Dispatches from “Enlightenment Now:” Intellectuals

One of the blog posts I’m working on demands that I give Steven Pinker’s Enlightenment Now an in-depth skim, and it’s dredging up all sorts of secondary things. I might as well take advantage of that, and spread the misery around.

For instance, are we sure Pinker isn’t a secret far-Right plant?

Intellectuals hate progress. Intellectuals who call themselves “progressive” really hate progress. It’s not that they hate the fruits of progress, mind you: most pundits, critics, and their bienpensant readers use computers rather than quills and inkwells, and they prefer to have their surgery with anesthesia rather than without it. It’s the idea of progress that rankles the chattering class — the Enlightenment belief that by understanding the world we can improve the human condition.

Pinker, Steven. Enlightenment Now: The Case for Reason, Science, Humanism, and Progress. Penguin, 2018. pg. 43.

His hatred for “intellectuals” is astonishing, especially since the blurb for Enlightenment Now calls him one. Isn’t the whole thesis of the book that we should all become more enlightened, more intellectual? And yet it contains an endless parade of scorn for those who are known for their intelligence.

At various times Western intellectuals have also sung the praises of Ho Chi Minh, Muammar Gaddafi, Saddam Hussein, Kim II-sung, Pol Pot, Julius Nyerere, Omar Torrijos, Slobodan Milogevié, and Hugo Chavez.

Why should intellectuals and artists, of all people, kiss up to murderous dictators? One might think that intellectuals would be the first to deconstruct the pretexts of power, and artists to expand the scope of human compassion. (Thankfully, many have done just that.) One explanation, offered by the economist Thomas Sowell and the sociologist Paul Hollander, is professional narcissism. Intellectuals and artists may feel unappreciated in liberal democracies, which allow their citizens to tend to their own needs in markets and civic organizations. Dictators implement theories from the top down, assigning a role to intellectuals that they feel is commensurate with their worth. But tyrannophilia is also fed by a Nietzschean disdain for the common man, who annoyingly prefers schlock to fine art and culture, and by an admiration of the superman who transcends the messy compromises of democracy and heroically implements a vision of the good society.

pg. 451

Though intellectuals are apt to do a spit take when they read a defense of capitalism, its economic benefits are so obvious that they don’t need to be shown with numbers. They can literally be seen from space. A satellite photograph of Korea showing the capitalist South aglow in light and the Communist North a pit of darkness vividly illustrates the contrast in the wealth-generating capability between the two economic systems, holding geography, history, and culture constant. Other matched pairs with an experimental group and a control group lead to the same conclusion: West and East Germany when they were divided by the Iron Curtain; Botswana versus Zimbabwe under Robert Mugabe; Chile versus Venezuela under Hugo Chávez and Nicolás Maduro — the latter a once-wealthy, oil-rich country now suffering from widespread hunger and a critical shortage of medical care.

pg. 95

This evidence-based take on the Enlightenment project reveals that it was not a naive hope. The Enlightenment has worked — perhaps the greatest story seldom told. And because this triumph is so unsung, the underlying ideals of reason, science, and humanism are unappreciated as well. Far from being an insipid consensus, these ideals are treated by today’s intellectuals with indifference, skepticism, and sometimes contempt. When properly appreciated, I will suggest, the ideals of the Enlightenment are in fact stirring, inspiring, noble — a reason to live.

pg. 11

In 2016, a majority of Americans named terrorism as the most important issue facing the country, said they were worried that they or a family member would be a victim, and identified ISIS as a threat to the existence or survival of the United States. The fear has addled not just ordinary citizens trying to get a pollster off the phone but public intellectuals, especially cultural pessimists perennially hungry for signs that Western civilization is (as always) on the verge of collapse.

pg. 196

Intellectual culture should strive to counteract our cognitive biases, but all too often it reinforces them.

pg. 53

(The myth, still popular among leftist intellectuals, that IQ doesn’t exist or cannot be reliably measured was refuted decades ago.)

pg. 248

I used to think that Trumpism was pure id, an upwelling of tribalism and authoritarianism from the dark recesses of the psyche. But madmen in authority distill their frenzy from academic scribblers of a few years back, and the phrase “intellectual roots of Trumpism” is not oxymoronic. Trump was endorsed in the 2016 election by 136 “Scholars and Writers for America” in a manifesto called “Statement of Unity.” Some are connected to the Claremont Institute, a think tank that has been called “the academic home of Trumpism.” And Trump has been closely advised by two men, Stephen Bannon and Michael Anton, who are reputed to be widely read and who consider themselves serious intellectuals. Anyone who wants to go beyond personality in understanding authoritarian populism must appreciate the two ideologies behind them, both of them militantly opposed to Enlightenment humanism and each influenced, in different ways, by Nietzsche. One is fascist, the other reactionary — not in the common left-wing sense of “anyone who is more conservative than me,” but in their original, technical senses.

pg. 452

Pinker is apparently unaware of the right-wing think tank machine, which props up shady characters as “intellectuals” in order to advance the interests of wealthy donors. Those 136 “scholars and writers” include Newt Gingrich and Peter Thiel, FYI. The organizer of the manifesto is F.H. Buckley, a member of the Heartland Institute, and said Institute is notorious for promoting climate change denial. Steve Bannon may consider himself an intellectual, but belief is not the same as reality, and Michael Anton is arguably more ridiculous.

I know, I know, you could argue that Pinker’s focusing just on the “literary intellectuals” as per C.P. Snow’s “Two Cultures.” Sorry, that’s not plausible. Notice the lack of any qualifiers for some of these quotes, as well; Pinker is including a significant majority of all intellectuals in his tirades, at minimum.

[feels a tap on his shoulder]

Er, uh what-

What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or ‘‘factors’’ reflect the functional organization of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demonstrate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor ‘‘g’’ is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these components of intelligence by dissociating them using questionnaire variables. We propose that intelligence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.

Hampshire, Adam, et al. “Fractionating human intelligence.” Neuron 76.6 (2012): 1225-1237.

Whoa whoa whoa, what’s a study that refutes the idea of a single-factor measure of intelligence doing here?! Shoo! Go away, you’re off topic!

[hears something scamper away]

That’s better.

Howard Gardner’s brilliant conception of individual competence has changed the face of education in the twenty-three years since the publication of his classic work, Frames of Mind. Since then thousands of educators, parents, and researchers have explored the practical implications and applications of Multiple Intelligences theory–the powerful notion that there are separate human capacities, ranging from musical intelligence to the intelligence involved in self-understanding. The first decade of research on MI theory and practice was reported in the 1993 edition of Multiple Intelligences. This new edition covers all developments since then and stands as the most thorough and up-to-date account of MI available anywhere. Completely revised throughout, it features new material on global applications and on MI in the workplace, an assessment of MI practice in the current conservative educational climate, new evidence about brain functioning, and much more.

Gardner, Howard E. Multiple intelligences: New horizons in theory and practice. Basic books, 2008.

THAT’S IT!! I’m ending this blog post right now!

Back to Basics

A friend asked for an explainer on Bayesian statistics, and I instinctively reached for Yudkowsky’s only to find this at the top:

This page has now been obsoleted by a vastly improved guide to Bayes’s Theorem, the Arbital Guide to Bayes’s Rule. Please read that instead. Seriously. I mean it.

You can see why once you’ve clicked the link; it asks for your prior experience, then tailors the explanation appropriately. There’s also some good diagrams, and it tries to explain the same concept multiple ways to hammer the point home. Their bit on p-values is on-point, too.

Speaking of stats, I’ve also been drawn back into a course on probability I started years ago. MIT OpenCourseware has a lot of cool offerings, but this entry on probability has been worth my attention. While E.T. Jaynes’ Probability Theory still has my favourite treatment of the subject, the video lectures are easier to parse and proceed at a faster clip.

Sam Harris “Corrects” the Record

Whelp, less than thirty-eight hours after my blog post Sam Harris finally deleted that old video. However, spotting that made me realise I’d missed his explanation for why he edited the episode. That was probably by design, the description to the podcast episode drops no hint that it’s there.

As before, I’ve done some light editing, but also included time-stamps so you can check my work.

[3:17] Just a little housekeeping for today’s episode. A few episodes back, I presented audio from an event I did with Christian Picciolini in Dallas, and that was a fun event, I enjoyed speaking with Christian a lot […]

[3:51] But unfortunately, in that podcast, Christian said a few things that don’t seem to have been strictly true, and as the weeks have passed and that podcast has continued streaming I’ve heard from two people who consider his remarks to have been unfairly damaging to their reputations. This is a problem that I am quite sensitive to, given what gets done to me, by my critics. Somewhat ironically, Christian seems to rely on the Southern Poverty Law Center for much of his information, but this is an organization, as many of you know, which is undergoing a full moral and intellectual self-immolation. In fact, Christian is confused enough about the stature of that organization that he retweeted an article from the SPLC website wherein I am described as a racist recruiter for the alt-right. […]

We’re barely a minute in, and Harris has badly distorted the record. One of Picciolini’s tweets references the Southern Poverty Law Center, true, but he also cites tweets by David Duke, The Daily Stormer, Wikipedia (and before you start, I checked the citations and it’s legit), Joe Rogan, YouTube recordings of Molyneux, and his experiences talking to families with Molyneux-obsessed members. Yet that one reference to the SPLC somehow translates into “much of his information?”

Harris also misrepresents that SPLC article. They didn’t declare him to be a recruiter, self-declared members of the alt-Right said that Sam Harris helped lead them to the alt-Right.

[Read more…]

The Return of COINTEL-PRO

You remember them, right? A secretive group within the FBI who targeted “domestic subversives” like Martin Luther King Jr. and Roberta Salper, with tactics that ranged from surveillance to blackmail to false flag ops and entrapment. Even the modern FBI agrees it was both unethical and unlawful.

Rakem Balogun thought he was dreaming when armed agents in tactical gear stormed his apartment. Startled awake by a large crash and officers screaming commands, he soon realized his nightmare was real, and he and his 15-year-old son were forced outside of their Dallas home, wearing only underwear.

Handcuffed and shaking in the cold wind, Balogun thought a misunderstanding must have led the FBI to his door on 12 December 2017. The father of three said he was shocked to later learn that agents investigating “domestic terrorism” had been monitoring him for years and were arresting him that day in part because of his Facebook posts criticizing police.

This isn’t on the same level, but it’s close. FBI officials monitored, arrested, and prosecuted Rakem Balogun for the high crime of being angry enough at how black people are treated in the USA to organize and agitate.

Authorities have not publicly labeled Balogun a BIE [Black Identity Extremist], but their language in court resembled the warnings in the FBI’s file. German said the case also appeared to utilize a “disruption strategy” in which the FBI targets lower-level arrests and charges to interfere with suspects’ lives as the agency struggles to build terrorism cases.

“Sometimes when you couldn’t prove somebody was a terrorist, it’s because they weren’t a terrorist,” he said, adding that prosecutors’ argument that Balogun was too dangerous to be released on bail was “astonishing”. “It seems this effort was designed to punish him for his political activity rather than actually solve any sort of security issue.”

The official one-count indictment against Balogun was illegal firearm possession, with prosecutors alleging he was prohibited from owning a gun due to a 2007 misdemeanor domestic assault case in Tennessee. But this month, a judge rejected the charge, saying the firearms law did not apply.

Ruined his life for it, too; he lost his job, house, and car because of overzealous FBI agents. Amazingly, their crusade lacks the weight of evidence.

The government’s own crime data has largely undermined the notion of a growing threat from a “black identity extremist” [BIE] movement, a term invented by law enforcement. In addition to an overall decline in police deaths, most individuals who shoot and kill officers are white men, and white supremacists have been responsible for nearly 75% of deadly extremist attacks since 2001.

The BIE surveillance and failed prosecution of Balogun, first reported by Foreign Policy, have drawn comparisons to the government’s discredited efforts to monitor and disrupt activists during the civil rights movement, particularly the FBI counterintelligence program called Cointelpro, which targeted Martin Luther King Jr, the NAACP and the Black Panther party.

OK, if I keep talking about this I’ll just wind up quoting the entire article. Go read it and witness the injustice yourself.

Continued Fractions

If you’ve followed my work for a while, you’ve probably noted my love of low-discrepancy sequences. Any time I want to do a uniform sample, and I’m not sure when I’ll stop, I’ll reach for an additive recurrence: repeatedly sum an irrational number with itself, check if the sum is bigger than one, and if so chop it down. Dirt easy, super-fast, and most of the time it gives great results.

But finding the best irrational numbers to add has been a bit of a juggle. The Wikipedia page recommends primes, but it also claimed this was the best choice of all:\frac{\sqrt{5} - 1}{2}

I couldn’t see why. I made a half-hearted attempt at digging through the references, but it got too complicated for me and I was more focused on the results, anyway. So I quickly shelved that and returned to just trusting that they worked.

That is, until this Numberphile video explained them with crystal clarity. Not getting the connection? The worst possible number to use in an additive recurrence is a rational number: it’ll start repeating earlier points and you’ll miss at least half the numbers you could have used. This is precisely like having outward spokes on your flower (no seriously, watch the video), and so you’re also looking for any irrational number that’s poorly approximated by any rational number. And, wouldn’t you know it…

\frac{\sqrt{5} - 1}{2} ~=~ \frac{\sqrt{5} + 1}{2} - 1 ~=~ \phi - 1

… I’ve relied on the Golden Ratio without realising it.

Want to play around a bit with continued fractions? I whipped up a bit of Go which allows you to translate any number into the integer sequence behind its fraction. Go ahead, muck with the thing and see what patterns pop out.

Abductive and Inferential Science

I love it when Professor Moriarty wanders back to YouTube, and his latest was pretty good. He got into a spot of trouble at the end, which led me to muse on writing a blog post to help him out. I’ve already covered some of that territory, alas, but in the process I also stumbled on something more interesting to blog about. It also effects Sean Carroll’s paper, which Moriarty relied on.

The fulcrum of my topic is the distinction between inference and abduction. The former goes “I have a hypothesis, what does the data say about it?,” while the latter goes “I have data, can I find a hypothesis which explains it?” Moriarty uses this as a refutation of falsification: if we start from the data instead of the hypothesis, we’re not trying to falsify anything! To add salt to the wound, Moriarty argues (and I agree) that a majority of scientific activity consists of abduction and not inference; it’s quite common for scientists to jump from one topic to another, essentially engaging in a tonne of abductive activity until someone forces them to write up a hypothesis. Sean Carroll doesn’t dwell on this as much, but his paper does treat abduction and inference as separate things.

They aren’t separate, at least when it comes to the Bayesian interpretation of statistics. Let’s use a toy example to explain how; here’s a black box with a clear cover:

import ("math/rand")

func blackbox() float64 {

     x := rand.Float64()
     return (4111 + x*(4619 + x*(3627 + x*(7392*x - 9206)))/1213
     }

Each time we turn the crank on this function, we get back a number of some sort. The abductive way to analyse this is pretty straightforward: we grab a tonne of numbers and look for a hypothesis. I’ll go for the mean, median, and standard deviation here, the minimum I’ll need to check for a Gaussian distribution.

Samples = 1000001
Mean    = 5.61148
Std.Dev = 1.40887
Median  = 5.47287

Looks like there’s a slight skew downwards, but it’s not that bad. So I’ll propose that the output of this black box follows a Gaussian distribution, with mean 5.612 and standard deviation 1.409, until I can think of a better hypothesis which handles the skew.

After we reset for the inferential analysis, we immediately run into a problem: this is a black box. We know it has no input, and outputs a floating-point number, and that’s it. How can we form any hypothesis, let alone a null and alternative? We’ve no choice but to make something up. I’ll set my null to be “the black box outputs a random floating-point number,” and the alternative to “the output follows a Gaussian distribution with a mean of 0 and a standard deviation of 1.” Turn the crank, aaaand…

Samples            = 1000001
log(Bayes Factor)  = 26705438.01142
  (That means the most likely hypothesis is H1 (Gaussian distribution, mean = 0, std.dev = 1))

Unsurprisingly, our alternative does a lot better than our null. But our alternative is wrong! We’d get that impression pretty quickly if we watched the numbers streaming in. There’s an incredible temptation to take that data to refine or propose a new hypothesis, but that’s an abductive move. Inference is really letting us down.

Worse, this black box isn’t too far off from the typical science experiment. It’s rare any researcher is querying a black box, true, but it’s overwhelmingly true that they’re generating new data without incorporating other people’s datasets. It’s also rare you’re replicating someone else’s work; most likely, you’re taking existing ideas and rearranging them into something new, so prior findings may not carry forward. Inferential analysis is more tractable than I painted it, I’ll confess, but the limited information and focus on novelty still favors the abductive approach.

But think a bit about what I did on the inferential side: I picked two hypotheses and pitted them against one another. Do I have to limit myself to two? Certainly not! Let’s rerun the analysis with twenty-two hypotheses: the flat distribution we used as a null before, plus twenty-one alternative hypotheses covering every integral mean from -10 to 10 (though keeping the standard deviation at 1).

Samples                                 = 100001
log(likelihood*prior), H0               = -4436161.89971
log(likelihood*prior), H1, mean = -10   = -12378220.82173
log(likelihood*prior), H1, mean =  -9   = -10866965.39358
log(likelihood*prior), H1, mean =  -8   = -9455710.96544
log(likelihood*prior), H1, mean =  -7   = -8144457.53730
log(likelihood*prior), H1, mean =  -6   = -6933205.10915
log(likelihood*prior), H1, mean =  -5   = -5821953.68101
log(likelihood*prior), H1, mean =  -4   = -4810703.25287
log(likelihood*prior), H1, mean =  -3   = -3899453.82472
log(likelihood*prior), H1, mean =  -2   = -3088205.39658
log(likelihood*prior), H1, mean =  -1   = -2376957.96844
log(likelihood*prior), H1, mean =   0   = -1765711.54029
log(likelihood*prior), H1, mean =   1   = -1254466.11215
log(likelihood*prior), H1, mean =   2   = -843221.68401
log(likelihood*prior), H1, mean =   3   = -531978.25586
log(likelihood*prior), H1, mean =   4   = -320735.82772
log(likelihood*prior), H1, mean =   5   = -209494.39958
log(likelihood*prior), H1, mean =   6   = -198253.97143
log(likelihood*prior), H1, mean =   7   = -287014.54329
log(likelihood*prior), H1, mean =   8   = -475776.11515
log(likelihood*prior), H1, mean =   9   = -764538.68700
log(likelihood*prior), H1, mean =  10   = -1153302.25886
  (That means the most likely hypothesis is H1 (Gaussian distribution, mean = 6, std.dev = 1))

Aha, the inferential approach has finally gotten us somewhere! It’s still wrong, but you can see the obvious solution: come up with as many hypotheses as you can to explain the data, before we look at it, and run them all as the data rolls in. If you’re worried about being swamped by hypotheses, I’ve got a word for you: marginalization. Bayesian statistics handles hypotheses with parameters by integrating over all of them; you can think of these as composites, a mash of point hypotheses which collectively do a helluva lot better at prediction than any one hypothesis in isolation. In practice, then, Bayesians have always dealt with large numbers of hypotheses simultaneously.

The classic example of this is conjugate priors, where we carefully combine hyperparameters to evaluate a potentially infinite family of probability distributions. In fact, let’s try it right now: the proper conjugate here is the Normal-Inverse-Gamma, as we’re tracking both the mean and standard deviation of Gaussian distributions.

Samples = 1000001
μ       = 5.61148
λ       = 1000001.00000
α       = 500000.50000
β       = 992457.82655

median  = 5.47287

That’s a good start, μ lines up with the mean we calculated earlier, and λ is obviously the sample count. The shape of the posteriors is still pretty opaque, though; we’ll need to chart this out by evaluating the Normal-Inverse-Gamma PDF a few times.Conjugate posterior for the collection of all Gaussian distributions which could describe the data.Excellent, the inferential method has caught up to abduction! In fact, as of now they’re both working identically. Think: what’s the difference between a hypothesis you proposed before collecting the data, and one you proposed after? In frequentism, the stopping problem implies that we could exit early and falsely reject our null, when data coming down the pipe would have pushed it back to “fail to reject.” There, the choice of hypothesis could have an influence on the outcome, so there is a difference between the two cases. This is made worse by frequentism’s obsession over one hypothesis above all others, the null.

Bayesian statistics is free of that problem, because every hypothesis is judged on their relative likelihood in reference to a dataset shared by all hypotheses. There is no stopping problem baked into the methodology. Whether I evaluate any given hypothesis before or after I collect the data is irrelevant, because either way it has to cope with all the data. This also frees me up to invent hypotheses whenever I wish.

But this also defeats the main attack against falsification. The whole point of invoking abduction was to save us from asserting any hypotheses in the beginning; if there’s no difference in when we invoke our hypotheses, however, then falsification might still apply.

Here’s where I return to giving Professor Moriarity a hand. He began that video by saying scientists usually don’t engage in falsification, hence it cannot be The Scientific Method, but ended it by approvingly quoting Feynman: “We are trying to prove ourselves wrong as quickly as possible, because only in that way can we find progress.” Isn’t that falsification, right there?

This is yet another area where frequentist and Bayesian statistics diverge. As I pointed out earlier, frequentism is obsessed with falsifying the null hypothesis and trying to prove it wrong. Compare and contrast with what past-me wrote about Bayes Factors:

If data comes up that doesn’t square well with a hypothesis, its certainty takes a hit. But if we’re comparing it to another hypothesis that also doesn’t predict the data, the Bayes Factor will remain close to 1 and our certainties won’t shift much at all. Likewise, if both hypotheses strongly predict the data, the Factor again stays close to 1. If we’re looking to really shift our certainty around, we need a big Bayes Factor, which means we need to find scenarios where one hypothesis strongly predicts the data while the other strongly predicts this data shouldn’t happen.

Or, in other words, we should look for situations where one theory is… false. That sounds an awful lot like falsification!

But it’s not the same thing. Scroll back up to that Normal-Inverse-Gamma PDF, and pick a random point on the graph. The likelihood at that point is less than the likelihood at the maximum point. If you were watching those two points as we updated with new data, your choice would have gradually gone from about equally likely to substantially less likely. Your choice is more likely to be false, all things being equal, but it’s also not false with a capital F. Maybe the first million data points were a fluke, and if we continued sampling to a billion your choice would roar back to the top? This is the flip-side of having no stopping problem: the door is always left open a crack for any crackpot hypotheses to make a comeback.

Now look closely at the scale of the vertical axis. That maximal likelihood is well above 100%! In fact it’s somewhere around 4,023,000% by my calculations. While the vast majority are dropping downwards, there’s an ever-shrinking huddle of points that are becoming more likely as data is added! Falsification should only make things less likely, however.

Under Bayesian statistics, falsification is treated as a heuristic rather than a core part of the process. We’re best served by trying to find areas where hypotheses differ, yet we never declare one hypothesis to be false. This saves Moriarty: he’s both correct in disclaiming falsification, and endorsing the process of trying to prove yourself wrong. The confusion between the two stems from having to deal with two separate paradigms that appear to have substantial overlap, even though a closer look reveals fundamental differences.

“Aggressive, unpredictable, unreliable”

It’s funny, Trump didn’t used to be this opposed to Iran. Now, between all the domestic scandals he faces, and his love of military power along with the warmongering far-right, he’s decided to reverse course and get aggressive with Iran.

“It is clear to me that we cannot prevent an Iranian nuclear bomb under the decaying and rotten structure of the current agreement,” Trump said from the White House Diplomatic Room. “The Iran deal is defective at its core. If we do nothing we know exactly what will happen.” In announcing his decision, Trump said he would initiate new sanctions on the regime, crippling the touchstone agreement negotiated by his predecessor. Trump said any country that helps Iran obtain nuclear weapons would also be “strongly sanctioned.”
“This was a horrible one-sided deal that should have never, ever been made,” the President said. “It didn’t bring calm, it didn’t bring peace, and it never will.” … “At the point when the US had maximum leverage, this disastrous deal gave this regime — and it’s a regime of great terror — many billions of dollars, some of it in actually cash — a great embarrassment to me as a citizen,” Trump said.

One problem: what are the consequences of withdrawing? Iran’s nuclear program was going fine when they were under earlier sanctions, so imposing sanctions isn’t going to have much effect. As for the political situation within Iran,

Sadeq Zibakalam, a prominent political commentator and professor of politics at Tehran University, struck a pessimistic tone about the consequences of Trump’s decision in Iran. “Many people are worried about war,” he told the Guardian on phone from Tehran. “Whenever the country faces a crisis in its foreign policy or economy, the situation gets better for hardliners, they’d be able to exert their force more easily.”

He added: “At the same time, hardliners will gain politically from this situation, because they’ll attack reformists and moderates like [President] Rouhani that this is evidence of what they had been saying for years, that the US cannot be trusted, and that US is always prepared to knife you in the back.”

Zibakalam, who is close to the reformists, said he did not think it would take long for Europeans and other nations to follow in the footsteps of the US, because they won’t endanger their economic ties with Washington, which would outweigh the benefits of doing business with Iran.

Rouhani has taken an aggressive stance to jump in front of the hardliners.

“This is a psychological war, we won’t allow Trump to win… I’m happy that the pesky being has left the Barjam,” he said referring to Persian acronym for JCPOA or the nuclear deal.

“Tonight we witnessed a new historic experience… for 40 years we’ve said and repeated that Iran always abides by its commitments, and the US never complies, our 40-year history shows us Americans have been aggressive towards great people of Iran and our region .. from the [1953] coup against the legitimate government of [Mohammad] Mosaddegh Mosadeq government and their meddling in the affairs of the last regime, support for Saddam [Hussein during Iran-Iraq war] and downing or our passenger plane by a US vessel and their actions in Afghanistan, in Yemen,” he said.

“What Americans announced today was a clear demonstration of what they have been doing for months. Since the nuclear deal, when did they comply? They only left a signature and made some statements, but did nothing that would benefit the people of Iran.”

Rouhani said the International Atomic Energy Agency (the IAEA) has verified that Tehran has abide by its obligations under the deal. “This is not an agreement between Iran and the US… for US to announce it’s pulling out, it’s a multilateral agreement, endorsed by the UN security council resolution 2231, Americans officially announcement today showed that their disregard for international commitments.. We saw that in their disregard for Paris agreement..

“Our people saw that the only regime that supports Trump is the illegitimate Zionist regime, the [s]ame regime that killed our nuclear scientists”

“From now on, this is an agreement between Iran and five countries… from now on the P5+1 has lost its 1… we have to wait and see how other react. If we come to the conclusion that with cooperation with the five countries we can keep what we wanted despite Israeli and American efforts, Barjam can cursive,” he said referring to Persian acronym for JCPOA or the nuclear deal.

“We had already come to the conclusion that Trump will not abide by international commitments and won’t respect Barjam.”

And the other signers to the Iran deal are keeping a stiff upper lip, at least for now.

According to the IAEA, Iran continues to abide by the restrictions set out by the JCPoA, in line with its obligations under the Treaty on the Non-Proliferation of Nuclear Weapons. The world is a safer place as a result. Therefore we, the E3, will remain parties to the JCPoA. Our governments remain committed to ensuring the agreement is upheld, and will work with all the remaining parties to the deal to ensure this remains the case including through ensuring the continuing economic benefits to the Iranian people that are linked to the agreement.

Most commentators are united in calling the withdrawal a prelude to disaster. Most Americans were fine with the Iran deal. Most of the world is starting to get on board this train:

Last year, on a reporting trip though a few European capitals, something I heard over and over from European foreign policy officials: We remember 2003, and we’re starting to think this is the real America. Aggressive, unpredictable, unreliable, and dangerous.

The Two Cultures, as per C. P. Snow

I’d never heard of C.P. Snow until Steven Pinker brought him up, but apparently he’s quite the deal. Much of it stems from a lecture Snow gave nearly sixty years ago. It’s been discussed and debated (funny meeting you here, Lawrence Krauss) to the point that I, several generations and one ocean away, can grab a reprint of the original with an intro about as long as the lecture itself.

Snow’s core idea is this: two types of intellectuals, scientists and elite authors, don’t talk with one another and are largely ignorant of each other’s work. His quote about elite authors being ignorant of physics is plastered everywhere, so I’d like to instead repeat what he said about scientists being ignorant of literature:

As one would expect, some of the very best scientists had and have plenty of energy and interest to spare, and we came across several who had read everything that literary people talk about. But that’s very rare. Most of the rest, when one tried to probe for what books they had read, would modestly confess “Well, I’ve tried a bit of Dickens”, rather as though Dickens were an extraordinarily esoteric, tangled and dubiously rewarding writer, something like Ranier Maria Rilke. In fact that is exactly how they do regard him: we thought that discovery, that Dickens had been transformed into the type-specimen of literary incomprehensibility, was one of the oddest results of the whole exercise. […]

Remember, these are very intelligent men. Their culture is in many ways an exacting and admirable one. It doesn’t contain much art, with the exception, and important exception, of music. Verbal exchange, insistent argument. Long-playing records. Colour photography. The ear, to some extent the eye. Books, very little, though perhaps not many would go so far as one hero, who perhaps I should admit was further down the scientific ladder than the people I’ve been talking about – who, when asked what books he read, replied firmly and confidently: “Books? I prefer to use my books as tools.” It was very hard not to let the mind wander – what sort of tool would a book make? Perhaps a hammer? A primitive digging instrument?

[Snow, Charles P. “The two cultures.” (1959): pg. 6-7]

To be honest, I have a hard time comprehending why the argument exists. If I were to transpose it to my place and time, it would be like complaining that Margaret Atwood, Alice Munro, and Michael Ondaatje are shockingly ignorant of basic physics, while if you were to quiz famous Canadian scientists about Canadian literature you’d eventually drag out a few mentions of Farley Mowat. I… don’t see the problem? Yes, it would be great if more people knew more things, but if you want to push the frontiers of knowledge you’ve got to focus on the specifics. Given that your time is (likely) finite, that means sacrificing some general knowledge. It would be quite ridiculous to ask someone in one speciality to explain something specific to another.

If we forget the scientific culture, then the rest of western intellectuals have never tried, wanted, or been able to understand the industrial revolution, much less accept it. Intellectuals, in particular literary intellectuals, are natural Luddites. [pg. 11-12]

The academics had nothing to do with the industrial revolution; as Corrie, the old Master of Jesus, said about trains running into Cambridge on Sunday, `It is equally displeasing to God and to myself’. So far as there was any thinking in nineteenth-century industry, it was left to cranks and clever workmen. American social historians have told me that much the same was true of the
U.S. The industrial revolution, which began developing in New England fifty years or so later than ours, apparently received very little educated talent, either then or later in the nineteenth century. [pg. 12]

… do we understand how they have happened? Have we begun to comprehend even the old industrial revolution? Much less the new scientific revolution in which we stand? There never was any thing more necessary to comprehend. [pg. 14]

Yep, that’s Snow trashing authors of high fiction for not having an understanding of the Industrial Revolution. It’s not an isolated case, either; Snow also criticises Cambridge art graduates for not being aware of “the human organisation” behind buttons [pg. 15]. He might as well have spent several paragraphs yelling at physicists for being unable to explain why Houlden Caulfield wanted to be a gas station attendant, he’s that far from reality.

Which gets us to the real consequences of Snow’s divide, and how he proposes heading them off at the pass.

To say we have to educate ourselves or perish, is a little more melodramatic than the facts warrant. To say, we have to educate ourselves or watch a steep decline in our own lifetime, is about right. We can’t do it, I am now convinced, without breaking the existing pattern. I know how difficult this is. It goes against the emotional grain of nearly all of us. In many ways, it goes against my own, standing uneasily with one foot in a dead or dying world and the other in a world that at all costs we must see born. I wish I could be certain that we shall have the courage of what our minds tell us. [pg. 20]

This disparity between the rich and the poor has been noticed. It has been noticed, most acutely and not unnaturally, by the poor. Just because they have noticed it, it won’t last for long. Whatever else in the world we know survives to the year 2000, that won’t. Once the trick of getting rich is known, as it now is, the world can’t survive half rich and half poor. It’s just not on.

The West has got to help in this transformation. The trouble is, the West with its divided culture finds it hard to grasp just how big, and above all just how fast, the transformation must be. [pg. 21-22]

So we need to educate scientists about the works of elite authors, and those authors about the work of scientists… because otherwise Britain will become impoverished, and/or we’d end poverty faster?! That doesn’t square up with the data. Let’s look at what the government of Namibia, a well-off African country, thinks will help end poverty.

  • Improving access to Community Skills Development Centres (Cosdecs) in remote areas and aligning the curriculum with that of the Vocational Training Centres.
  • To improve career options and full integration into the modern economy, there is need to introduce vocational subjects at upper primary and junior secondary levels. This will facilitate access to vocational education and labour market readiness by the youth.
  • Improving productivity of the subsistence agriculture by encouraging the use of both traditional and modern fertiliser and by providing information on modern farming methods.
  • The dismantling of the “Red Line” seems to hold some promise for livestock farmers in the North who were previously prevented access to markets outside of the northern regions.
  • Consider establishing a third economic hub for Namibia to relief Khomas and Erongo from migration pressure. With abundant water resources, a fertile land and being along the Trans Zambezi Corridor, Kavango East is a good candidate for an agricultural capital and a logistic growth point.
  • Given persistent drop-out rates especially in remote rural areas, there is need for increased access to secondary education by addressing both the distance and the quality of education.
  • Educate youth on the danger of adolescence pregnancy both in terms of exclusion from the modern economy and health implications.
  • Given the established relationship between access to services, poverty and economic inclusion, there is need for government to strive towards a regional balanced provision of access to safe drinking water, sanitation, electricity and housing. [pg. 58-59]

I don’t see any references to science in there, nor any to Neshani Andreas or Joseph Diescho. Britain’s the same story. But who knows, maybe an author/chemist who thought world poverty would end by the year 2000 has a better understanding of poverty than government agencies and century-old NGOs tasked with improving social conditions.

There’s a greater problem here, too. Let’s detour to something Donald Trump said:

Trump: “The Democrats don’t care about our military. They don’t.” He says that is also true of the border and crime

How would we prove that Democrats don’t care about the military, the US border, or crime? The easiest approach would be to look at their national platform and see it those things are listed there (they’re not, I checked). A much harder one would be to parse their actions instead. If we can find a single Democrat who does care about crime, then we’ve refuted the claim in the deductive sense.

But there’s still an inductive way to keep it alive: if “enough” Democrats don’t care about those things, then Trump can argue he meant the statements informally and thus it’s still true-ish. That’s a helluva lot of work, and since the burden is on the person making the claim it’s not my job to run around gathering data for Trump’s argument. If I’m sympathetic to Trump’s views or pride myself in being intellectually “fair,” however, there’s a good chance I’d do some of his homework anyway.

Lurking behind all of the logical stuff, however, is an emotional component. The US-Mexico border, the military, and crime all stir strong emotions in his audience; by positioning his opponents as being opposed to “positive” things, at the same time implying that he’s in favour of them, Trump’s angering his audience and motivating them to being less charitable towards his opponents.

That’s the language of hate: emotionally charged false statements about a minority, to be glib. It’s all the more reason to be careful when talking about groups.

The non-scientists have a rooted impression that the scientists are shallowly optimistic, unaware of man’s condition. On the other hand, the scientists believe that the literary intellectuals are totally lacking in foresight, peculiarly unconcerned with their brother men,
in a deep sense anti-intellectual, anxious to restrict both art and thought to the existential moment. And so on. Anyone with a mild talent for invective could produce plenty of this kind of subterranean back-chat. [pg. 3]

If you side with either scientists or elite authors, this is emotionally charged language. At the same time, I have no idea how you’d even begin to prove half of that. Snow’s defence consists of quoting Adam Rutherford and T.S. Elliot, all the rest comes from his experiences with “intimate friends among both scientists and writers” and “living among these groups and much more.” [pg. 1] Nonetheless, that small sample set is enough for Snow to assert “this is a problem of the entire West.” [pg. 2] Calling scientists or elite authors a minority is a stretch, but the net result is similar: increased polarisation between the two groups, and the promotion of harmful myths.

Yes, Snow would go on propose a “third culture” which would bridge the gap, but if the gap doesn’t exist in the first place this amounts to selling you a cure after convincing you you’re sick.

What’s worse is that if you’re operating in a fact-deficient environment, you’ve got tremendous flexibility to tweak things to your liking. Is J.K. Rowling a “literary intellectual?” She doesn’t fit into the highbrow culture Snow was talking about, but she is a well-known and influential author who isn’t afraid to let her opinions be known (for better or worse). Doesn’t that make her a decision maker, worthy of inclusion? And if we’ve opened the door for non-elite authors, why not add other people from the humanities? Or social scientists?

This also means that one of the harshest critics of C. P. Snow is C. P. Snow.

I have been argued with by non-scientists of strong down-to-earth interests. Their view is that it is an over-simplification, and that
if one is going to talk in these terms there ought to be at least three cultures. They argue that, though they are not scientists themselves, they would share a good deal of the scientific feeling. They would have as little use-perhaps, since they knew more about it, even less use-for the recent literary culture as the scientists themselves. …

I respect those arguments. The number 2 is a very dangerous number: that is why the dialectic is a dangerous process. Attempts to divide anything into two ought to be regarded with much suspicion. I have thought a long time about going in for further refinements: but in the end I have decided against. I was searching for something a little more than a dashing metaphor, a good deal less than a cultural map: and for those purposes the two cultures is about right, and subtilising any more would bring more disadvantages than it’s worth. [pg. 5]

He’s aware that some people regard “the two cultures” as an oversimplification, he recognises the problem with dividing people in two, and his response amounts to “well, I’m still right.” He’s working with such a deficiency of facts that he can undercut his own arguments and still keep making them as if no counter-argument existed.

I think it is only fair to say that most pure scientists have themselves been devastatingly ignorant of productive industry, and many still are. It is permissible to lump pure and applied scientists into the same scientific culture, but the gaps are wide. Pure scientists and engineers often totally misunderstand each other. Their behaviour tends to be very different: engineers have to live their lives in an organised community, and however odd they are underneath they manage to present a disciplined face to the world. Not so pure scientists. [pg. 16]

Snow makes a strong case for a third culture here, something he earlier said “would bring more disadvantages than it’s worth!” He’s seeing gaps and division everywhere, and defining things so narrowly that he can rattle off five counter-examples then immediately dismiss them (emphasis mine).

Almost everywhere, though, intellectual persons didn’t comprehend what was happening. Certainly the writers didn’t. Plenty of them shuddered away, as though the right course for a man of feeling was to contract out; some, like Ruskin and William Morris and Thoreau and Emerson and Lawrence, tried various kinds of fancies which were not in effect more than screams of horror. It
is hard to think of a writer of high class who really stretched his imaginative sympathy, who could see at once the hideous back-streets, the smoking chimneys, the internal price—and also the prospects of life that were opening out for the poor, the intimations, up to now unknown except to the lucky, which were just coming within reach of the remaining 99.0 per cent of his brother men.

Snow himself mentions Charles Dickens earlier in the lecture, a perfect fit for the label of “a writer of high class who really stretched his imaginative sympathy.” And yet here, he has difficulty remembering that author’s existence.

It’s oddly reminiscent of modern conservative writing: long-winded, self-important, and with only a fleeting connection to the facts. No wonder his ideas keep getting resurrected by them, they can be warped and distorted to suit your current needs.