133. What does “follow the science” mean?


LeonardoWe’re told these days by our leaders that they’re “following the science” in their handling of the coronavirus pandemic. And, of course, we know what they mean. In an age where it became fashionable not to listen to the experts, they’ve never needed experts more. Briefings abound with flattenings of curves and keeping the R value below 1.

But, if I’m uncharitable enough to unpack the catchphrase, an oddity leaps out.

Politicians and scientists have a different understanding of truth. Politicians want clear answers—should we do this, yes or no? Invoking science should be the gold standard of clarity.

Scientists, on the other hand, deal in uncertainties. Hypotheses are contingent on testing, interpretations are contested, epoch-making claims turn out to be mere statistical blips as more data emerges.

There is so little data as yet on this new virus that “the science” is less a provider of clear yeses and nos than it is a habit of thought.  That habit of thought is the opposite of what the politicians mean—it is a cultivated scepticism, an openness of mind, a willingness to change your mind when the evidence changes.

In the future we’ll know a lot about this virus. But now we don’t know whether people who have recovered generate immunity or whether they can catch it again. We know that it appears to differentially affect men, the elderly and those with underlying health conditions, but we don’t know why some young patients with no known health conditions have a severe response. We think of it is a respiratory illness, but it doesn’t always respond to ventilation in severe cases and it appears to cause kidney problems in some patients. Other patients seem to be overwhelmed by their own immune responses, a so-called cytokine storm. It may not really be a respiratory condition at all.

We don’t think the virus is mutating in the way the influenza does, but we’re not sure. We don’t even know for sure yet what the death rate is.

Not being sure is “following the science”, but this doesn’t cohere well with policy-making. And we want simple clear answers. This is understandable in a population where scientific literacy is low. We’re only just getting used to weather forecasts that give us probabilities of rainfall rather than simple yes-no predictions. But, perhaps we’ll use this crisis to become more comfortable with uncertainty and more conscious of which things we can be certain about.

Angela Merkel, in a broadcast to the German nation, gave a detailed epidemiological explanation of what different values of R meant for the health system. Covid 19 is thought to have an R of between 2 and 3. This means, without intervention, every infected person goes on to infect between two and three others. If measures like social distancing keep R below 1, the chain of transmission starts to be broken. Merkel explained what a small increase in R meant: if it goes up to 1.1, the German health system would be overrun by October; at 1.2, the crisis would come in July, and at 1.3, by June.

Even where there is a certainty within a discipline, building a response to the pandemic involves different disciplines with different answers. An obvious example is the answer to the question “how long does the lockdown need to last for?” Epidemiology says the best answer is as long as there are high levels of the virus circulating in the population. But behavioural science tells us that people will only tolerate being cooped up for so long before they begin to go walk-about. There were already some signs in the fifth week of the British lockdown that this was starting to happen.

So, from an epidemiological point of view, the lockdown on 23 March came late. But from a behavioural viewpoint, this may have been the optimal time. And, of course, other factors have to be considered too, most particularly the effect on the economy, on people’s livelihoods and consequently on their mental and physical health, covid 19 notwithstanding. We won’t know until the official papers are released, but there are speculations that there was a policy debate in the UK in March as to whether to bear down on the spread of the virus or, alternatively, whether to let infections rip hoping for a quick peak and the creation of “herd immunity”. The world has never encountered anything like this, not even in the Spanish Flu pandemic of 1918-19, because there was no lockdown then. On the contrary, the First World War ground on towards its grisly conclusion despite the virus.

So there really is no simple “science” that can be followed. It’s all a matter of balancing some things that are known and guessing at some things that are not yet known. The decisions are ultimately political, not scientific. The “following the science” mantra may simply serve to shift blame onto the scientists if things go wrong.

119. Brexit, uncertainty and the toast Jesus

In 2004, a woman in Florida sold for US$28,000 a grilled cheese sandwich on which she claimed to see the image of Jesus Christ. The toast Jesus phenomenon tells us something interesting about knowledge.

toast Jesus

Our brains are programmed to seek and find patterns in things. Not all the patterns we see are real. Random events can create an illusion of structure where none really exists. We think we’ve seen a signal in the noise but all we’ve seen is random noise.

Michael Blastland delivered a lecture at the Royal Society of Arts on this theme. One of his examples comes from the announcement in January 2018 by the Office for National Statistics that unemployment in the UK had fallen by 3,000 people to 1.44 million.  So far so certain. But in the methodology section of the report they acknowledge that statistically this figure has a 95% chance of being true, plus or minus 77,000. In other words, unemployment might have fallen by as much as 80,000, but it might just as easily have risen by 74,000.

Blastland argues that the great threat to progress is not ignorance, it’s the illusion of knowledge.

So how do we get from the toast Jesus problem to Brexit? Andrew Neil on 12 July 2019 interviewed the two candidates for leadership of the UK Conservative Party and hence for the Prime Ministership of the country. He took Jeremy Hunt to task for not being willing to promise that the UK would have left the European Union by the 31 October deadline.

Andrew Neil Jeremy Hunt

Hunt explained, not unreasonably, that nobody could know what would happen if no deal was agreed with the EU. He noted that Parliament might block a no-deal exit and that this might lead to an election. Hunt said he was simply being honest, but Neil accused him of being slippery and untrustworthy.

We human beings prefer certainty to uncertainty. At least for some things. It’s true that we prefer not to be told how a novel turns out before we read it. And we can cope with uncertainty in weather reports. But we don’t care for it much in our politicians. Perhaps we’ll only get the politicians we really deserve when we’re less insistent on easy certainty.

102. The bots are reading your mind! Not

Do we need to be scared of big data and its claimed spooky ability to know more about us than our partners, to mould our behaviour like puppeteers?

An e-mail dropped into my inbox today from Amazon. I won’t name the book or the author the tech giant’s algorithm was trying to market to me. Usually I delete Amazon’s recommendations unread, but this time I looked at the book. Not because I expected I’d want to read it, but because I wanted to understand the marketing. The book was described as “An emotional psychological thriller with a twist.”  That already annoyed me: why both psychological and emotional? And, yeah, of course it has a twist. The only thing it didn’t tell me is what reading level I need in order to follow the prose.

I began to read the taster. It began with an odd question. That was designed to intrigue and to hook my attention. The meaning of the question is explained by the bottom of the first page, in case my patience flags. There’s a hammer-beat of short staccato sentences, designed to lunge for my heart. There’s a bit of backstory. Hmm. Backstory on the first page? That’s a mistake when we’re supposed to be in the relentless attention-grabbing now.

The machine algorithm is marketing something to me I wouldn’t read in a million years. Primarily because it feels like it was assembled by a machine according to a formula. Facebook’s algorithms keep showing me pictures of cute dogs. Actually, it’s my wife who’s keen on cute dogs, not me.

My point is despite all that machine learning and big data, these two tech giants still have little clue who I am and what I like.

facebook fingers crossed
Image credit Wired


So, exactly how afraid should we be of Cambridge Analytica? The data breach that allowed the company to harvest the details of 50 million Facebook users is undoubtedly serious. But did it get Donald Trump elected President of the US? Did similar dirty tricks swing the Brexit referendum in the UK?  Let’s examine what they’re able to do with the data.

The core of the data analysis seems to be a personality quiz app, developed by a Cambridge University academic and downloaded by 27,000 people. The quiz broke people down into groups, dominated by traits like agreeableness, openness, neuroticism etc. We’ve all done such tests in magazines. There are 72 different online personality tests available on the website of Cambridge University’s (not to be confused with Cambridge Analytica) Psychometrics Centre. Clearly this is not an exact science.

What was different in this case was the ability to look for correlations between the personality quiz results and Facebook records, such as what people liked. Here it does start to get a bit more sinister. For example, a 2013 research paper by three academics from the Psychometrics Centre showed that it was possible to predict intimate information about a person from their Facebook likes, information such as sexuality and political leanings.

In some cases, the correlations were pretty obvious – liking the “No H8” campaign and being gay. In others they were less clear. For example, users who liked the “Hello Kitty” brand tended to be high on “Openness” and low on “Conscientiousness”, “Agreeableness”, and “Emotional Stability”. They were also more likely to have Democratic political views (75%) and to be of African-American origin (82%), predominantly Christian (69%), and slightly below average age.

While it’s not precise, what this does is allow micro-targeting. Instead of standing at a hustings and bellowing the same message to everyone, a political candidate can whisper different messages to different groups – threat messages to the fearful, for example, and optimistic messages to the bold. The Cambridge Analytica whistle-blower, Christopher Wylie, said this is exactly what the company did.

Was that enough to lose Hilary Clinton the US presidential election? We don’t yet know. A scientific test would require demonstration that micro-targeted ads outperform random ads in changing consumer actions. But my guess is that Cambridge Analytica was better at marketing itself to sleazy clients than it was at targeting and changing voters’ behaviour. Predicting personality attributes is not the same thing as changing behaviour. And, despite the hype, it’s not at all clear that the algorithm is any better at prediction than a human would be.  If Amazon can’t even get my reading preferences right, what chance big data can make me vote for someone whose politics I don’t like?