We once had a compulsory company mass choir where we had to learn “Don’t Stop Me Now” in three-part harmony. Fun! And we had a talk from a mountaineer who had climbed Everest, which I assume was supposed to be an inspiring exemplar of determination in a hostile environment that is a bit like the current media environment. But I remember left me worrying about the frozen barrels of human waste just off to the side of the slides.

And then we had this email, which offered a guaranteed way of lifting our beleaguered spirits to new heights of productivity. All we had to do, it explained, was assume powerful poses, and we would become powerful! Out with slouching, in with wide-legged stances and chins held aloft. Astonishing, yes, but there was science to support it — as you would find, if you watched a 2012 TED Talk by psychologist Amy Cuddy, which has now been viewed over 60 million times.

Power posing, as laid out in a 2010 paper co-authored by Cuddy, is one of the great success stories of popular psychology. It didn’t hurt that it “fit neatly into the established self-help niche in American life”, as Jesse Singal explains in his new book The Quick Fix: Why Fad Psychology Can’t Fix Our Social Ills. And nor was it any disadvantage at all that Cuddy was a brilliant speaker with a powerful story of overcoming personal adversity (she recovered from a traumatic brain injury to achieve a PhD from Princeton, and then a job at Harvard). The power posing theory had almost everything to recommend it — apart from the solid basis in experimental science that it was claimed to have.

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The peak of power posing’s influence, in the UK at least, probably came at the 2015 Conservative conference, when George Osborne appeared on stage with his legs splayed as though he expected a train to run through the middle of them. By the time it was being offered to me as a corporate pick-me-up, its reputation was already on the skids. The two keys claims Cuddy made were that, compared to a control group, power posers saw increased levels of testosterone, and an increased propensity for risk-taking. A 2015 attempt at replication (that is, rerunning the experiment to see if the result stood) had failed; and then in 2016, one of Cuddy’s co-authors on the original paper disowned the findings entirely.

The apparently empirical effect the researchers had observed was actually generated by something known as “p-value hacking”, in which results are included or excluded until something that looks like statistical significance is achieved, and the work becomes suddenly of interest to academic journals (who, like everyone else, are much more excited by a sexily counterintuitive finding than no finding at all).

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And so the story of power posing, and its journey from one paper that ought to have been challenged at peer review, to near-universal acceptance and an appearance in my work inbox, is a parable for the way bad ideas promulgate themselves — and a perfect example of the kind of bad idea that prospers.

Something like power posing appeals because it makes you feel like the success is a matter of volition. Reading about it at my sad strip-lit desk, in an email from the same address that had announced multiple rounds of redundancy, looking round an office haunted by the empty chairs of the ones who’d already gone, I did not feel any filip to my sense of self-command, however. I felt that I was being cheated, played, fobbed off.

Like all the examples looked at in Singal’s book, power posing sold an individual solution to an institutional or structural problem. After all, if you feel powerless, the most likely reason is that you are powerless. Even if it made you take more risks, which it apparently doesn’t, and even if that were obviously a good thing, which it isn’t necessarily (as Singal wryly asks, “Does American society, and the American economy … suffer from a dearth of pointless risk taking?”), it’s not clear how that would ultimately protect you from the vicissitudes of the market, to which all but the absurdly rich (like Osborne) are beholden.

Similarly, the doctrine of self-esteem pitched the idea that people would do better if they just felt better about themselves. It turned out this was wrong in many ways, but one of the most grimly amusing pieces of evidence against it is this: some research, explains Singal, found that “criminals actually had higher self-esteem than law-abiders”.

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Later, the concept of “grit” — meaning “determination” — was picked up by the American education system as the secret of student success. Cultivate “grit” in the individual, and you could save them from failure. The shadow side of that faith, of course, is that failure must come down to a lack of grit: rather than addressing the gross inequalities that stymie children’s chances, interventions focused on changing the child, despite the fact that no one could convincingly explain what “grit” was measuring or how it was critical to achievement.

What’s fascinating about many of the “fads” Singal highlights is that they drew support from Left and Right: the Left could see an effort to mitigate unfair circumstances, and the Right could see the empowerment of the individual. Anyone in a position to control budgets could see that such interventions were blessedly inexpensive compared to other ways of approaching these problems. And so long as they seemed plausible and exciting, the question of whether they actually worked could be left to one side, like the unpleasant sewerage barrels no one wants to think about when celebrating their triumphant ascent of Everest.

Several of Singal’s examples have already started their slide towards irrelevance, but one of them is still going strong. The Implicit Association Test (IAT) caught the wave of Black Lives Matter-inspired corporate concern to address racism, and has been widely adopted by businesses. Its promise is that, by assessing your reaction time to certain words or phrases, it can judge the depth of your “implicit bias” against certain races. Once confronted with a numerical measure of your own racism, you can — the theory goes — begin to undo it.

The IAT’s claim is excitingly bold: “a ten-minute computer task with no connection to the real world could predict subtle forms of real-world discrimination,” Singal writes. But a connection between IAT results and in-practice racist attitudes hasn’t been established. The depressing conclusion is that an awful lot of people, who say that they awfully want to fix racism, are throwing resources at something that will not and cannot do the job.

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There are two ways to read that, one of them generous and one of them cynical. Perhaps people simply don’t know that the IAT is a flawed implement, and if you explain that to them, they’ll move onto something else. But that hasn’t happened. In fact, expressing scepticism about the IAT is, as Singal found, treated as tantamount to trying to debunk the existence of racism itself (which, the logic goes, only a racist would do). The more you want to be perceived as anti-racist, the more fervently you are required to advocate for something that is no threat to racism at all.

So the cynical view is this. Things like the IAT and self-esteem and power posing and grit appeal precisely because they don’t work. At the institutional level, no one sincerely wants things to change, and when everything stays the same, and psychology fads make it possible to pin that on personal deficiency: you weren’t gritty, and you failed to address your implicit bias, and you slouched too much. Its nobody else’s fault that the same old messes persist. The real beauty of quick fixes — and the reason they’ll keep coming back, despite Singal’s entertaining and elegant broadside against them — it’s that they’re not really any kind of fix at all.

Someone tells you that there’s a chemical found in school wallpapers that makes the disease more likely to spread. But, good news, they have a test which they can run, which detects the levels of the chemical, and then — if levels are high — they can strip the wallpaper for you. Great! You get them to run the test, they find the chemical, they strip the wallpaper; they run the test again, no chemical.

But then you learn that lots of other local schools have had the same treatment, and in the months afterward, some of them get the disease and some of them don’t; the results of the test, and whether or not the wallpaper was subsequently stripped, doesn’t seem to have any effect on whether or not the disease spreads in the school.

So you say to the people who did the test, hey, what’s going on here? And they say “The disease is real! Are you suggesting the disease isn’t real?” No, you say, I know the disease is real, I’m just saying that the test you’ve run and the treatment you’ve administered doesn’t seem to have any relation to whether the disease comes or not. “No, the disease is definitely real,” they tell you. Presumably you would be unimpressed.

On which note, there was an extraordinary programme on Channel 4 recently, The School That Tried To End Racism. It took a bunch of 11-year-old kids at a school and made them take an apparently scientific test to detect unconscious racial bias.

The test finds that most of the children — 18 out of 24, in a class that’s 50% non-white! — “felt an unconscious bias towards white people”. The test, they say, “is now widely accepted as an accurate measurement of unconscious racial bias”, something that understandably shocks the children. 

They then make the kids embark on a three-week programme to reduce their unconscious bias. The kids are separated into “affinity groups”, i.e. white children in one room, non-white children in another, to talk about their experiences in their racial groups; a mixed-race child strongly resents being forced to choose which room she goes in. One child ends up in tears.

Then, three weeks later, they take the test again and most of the class is apparently “near to the neutral position: very little or no unconscious bias”.

It’s powerful television, and incredibly uncomfortable to watch. But there are two huge problems with it, and they’re the same problems in our imaginary school, above: disease is real, but the test and the treatment are not.

Problem number one, the “implicit associations test”, or IAT, on which it is based, is essentially useless as a measure of prejudice; it’s certainly not “widely accepted as an accurate measurement of unconscious racial bias”.

And problem number two, the “unconscious bias training” used to reduce the impact of this unconscious prejudice has not been shown to work, and in fact it’s just possible that it may even have a negative effect. 

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This has been known for some years now, but the two tools — the IAT, and the training — have now become embedded in the public consciousness. So much so, in fact, that Sir Keir Starmer — the leader of the Labour Party — announced on LBC that he was going to undergo unconscious bias training, after he was criticised for his use of language around the Black Lives Matter protests, and in fact to introduce it for all Labour Party staff. “I think everybody should have unconscious bias training,” he said. “I think it is important.”

To drum the analogy home one more time: racism, like our imaginary disease, is real; and it would be astonishing if it isn’t at least partly unconscious, or subconscious, or related to some sort of attitudes not fully available to our conscious minds. “Unconscious bias” is a real thing. 

But these two tools for measuring and reducing it do not do the job they are supposed to do. It is pernicious that Channel 4 and Sir Keir are both supporting and publicising them in this context; our social battle against racism will not be helped by using unevidenced tools.

The IAT is a simple and rather clever idea; if you watch the Channel 4 programme you’ll see what I mean, or read this piece I wrote earlier this year. It measures whether people find it easier to associate positive words (“happy”, “wise”, “beautiful”) with white faces and negative words (“pain”, “angry”, “stupid”) with black faces, or vice versa, by measuring their reaction times. Most people (including black people) end up having a “preference for white faces over black faces”.

But there are two problems. One, if you test someone with the IAT twice, you’re likely to get two very different scores; it has a low “test-retest validity”. If you measure my height on Monday and then again on Tuesday, you’ll get almost the same result both times; but if you do the same with the IAT, it’s very possible that it’ll say I’m strongly prejudiced one day and not at all the next. (Which makes the children doing better on their second test less surprising or meaningful, although the odds of a total fluke are much lower when it’s 24 of them being tested.)

Second, whether you score highly or not on the IAT does not correlate with whether or not you behave in prejudiced ways in real life. It is essentially useless as a predictor of individuals’ actual, real-world behaviour. 

The IAT’s own creators say that it should not be used to diagnose levels of prejudice in individuals; they do think it can be useful at population levels, although even then it throws up weird effects, such as all categories of women being more prejudiced against women than all categories of men in the 2016 US presidential election. The idea that the average male Trump voter is less prejudiced against women than the average female Clinton voter is … well, it’s not inherently ridiculous, but it would require a huge redrawing of society’s understanding of what prejudice is and who has it.

I know “internalised misogyny” is a crucial feminist idea, but (to me, at least) it seems deeply weird to think that it would be internalised to that degree. Either way, it doesn’t make it all right to use it on a class of children to tell them that they’re prejudiced against black people.

The idea of training people so that their unconscious bias goes away is on equally shaky ground, if not shakier. A 2017 Equality and Human Rights Commission report found, firstly, that most workplace training uses tests like the IAT to diagnose individual levels of bias, which as we’ve seen is not a good idea. It also found that while bias training can improve IAT scores, there was “limited” evidence for behavioural change, and “potential for back-firing effects”, ie they may make the problem worse.

A 2019 meta-analysis found no evidence of backfire, but also “trivial” impact on behavioural change and only a small effect on IAT scores. This systematic review did find some evidence of effect, but only looked at the impact on implicit bias scores, not real-world behaviour. This one says basically that all the research on the topic is complete crap and not to be trusted.

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I don’t know which particular flavour of unconscious bias training Sir Keir and the Labour Party will undergo; I gather it will involve “The meaning of unconscious bias; its impact on people we work with; common types; recognising and challenging personal biases; practical tips to uncover and challenge bias”, but I don’t know which particular practitioners or methods they’ll use. Some methods may be more well-evidenced than others. 

Similarly, I can’t find any research on the “affinity groups” model practised in the Channel 4 programme; it was led by a woman called Mariama Richards, who has been doing something similar in US schools since at least 2015. The article about it talks about the work of Claude Steele on “stereotype threat” — the idea that minorities “fail to achieve their potential because they internalise stereotypes” about their group. 

But the intervening years have not been kind to stereotype threat research; many of its most celebrated findings have failed to replicate. That may not be crucial to Richards’ work but I can’t find any research directly related to it, so it’s all I’ve got to rely on. 

For the record: I find the idea of telling children that they are prejudiced against black people, on the basis of an at best highly controversial and at worse flatly unevidenced test, deeply uncomfortable. Dividing them up into racial groups, to at least one child’s obvious distress, likewise. If the benefit was well-evidenced I could understand it, but in the absence of that – and, in fact, given the small but real possibility that it could exacerbate prejudice – it seems needlessly cruel. Putting the whole thing on telly seems doubly so.

Again: no one sensible is suggesting that humans are not unconsciously biased (least of all me). Of course we’re biased; it’s probably easiest to think of our brains as a collection of biases, loosely strung together. And of course we’re biased towards and against racial and ethnic groups, different sexes, different classes, in societally relevant ways. That seems so obvious, just from observing society or even honest introspection, that it hardly needs saying.

But the IAT, when used like this, is not simply that obvious truth in vaguely scientific language. It is a measure of your score on this specific test, which does not seem to be related (at least at the individual level) to any actual detectable real-world prejudice. And unconscious bias training, much of which seems to be aimed at improving people’s score on the IAT, seems to lack any good evidence for its effectiveness (and, similarly, all that much good evidence against it being harmful).

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As I’ve written before, lots of major companies use the IAT and implicit bias training. I think that’s a waste of money and employee time, but it’s the companies’ money; as long as it’s not actively making things worse then whatever. It’s sort of the same for the Labour Party, although I’m not sure how its members would feel if they knew their money was going to pay for unevidenced training like this.

But the equation changes when schools are doing it to children, especially with cameras inside their race-segregated groups, and their real names and faces on national television. This should require a higher standard of evidence than “it probably isn’t harmful”. 

A retired clinical psychologist wrote to me about it, suggesting that it probably breaks British Psychological Society guidelines on research on children; certainly the ethical questions over whether it is okay to test these controversial and poorly evidenced tools on children, with no anonymising, are profound.

Channel 4 got back to me with a statement, saying: “The course followed by the school was developed by academics and educators and is based on similar schemes run in US schools. Whilst some academics argue that this test is not perfect, many agree it is a good indicator of implicit bias and it continues to be widely used both in academia and in the real world.” I think it’s worth noting that the “some academics” who “argue that it is not perfect” include the test’s own creators, who say that it should not be used to assess individual prejudice in the way this programme uses it.

Go back to our original analogy. The disease is real; racism is real, unconscious bias is real. We really do want to reduce prejudice against ethnic groups, because it really does affect people’s life chances. I’m happy to take all that as read, and while I’m really heartened by the fact that on most measures, Britain is slowly getting less prejudiced, we can probably all agree that it’s not happening fast enough.

But the IAT does not tell us anything about whether a class, or a person, is more likely to be prejudiced than anyone else. It does not do what unconscious-bias-training courses are selling it as doing. And the courses themselves are not supported by good evidence, even to the point that we can be sure they’re not doing more harm than good. If you want to protect your class from this disease, then you need a test that works and a treatment that’s effective; otherwise you’re just stripping the wallpaper.

It wasn’t just hiring practices: they also put systems in place to ensure that, once established, staff were made to feel that they were welcome, such as workshops led by minority journalists to help straight/white/male journalists avoid common pitfalls, or support groups for BME journalists.

Hiring more journalists from various minorities and listening to them seems pretty obviously a good thing to do. Of course it’s not going to immediately solve every one of the various problems that people of colour, or women, or LGBT people face in the workplace, but it was a start, and not every company I’ve worked for has managed even that.

At one point, though, something pulled me up short. During one meeting about diversity there was a lengthy segment about “implicit bias” — specifically, the implicit bias measured by something called the Implicit Associations Test (IAT) — and how we could reduce it in ourselves. That startled me, because — nerd that I am — I knew about the IAT’s troubled history.

That history is in my mind at the moment because a large new study is out about the IAT, and more specifically interventions intended to reduce our bias. And it tells us, I think, that sometimes there is a tension between activism and reporting.

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It is hardly controversial to say that unconscious biases affect our judgment. It would be amazing if that weren’t true about biases against minorities; that there aren’t subconscious ways in which we treat people from other groups differently from those in our own group. “People might be racist in subtle ways of which they are unaware” should not be a surprising statement; after all, there is evidence showing that people are less likely to hire job applicants or accept tenants with stereotypical black-sounding names than they are ones with stereotypical white-sounding names.

The IAT, when it was introduced more than two decades ago, promised to offer a way of measuring that unconscious bias. It involves a simple test. In the classic “measuring racial bias” version, you sit down at a computer and, on screen, a series of images and words pop up. If you see a positive word like “happy”, you press “i”; if you see a negative one like “pain”, you press “e”. And if you see a picture of a black person, you press “i”; if you see a white person, you press “e”. Then the categories are swapped around (same button for white person as positive word, etc). And the computer measures your reaction times.

Your implicit bias score is the algorithmic product of those reaction times — how long it takes to associate white faces with good words and black faces with good words, and vice versa. You can have a slight, moderate, or strong “preference for white faces over black faces”, or less commonly for black faces over white. Most people, including a sizeable minority of black people, record a bias towards white faces, because they take a tenth of a second or so longer to press the button when black faces and good words are combined.

The IAT became a phenomenon. Tens of millions of people have taken the test at Harvard’s website. Hillary Clinton namechecked “implicit bias” in one of her debates with Donald Trump in 2016. Malcolm Gladwell mentions it in his bestseller Blink. It was described as a “revolution” in social psychology. Its proponents said that it could detect hidden racism even among people who honestly believed themselves to be egalitarians — that it had been “shown, reliably and repeatedly, to predict discriminatory behavior that was observed in the research”. And, of course, many organisations sprang up to offer diversity training to firms (such as my former employers) who wanted to reduce their employees’ implicit bias.

There was, however, a problem. Or more than one, but they became one big problem: it doesn’t work. For the full story you really (really) ought to go and read Jesse Singal’s long and splendid 2017 piece at New York Magazine, which documents the ways in which so much of it unravelled. But there were really two main issues, I think.

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First, if you test someone with the IAT, they get a score. But if they take it again later, their score is likely to be very different. It has a low “test-retest reliability”. The lower a measure’s test-retest reliability, the more random and uninformative it is. The IAT’s score is about halfway between “perfect” and “completely useless”, so it’s not utterly without value, but it’s well below the standards of most measures: where the IAT scores about 0.55 on a scale of 0 to 1, a depression-diagnosing questionnaire, for instance, scores about 0.86, and that’s about the minimum requirement for most psychological evaluation tests.

As Singal says in his piece, “If a depression test … has the tendency to tell people they’re severely depressed and at risk of suicidal ideation on Monday, but essentially free of depression on Tuesday, that’s not a useful test.”

But perhaps more damningly, the IAT does not do what it says it does. It is meant to detect secret racism among people who claim — or believe themselves — to be non-racist. But it turns out that people who score higher on the IAT are not, in fact, significantly more likely to discriminate against black people than people who score lower.

Even the proponents of the test now acknowledge that it should not be used to diagnose racism — or a tendency “to engage in discrimination” — in individuals, although they say that there is still a use for it for examining implicit bias when aggregated across large groups. In short, people we would call “racist”, under most reasonable definitions of the word, do not score higher on the IAT than people who we would not.

The trouble is, that news does not seem to have managed to make it to employers. Facebook offers in-house implicit bias training. So do Google, and Starbucks, and many other places, including my own former workplace.

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That’s where this latest study I mentioned comes in. It was a major meta-analysis, with 87,000 subjects across 492 individual studies. It was carried out by one of the original proponents of the IAT, Brian Nosek, an excellent and careful scientist. It was pre-registered, so it couldn’t p-hack its way to the results it wanted. These are all good reasons to trust it.

And it found that corporate training to reduce your implicit bias has only a weak effect on your actual implicit bias score, and no effect on your actual behaviour. If this is right, then millions of pounds and countless man-hours have been wasted on diversity training programmes that have zero impact. (Some people even suggest — with some empirical support — that they have the opposite effect of worsening implicit bias, because you’re reminding people of negative stereotypes and thus reinforcing them. But the new study didn’t find that.)

Why — in the face of all these problems — is the notion of implicit bias so sticky, then? Why is it something we all know about, and which companies still spend vast resources trying to eradicate?

Partly, I think, it’s just an intuitive idea. It is true that we are biased, implicitly. The specific “implicit bias” measure might be unhelpful, but still, we do have unconscious race- and gender-based biases. So we hear “implicit bias” and think “obviously true thing” without bothering to check the details.

But perhaps more importantly, I think it is because it is hard to argue against without looking like a horrible racist. Look at this piece: see how I spent the first several paragraphs establishing that I am totally in favour of measures to improve workplace diversity. That’s the rhetorical price that needs to be paid in order to then say “but this specific thing here, which purports to help with that, doesn’t work”. That’s because we don’t tend to think in terms of single, specific arguments; we work with a great messy agglomeration of interconnected thought-stuff which signals tribal loyalties.

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If I don’t pay that price, if I leap right in and say “diversity training is a waste of time”, you’ll immediately lump me in with a certain kind of Right-wing anti-wokeness writer and (reasonably) ignore the actual argument I’m making, because I’m obviously not trying to persuade: I’m just trying to shock you and get a cheer from My Side.

This makes writing about the science of these topics immensely tricky. If I write something about, say, innate sex differences in interests, and whether they affect women’s participation in STEM careers, the conclusions I come to might be right or wrong, but they should be based purely on my assessment of the science. But whatever those conclusions are will inevitably lead people to make assumptions about my political views, because the tribal lines on that issue are so well-defined. Admitting that the whole concept of implicit bias is probably irretrievably flawed just sounds like you’re saying you don’t think racism is a problem in the workplace. It should be a simple question of trying to say true things, but instead it’s seen as flying a flag of allegiance.

I suspect a lot of people reading this will think that this is getting worse, that we all have to be super-woke now in everything we write and that science journalism is becoming a branch of social justice activism. I don’t think that’s fair. Sometimes, when I read pieces like this one blaming “whiteness” for the growth in opioid deaths and firearm suicides in the US, I do wonder; but I suspect that every generation had its shibboleths and hard-to-declare truths, and scientists and everyone else had to work within the political confines of the time.

Scott Alexander calls this “Kolmogorov complicity”, after the great Soviet scientist who carefully never said anything that would offend the Politburo and concentrated on the scientific truths he could discover without getting thrown into a gulag. (Getting cancelled might be bad, but the Soviets had it worse.)

Still. At least, now, we can probably say without great fear of being burnt at the stake like Giordano Bruno that the IAT is no use as a predictor of racism, and that corporate measures to reduce implicit bias are largely useless. Except – hang on! I just took the test myself, and was found to have “little to no automatic preference between White people and Black people”! So I’m much less racist than you. Scratch everything I just said: all hail the IAT. Just don’t make me take it again.