Instant Genius - Can science explain everything? – Michael Blastland

Episode Date: May 15, 2019

We know a lot. In scientific studies, we can count data, observe trends, infer links and calculate risks. But we also spend a lot of time ignoring noise – the unexplained variations in our results that we can’t account for. Take smoking for example. We all know that smoking kills, but it doesn’t kill everyone, and we can’t predict which lifelong smokers will be struck down by lung cancer, and which won’t. In his new book The Hidden Half (£14.99, Atlantic Books), Michael Blastland discusses how, even in the most tightly controllable situations, we often still see variations in outcomes. He argues that our unwillingness to admit uncertainty can affect science, economics, politics and business, sometimes with disastrous consequences. But it’s not all bad news. New research that shows that admitting the extent to which we’re not sure could make us seem more trustworthy. And he explains that even though we don’t know everything, experts and the scientific method are still the most important places for us to turn to for guidance. He talks to Helen Glenny, editorial assistant at BBC Science Focus Magazine, in this week’s episode of the Science Focus Podcast. If you like what you hear, then please rate, review, and share with anybody you think might enjoy our podcast. You can also subscribe and leave us a review on your favourite podcast apps. Also, if there is anybody you’d like us to speak to, or a topic you want us to cover, then let us know on Twitter at @sciencefocus. Listen to more episodes of the Science Focus Podcast: What happens when maths goes horribly, horribly wrong? – Matt Parker There’s no such thing as Blue Monday – Sir David Spiegelhalter What’s the deal with algorithms? – Hannah Fry Inside the mind of a comedian – Robin Ince Is the cure for cancer hiding in human breast milk? – Professor Catharina Svanborg Is gene editing inspiring or terrifying? – Nessa Carey Follow Science Focus on Twitter, Facebook, Instagram and Flipboard Hosted on Acast. See acast.com/privacy for more information. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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The Hilton sale is on now. Book on Hilton.com or the Hilton app and save up to 20% to get the stay you expected. When you want savings, not surprises. It matters where you stay. Hilton, for the stay. This podcast is sponsored by name, audio and focal. Streaming has made music more accessible than ever, but true listening is about more than ease.

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So a lot of the social and biological sciences, human sciences, are discovering that findings that we thought we'd established are suddenly when we try and repeat the experiments that established them, failing to stand up. You're listening to the Science Focus podcast from the BBC, Science Focus Magazine team, with the UK's best-selling science and technology monthly, available in print and in several digital formats throughout the world. Find out more at ScienceFocus.com or look out for us in your app store. Hello and welcome to the Science

Focus podcast. I'm Alexander McNamara, online editor at BBC Science Focus magazine. We know a lot. In scientific studies, we can count data, observe trends, infer links and calculate risks. But we also spend a lot of time ignoring noise, the understanding. explain variations in our results that we can't account for. Take smoking, for example. We all know that smoking kills, but it doesn't kill everyone, and we can't predict which lifelong smokers will be struck down by lung cancer and which won't. In his new book, Michael Blastelin discusses how, even in the most tightly controllable situations, we often still see variations in outcomes. He argues that our unwillingness to admit uncertainty can affect science, economics, politics and business,

sometimes with disastrous consequences. But it's not all bad news. New research shows that omitting the extent to which we're not sure could make us seem more trustworthy. And he explains that even though we don't know everything, experts and the scientific method are still the most important places for us to turn to for guidance. Here's Helen Glennie, editorial assistants of BBC Science Focus magazine,

talking to Michael Blasteland. Okay, so Michael, first of all, can you tell me a bit about the book? the book is called The Hidden Half, and I think of it as a book of mysteries and errors that reveal to us the extent of our ignorance about what's going on in the world. So in some cases, they simply reflect the fact that our knowledge is much weaker and much less reliable than we think it is. I think very commonly, we assume we know a great deal more than we actually do. In other cases, I think, they just leave us with an imponderable, something which we imagine we had secure knowledge about.

And actually, there are great gaping holes in our knowledge. And I don't think these are widely appreciated. So what I've tried to do is tell some of the stories about the kind of emerging understanding that we're getting now, which instead of revealing to us secure, robust knowledge of causal influences and they're like, are actually showing us that we don't and possibly never will have secure knowledge of some of the causal processes in our lives and in society. It's quite an uncomfortable thing to point out this. Well, I'm okay with that. I mean, I don't know how you feel, but I feel reasonably good about

uncertainty. I know a lot of people say that they don't like it, but my own view is that we exaggerate our distaste for uncertainty. It's very commonly said people don't like it. And there's evidence from psychology, for example, that our brains just can't cope with ambiguity very easily. So you know the classic picture of the duck and the rabbit. Is it a duck? Is it a rabbit? And you can't hold both things in mind at once. You either have to see it one way or the other.

And this is sometimes taken as evidence that the brain is fundamentally antagonistic to the idea of an ambiguous state of mind. You can't sort of sit between these two views. You have to choose. but I'm not sure that's valid. And you only have to start asking yourselves a very few simple everyday questions about uncertain events or moments to see that there are quite a few of them that we do like. So if I say to you, do you want to know all your Christmas presents for the rest of your life? Yeah, absolutely not. Do you want to know the time and date and manner of your death?

Yeah, no, no way. How does that feel? Do you want to know the ending of all the films? You know, you go see. So there are clearly some instances where uncertainty is actually a pretty good thing. So the question is, can we use it in ways which people find acceptable for the more tricky questions about, say, information about what's going on in the world, news and so on? Because the fear there is that if people admit uncertainty, then they lose their authority.

If you say, I'm not sure, then people say, oh, well, I'm going to listen to you. then. And I think a lot of people are in fear of that sort of reception. So let me describe to you a little piece of research, which is being done by an organisation called the Winton Centre for Risk and Evidence Communication, which I have some involvement. And what they do is they say to people, okay, we're going to tell you how many tigers there are in the world. And then we're going to ask you whether you trust the information and whether you trust the person telling you, two separate questions. So they say, okay, there are X,000 tigers. What are you think of that and do you trust me? And people might say, well, how sure are you? And then,

you know, so it goes on. But then you can say, okay, well, we think there are X,000 tigers, but we're not quite sure about that. Now, how well do you trust the information? How well do you trust me? And the third one, okay, we think there are X,000 tigers, but we're pretty confident that the answer is maybe about a thousand more or a thousand fewer. Now do you trust me? And the funny thing is that the last of those achieves the highest level of trust. People lose confidence in the number

a bit, which actually they should because we're not that sure about the number. But they gain confidence in the person giving them in the information. So it's the old belief that you lose authority if you admit to uncertainty doesn't

necessarily hold up. We can present information in ways which admit the real genuine, truthful, unavoidable uncertainty and gain credibility. Uh-huh, yeah,

because you'd expect that that people know on some level that we're not always sure about information, and admitting to that is, yeah, it could make you seem quite reliable. I think that's right.

I mean, I think a lot of us do know in our hearts that these are phenomenally complicated things to measure and capture. And we have a lot of people telling us, it will be. I know. It's like this. So we have a lot of people telling us things with great precision, supposedly, and claiming that they have a good deal of authority to give these kind of

verdicts, and I often suspect that they just don't know what they're talking about, you know, or that they simply can't know it with anything like that sort of precision. And in those cases, I think, admitting that the uncertainty would do us a lot of good, and it would enhance people's credibility. I think straining too far for an unreasonable certainty actually diminishing. is your credibility. Yeah, absolutely. It's actually quite, I hadn't thought about this before, but it's quite amazing timing,

this book coming out in the midst of this Brexit chaos, a book about what we don't know, especially as that applies to politics and a few places in the book. I'm pleased you said that, because I think it's very true. We've had a couple of shocks recently to our self-confidence about our ability

to understand what's going on in the world. So just a few examples. I mean, we had a recession in 2008, the consequences of which are still being felt. And that came out of the blue. You know, hardly anybody saw that coming with the ferocity that it actually delivered. And, you know, economics believed it had a reasonably robust understanding of quite a lot of the factors that should have governed the way the economy behaved in those periods. and it failed. And on reflection, we decided that we didn't really understand the way the banking sector worked within the economy.

We're still wrestling with questions about productivity, for example. We've decided that we have a bit of a productivity crisis. Productivity seems to have slowed down. This is one of these things that's still rumbling on. We're just not building up our growth as much as we used to. and this productivity puzzle, as it's called, is still with us. We do not understand fully what's happened to productivity, and productivity is the central element of economics.

It's what delivers all future prosperity and growth. So those are a couple in, you know, one big area of policy. We're in the middle of what some people call a replication crisis in science at the moment. So a lot of the social and biological sciences, human sciences, are discovering that findings that we thought we'd established are suddenly, when we try and repeat the experiments that established them, failing to stand up. And there are dozens and dozens of instances of these kind of things.

I'll give you one very popular example you may have come across, which has attracted a lot of attention, the power pose. You may have heard about the power. If you adopt a certain confident posture before you go into a meeting, this produces measurable improvements in your performance. Well, the power pose on subsequent examination now looks a little bit debatable. One or two people are still standing up for it, but quite a lot of wondering whether it was really there in the first place, whether it was ever properly discovered. And this is happening on an extraordinary scale. So there are some people who say that possibly up to about half of the published

findings are unreliable. Now, those have gone through peer review. They're very often in world leading journals, and when we try to repeat them, we don't get the same results. And so that's another one. We've had these kind of rather shocking things in economics. We've had shocking things in science. We've had shocking things in politics. I mean, if you look at Trump, the election of Donald Trump in the United States, you look at the rise of the political right in Europe. You look at Brexit in the UK. There are numerous political events, which again, people have said, where did that come from? You know, we just didn't expect this. It's, you know, it's upset the apple cart entirely. And again, the political scientists didn't really see it

coming. So everywhere you look, it seems, there's evidence that our self-confidence ought to take a little bit of a knock, because we do not know. We are not successfully predicting with anything like the kind of assurance that we pretend we ought to be able to have. We're failing across the board, I think, to acknowledge the degree to which our supposedly robust knowledge

about the way things work and the way they can be expected to work in the future is simply not bearing out. Yeah, now you start in the book with the example of these marma crabs, which lays out this problem of unpredictability, I think, really, really well. Can you talk me through that example? Oh, the marma crebs are just a delight. I've slightly fallen in love with these crepefish. So the story is that in the 1990s in Germany, people who were enthusiasts for aquariums, so people in the aquarium trade, people who have

fish tanks at home. They suddenly started noticing this unusual new creature in their aquaria. And there were a couple of oddities about it. One was that they were all female. There were no males. So they started saying to themselves, well, where did this thing come from? Because there's no evidence of it in the wild. It's just popped up overnight in the aquarium trade. and why are they all females? And it turned out that basically the mothers had started cloning themselves spontaneously overnight, new species in a fish tank,

which is all wonderful enough. But the kind of interesting consequence of that story is that scientists became very interested in these creatures because, of course, if you've got a cloned creature, this is a wonderful thing because it means that any differences you observe in the way this creature develops cannot be due to its genetics.

If the genetics are the same in every single animal, then genetics can't explain any differences between the animals. So they took these creatures and they put them in the lab, but then they went a step further. They made the lab conditions absolutely identical. So they were all in the same kind of water at the same temperature. They were all fed the same kind of food. They were all given food in abundance,

so there were no differences in the animals access to food. They could all have as much as they wanted. They even went so far as making sure the same person examined these creatures on every occasion, wearing the same brand of gloves, you know. So they standardised the environment as well. So now you have identical genetics and identical environment. Everything, so far as we know, is the same for these creatures. As I say in the book, it's the most boring conformity that humans can,

could contrive. So what did they look like, these genetically identical creatures in an identical environment? Well, they're radically different. They're chalk and cheese. One of them is 20 times the weight of another. 20 times, you know, these are phenomenal differences in size. They actually have physically different internal organs, the structure of some of their internal organs, the structure of some of their feeding parts are physically different. Every single marmacrebs studied has a different pattern of markings on its carapace. They're almost like fingerprints. They're genetically identical and they're environmentally identical,

and every single one of them is different. They're behaviorally different. So when they sleep, some of them sleep on their backs. Some of them sort of sit under shelter. Some of them are loners. Some of them are very sociable. Some of them are dominant. Some of them are subservient.

the lifespans differ by a factor of two to three. You know, some of them live 400 days, some of them live for 900 days or more. They lay different numbers of eggs in different batches, quantities of batches. They start laying at different points in their lifetime. I mean, it's extraordinary. You know, it's as if the expectation is almost like, you know, you take a tin of whitewash and it comes out striped. It's just absolutely not what you expect. And then the real question, you know, the real poser, if you've stabilized, standardized,

everything that causes anything, where in earth does all this difference come from? Why are they so different? Because everything's the same. Everything that goes in is the same. How can what comes out be so radically different? And the answer is, we don't know. We do not know what explains all this difference. They're still recognisably marmachrebs.

If you looked at them from the distance, you'd say, oh, yeah, they're all the same creature. So clearly genetics have an influence. They have a very strong influence. And if you gave them no food at all, you know, they'd all die very quickly. So clearly the environment has a very powerful influence. We're not trying to deny either of those things. But there's this huge range of difference between these creatures, which we just cannot explain, except in the most general terms.

So there were a couple of potential explanations for this. We don't know how they work in any detail, but very roughly I can describe a couple of processes which might be part of the picture. One of them is that there is just innate randomness in the way that people develop. And you can see this, for example, in identical twins. So if you compare identical twins, they're not identical.

There are a little bit of difference in them. And that difference extends even into the brain structure. So you can do scans of the brains and you can observe small differences. Now, how do those small differences come about? Well, between the gene and the physical person, the phenotype, the way that people turn out, there are a huge number of genetic and biological processes. going from the gene to the person can be interrupted by all kinds of randomness.

For example, the ways that the cells develop in the brain can be affected simply by temperature. So that what you're getting is the blueprint is not quite being built with perfection. And as I say, you can see this in twins. You can even see it in a single person because the two sides of your face, for example, are not perfectly symmetrical.

Now, so when the body clones itself, which is basically what it's doing when it's reproducing the two halves of us, you actually see quite significant differences. I mean, facial differences are often fairly minor, but you can see very profound differences in some other areas. So, for example, our susceptibility to cancer can vary radically from one half of the body to the other, even though that body has been susceptible to exactly the same environmental influences and exactly the same genetics, but you can get profoundly different differences. breast cancer in one breast, how likely are you to have it in the other breast? Not much more likely than a stranger is to have it for the first time. It's, you know, what's the world are called the contralateral risks of breast cancer are not very much raised if you've already had it in one breast, suggesting that, you know, the two halves of the body are behaving in quite fundamentally different ways, even though they're all exposed to the same things. As I say, two halves of the brain,

the same brain, can exhibit differences, even though the body tries to reproduce, two more or less identical halves of the brain. You can see differences in internal organs and so on. And the simple idea is that even if you have the same rulebook, the same genetic instructions, you do not get the same outcome. And a nice way of capturing this idea is that you just can't step in the same river twice. You can't bake the same cake twice.

You use the same recipe. You have the same ingredients. You do it in the same kitchen. You know, all the rest of it, but the cake just doesn't turn out the same way twice. And humans are very much the same. We do not turn out the same way twice. So this is one potential explanation for the kind of differences that you observe in these creatures,

that essentially what's going on is quite a large degree of randomness in the application of the genetic code. And this could explain some of the difference that we see in creatures like marmcripps. Another explanation is that the kind of differences that are creeping in are what are called sometimes microenvironmental. mental influences. Now, in other words, they're too small for us to see. So you imagine those marmacrebs again. Could there be some kind of extraordinarily subtle influence in their environment, which we just don't observe, which is actually almost like in a chaotic fashion, becoming a small initial difference which magnifies and magnifies until it produces some radical changing behavior. So you know, you could hypothesize that maybe at some point in their development, you know, you've got a couple of marma crebs in the tank.

And even though they all have more than enough to eat, the first drop of food that falls into that tank, there's a bit of a race for it. And one of them gets there first. And even though the other one can turn around and go and get some more, maybe that establishes a bit of a pecking order. And out of that pecking order, the first one feels a bit more aggressive and confident. and the other one feels a little bit less. And all that it depends on is who was closest to the drop of food when it first appeared in the tank. But maybe this set up some kind of spiral of behavior which became amplified in subsequent behaviors and so on. And it's interesting actually that if you put these marmochrobs in groups,

you find that one group will exhibit a different spectrum of behavior to another group. So there are differences between individuals, but there were also differences between the groups, which kind of suggests that the dynamics within each group are having an effect on the way that these creatures develop. It's almost like, you know, put you and me together in a group, and our conversation will be different to somebody else's conversation. And even if we're all clones, there's something about the nature of those slight differences in conversation, which produces different kinds of people. And in both cases, I think, in the innate case where we're looking at innate differences in development, which are just random, and in the environmental influences that produce differences that we simply can't trace, we are looking at the tiniest little influences. But as we're beginning to see, they can have quite profound influences. Sorry, they can have quite profound effects.

And the difficulty then is, will we ever be able to detect these things? things, and I think in very many cases the view is that we simply won't. If you're thinking about some of those brain structure development questions, there are millions and millions of them, potentially. They can be, you know, something as simple as the temperature when a neuron puts out of synapse. As simple as I say, possibly, is where the first piece of food appears in a fish tank. If you start to think of it. about that kind of thing in a human context, is it possible that a single conversation could be influential? Could there be turning points in people's lives which revolve around a single

conversation? Well, clearly, anecdotally, we all say that there have been. We often say, I was changed by a conversation or something like that. Are we ever, through research, going to be able to discover systematically the way those kind of influence, we, are we, work, I don't think we will. I think they're, they're just going to be lost in the noise, those, those things. I don't think we will ever be able to nail them down in a sufficiently accurate way to get beyond the kind of, oh, we can roughly, we can roughly define, we can roughly explain about 50% of the way people turn out, which is the way things are at the moment. A common number is about 50%. We can find causes and explanations for that,

but that's where I take the metaphor, the hidden half. There's about half a bit. If I can very crudely, and I am being very crude here, very crudely summarise what I understand the science to be telling us, there is about half which exists at this micro level, which I think we will quite conceivably never be able to explain. Now, this really seems to throw a spanner into the works for scientific research, particularly biological or medical research,

a place where we like to have all the variables constrained really tightly. So how's that being dealt with or is it being dealt with? Well, I think to some extent it's being dealt with by denial. We're just pretending it's not really as big a problem as it is. There are two responses. One is to say that all we can do is say things probabilistically. we're not going to be able to get to that stage where we can, with perfect accuracy, define the trajectory for every individual through illness and treatment and so on.

All we can do is say we think there's a 60% chance or a 30% chance or we can look at your genes and say, well, you know, about 60% of people with these kind of genes have this sort of thing, you know, or maybe only 5% or whatever it is. So we can do these kind of things probabilistically. clearly are you going to be in the group that will or the group that won't, you know, you don't know. So there are severe limits to the individual level of prediction that we can achieve, even though we know things across a whole population. We can say 40 out of 100 or whatever will be like this. So that's one approach, and we can do the same thing with treatments.

We can say that medicine works this often. so it might work for you on this occasion. It might not. Here's how often we think it works. And we just have to be content with that. And probabilistic knowledge is quite powerful knowledge. It can be very effective if you apply it across a whole population, you can achieve remarkable things.

But it does have severe limits for any individual. Predictive powers are extremely weak for individuals. The other response to the problem is to say, well, we just have to get a little bit cleverer and really work a lot harder at discovering what these kind of micro-influences are. And we have to track everybody's genome and we have to track their environmental exposures. And we can work out precisely what sort of medicines are going to work on this person at this moment and all the rest of it. And we say that we will get to a state of precision medicine and this sort of thing. I think a lot of the talk around that is exaggerated.

I think there are some real gains to be had. Don't get me wrong. I'm not knocking it entirely. I think you can find precise treatments for different types of cancer, for example. I think that's one example where I think there is real possibility of progress. But I think in other areas, this notion that we will be able to nail down with absolute precision, what kind of person you are and what kind of illness you will have

because of your genes and what kind of treatment will make you better and know all that with security I think is pie in the sky. I just, you know, you only have to look at the difference between the genotype and the phenotype. I can track all your genes. I can have them down with absolute precision

but I still don't know how you're going to turn out. There's that gap. There's that potential random. between genotype and phenotype. Now, given that, even if I know all your genes, I still don't know what you're going to be like, and I still don't know how you're going to respond in different contexts to different sorts of medicine.

There may be other things going on in your life, which mean the pill that worked yesterday won't work today because there's some interfering illness that you have or something of that sort. We will never have perfect prediction of those kind of things, I think. So I think some things are possible with precision medicine or personalized medicine, as it's also sometimes called. But I'd be much happy if people said we can make it a bit more precise, rather than saying we'll make it precise. I don't think it ever will be precise. So those are

the two options. One to try and nail it all down perfectly, the other just to accept the probabilities. I think we'll always have to accept that our knowledge is probabilistic at best in some cases. Now we've got that in medicine. You've talked about the replication crisis and science. You also mentioned the book about science influencing public policy and how that is subject to some level of unpredictability and it's not always right as well. How does all of this together affect the way that we view scientific knowledge, you know, something that we normally hold up as the most reliable source of information that we have? Well, oddly, I think it still is the most reliable source of information that we have. But it's still unreliable. And we have to get used to it. I think holding it up as the most

authority is fine. And it's true. I do think we know some things better than other things. And I think the scientific method is still by a street the best way of finding them out. But I think we just have to acknowledge its limitations. And oddly enough, acknowledging the limitations is one of the most fundamentally important things we can do in making further advances. I think science is the best way that we have of establishing truths about the world. I'm not a nihilist. I'm not a relativist.

I do think real knowledge is possible, and I think it does advance. And the scientific method is absolutely the best way of making progress. But I also think that acknowledging our limitations is an important part of making that progress. If we fool ourselves that we have more secure knowledge than we really do, then our ability to spot the weaknesses and therefore advance further is impaired. Fuling ourselves about the degree of our understanding means we fail to correct our misunderstanding. So it's integral to the scientific method that we acknowledge the exceptions, the difficulties, the awkwardness, the weakness. So there's a physicist, Richard Feynman, who wrote an essay about what he called Cargo Cult Science years ago now. And it's a celebrated essay.

But what he talks about is an absolutely scrupulous honesty. when we reflect on the weaknesses of our own evidence and argument. He says this is vital to making scientific progress to fess up about all our doubts and uncertainties, all the potential weaknesses in our data, all the second thoughts we may be having about our methods, were they the best methods, was the research design, the optimal design.

are we completely sure that we've got this right and if we're not tell other people now that feels extraordinarily risky when your scientific career is at stake if you say well here's my paper and I want you to read this paper and be impressed by it and give me another research grant so that I can write another one and this kind of thing and get me promoted and all of these sort of issues and I want to make a difference in the world. It's not only selfish interests that we're talking about here. People genuinely want to feel that they're making discoveries which are going to contribute to human betterment.

I think it's all absolutely laudable, but it can cause us slightly sometimes to overlook the deficiencies in our knowledge. Now, if we do that, I don't think we're contributing as well as we could be. Recognizing the uncertainties and the limitations is an absolutely fundamental part of the scientific method and a scientific enterprise, and we need to encourage it, because at the moment, too many of the incentives are for people to disguise those weaknesses, because they feel that it will impair the reception of their work and damage them personally. But it's not collectively for our good. So we have to change.

That was Michael Blastland, talking about the uncertainty that pervades science, economics and policy. His book, The Hidden Half, is out now. Thanks for listening to The Science Focus podcast. The May issue of BBC Science Focus is on sale now. In it, we marvel at the first ever photograph of a black hole and find out what we can learn from it. We look at the new dementia research that's providing hope for patients and talk to a psychiatrist that's keeping patients awake all night in a radical nutrient. treatment for depression. And as always, there's much, much more inside.

Thank you for listening to the Science Focus podcast from the BBC Science Focus magazine team. With the UK's best-selling sites and technology monthly, available in print and in several digital formats throughout the world. Find out more at sciencefocus.com or look out for us in your app store. This podcast is sponsored by name, audio and focal. The texture and emotional depth of music can be lost through digital sources or poor signal. Name Audio believes you can have digital precision with analog warmth. Alongside French acoustic specialist vocal, Name creates high-end audio systems combining innovation with craftsmanship, so you can listen to music, just as the artist intended. Discover more at nameadio.com.

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