Cognitive Ability and Vulnerability to Fake News: David Z. Hambrick and Madeline Marquardt

Some interesting research in Scientific American on fake news and vulnerability to it:

“Fake news” is Donald Trump’s favorite catchphrase. Since the election, it has appeared in some 180 tweets by the President, decrying everything from accusations of sexual assault against him to the Russian collusion investigation to reports that he watches up to eight hours of television a day. Trump may just use “fake news” as a rhetorical device to discredit stories he doesn’t like, but there is evidence that real fake news is a serious problem. As one alarming example, an analysis by the internet media company Buzzfeed revealed that during the final three months of the 2016 U.S. presidential campaign, the 20 most popular false election stories generated around 1.3 million more Facebook engagements—shares, reactions, and comments—than did the 20 most popular legitimate stories. The most popular fake story was “Pope Francis Shocks World, Endorses Donald Trump for President.”  

Fake news can distort people’s beliefs even after being debunked. For example, repeated over and over, a story such as the one about the Pope endorsing Trump can create a glow around a political candidate that persists long after the story is exposed as fake. A study recently published in the journal Intelligence suggests that some people may have an especially difficult time rejecting misinformation. Asked to rate a fictitious person on a range of character traits, people who scored low on a test of cognitive ability continued to be influenced by damaging information about the person even after they were explicitly told the information was false. The study is significant because it identifies what may be a major risk factor for vulnerability to fake news.

Ghent University researchers Jonas De keersmaecker and Arne Roets first had over 400 subjects take a personality test. They then randomly assigned each subject to one of two conditions. In the experimental condition, the subjects read a biographical description of a young woman named Nathalie. The bio explained that Nathalie, a nurse at a local hospital, “was arrested for stealing drugs from the hospital; she has been stealing drugs for 2 years and selling them on the street in order to buy designer clothes.” The subjects then rated Nathalie on traits such as trustworthiness and sincerity, after which they took a test of cognitive ability. Finally, the subjects saw a message on their computer screen explicitly stating that the information about Nathalie stealing drugs and getting arrested was not true, and then rated her again on the same traits. The control condition was identical, except that subjects were not given the paragraph with the false information and rated Nathalie only once.

The subjects in the experimental condition initially rated Nathalie much more negatively than did the subjects in the control condition. This was not surprising, considering that they had just learned she was a thief and a drug dealer. The interesting question was whether cognitive ability would predict attitude adjustment—that is, the degree to which the subjects in the experimental condition would rate Nathalie more favorably after being told that this information was false. It did: subjects high in cognitive ability adjusted their ratings more than did those lower in cognitive ability. The subjects with lower cognitive ability had more trouble shaking their negative first impression of Nathalie. This was true even after the researchers statistically controlled for the subjects’ level of open-mindedness (their willingness to change their mind when wrong) and right-wing authoritarianism (their intolerance toward others), as assessed by the personality test. Thus, even if a person was open-minded and tolerant, a low level of cognitive ability put them at risk for being unjustifiably harsh in their second evaluation of Nathalie.

One possible explanation for this finding is based on the theory that a person’s cognitive ability reflects how well they can regulate the contents of working memory—their “mental workspace” for processing information. First proposed by the cognitive psychologists Lynn Hasher and Rose Zacks, this theory holds that some people are more prone to “mental clutter” than other people. In other words, some people are less able to discard (or “inhibit”) information from their working memory that is no longer relevant to the task at hand—or, as in the case of Nathalie, information that has been discredited. Research on cognitive agingindicates that, in adulthood, this ability declines considerably with advancing age, suggesting that older adults may also be especially vulnerable to fake news. Another reason why cognitive ability may predict vulnerability to fake news is that it correlates highly with education. Through education, people may develop meta-cognitive skills—strategies for monitoring and regulating one’s own thinking—that can be used to combat the effects of misinformation.      

Meanwhile, other research is shedding light on the mechanisms underlying the effects of misinformation. Repeating a false claim increases its believability, giving it an air of what Stephen Colbert famously called “truthiness.” Known as the illusion of truth effect, this phenomenon was first demonstrated in the laboratory by Hasher and her colleagues. On each of three days, subjects listened to plausible-sounding statements and rated each on whether they thought it was true. Half of the statements were in fact true, such as Australia is approximately equal in area to the continental United States, whereas the other half were false, such as Zachary Taylor was the first president to die in office (it was William Henry Harrison). Some of the statements were repeated across days, whereas others were presented only once. The results showed that the average truth rating increased from day to day for the repeated statements, but remained constant for the non-repeated statements, indicating that subjects mistook familiarity for verity.

More recent research reveals that even knowledge of the truth doesn’t necessarily protect against the illusion of truth. In a 2015 study published in the Journal of Experimental Psychology: General, Lisa Fazio and her colleagues asked subjects to rate a set of statements on how interesting they found them. Following Hasher and colleagues’ procedure, some of the statements were true, whereas others were false. The subjects then rated a second set of statements for truthfulness on a six-point scale, from definitely false to definitely true. Some of the statements were repeated from the first set, whereas others were new. Finally, the subjects took a knowledge test that included questions based on the statements. The results revealed that repetition increased the subjects’ perception of the truthfulness of false statements, even for statements they knew to be false. For example, even if a subject correctly answered Pacific Ocean to the question What is the largest ocean on Earth? on the knowledge test, they still tended to give the false statement The Atlantic Ocean is the largest ocean on Earth a higher truth rating if it was repeated. When a claim was made to feel familiar through repetition, subjects neglected to consult their own knowledge base in rating the claim’s truthfulness.

These studies add to scientific understanding of the fake news problem, which is providing a foundation for an evidenced-based approach to addressing the problem. A recommendation that follows from research on the illusion of truth effect is to serve as your own fact checker. If you are convinced that some claim is true, ask yourself why. Is it because you have credible evidence that the claim is true, or is it just because you’ve encountered the claim over and over? Also ask yourself if you know of any evidence that refutes the claim. (You just might be surprised to find that you do.) This type of recommendation could be promoted through public service announcements, which have been shown to be effective for things like getting people to litter less and recycle more. For its part, research on individual differences in susceptibility to fake news, such as the study by De keersmaecker and Roets, can help to identify people who are particularly important to reach through this type of informational campaign.

At a more general level, this research underscores the threat that fake news poses to democratic society. The aim of using fake news as propaganda is to make people think and behave in ways they wouldn’t otherwise—for example, hold a view that is contradicted by overwhelming scientific consensus. When this nefarious aim is achieved, citizens no longer have the ability to act in their own self-interest. In the logic of democracy, this isn’t just bad for that citizen—it’s bad for society.”

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Readers’ Responses to Edward Luce’s “The Discrete Terror of the American Bourgeoisie”

The responses to Edward Luce’s article below was as interesting as the original:

  “Real politicians know that they must ask people for their vote: never take anything for granted. It is an equally good idea for columnists to ask readers for their feedback, as I did for my Financial Times column “The discreet terror of the American bourgeoisie”. I even used the word “please”.
My rare plea has elicited about 200 emails, a lot of Twitter activity and many online reader comments — almost all of them thought provoking. I asked whether opponents of Donald Trump should examine their own faults — and whether America’s meritocratic elites should rethink their idea of a “fair society”. 

Almost every respondent agreed that the pre-Trumpian model is broken. Some believe inherited wealth should be taxed far more heavily. Others want to delink education from vocation and return learning to its Socratic ideals. What strikes me most, however, was the resonance of the meritocracy debate with so many readers. Everyone appears to be thinking about it. Some columns bring out the argumentative reader. This one brought out their constructive side. Below is an edited sample of what FT readers think.

The fate of Democrats Whatever happened to the party of the people, asks James Emmet of Palm Beach, Florida? Wake up American Democrats! It’s actually fairly easy: a $15 minimum wage, progressive income tax rates as they existed in the 1940s and 1950s, a progressive wealth tax, levied heavily on the unearned increment of land values, real tariff protection for US labour, indexed to exchange rates, and a serious antitrust regime. A single payer healthcare system and a drastic lowering of the length of the term of copyright protection.

Tax reform As an MBA student at Chicago Booth coming from a Chicago public school education and a middle class family, I can appreciate both sides of the spectrum, writes Owen Reynolds. The uneducated no longer feel valued in society — but without technical skills what value are they even empowered to bring? Lowering taxes on corporations was smart (I’d even say go further to ~15 per cent). But without increasing taxes on capital gains, outsized income, and estates commensurately, we’re not only being fiscally irresponsible, we’re rigging the game. Allowing the accumulation of intra-familial capital is anti-meritocratic and disjoints the playing field, putting children from uneducated families with few resources at a huge social and financial disadvantage. The statistical likelihood of financial success for those children is extremely low — what happened to the American dream?

Tackling inherited wealth The core hypocrisy of the meritocratic mindset, in my opinion, relates to wealth, says Steve Roth. US owners receive trillions of dollars in unearned income per year simply for . . . owning things. Roughly 60 per cent of US wealth — hence the income from that wealth — is inherited. It’s simply impossible to in any way justify this unearned income as resulting from “merit”. And this before even considering the opportunities that wealth and income deliver for wealth holding families. Arguably, “opportunity” is primarily a function of . . . having money.

Downward mobility Those in the elite have to resist the temptation to take personal advantage of their position, writes Florian Rittmeyer. If they cannot resist, they should surround themselves with people who will slap their fingers if they cross lines. Being part of the elite means winning trust in advance from those who are not part of the elite. Maybe every member of the elite should have a picture in their office of the June Rebellion of 1832 in Paris. Belonging to the elite is no gift for self-fulfillment, but rather a temporary mandate, and members should ostracise those who abuse that mandate. If we live in a meritocracy, then ascending to the elite bears the risk of falling. Those willing to attempt the climb should keep that in mind.

Rethinking education I’d go with GK Chesterton rather than D Trump, says GDCC in online comments. “Without education, we are in a horrible and deadly danger of taking educated people seriously.” Education has been diverted from its original purpose (to make us more human), and is now mainly viewed as a way to increase one’s share of the pie (making us more animal). The liberal elites’ obsession with education may be just a coincidence . . .

Elite self-delusion The idea that the best people get to the top is always appealing to those at the top, says Sound of the Suburbs in reader comments. Even the UK’s privately educated elite have managed to convince themselves that they have got to the top purely on their own merit. The US’s social mobility is just as bad as that in the UK, and the idea that they live in a meritocracy is a shared delusion. The OECD supplies figures on social mobility. Look them up and come back down to earth.

Finally, economist Branko Milanovic, author of Global Inequality, tweeted: “The combination of moral superiority with wealth (often acquired by actions that belied that moral superiority) is the key defect of Bobos [bourgeois bohemians].

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Guide to Statistics in a Mis-Leading Age: Tim Harford

Great insights from Tim Harford in the UK Financial Times:

“The best financial advice for most people would fit on an index card.” That’s the gist of an offhand comment in 2013 by Harold Pollack, a professor at the University of Chicago. Pollack’s bluff was duly called, and he quickly rushed off to find an index card and scribble some bullet points — with respectable results.

When I heard about Pollack’s notion — he elaborated upon it in a 2016 book — I asked myself: would this work for statistics, too? There are some obvious parallels. In each case, common sense goes a surprisingly long way; in each case, dizzying numbers and impenetrable jargon loom; in each case, there are stubborn technical details that matter; and, in each case, there are people with a sharp incentive to lead us astray. The case for everyday practical numeracy has never been more urgent. Statistical claims fill our newspapers and social media feeds, unfiltered by expert judgment and often designed as a political weapon. We do not necessarily trust the experts — or more precisely, we may have our own distinctive view of who counts as an expert and who does not. 

Nor are we passive consumers of statistical propaganda; we are the medium through which the propaganda spreads. We are arbiters of what others will see: what we retweet, like or share online determines whether a claim goes viral or vanishes. If we fall for lies, we become unwittingly complicit in deceiving others. On the bright side, we have more tools than ever to help weigh up what we see before we share it — if we are able and willing to use them. In the hope that someone might use it, I set out to write my own postcard-sized citizens’ guide to statistics.

Here’s what I learnt. Professor Pollack’s index card includes advice such as “Save 20 per cent of your money” and “Pay your credit card in full every month”. The author Michael Pollan offers dietary advice in even pithier form: “Eat Food. Not Too Much. Mostly Plants.” Quite so, but I still want a cheeseburger. 

However good the advice Pollack and Pollan offer, it’s not always easy to take. The problem is not necessarily ignorance. Few people think that Coca-Cola is a healthy drink, or believe that credit cards let you borrow cheaply. Yet many of us fall into some form of temptation or other. That is partly because slick marketers are focused on selling us high-fructose corn syrup and easy credit. And it is partly because we are human beings with human frailties. Listen:  my statistical postcard begins with advice about emotion rather than logic. When you encounter a new statistical claim, observe your feelings. Yes, it sounds like a line from Star Wars, but we rarely believe anything because we’re compelled to do so by pure deduction or irrefutable evidence.

We have feelings about many of the claims we might read — anything from “inequality is rising” to “chocolate prevents dementia”. If we don’t notice and pay attention to those feelings, we’re off to a shaky start. What sort of feelings? Defensiveness. Triumphalism. Righteous anger. Evangelical fervour. Or, when it comes to chocolate and dementia, relief. It’s fine to have an emotional response to a chart or shocking statistic — but we should not ignore that emotion, or be led astray by it. 

There are certain claims that we rush to tell the world, others that we use to rally like-minded people, still others we refuse to believe. Our belief or disbelief in these claims is part of who we feel we are. “We all process information consistent with our tribe,” says Dan Kahan, professor of law and psychology at Yale University. In 2005, Charles Taber and Milton Lodge, political scientists at Stony Brook University, New York, conducted experiments in which subjects were invited to study arguments around hot political issues. Subjects showed a clear confirmation bias: they sought out testimony from like-minded organisations.

For example, subjects who opposed gun control would tend to start by reading the views of the National Rifle Association. Subjects also showed a disconfirmation bias: when the researchers presented them with certain arguments and invited comment, the subjects would quickly accept arguments with which they agreed, but devote considerable effort to disparage opposing arguments.  Expertise is no defence against this emotional reaction; in fact, Taber and Lodge found that better-informed experimental subjects showed stronger biases. The more they knew, the more cognitive weapons they could aim at their opponents.

“So convenient a thing it is to be a reasonable creature,” commented Benjamin Franklin, “since it enables one to find or make a reason for everything one has a mind to do.” This is why it’s important to face up to our feelings before we even begin to process a statistical claim. If we don’t at least acknowledge that we may be bringing some emotional baggage along with us, we have little chance of discerning what’s true. As the physicist Richard Feynman once commented, “You must not fool yourself — and you are the easiest person to fool.”

The second crucial piece of advice is to understand the claim. That seems obvious. But all too often we leap to disbelieve or believe (and repeat) a claim without pausing to ask whether we really understand what the claim is. To quote Douglas Adams’s philosophical supercomputer, Deep Thought, “Once you know what the question actually is, you’ll know what the answer means.”

For example, take the widely accepted claim that “inequality is rising”. It seems uncontroversial, and urgent. But what does it mean? Racial inequality? Gender inequality? Inequality of opportunity, of consumption, of education attainment, of wealth? Within countries or across the globe? Even given a narrower claim, “inequality of income before taxes is rising” (and you should be asking yourself, since when?), there are several different ways to measure this. One approach is to compare the income of people at the 90th percentile and the 10th percentile, but that tells us nothing about the super-rich, nor the ordinary people in the middle. An alternative is to examine the income share of the top 1 per cent — but this approach has the opposite weakness, telling us nothing about how the poorest fare relative to the majority. 

There is no single right answer — nor should we assume that all the measures tell a similar story. In fact, there are many true statements that one can make about inequality. It may be worth figuring out which one is being made before retweeting it. If we don’t acknowledge that we may be bringing emotional baggage when processing a statistical claim, we have little chance of discerning what’s true Perhaps it is not surprising that a concept such as inequality turns out to have hidden depths.

But the same holds true of more tangible subjects, such as “a nurse”. Are midwives nurses? Health visitors? Should two nurses working half-time count as one nurse? Claims over the staffing of the UK’s National Health Service have turned on such details. All this can seem like pedantry — or worse, a cynical attempt to muddy the waters and suggest that you can prove anything with statistics. But there is little point in trying to evaluate whether a claim is true if one is unclear what the claim even means.

Imagine a study showing that kids who play violent video games are more likely to be violent in reality. Rebecca Goldin, a mathematician and director of the statistical literacy project STATS, points out that we should ask questions about concepts such as “play”, “violent video games” and “violent in reality”. Is Space Invaders a violent game? It involves shooting things, after all. And are we measuring a response to a questionnaire after 20 minutes’ play in a laboratory, or murderous tendencies in people who play 30 hours a week? “Many studies won’t measure violence,” says Goldin. “They’ll measure something else such as aggressive behaviour.” Just like “inequality” or “nurse”, these seemingly common sense words hide a lot of wiggle room.

Two particular obstacles to our understanding are worth exploring in a little more detail. One is the question of causation. “Taller children have a higher reading age,” goes the headline. This may summarise the results of a careful study about nutrition and cognition. Or it may simply reflect the obvious point that eight-year-olds read better than four-year-olds — and are taller. Causation is philosophically and technically a knotty business but, for the casual consumer of statistics, the question is not so complicated: just ask whether a causal claim is being made, and whether it might be justified. 

Returning to this study about violence and video games, we should ask: is this a causal relationship, tested in experimental conditions? Or is this a broad correlation, perhaps because the kind of thing that leads kids to violence also leads kids to violent video games? Without clarity on this point, we don’t really have anything but an empty headline.  We should never forget, either, that all statistics are a summary of a more complicated truth. For example, what’s happening to wages? With tens of millions of wage packets being paid every month, we can only ever summarise — but which summary? The average wage can be skewed by a small number of fat cats. The median wage tells us about the centre of the distribution but ignores everything else. Or we might look at the median increase in wages, which isn’t the same thing as the increase in the median wage — not at all. In a situation where the lowest and highest wages are increasing while the middle sags, it’s quite possible for the median pay rise to be healthy while median pay falls. 

Sir Andrew Dilnot, former chair of the UK Statistics Authority, warns that an average can never convey the whole of a complex story. “It’s like trying to see what’s in a room by peering through the keyhole,” he tells me.  In short, “you need to ask yourself what’s being left out,” says Mona Chalabi, data editor for The Guardian US. That applies to the obvious tricks, such as a vertical axis that’s been truncated to make small changes look big. But it also applies to the less obvious stuff — for example, why does a graph comparing the wages of African-Americans with those of white people not also include data on Hispanic or Asian-Americans? There is no shame in leaving something out. No chart, table or tweet can contain everything.

But what is missing can matter. Channel the spirit of film noir: get the backstory. Of all the statistical claims in the world, this particular stat fatale appeared in your newspaper or social media feed, dressed to impress. Why? Where did it come from? Why are you seeing it?  Sometimes the answer is little short of a conspiracy: a PR company wanted to sell ice cream, so paid a penny-ante academic to put together the “equation for the perfect summer afternoon”, pushed out a press release on a quiet news day, and won attention in a media environment hungry for clicks. Or a political donor slung a couple of million dollars at an ideologically sympathetic think-tank in the hope of manufacturing some talking points. Just as often, the answer is innocent but unedifying: publication bias. A study confirming what we already knew — smoking causes cancer — is unlikely to make news. But a study with a surprising result — maybe smoking doesn’t cause cancer after all — is worth a headline. The new study may have been rigorously conducted but is probably wrong: one must weigh it up against decades of contrary evidence.

Publication bias is a big problem in academia. The surprising results get published, the follow-up studies finding no effect tend to appear in lesser journals if they appear at all. It is an even bigger problem in the media — and perhaps bigger yet in social media. Increasingly, we see a statistical claim because people like us thought it was worth a Like on Facebook. David Spiegelhalter, president of the Royal Statistical Society, proposes what he calls the “Groucho principle”. Groucho Marx famously resigned from a club — if they’d accept him as a member, he reasoned, it couldn’t be much of a club. Spiegelhalter feels the same about many statistical claims that reach the headlines or the social media feed. He explains, “If it’s surprising or counter-intuitive enough to have been drawn to my attention, it is probably wrong.” 

OK. You’ve noted your own emotions, checked the backstory and understood the claim being made. Now you need to put things in perspective. A few months ago, a horrified citizen asked me on Twitter whether it could be true that in the UK, seven million disposable coffee cups were thrown away every day.  I didn’t have an answer. (A quick internet search reveals countless repetitions of the claim, but no obvious source.) But I did have an alternative question: is that a big number? The population of the UK is 65 million. If one person in 10 used a disposable cup each day, that would do the job.  Many numbers mean little until we can compare them with a more familiar quantity. It is much more informative to know how many coffee cups a typical person discards than to know how many are thrown away by an entire country. And more useful still to know whether the cups are recycled (usually not, alas) or what proportion of the country’s waste stream is disposable coffee cups (not much, is my guess, but I may be wrong). 

So we should ask: how big is the number compared with other things I might intuitively understand? How big is it compared with last year, or five years ago, or 30? It’s worth a look at the historical trend, if the data are available. 

Finally, beware “statistical significance”. There are various technical objections to the term, some of which are important. But the simplest point to appreciate is that a number can be “statistically significant” while being of no practical importance. Particularly in the age of big data, it’s possible for an effect to clear this technical hurdle of statistical significance while being tiny. 

One study was able to demonstrate that unborn children exposed to a heatwave while in the womb went on to earn less as adults. The finding was statistically significant. But the impact was trivial: $30 in lost income per year. Just because a finding is statistically robust does not mean it matters; the word “significance” obscures that. In an age of computer-generated images of data clouds, some of the most charming data visualisations are hand-drawn doodles by the likes of Mona Chalabi and the cartoonist Randall Munroe. But there is more to these pictures than charm: Chalabi uses the wobble of her pen to remind us that most statistics have a margin of error. A computer plot can confer the illusion of precision on what may be a highly uncertain situation.

“It is better to be vaguely right than exactly wrong,” wrote Carveth Read in Logic (1898), and excessive precision can lead people astray. On the eve of the US presidential election in 2016, the political forecasting website FiveThirtyEight gave Donald Trump a 28.6 per cent chance of winning. In some ways that is impressive, because other forecasting models gave Trump barely any chance at all. But how could anyone justify the decimal point on such a forecast? No wonder many people missed the basic message, which was that Trump had a decent shot. “One in four” would have been a much more intuitive guide to the vagaries of forecasting. 

Exaggerated precision has another cost: it makes numbers needlessly cumbersome to remember and to handle. So, embrace imprecision. The budget of the NHS in the UK is about £10bn a month. The national income of the United States is about $20tn a year. One can be much more precise about these things, but carrying the approximate numbers around in my head lets me judge pretty quickly when — say — a £50m spending boost or a $20bn tax cut is noteworthy, or a rounding error. My favourite rule of thumb is that since there are 65 million people in the UK and people tend to live a bit longer than 65, the size of a typical cohort — everyone retiring or leaving school in a given year — will be nearly a million people. Yes, it’s a rough estimate — but vaguely right is often good enough.

Be curious. Curiosity is bad for cats, but good for stats. Curiosity is a cardinal virtue because it encourages us to work a little harder to understand what we are being told, and to enjoy the surprises along the way.  This is partly because almost any statistical statement raises questions: who claims this? Why? What does this number mean? What’s missing? We have to be willing — in the words of UK statistical regulator Ed Humpherson — to “go another click”. If a statistic is worth sharing, isn’t it worth understanding first? The digital age is full of informational snares — but it also makes it easier to look a little deeper before our minds snap shut on an answer. While curiosity gives us the motivation to ask another question or go another click, it gives us something else, too: a willingness to change our minds.

For many of the statistical claims that matter, we have already reached a conclusion. We already know what our tribe of right-thinking people believe about Brexit, gun control, vaccinations, climate change, inequality or nationalisation — and so it is natural to interpret any statistical claim as either a banner to wave, or a threat to avoid. If it’s surprising or counter-intuitive enough to have been drawn to my attention, it is probably wrong David Spiegelhalter, president of the Royal Statistical Society Curiosity can put us into a better frame of mind to engage with statistical surprises. If we treat them as mysteries to be resolved, we are more likely to spot statistical foul play, but we are also more open-minded when faced with rigorous new evidence.

In research with Asheley Landrum, Katie Carpenter, Laura Helft and Kathleen Hall Jamieson, Dan Kahan has discovered that people who are intrinsically curious about science — they exist across the political spectrum — tend to be less polarised in their response to questions about politically sensitive topics. We need to treat surprises as a mystery rather than a threat.  Isaac Asimov is thought to have said, “The most exciting phrase in science isn’t ‘Eureka!’, but ‘That’s funny…’” The quip points to an important truth: if we treat the open question as more interesting than the neat answer, we’re on the road to becoming wiser. 

In the end, my postcard has 50-ish words and six commandments. Simple enough, I hope, for someone who is willing to make an honest effort to evaluate — even briefly — the statistical claims that appear in front of them. That willingness, I fear, is what is most in question.  “Hey, Bill, Bill, am I gonna check every statistic?” said Donald Trump, then presidential candidate, when challenged by Bill O’Reilly about a grotesque lie that he had retweeted about African-Americans and homicides.

And Trump had a point — sort of. He should, of course, have got someone to check a statistic before lending his megaphone to a false and racist claim. We all know by now that he simply does not care. But Trump’s excuse will have struck a chord with many, even those who are aghast at his contempt for accuracy (and much else). He recognised that we are all human. We don’t check everything; we can’t. Even if we had all the technical expertise in the world, there is no way that we would have the time. My aim is more modest. I want to encourage us all to make the effort a little more often: to be open-minded rather than defensive; to ask simple questions about what things mean, where they come from and whether they would matter if they were true. And, above all, to show enough curiosity about the world to want to know the answers to some of these questions — not to win arguments, but because the world is a fascinating place. 

Posted in Academic Conflict, Conflict Processes, Conflict Statistics, Neuro-science of conflict, PERSONAL CONFLICT RESOLUTION: CREATIVE STRATEGIES, Philosophy of Conflict, Uncategorized, US Political Conflict, Ways to handle conflict | Tagged , , , | Leave a comment

The Discrete Terror of the American Bourgeoisie by Edward Luce

A Brilliant article in today’s Financial Times that nails the core problem. And the test of whether it is right: how much support would a policy to equalize school expenditure across the nation find from the so-called meritocrats? Zero is my guess, yet in a cognitively driven economy that would be the obvious first step to fixing inequality but also threatening the Bobos competitive standing in the educational arms race.

Elites thought they could have it both ways: capital gains and moral certainty

Donald Trump’s victory in the presidential election strengthened and shattered the elite’s worldview

Almost 20 years ago, the columnist David Brooks caught the spirit of the age. His book Bobos in Paradise hailed the marriage between bohemian 1960s radicals and the money-chasing bourgeoisie of the 1980s. They had merged into the Clintons. In place of America’s Episcopalian elites came the meritocratic establishment. Anyone with talent could join. “From each according to his abilities, to each according to his abilities,” wrote Mr Brooks.

This elite disliked glitzy consumption and lowbrow culture. Then, as now, Donald Trump topped the list of pariahs. His victory has strengthened and shattered their worldview. Beneath the conviction about Mr Trump’s wrongness lurks an angst that dare not speak its name. Mr Trump is a distraction from a reckoning that cannot be postponed forever.

What will America’s elites see when they look inwards? The first will be the shock of self-recognition. Bourgeois bohemians thought they could have it both ways: capital accumulation and moral certainty with no trade-offs. If you studied hard and earned merit, there was plenty of room at the top.

But there was a flaw in this thinking. America’s elites have stored more wealth than they can consume. This creates three problems for everyone else. First, elites invest their surpluses in replicating their advantages. Kids raised in poorer neighbourhoods with mediocre schools stand little chance. Their parents cannot match the social capital of their wealthier peers. The drawbridge is rising. The gap between the self image of meritocratic openness and reality is wide. Psychologists call this “self-discrepancy”. Economists call it barriers to entry.

Scarce goods, such as an Ivy League degree or living in a neighbourhood where you do not need a car, are manically contested © Getty

The second response to having such vast wealth is to create other kinds of scarcity. Since most people now have basic things — cars, smartphones and college education — material goods are no markers of success. Conspicuous consumption is played down. Scarce goods, such as an Ivy League degree or living in a neighbourhood where you do not need a car, are manically contested.

So are cultural advantages. America’s elites preach the gospel of a so-called stem education — science, technology, engineering and maths. But that is for other people. Social capital is about knowing what to say to whom and when, which is a sophisticated skill. Technical learning is for others. Children of the elites are learning how to raise money for philanthropic causes. Economists define this as a positional good. Sociologists call it virtue signalling. Mr Trump calls it political correctness.

The third challenge is the hardest to fix. Since there is too much capital chasing too few investment opportunities — what Lawrence Summers, former US Treasury secretary, calls “secular stagnation” — today’s America is cursed by an educational arms race. The jobs available do not match the qualifications millennials are acquiring. There is nothing relaxing about being a member of today’s aspiring classes. Kids must study harder and for longer than their parents to find jobs that do not often repay the effort.

The children of the wealthiest do not need student loans and live off their parents’ capital. The rest are struggling to justify the expense. It is as though they were led up to the promised land at sundown. The ratio of effort to outcome is rising. The more people study, the lower the returns to education. You always need more credentials, which most cannot afford. Instead of capital, losers accumulate frustration.

Which brings us back to Mr Trump. During the 2016 presidential election campaign, he said: “I love the poorly educated.” It seemed like a crass sentiment. But it appealed to many because it was the opposite of what other politicians would say. Mr Trump’s tweets betray his semi-literacy. He uses the word “their” when he means “there”. He talks of “unpresidented” when he means “unprecedented”. He uses quotation marks where they are not meant to “be”.

Mr Trump’s antics are a comfort blanket to the cognitive elites. He validates our moral superiority. Yet he eats away at it too. Somewhere in our bourgeois subconscious is the realisation that Mr Trump is no accident. He holds up a cracked mirror to our illusions. When we mock him, he draws strength. When he provokes, we stumble. Yet we cannot help ourselves. He is deeply outrageous.

Therein lies our deepest secret. We need Mr Trump just as he needs us. It is a ghastly symbiosis. Without Mr Trump, there would be no distraction. We might be forced to examine whether we live up to our own values. Do we love the highly educated? Do they deserve by virtue of credentials to be celebrated? Or should we revisit what we mean by a fair society? Answers sought by email or Twitter — but in correct English if you please.

edward.luce@ft.com

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What really caused the Nazis, and how can we avoid their return?

I received a very interesting and thoughtful answer to my question I posted here and on Quora: PH said in answer to my question: “What really caused the Nazis, and how can we avoid their return? Are they something else, or is there a little Nazi in all of us that social circumstances permit us to exhibit?”

Excellent question! There were many factors which caused the rise of the Nazis, and to a larger extent, the Fascism. Their rise included certain economic conditions, a need to regain a loss national pride and purpose, an exaggerated past—-especially a mythological past, the creation of a super powerful enemy (real or imagined) as well as a scapegoat, just to name a few.

Nazism was an extreme form of Fascism. Many people try to tie both to the Left, especially Nazism because of the use of the word “socialism” in the formal name, National Socialist German Workers Party. However, Hitler made it clear that the use of the term did not apply to international socialism in the same way as used by Marx or Lenin. His use of the word meant the creation of a wholly “German social community”. Hitler also used the term “worker” which implied unions or worker associations, which he had no use for. In fact, the day after celebrating the International Day of the Worker—May Day or May 1st—with President Paul von Hindenburg, Hitler outlawed and shut down all unions and associations! In its place, he created a state run union, the German Labor Front (DAF) led by Robert Ley. Hitler’s aim, so he said, was to create a name to attract as many groups as possible to his cause.

Fascism itself is a partnership between the state and big business. In Nazi Germany, it was clear that the state was the senior partner, and the party was the state. Whereas in Communism, there is no corporate partnership. There is no private ownership or boardrooms. The state owns and controls everything. Fascism also borrows from both the Left and Right; mostly from the Left on social issues, but the Right in terms of strong corporations, weak or no unions, a strong sense of nationalism or patriotism. This is what makes it so difficult to place on our outdated Left/Right political spectrum. We tend to think “either/or”, which is completely inaccurate when thinking about Fascism or even Nazism.

As to the last part of your question, sadly I have to say “yes”. I think it’s part of the human condition to want to find and blame others for what happened to us. We still think in terms of tribes, which are an extension of the family unit. Tribes can be familial, racial, cultural, religious, and even national, which is where our sense of nationalism comes form. Wars are usually portrayed in terms similar to tribe vs tribe. It’s why we demonize the other side; we see them as something less than human. There is a “us vs them” mentality that seems to be hardwired into us. It was great for survival once, but not so much nowadays.”

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How to be a Conservative-Liberal-Socialist” By Leszek Kolakowski

I guess I am a conservative-liberal-socialist like the Polish philosopher and dissident Leszek Kolakowski 

“Motto: “Please step forward to the rear!” This is an approximate translation of a request I once heard on a tram-car in Warsaw. I propose it as a slogan for the mighty International that will never exist.

A Conservative Believes:

  1. That in human life there never have been and never will be improvements that are not paid for with deteriorations and evils; thus, in considering each project of reform and amelioration, its price has to be assessed. Put another way, innumerable evils are compatible (i.e. we can suffer them comprehensively and simultaneously); but many goods limit or cancel each other, and therefore we will never enjoy them fully at the same time. A society in which there is no equality and no liberty of any kind is perfectly possible, yet a social order combining total equality and freedom is not. The same applies to the compatibility of planning and the principle of autonomy, to security and technical progress. Put yet another way, there is no happy ending in human history.
  2. That we do not know the extent to which various traditional forms of social life–families, rituals, nations, religious communities–are indispensable if life in a society is to be tolerable or even possible. There are no grounds for believing that when we destroy these forms, or brand them as irrational, we increase the chance of happiness, peace, security, or freedom. We have no certain knowledge of what might occur if, for example, the monogamous family was abrogated, or if the time-honored custom of burying the dead were to give way to the rational recycling of corpses for industrial purposes. But we would do well to expect the worst.
  3. That the idee fixe of the Enlightenment–that envy, vanity, greed, and aggression are all caused by the deficiencies of social institutions and that they will be swept away once these institutions are reformed– is not only utterly incredible and contrary to all experience, but is highly dangerous. How on earth did all these institutions arise if they were so contrary to the true nature of man? To hope that we can institutionalize brotherhood, love, and altruism is already to have a reliable blueprint for despotism.

 A Liberal Believes:

  1. That the ancient idea that the purpose of the State is security still remains valid. It remains valid even if the notion of “security” is expanded to include not only the protection of persons and property by means of the law, but also various provisions of insurance: that people should not starve if they are jobless; that the poor should not be condemned to die through lack of medical help; that children should have free access to education–all these are also part of security. Yet security should never be confused with liberty. The State does not guarantee freedom by action and by regulating various areas of life, but by doing nothing. In fact security can be expanded only at the expense of liberty. In any event, to make people happy is not the function of the State.
  2. That human communities are threatened not only by stagnation but also by degradation when they are so organized that there is no longer room for individual initiative and inventiveness. The collective suicide of mankind is conceivable, but a permanent human ant-heap is not, for the simple reason that we are not ants.
  3. That it is highly improbable that a society in which all forms of competitiveness have been done away with would continue to have the necessary stimuli for creativity and progress. More equality is not an end in itself, but only a means. In other words, there is no point to the struggle for more equality if it results only in the leveling down off those who are better off, and not in the raising up of the underprivileged. Perfect equality is a self-defeating ideal.

 A Socialist Believes:

  1. That societies in which the pursuit of profit is the sole regulator of the productive system are threatened with as grievous–perhaps more grievous–catastrophes as are societies in which the profit motive has been entirely eliminated from the production-regulating forces. There are good reasons why freedom of economic activity should be limited for the sake of security, and why money should not automatically produce more money. But the limitation of freedom should be called precisely that, and should not be called a higher form of freedom.
  2. That it is absurd and hypocritical to conclude that, simply because a perfect, conflict-less society is impossible, every existing form of inequality is inevitable and all ways of profit-making justified. The kind of conservative anthropological pessimism which led to the astonishing belief that a progressive income tax was an inhuman abomination is just as suspect as the kind of historical optimism on which the Gulag Archipelago was based.
  3. That the tendency to subject the economy to important social controls should be encouraged, even though the price to be paid is an increase in bureaucracy. Such controls, however, must be exercised within representative democracy. Thus it is essential to plan institutions that counteract the menace to freedom which is produced by the growth of these very controls.

So far as I can see, this set of regulative ideas is not self-contradictory. And therefore it is possible to be a conservative-liberal-socialist. This is equivalent to saying that those three particular designations are no longer mutually exclusive options.

As for the great and powerful International which I mentioned at the outset–it will never exist, because it cannot promise people that they will be happy.

From Leszek Kolakowski, Modernity on Endless Trial (University of Chicago, 1990).

 

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Questions for the New Year 2018

One of the things I did when I retired in 2003 was to list some questions I thought interesting that I might explore in my researches or in how I lived post retirement. I changed them a little bit in 2006 and just re-discovered them. Here is a slightly shorter version to take out conflict technical questions:
1. Why do people find it so hard to follow any disciplined process, even when it is shown to work?
2. Why do people find it so hard to apply learning from books and the classroom in the practical/work world or in their own lives?
3. Why does short-term, immediate self interest so dominate decision making? Is it evolutionary wiring we are only just growing out of?
4. Why do people self-sabotage so often?
5. Why do people spend so little of their time doing what they enjoy? Why do they try so few ways of enjoyment? Why do they invent so many ways to make themselves and others miserable?
6. In organizations, governments, political parties etc. why do so many stupid, immoral, anti-social people get promoted over more intelligent moral, pro-social ones?
7. Why do so many relatively poor people vote for conservative parties that do not serve their interests?
8. Why are people so obsessed with their position relative to others versus absolute level of their interests/life
9. Why do people want to perpetuate their genes by looking after their children, leaving them money, but fail to want to perpetuate them by looking after the planet their children need to live on?
10. Why are religions so obsessed with sex (the stopping of it or the associating of it with guilt) when their holy texts don’t spend that much time on it?
11. What would it take to convince the Republican Party/Religious Right to take global warming seriously? Aka why don’t conservatives want to conserve civilization?
12. What attracts so many people to war? How are they psychologically different from those that oppose it?
13. What really caused the Nazis and how can we avoid their return? Are they something else or is there a little Nazi in all of us that social circumstances permit us to exhibit?
14. How do we really learn so that we change ourselves?
15. Can we successfully change our selves and others to save the world?

Nearly 15 years on I haven’t really found any good answers. 🙂 But hey I still like the questions…..

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