Bayesian theories of perception have traditionally cast the brain as an idealised scientist, refining predictions about the outside world based on evidence sampled by the senses. However, recent predictive coding models include predictions that are resistant to change, and these stubborn predictions can be usefully incorporated into cognitive models.
By Jacob Ward at The New York Times. Do read the whole thing, here is just one small bit:
The geno-economists seem confident that human genes have a measurable influence on human outcomes. But publicizing whatever predictive power does lie in our genes runs the risk of misleading the rest of us into believing that control of our genes is control of our future. They’re adamant that their motives are in forestalling the dystopian implications of the work, in fighting off misinformation and misguided policies. “The world in which we can predict all sorts of things about the future based on saliva samples — personality traits, cognitive abilities, life outcomes — is happening in the next five years,” Benjamin says. “Now is the time to prepare for that.”
Via Garett Jones.
…we ran a survey asking scientists to compare Nobel prizewinning discoveries in their fields. We then used those rankings to determine how scientists think the quality of Nobel prizewinning discoveries has changed over the decades…
Our graph stops at the end of the 1980s. The reason is that, in recent years, the Nobel Committee has preferred to award prizes for work done in the 1980s and 1970s. In fact, just three discoveries made since 1990 have yet been awarded Nobel Prizes. This is too few to get a good quality estimate for the 1990s, and so we didn’t survey those prizes.
However, the paucity of prizes since 1990 is itself suggestive. The 1990s and 2000s have the dubious distinction of being the decades over which the Nobel Committee has most strongly preferred to skip back and award prizes for earlier work. Given that the 1980s and 1970s themselves don’t look so good, that’s bad news for physics…
Why has science gotten so much more expensive, without producing commensurate gains in our understanding?
That is the topic of my latest column for Bloomberg, here is one excerpt:
Now enter a newly announced project, called the Journal of Controversial Ideas. It will publish one issue per year, devoted to ideas that otherwise may not receive a fair hearing, and it will allow for anonymous or pseudonymous publication. Princeton philosopher Peter Singer is one of the names associated with the journal, which does not yet have an agreement with a publisher.
I am skeptical though not hostile toward this enterprise. It is sad that such a journal is seen as necessary. But I would suggest instead putting forth your ideas on a blog, on Twitter or on YouTube. Many politically incorrect figures have done just that. A Jordan Peterson YouTube lecture might range from the Bible to Jung to a critique of contemporary feminism, none of it refereed, but he has attracted millions of viewers. At the end of it all you get the Jordan Peterson worldview, which I suspect has more resonance than any particular empirical claim Peterson might make along the way.
In an internet-centered intellectual world, what persuades people is reading or hearing a charismatic personality, year in year out, promoting a particular view of the world. A lot of controversial ideas will have to ride that roller coaster, for better or worse.
The Journal of Controversial Ideas is intended to be open access, though without a publishing contract we can’t know if it will have an open online comments section. It would be odd if not (would we have to create a companion Journal of Controversial Comments?), but with open comments you have to wonder whether a prestige publisher will take on the associated libel and reputational risks, and how high status the journal actually will be. It would not be practical to referee the comments, but that may mean the truly open internet, with its free-for-all atmosphere, will remain the dominant source for controversial ideas. “Controversial for me but not for thee” hardly seems like a winning slogan for such a revisionist enterprise.
Overall, I think controversial ideas will do best on the non-refereed internet, but I am not opposed to giving this venture a try. Refereeing is supposed to boost status, but will anyone put a publication here on their tenure vita? And:
To make a controversial idea stick through the academic process, maybe you do have conquer the biases and beat the odds against you, as Harvey Mansfield, Robert P. George and Oded Galor have done (to name just three). You also might pursue a “Straussian” approach, embedding subversive messages in your paper and covering them up with flowery rhetoric, hoping that some but not too many people notice what you are really saying.
Do read the whole thing.
Soon I will be doing a Conversation with recent Nobel Laureate Paul Romer, no associated public event. What should I ask him?
I thank you all in advance for your wise counsel.
One of my biggest personal fears is working in the wrong field to achieve the goal I care about. If you were around pre-1900s, and wanted to contribute to biology, you should have been a physicist (Robert Hooke, a physicist discovers the first cell, making a better microscope is a major driver of progress). In which field should you work to maximize progress in biology today?
…But something interesting happened around the 1950s. If you look at the most important techniques in biology, in the second half of the 1900s, they’re all driven by tools discovered in biology itself. Biologists aren’t just finding new things – they’re making their new tools from biological reagents. PCR (everything that drives PCR, apart from the heater/cooler which is 1600s thermodynamics, is either itself DNA or something made by DNA), DNA sequencing (sequencing by synthesis – we use cameras/electrical detection/CMOS chips as the output, but the hijacking the way the cell makes DNA proteins remains at the heart of the technique), cloning (we cut up DNA with proteins made from DNA, stick the DNA into bacteria so living organisms can make more copies of it for us), gene editing (CRISPR is obviously made from DNA and with RNA attached), ELISA (need the ability to detect fluorescence – optics – and process the signal, but antibodies lie at the heart of this principle), affinity chromatography (liquid chromatography arguably uses physical principles like steric hindrance, or charge, but those can be traced back to the 1800s – antibodies and cloning have revolutionized this technique), FACS uses the same charge principles that western blots do, but with the addition of antibodies…
Something special happens when a field becomes self-reinforcing. Previously, biology looked to physics and other disciplines for tools to break open new frontiers. But, empirically, since the 1950s, that has all changed.We don’t make mutant mice with x-rays and microscopes – we figure out the gene we want to go after, and we use high-precision biological tools to change it. Computer science has certainly played an important role in processing all of the information now streaming out of biological systems, but the major advances – the core things driving progress in biology forward – have come from biology itself. Biology is eating physics (and, some would jokingly suggest, based on the outperforming endurance of DNA compared to any modern hardware and plausibility of biological computation, possibly computation itself).
Naively, if we can expect n new discoveries / t tools we have, if the tools are static, maybe that’s a fixed number of discoveries per year. But if t tools increases, then we get more discoveries. What if it increases as a function of n?
This is important because it’s a self-reinforcing loop. The more things in biology we discover today, the faster we can discover things tomorrow. Biologists are the new engineers. But their tools look a lot different than any we’ve seen before. Sequencing is the microscope of tomorrow. And sequencing was built by biological tools.
The entire (short) essay is of interest. Here is more on Laura Deming.
People often express political opinions in starkly dichotomous terms, such as “Trump will either trigger a ruinous trade war or save U.S. factory workers from disaster.” This mode of communication promotes polarization into ideological in-groups and out-groups. We explore the power of an emerging methodology, forecasting tournaments, to encourage clashing factions to do something odd: to translate their beliefs into nuanced probability judgments and track accuracy over time and questions. In theory, tournaments advance the goals of “deliberative democracy” by incentivizing people to be flexible belief updaters whose views converge in response to facts, thus depolarizing unnecessarily polarized debates. We examine the hypothesis that, in the process of thinking critically about their beliefs, tournament participants become more moderate in their own political attitudes and those they attribute to the other side. We view tournaments as belonging to a broader class of psychological inductions that increase epistemic humility and that include asking people to explore alternative perspectives, probing the depth of their cause-effect understanding and holding them accountable to audiences with difficult-to-guess views.
That is a new paper from Barbara Mellers, Philip Tetlock, and Hal R. Arkes, via the excellent Kevin Lewis and Michelle Dawson. One very general implication is that there are mental, writing, and practical exercises that really can improve your habits of thought.
COWEN: So you receive an offer to run Google. Why were you so skeptical about Google at first?
SCHMIDT: Well, I assumed that search wasn’t very important, and I assumed the ads didn’t work. I was so concerned about the ads that, after I accepted the offer — because it just seemed like it was interesting, and a lot of luck comes from doing things that are interesting, and sort of creating your own luck — I hauled the then–sales executive, whose name was Tim Armstrong, who you all know well, and I said, “Tim, prove to me that these ads work.”
So they showed me a set of ads, and they looked pretty foolish to me. So I said, “Well, let’s go find the finance person,” of which there was one, and the accounting system was done on QuickBooks. I said, “Prove to me that people are paying for these ads,” and they did.
We then did an ads conversion in the first year, which was called Project Drano, where we basically took three different ads databases, which were simple compared to today’s databases, and merged them into one. And I was terrified, absolutely terrified that the ruse that we had — because we had fixed pricing on our ads — that people would discover that our ads were not worth anything.
So I organized what I called the cash restriction period, where the only thing you could do if you wanted to spend money, is you could only spend money on Friday at 10 AM, and you had to come to me to justify it, which very much shuts down spending.
So we get to this conversion, we turn the thing over, and of course, we didn’t bother to build into the tools. We had no metrics. We didn’t know what was going on. I’m going, “Oh my God, the company is bankrupt. My first year, I’ve done a terrible job. What will the board think?” I did my best to notify everybody we were going to go kaput.
The auction produced a price that was three times higher than the previous prices. Very interesting. So much for the cash restriction period, and the rest is history.
And from Eric:
We did all sorts of things. My favorite example is that we would interview people to death. We interviewed this one gentleman sixteen times, and we couldn’t decide. So I picked a random number, which was half, and I said, “We should have a max of eight, and if we can’t decide after eight . . .” We’ve since done a statistical analysis, and the answer today is four to five interviews.
And here is my bit on Eric:
COWEN: Now early on, you were an intern at Bell Labs, and also PARC, which belonged to Xerox, and I think of those two institutions as stemming from earlier glory years of American science.
Is it fair to think of your career as in some sense, you’re the person who spans those two eras, the Bell Labs-PARC era of doing things, and then the tech era of manipulating information, and that your ability to bring expertise from those two areas together is what has made you a unique figure? Is that a fair assessment of how you fit into the picture?
And there is this bit:
COWEN: How did it influence you having a father who was a famous economist? He wrote on balance of payments crises. What did you draw from him? Did that have a role in using so much economics in Google?
SCHMIDT: Well, what’s interesting is, I asked my father, “If you’re such a good economist, why are we not rich?”
Jeffrey Sachs (not the economist) asks, Why are psychologists so prevalent in the free speech movement?:
If any academic field is associated with the contemporary debate surrounding free speech, it’s psychology. Haidt, Pinker, Peterson, Saad, Jussim, even Lehmann. All specialize or have backgrounds in academic psych.
The Scholar’s Stage offers a good answer:
I attribute this all to three things.
1. The conclusions academics reach tend to rankle the right. There are exceptions. If your research draws on evolutionary psychology, focuses on innate behavioral differences, or touches any sort of psychometrics (e.g., IQ), the angry tide does not sweep in from the right. The wave these men and women fear crashes in from leftward side. Moreover, the sort of leftist opposition that the academic consensus on these topics face leaves little room for rational debate or compromise: controversies over psychometrics or evolutionary psychology are usually framed in terms of good and evil, not right and wrong. The scientists involved are to be conquered, not reasoned with.
So that is point one: the people who want to shut controversial psychologists up are overwhelmingly creatures of the left.
2. Psychology, especially social psychology, is itself an overwhelmingly leftist discipline. We actually have data on this, and it is pretty grim: a recent survey of American tenure-track professors reveals that there 17.4 registered Democrat psychologists for every single registered Republican. If there is a field of people who ought to be sympathetic to social justice railroading, these people are it.
3. Despite this, behavioral scientists have not yet adopted the rhetorical techniques or methodology of inquiry of “critical theory.” In contrast, see how these modes of inquiry have swallowed up the fields of anthropology and communications, and established creeping colonies in history, sociology, and area studies. Given the left-leaning sympathies of almost all in the profession, the threat that the same might happen to the study of human behavior is real.
…Haidt et. al. are confident they can win the debate if they are allowed to debate. For the heterodox anthropologist or sociologist the game is already over: their discipline has already been conquered. For the economist, the threat is too remote to take seriously. Behavioral science exists in that rare in-between: methodologically, it has the tools to fight back against the excesses of the activist. Socially, it provides a compelling reason for its practitioners to use them.
Previously, she has made dairy products from the perspiration of Bill Gates and Mark Zuckerberg.
Here is the full article. And:
In one exhibition, [Sissel] Tolaas captured the armpit sweat of severely anxious men from Greenland to China, recreated their individual smells and painted them onto the walls of the installation. (“There was a composite odor of anxiety that just infused the whole room, and it was really unhinging,” said Howes, who saw it in Basel, Switzerland). After the smell of fear, Tolaas recreated the smell of violence from cage fighters in East London. She has recreated the scents of Berlin’s famed Berghain nightclub, New York’s Central Park in October, World War I, communism and the ocean. Her shows are immersive and emotional in a distracted world. They aim to grip audiences right by the lizard brain.
Tolaas also invented 1,500 “smell memory kits” — abstract odors that have never been smelled before. When you want to remember an event, you open the amulet and inhale, sealing the moment in your emotional core. For the London Olympics, she made a Limburger cheese sourced from David Beckham’s sweaty socks, which was served to VIPs.
File under “Department of Why Not?”
Could ‘Oumuamua be debris from a technological civilization, a discarded lightsail?
Here is more.
We use a novel dataset of job flyouts for junior economists to investigate three aspects of the market for “stars”. First, what is the background of students who become stars? Second, what type of research does the top of the market demand? Third, where do these students take jobs? Among other results, we show that stars are more international and less female than PhDs overall, that theoretical and semi-theoretical approaches remain dominant, that American programs both produce the most stars and hire even more, that the private sector is largely uncompetitive, and that there is a strong shift toward stars having pre-PhD full-time academic research jobs.
And here is a point on the stickiness of academic rankings over time:
In economics, among the 13 programs with the most published pages in a Top 5 journal by their faculty between 2002 and 2009, all 13 were among the top 18 in the same ranking for publications between 1974 and 1978 (McPherson )!
“!” is right! And this:
…almost 80% of the faculty at a top 10 economics department did their PhD in a top 10, compared to 58% in mathematics and 63% in literature.
Nor are any criticisms of that research presented. The title and subheader of the piece (NYT) are:
A Dark Consensus About Screens and Kids Begins to Emerge in Silicon Valley
“I am convinced the devil lives in our phones.”
Doesn’t a consensus have to be…scientific? The article does cite many tech people who are limiting the screen time of their children. That may well be a good thing. But tech people also may not have the best balanced understanding of the scientific issues involved, or of how tech is used outside of tech communities (and their children) themselves.
Literally speaking, the headline refers only to a consensus in Silicon Valley. But I do not myself see such a consensus out there during my visits, and it is not obvious within the article what the views of the dissenters might be, or how prominent or numerous those dissenters are. Or even whether they are dissenters or the mainstream. Furthermore, most readers will take this piece to be referring to a broader scientific consensus, which does not in fact exist. And yes I have read some of the published research indicating that tech damages people’s mental capacities and, while such claims may end up being true, I do not find the current research very convincing. In any case, such research ought to have been considered, pro and con.
We have now reached the point where tech is one of the worst covered subject areas by the U.S. and also British media.
To say the least:
Suppose that asset pricing factors are just data mined noise. How much data mining is required to produce the more than 300 factors documented by academics? This short paper shows that, if 10,000 academics generate 1 factor every minute, it takes 15 million years of full-time data mining. This absurd conclusion comes from rigorously pursuing the data mining theory and applying it to data. To fit the fat right tail of published t-stats, a pure data mining model implies that the probability of publishing t-stats < 6.0 is ridiculously small, and thus it takes a ridiculous amount of mining to publish a single t-stat. These results show that the data mining alone cannot explain the zoo of asset pricing factors.
That is from a new paper by Andrew Y. Chen at the Fed.
A new paper in Science adds support to the so-called gender-equality paradox. Using a survey of some 80,000 people across 76 countries Falk and Hermle find that for a variety of preferences the differences between the genders gets larger the greater is economic development and gender equality. The basic story is here:
As the authors put it:
In sum, greater availability of material and social resources to both women and men may facilitate the independent development and expression of gender-specific preferences, and hence may lead to an expansion of gender differences in more developed and gender-egalitarian countries.
As I pointed out in my post, Do Boys Have a Comparative Advantage in Math and Science? results like this can explain why there are proportionately fewer women entering STEM fields in richer and more gender-equal countries than in poorer and less gender-equal countries.
One point which many people are missing is that small but growing gender differences with development are only one minor effect of a much bigger phenomena. In a primitive economy, everyone does more or less the same thing, subsistence farming. Only in a market economy under the division of labor can people specialize. Specialization reflects and amplifies diverse personalities and interests. People sometimes complain about “excess” variety in a market economy but do they extend that complaint to careers, arts, and lifestyles? In a market society we get Corn Flakes, Frosted Flakes and Coconut Flakes and we get cardiologists, dermatologists and otolaryngologists and we get Chicago Blues, dub step, and K-Pop and we also get a flowering of sexual preferences and lifestyles. As Mises once said the very idea of personality as we know it today is a result of the market economy. The small gender differences some people focus on are merely the averaging by gender of much larger individual differences. Thus, I would revise the authors:
In sum, greater availability of material and social resources facilitates the independent development and expression of individual-specific preferences, and hence may lead to an expansion of individual differences in more developed and equal-opportunity countries.