cole, Known and Strange Things, a book of essays.

And here is yet a further update on Nigerian plastic rice.

How to make annoying alarms

by on December 23, 2016 at 1:07 am in Law, Medicine, Science | Permalink

The faster an alarm goes, the more urgent it tends to sound. And in terms of pitch, alarms start high. Most adults can hear sounds between 20 Hz and 20,000 Hz—Baldwin uses 1,000 Hz as a base frequency, which is at the bottom of the range of human speech. Above 20,000 Hz, she says, an alarm “starts sounding not really urgent, but like a squeak.”

Harmonics are also important. To be perceived as urgent, an alarm needs to have two or more notes rather than being a pure tone, “otherwise it can sound almost angelic and soothing,” says Baldwin. “It needs to be more complex and kind of harsh.” An example of this harshness is the alarm sound that plays on TVs across the U.S. as part of the Emergency Alert System. The discordant noise is synonymous with impending doom.

After the alarm designers create a range of sounds in the lab, says Baldwin, they will test the annoyance factor of these sounds in a process called “psychophysical matching, or psychophysical ratings.” Yes, this involves subjecting human beings to a bunch of irritating sounds. Participants determine how annoying the sounds are by sorting them into categories ranking them on a scale of one to 100. 

Then there’s more testing. “If it’s a medical alarm, for instance, we’ll start using that sound and then we’ll maybe measure people’s physiological response to it—does their heart rate go up, does their skin conductance level go down, what happens to their brain activity,” says Baldwin. Skin conductance measures how much the sound affects the body—skin gets better at conducting electricity when the body is physiologically aroused.

An effective audio alarm is one in which the annoyance factor and perceived urgency of the sound is matched to the hazard level—a soft little chime for the fridge door, say, and a “BREHHHHK BREHHHHK BREHHHHK” for a plane in a tailspin. “We want it to be detectable, so to get your attention, but for you to recognize what it means right away,” says Baldwin.

It turns out this is a problem in hospitals:

In hospitals in particular, there are “so many nuisance alarms going off all the time, that people—nurses, doctors—just tune them out,” says Baldwin. “They don’t even hear them anymore.” The statistics say that most of these alarms are not indications of peril. A 2012 review of medical audio alarms found that in one intensive therapy unit, “of 1455 soundings of alarms, only eight were associated with potentially life-threatening problems.”

Here is the full piece, from the excellent Atlas Obscura, and for the pointer I thank Torsten Kehler.

In early November Google Translate took a Japanese translation of the opening of Hemingway’s “The Snows of Kilimanjaro,” and returned:

Kilimanjaro is 19,710 feet of the mountain covered with snow, and it is said that the highest mountain in Africa. Top of the west, “Ngaje Ngai” in the Maasai language, has been referred to as the house of God. The top close to the west, there is a dry, frozen carcass of a leopard. Whether the leopard had what the demand at that altitude, there is no that nobody explained.

One day later Google Translate took the same passage and returned:

Kilimanjaro is a mountain of 19,710 feet covered with snow and is said to be the highest mountain in Africa. The summit of the west is called “Ngaje Ngai” in Masai, the house of God. Near the top of the west there is a dry and frozen dead body of leopard. No one has ever explained what leopard wanted at that altitude.

What happened on that day is that Google turned its Translate service over to Google Brain, it’s new division that uses “neural networks” to solve AI problems. Google Brain and it’s history is the subject of  an excellent longread, The Great AI Awakening, from Gideon Lewis-Kraus (from which I have drawn the example).

Today, however, I want to make a different point. In my paper, Why Online Education Works, I wrote:

Online education has the potential to break the cost disease by substituting capital for labor and hitching productivity improvements in education to productivity improvements in software, artificial intelligence, and computing.

The improvements to Google Translate provide an example. Our Principles of Microeconomics and Principles of Macroeconomics courses at Marginal Revolution University are captioned in over a hundred languages. Professional human-written captions have been produced for most of our videos in English, Spanish, French, Chinese and Arabic and we are working on more translations. Most of the translations, however, including those for Corsican, Kyrgyz, and Urdu are provided by Google. The earlier machine-translations weren’t great but were still useful to students in Pakistan who might need a bit of extra help to understand a new concept. The translations, however, are getting better.

Indeed, every improvement in Google Translate automatically becomes an improvement to Marginal Revolution University. Amazing.

I was watching the excellent Rogue One when suddenly I thought “Wow, they sure found an actor who looks just like Peter Cushing.”  As the scene, progressed my thoughts changed to “Tyler, are you sure that Peter Cushing passed away?”  As I watching the credits, I saw a thanks to the “Estate of Peter Cushing, OBE,” and so I went back to wondering about the actor, but then why did they thank the estate?

The reality is this:

…the face of Peter Cushing, the imposing British actor who died in 1994, lends an especially memorable presence to “Rogue One” by helping to “reprise” his “Star Wars” character, Grand Moff Tarkin, the Imperial governor who practically rules by force of glare, intonation and cheekbone.

…Under director Gareth Edwards, “Rogue One” represents another marker in the decades-long quest for the best CGI-fashioned human replicas. The filmmakers auditioned actors to “play” Cushing’s Tarkin, settling on BBC soap actor Guy Henry. This Tarkin is thus free of the dreaded “dead eye” effect. Lo, though the effects wizards walk through the “uncanny valley,” Tarkin registers as quite alive — even if his facial proportions sometimes read as ever so slightly off from the Original Trilogy. We are nearing the reality of a fully fleshed-out, CGI-enhanced performance long after an actor has passed.

If “Rogue One” wins an Oscar for effects, Cushing should be in no small part why.


When will the slope start where amateur video becomes significantly less trustworthy as well?  Or even just “But Mom, I saw him do it on TV!”  While we’re at it, how about a symphony orchestra conducted by “Beethoven”?

Are Ideas Getting Harder to Find? Yes, say Bloom, Jones, Van Reenen, and Webb. A well known fact about US economic growth is that it has been relatively constant over a hundred years or more. Yet we also know that the number of researchers has increased greatly over the same time period. More researchers and the same growth rate suggest a declining productivity of ideas. Jones made this point in a much earlier paper that has long nagged at me. With just one country and rising world growth rates, however, I wondered if the US had somehow had offsetting factors. Bloom, Jones, Van Reenen and Webb, however, now return to the same issue with a more detailed investigation of specific industries and the picture isn’t pretty.

Moore’s law (increasing transistors per CPU) is often trotted out as the stock example of an amazing increase in productivity and it is when measured on the output side. But when you look at Moore’s law from the perspective of inputs what we see is a tremendous decline in idea productivity.

The striking fact, shown in Figure 4, is that research effort has risen by a factor of 25 since 1970. This massive increase occurs while the growth rate of chip density is more or less stable: the constant exponential growth implied by Moore’s Law has been achieved only by a staggering increase in the amount of resources devoted to pushing the frontier forward.


In some ways Moore’s law is the least disturbing trend because massive increases in researchers has at least kept growth constant. In other areas, growth is slowing despite many more researchers.

Agricultural yields, for example, are increasing but the rate is constant or declining despite big increases in the number of researchers.


Since 1950 life expectancy at birth has been growing at a remarkably steady rate of about 1.8 years per decade but that growth has only been bought by ever increasing number of researchers. Here, for example, is cancer mortality as function of the number of publications or clinical trials. Each clinical trial used to be associated with ~8 lives saved per 100,000 people but today a new clinical trial is associated with only ~1 life saved per 100,000. lifeexpectancy

And how is this for a depressing summary sentence:

…the economy has to double its research efforts every 13 years just to maintain the same overall rate of economic growth.

In my TED talk and in Launching I pointed to increased market size and increased wealth in developing countries as two factors which increase the number of researchers and therefore increase the global flow of ideas. That remains true. Indeed, if Bloom et al. are correct then even more than before we can’t afford to waste minds. To maximize growth we need to draw on all the world’s brain power and that means we need a world of peace, trade and the free flow of ideas.

Nevertheless the Bloom et al findings cut optimism. The idea of the Singularity, for example, comes from projecting constant or increasing growth rates into the future but if it takes ever more researchers just to keep growth rates from falling then growth must slow as we run out of researchers. As China and India become wealthy the number of researchers will increase but better institutions can only push lower growth rates into the future temporarily. Most frighteningly, can we sustain a world of peace, trade and the free flow of ideas with lower growth rates?

Just because idea production has become more difficult in the past, however, doesn’t make it necessarily so forever. We could be in a slump. Breakthroughs in ideas for improving idea production could raise growth rates. Genetic engineering to increase IQ could radically increase growth. Artificial intelligence or brain emulations could greatly increase ideas and growth, especially as we can create AIs or EMs faster at far lower cost than we can create more natural intelligences. That sounds great but if computers and the Internet haven’t already had such an effect one wonders how long we will have to wait to break the slump.

I told you the paper was depressing.

“Folding Beijing”

by on December 16, 2016 at 2:40 am in Books, Economics, Science | Permalink

It is an extraordinary short story, one of the best things I’ve read all year, and it’s proof positive of how rapidly China is becoming a society supercharged with creativity.  I am pleased to see it received a Hugo Award for best novelette.

The author is Hao Jingfang and it’s on-line here.  Did you know she is a macroeconomics researcher at a quango in Beijing?  One key part of the plot and premise revolves around macroeconomic theory, here is an excerpt:

“Hard to say.” Lao Ge sipped the baijiu and let out a burp. “I suspect not. You have to understand why they went with manual processing in the first place. Back then, the situation here was similar to Europe at the end of the twentieth century. The economy was growing, but so was unemployment. Printing money didn’t solve the problem. The economy refused to obey the Phillips curve.”

He saw that Lao Dao looked completely lost, and laughed. “Never mind. You wouldn’t understand these things anyway.”

I cannot excerpt more without giving away spoilers.  Definitely recommended, and for the pointer I thank Eva.

Exploration and exploitation of Victorian science in Darwin’s reading notebooks.

Murdock J, Allen C, and DeDeo S


Search in an environment with an uncertain distribution of resources involves a trade-off between exploitation of past discoveries and further exploration. This extends to information foraging, where a knowledge-seeker shifts between reading in depth and studying new domains. To study this decision-making process, we examine the reading choices made by one of the most celebrated scientists of the modern era: Charles Darwin. From the full-text of books listed in his chronologically-organized reading journals, we generate topic models to quantify his local (text-to-text) and global (text-to-past) reading decisions using Kullback-Liebler Divergence, a cognitively-validated, information-theoretic measure of relative surprise. Rather than a pattern of surprise-minimization, corresponding to a pure exploitation strategy, Darwin’s behavior shifts from early exploitation to later exploration, seeking unusually high levels of cognitive surprise relative to previous eras. These shifts, detected by an unsupervised Bayesian model, correlate with major intellectual epochs of his career as identified both by qualitative scholarship and Darwin’s own self-commentary. Our methods allow us to compare his consumption of texts with their publication order. We find Darwin’s consumption more exploratory than the culture’s production, suggesting that underneath gradual societal changes are the explorations of individual synthesis and discovery. Our quantitative methods advance the study of cognitive search through a framework for testing interactions between individual and collective behavior and between short- and long-term consumption choices. This novel application of topic modeling to characterize individual reading complements widespread studies of collective scientific behavior.

Here you will find the transcript, podcast, and video of the chat, Joe of course was in top form.  In addition to a wide-ranging conversation on cultural and social evolution, we touched on topics such as Star Trek, Hayek’s atavism theory, what he learned from the Mapuche, the pleasures of cooking in coconut milk, why WEIRD matters, whether Neanderthals were smarter than humans, and whether Joe is a conservative after all.  Here is one bit:

COWEN: The Flynn effect in the short run puzzles me more than in the long run. If I compare today to the 18th century, I can see where the difference might be. But in many countries, it seems the Flynn effect hasn’t stopped. Nutritional gains probably are over.

The environment — smartphones are newer than the Flynn effect, but it doesn’t seem to be changing now compared to a generation ago. They both seem quite complex. We’ve had TV for a while. People have books, market society. What exactly is the difference over the last generation in the short run?

HENRICH: It’s a cultural-evolutionary treadmill. One place where you see this is the complexity of television shows. Now, you have an ensemble cast and 20 different plots going on. You’ve got to track all these different plots. That wasn’t the television of the 1950s. It was one plot, one thing after another. Simple. The whole world is getting more complex, at least in terms of your need for analytic thinking.

COWEN: Some of that in your view is the supply-side effect. It’s not that we got smarter and they made TV better, it’s also they made TV better and that made some of us smarter.

HENRICH: Coevolutionary.

COWEN: Coevolutionary. This is going to make you out to be quite an optimist, then, because TV is going to get better and better. We’re just going to keep on getting smarter.

HENRICH: Yeah, of course.


COWEN: You’re an anthropologist. You’ve spent a lot of time with economists — coauthored, worked with Paul Romer, Colin Camerer, others. As an anthropologist, what do you find strange about the tribe known as econ? [laughs]

HENRICH: I had a real opportunity. I was very fortunate in my career to be a professor of psychology and a professor of economics at the same time but to be neither in some deep sense. I would get to go back and forth from seminars in economics and psychology.

In economics, there’s this really competitive culture. The way I like to describe it: If you’re giving a seminar in economics, the crowd — everybody’s trying to show who’s the smartest guy in the room. Just on your first slide, someone will raise their hand. (I’m like, I haven’t said anything yet!) Then they’ll try to ask the killer question which undercuts your whole talk so that they can get you right at the beginning.


HENRICH: Whereas psychologists, they’ll sit quietly. They watch your talk. You go through your whole PowerPoint. You probably touched a lot of different research projects.

Then there’ll be question time; at first no hands will go up. Then someone will be like, “I got a question.” Then they say, “I just have one small question. I mean, it was a great talk and this is just a very minor thing.”

Then it could be a killer question at that point when they’ve done the preface. It’s a very strong cultural difference between the econ tribe and the psychology tribe.

I’ve always wanted to write an ethnography: My Life among Two Strange Tribes: The Psychologists and the Economists.

Do read, hear, or watch the whole thing.

Here you can order Joe’s book The Secret of our Success: How Culture is Driving Evolution, Domesticating Our Species, and Making us Smarter.


“By far the best way to eat mealworms” is another insight on tap.

Here is the AtlasObscura story, via the excellent Mark Thorson.

Stumped for solutions to hundreds of industrial and technical problems, businesses and governments alike are turning the search for innovative ideas into prize-worthy puzzles that capitalize on the ingenuity of the crowd.

At a time when the pace of innovation seems to be slowing, prize sponsors hope that today’s hackers and makers can step into the breach and jump-start progress in a way that today’s research institutions—with their many constituencies and restraints—are struggling to do.

Improve smartphone voice recognition? There’s a $10,000 prize for that. Design a delivery drone? $50,000. Extend the human lifespan? Venture capitalist Dr. Joon Yun offers the $1 million Palo Alto Longevity Prizes. Diagnose antibiotic resistance? That’s worth $20 million. And if anyone can profitably repurpose the carbon emissions involved in global warming, there are prizes totaling $55 million in the offing.

“You name it, there is a prize for it,” said Karim Lakhani at the Harvard Business School’s Crowd Innovation Lab, who has helped run 650 innovation contests in the past six years.

In addition, crowdsourcing companies such as InnoCentive Inc., NineSigma, and Kaggle have posted hundreds of these lucrative research contests on behalf of corporate and government clients, offering cash prizes up to $1 million for practical problems in industrial chemistry, remote sensing, plant genetics and dozens of other technical disciplines. Among them, the three companies can draw on the expertise of two million freelance researchers who have registered for access to the prize challenges.

All told, more than 30,000 significant prizes are awarded every year worth $2 billion and growing, according to McKinsey & Co. The total value of purses from the 219 largest prizes has tripled in the past 10 years. Not only are there more prizes than ever, but nearly 80% of all the major new prizes announced since 1991 are designed to spur specific innovations.

Yet here is a cautionary note:

To be sure, there is little evidence that crowdsourcing competitions have significantly altered the innovation landscape yet. “Prizes are important, but they are not the ultimate incentive for innovation” said Luciano Kay, a research fellow at the University of California at Santa Barbara who studies incentive prizes. “They are not big enough to change how industry works in general.”

Here is the full Robert Lee Hotz WSJ article.  Here are previous MR posts on prizes.  Here is an MRU video on prizes.  Here is my 2007 talk at Google on prizes as a means of funding innovation.

For the pointer I thank Ray Lopez.

Animal rights will be the big social revolution of the 21st century. Most people have a vague feeling that factory farms aren’t quite ethical. But few people are willing to give up meat so such feelings are suppressed because acknowledging them would only make one feel guilty not just. Once the costs of giving up meat fall, however, vegetarianism will spread like a prairie wildfire changing eating habits, the use of farm land, and the science and economics of climate change.

Lab grown or cultured meat is improving but so is the science of veggie burgers. Beyond Meat has sold a very successful frozen “chicken” strip since 2013 and their non-frozen burger patties are just now seeing widespread distribution in the meat aisle at Whole Foods. Beyond Meat extracts protein from peas and then combines it with other vegetable elements under heating, cooling and pressure to realign the proteins in a way that simulates the architecture of beef.

I picked up at two-pack on the weekend. Beyond Meat burgers look and cook like meat. But what about the taste?


The taste is excellent. The burger has a slightly smokey taste, not exactly like beef but like meat. If you had never tasted a buffalo burger before and I told you that this was a buffalo burger you would have no reason to doubt me. A little sauce and salt and pepper and this is a very good-tasting burger not a sacrifice for morality.

The price is currently more than beef, $6 for two patties but that’s Whole Foods expensive not out of reach expensive. I will buy more.

The revolution has begun.


The second picture is the BuzzFeed version. My burger wasn’t quite so artfully arranged but was still delicious and I attest to the overall accuracy.

Addendum: 20 g protein: 6 g carb: 22g fat (5g saturated).