# Bonus: Why We Believe What Isn't True (with Axios Today)

An episode of [Cautionary Tales with Tim Harford](https://invisiblenetwork.ai/podcast/1484511465), 12 Feb 2021, 14 min.

Audio: https://podtrac.com/pts/redirect.mp3/pdrl.fm/18db03/tracking.swap.fm/track/SxlTEPDY7xDg35RXkASs/traffic.omny.fm/d/clips/e73c998e-6e60-432f-8610-ae210140c5b1/c0ae8c6e-22f0-4e9b-ac1c-ae390037ac53/96113bc4-cf9e-459c-a4bd-ae39003d922c/audio.mp3?utm_source=Podcast&in_playlist=7f5a4714-6b10-4ccf-a424-ae390037ac70

We're no stranger to stories about misinformation or deliberate disinformation. We live in a world where now more than ever, you have to be skeptical. That skepticism can be healthy, but it also can be used to cast more doubt and misinformation on data and statistics that are very real. Tim Harford talks to Niala Boodhoo, from the news podcast Axios Today, about why people believe things that aren't true. Check out Axios Today, where Niala delivers the news every weekday - in just 10 minutes. Subscribe to Axios Today wherever you get your podcasts. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com See omnystudio.com/listener for privacy information.

## Transcript

[0:15] Speaker 1: Pushkin. Hello, Cautionary Tales listeners. As I'm getting ready to
[0:25] Speaker 1: kick off my second season on the twenty sixth of February,
[0:29] Speaker 1: I wanted to share my appearance on a different show
[0:32] Speaker 1: from our friends at Pushkin and Axios. On this episode
[0:37] Speaker 1: of Axios Today, I talk with host Nila Boodoo about
[0:41] Speaker 1: my book, The Data Detective and why people believe things
[0:45] Speaker 1: that aren't true. We live in a world where, now
[0:48] Speaker 1: more than ever, you have to be skeptical. That skepticism
[0:51] Speaker 1: can be healthy, but it can also be used to
[0:54] Speaker 1: cast doubt on data and statistics that are very real,
[0:58] Speaker 1: and to spread misinformation. Listen to my conversation with Nila
[1:03] Speaker 1: and subscribe to Axios Today wherever you get your podcasts.
[1:08] Speaker 1: Here's the show. Tim Harford is a senior columnist with
[1:13] Speaker 1: The Financial Times, and he's also author of The Data Detective,
[1:16] Speaker 1: which is just out this week. Hi, Tim, welcome to
[1:19] Speaker 1: ax Yesterday. Oh thank you very much for having me.
[1:22] Speaker 1: So I have to first just ask you. The title
[1:25] Speaker 1: of this is how to make the World Add Up
[1:27] Speaker 1: outside the US, but it's The Data Detective here in
[1:30] Speaker 1: the US. Is this like a Harry Potter situation? Why
[1:33] Speaker 1: do we have a different title. Yeah, I'm hoping for
[1:36] Speaker 1: the Harry Potter sales. That would be nice. Yeah, it's
[1:39] Speaker 1: as simple as the UK publisher didn't like the US title.
[1:42] Speaker 1: The US publisher didn't like the UK title, and I
[1:44] Speaker 1: just have to explain it to everybody that I talked about. No,
[1:47] Speaker 1: I thought it had some greater significance, like statistically about
[1:51] Speaker 1: the way that Americans interpret words. It's exactly the same
[1:54] Speaker 1: book all over the world, just a different title. And
[1:57] Speaker 1: it's all about trying to help people think clearly about
[2:01] Speaker 1: the world, using, among other things, the tools of statistics.
[2:06] Speaker 1: And you're right that we might be at a bit
[2:09] Speaker 1: of a fork in the road or a moment when
[2:11] Speaker 1: it comes to statistics, particular when we think about the pandemic. Yeah,
[2:15] Speaker 1: I think so, because we've seen a tremendous amount of
[2:20] Speaker 1: misinformation and even deliberate disinformation, but we've also seen a
[2:26] Speaker 1: credible appreciation of just how life saving accurate numbers can be.
[2:31] Speaker 1: All of the questions we want answering, like, you know,
[2:34] Speaker 1: where is the virus, who's got it, how's it spreading?
[2:36] Speaker 1: What are the risky activities? Do masks help, what treatments work,
[2:41] Speaker 1: do the vaccines work? All of these life or death questions,
[2:45] Speaker 1: you can't answer any of them without good data. And
[2:49] Speaker 1: so I think people have started to appreciate that while
[2:53] Speaker 1: there is a lot of polarization, there is a lot
[2:55] Speaker 1: of misinformation, they are helping us make incredibly important and
[3:00] Speaker 1: consequential decisions. But of course, our societal problems and the
[3:03] Speaker 1: polarization aren't about the statistics themselves. They're about whether we
[3:07] Speaker 1: believe them. Today twenty one, the idea that statistics are
[3:10] Speaker 1: a lie is almost accepted fact. Yeah, although it's a
[3:14] Speaker 1: lot easier to lie without statistics. Let me tell you so.
[3:17] Speaker 1: I mean that idea goes back, way, way, way way back.
[3:20] Speaker 1: So the time of Mark Twain, people were talking about lies,
[3:23] Speaker 1: damned lies and statistics. But for me, at the moment
[3:27] Speaker 1: that I really identified as significant was nineteen fifty four.
[3:32] Speaker 1: Because two different things happened in nineteen fifty four in
[3:35] Speaker 1: the same year. You've got this, to me incredibly dramatic
[3:39] Speaker 1: illustration of these different views of statistics. There's this one guy,
[3:44] Speaker 1: Darryl Half, who wrote How to Lie with Statistics, who's saying, yeah,
[3:48] Speaker 1: it's like a stage magician's trick. You can never trust them.
[3:52] Speaker 1: It's fun to figure out how the trick is done,
[3:55] Speaker 1: and I'll show you how statistics are used to deceive you.
[3:59] Speaker 1: And then you've got these these two epidemiologists, Richard darl
[4:03] Speaker 1: and Austin Bradford Hill, who are saying this is not
[4:05] Speaker 1: a trick, this is life or death, and their discover
[4:09] Speaker 1: that smoking cigarettes dramatically increases your risk of lung cancer
[4:13] Speaker 1: has helped to save hundreds of millions of lives. It's
[4:17] Speaker 1: not not a game at all. The irony of that
[4:21] Speaker 1: bifurcation back in nineteen fifty three is that pretty soon
[4:24] Speaker 1: Darryl Half, the How to Lie with Statistics guy, ended
[4:28] Speaker 1: up testifying in front of Congress, basically saying where you
[4:31] Speaker 1: couldn't really believe all the statistics that showed you that
[4:33] Speaker 1: cigarettes were dangerous. So it was a very short trip
[4:37] Speaker 1: from here's a fun book exposing statistical fallacies. I'm standing
[4:43] Speaker 1: in front of Congress and I'm telling you that there's
[4:45] Speaker 1: no evidence that cigarettes are dangerous. It's pretty dark. And
[4:49] Speaker 1: how do you see that direct line from that moment
[4:52] Speaker 1: with casting doubt on scientists work when it comes to
[4:56] Speaker 1: tobacco and cancer, to climate science deniers or to what
[5:02] Speaker 1: we see now, Well, there's a well documented link. Now
[5:09] Speaker 1: that we've got more than four hundred thousand Americans dead
[5:13] Speaker 1: and my own country more than one hundred thousand BRIT's dead.
[5:18] Speaker 1: Now that you know those reassurances have been proved to
[5:23] Speaker 1: be false, the defense mechanism is to say, oh, well, look,
[5:26] Speaker 1: the scientist's got a load of stuff wrong as well.
[5:28] Speaker 1: So they'll, for example, points to the WHO, and they'll say,
[5:33] Speaker 1: the WHO told us that the infection fatality rate was
[5:36] Speaker 1: about three and a half percent at the beginning of
[5:38] Speaker 1: the pandemic, and nobody now thinks it's three and a
[5:41] Speaker 1: half percent. It's it's below one percent. But that smear
[5:45] Speaker 1: on the WHO is actually a deliberate distortion. Who never
[5:49] Speaker 1: said that the infection fatality rate was three point five percent.
[5:53] Speaker 1: They said something else was three point five percent the
[5:55] Speaker 1: case fatality rate, and that difference doesn't really matter. What
[5:59] Speaker 1: I think is interesting is you've got that same tactic
[6:03] Speaker 1: being used, which is I've been caught out, I've been discredited,
[6:07] Speaker 1: and I'm going to lash out and others the scientists
[6:10] Speaker 1: and claim that they've got stuff wrong that in fact
[6:12] Speaker 1: they haven't. Why is it easier to discredit arguments? Then
[6:15] Speaker 1: it's almost like an easier fight to discredit something than
[6:19] Speaker 1: to support something and prove it right. There are so
[6:23] Speaker 1: many ways to answer that question. I think, really, I'm
[6:27] Speaker 1: not sure why it's easier, but it is easier, and
[6:30] Speaker 1: we've got good evidence that it's easier. I mean, you
[6:32] Speaker 1: just have to look around at the preponderance of negative campaigning,
[6:36] Speaker 1: for example. But we've got somebody nice evidence in experiments
[6:41] Speaker 1: conducted by political scientists and psychologists. So there's one from
[6:45] Speaker 1: the mid nineties that just showed people a bunch of
[6:49] Speaker 1: arguments about real hot button issues like the death penalty,
[6:53] Speaker 1: gun control, abortion rights, the sorts of things that people
[6:56] Speaker 1: get really heated about and feel very passionately about, and
[6:59] Speaker 1: they ask people to evaluate the strengths and weaknesses of
[7:05] Speaker 1: these different political arguments. And what the research has found was, Yeah,
[7:09] Speaker 1: people find it a lot easier to come up with
[7:12] Speaker 1: arguments supporting what they already believe, and they find it
[7:16] Speaker 1: harder to come up with arguments supporting the opposing point
[7:20] Speaker 1: of view. But they found that that's doubly true when
[7:23] Speaker 1: it comes to negative arguments. People found it incredibly easy
[7:27] Speaker 1: to produce negative arguments reasons to disbelieve the political positions
[7:34] Speaker 1: that they disagreed with. And I think that that's behind
[7:36] Speaker 1: the tobacco strategy, the climate change strategy, now the COVID
[7:40] Speaker 1: denial strategy, the same basic approach. If you don't want
[7:43] Speaker 1: to believe this, it's very easy for me to give
[7:46] Speaker 1: you reasons to doubt, very easy. Indeed, doubt has this
[7:49] Speaker 1: special kind of power, it seems, it's very tempting. Even
[7:52] Speaker 1: for people who really respect the numbers and respect evidence.
[7:56] Speaker 1: It's easy for us to fall into the trap of
[7:59] Speaker 1: constantly focusing on errors and mistakes, and that, I think
[8:03] Speaker 1: just feeds into this narrative that the numbers are always lying,
[8:06] Speaker 1: that they'll never tell you anything useful, and that's just
[8:09] Speaker 1: not right. So how do we, for example, for someone
[8:12] Speaker 1: like you who love statistics, obviously, how do we not
[8:16] Speaker 1: take numbers for granted? I think, just to notice how
[8:22] Speaker 1: important they have been in the pandemic. The metaphor for me,
[8:27] Speaker 1: it's like radar. So when we developed radar in the
[8:31] Speaker 1: late nineteen thirties, that turned out to be an incredibly
[8:34] Speaker 1: important innovation in the UK. It helped us turn back
[8:39] Speaker 1: the German Luftwaffe. Then we took radar technology, took it
[8:42] Speaker 1: to the States and the United States poured an incredible
[8:45] Speaker 1: amount of money into perfecting radar and perfecting that technology
[8:50] Speaker 1: because it's just so incredibly important to be able to
[8:52] Speaker 1: see what's coming at you. And for me, statistics are
[8:55] Speaker 1: like that. They're showing us the threats, they're showing us
[8:59] Speaker 1: the weaknesses on our own system. They're showing us where
[9:02] Speaker 1: policy is working and where policy is failing to work. Now,
[9:05] Speaker 1: where the supplies of PPE are going, where the supplies
[9:08] Speaker 1: are accina going, who is suffering most, and who needs support?
[9:12] Speaker 1: All of these things. You've got no chance of figuring
[9:16] Speaker 1: out any of this stuff without good statistics, without good data.
[9:20] Speaker 1: And so it frustrates me when we sit around going,
[9:23] Speaker 1: oh yeah, lies down, lies and statistics, and we treat
[9:26] Speaker 1: it as though it's just a weapon in a political argument,
[9:30] Speaker 1: and it's so much more important than that and so
[9:32] Speaker 1: much more useful. I think part of this is just
[9:34] Speaker 1: the natural. Also, we've talked about the human nature and
[9:37] Speaker 1: just sort of our tendency to doubt. I think a
[9:39] Speaker 1: lot of us also is how overwhelmed we are with
[9:43] Speaker 1: the amount of information and statistics that are coming at us.
[9:46] Speaker 1: And so how do you personally manage that? How do
[9:49] Speaker 1: you keep from being overwhelmed with information and statistics. The
[9:54] Speaker 1: first piece of advice that I give in the book
[9:57] Speaker 1: I think has surprised quite a lot of people. It's
[9:59] Speaker 1: nothing to do with technical tips on correlations or our
[10:06] Speaker 1: squared or sampling by so any of that stuff. I
[10:09] Speaker 1: just say, whenever you see a claim, statistical claim, a
[10:14] Speaker 1: newspaper headline, ask yourself how you are feeling when you
[10:20] Speaker 1: see that. Ask yourself what your emotional reaction is to
[10:24] Speaker 1: the claim. Because so many media headlines, so many social
[10:28] Speaker 1: media posts, are designed to arouse an emotional reaction. That's
[10:32] Speaker 1: kind of that's what makes a good newspaper headline, that's
[10:35] Speaker 1: what gets the clicks, that's what gets the shares and
[10:37] Speaker 1: the likes. But if you're processing information and you're in
[10:42] Speaker 1: an emotionally hot state, you're feeling angry, you're feeling vindicated, joyful,
[10:47] Speaker 1: any emotion at all, you're not thinking clearly. So my
[10:50] Speaker 1: advice is just you don't even need to count to ten.
[10:53] Speaker 1: Just count to three, notice your emotional reaction, and then
[10:58] Speaker 1: go back and look at the claim a second time,
[11:00] Speaker 1: and you'll already be thinking in a calmer and clearer way.
[11:05] Speaker 1: I know I sound like some yoga instruction that when's
[11:09] Speaker 1: the last time you do that? Well, I do that
[11:12] Speaker 1: all the time. It's like a It's a total habit
[11:15] Speaker 1: of mind for me, because I'm as vulnerable to emotional
[11:20] Speaker 1: thinking as anybody else. But it's just a complete reflex.
[11:24] Speaker 1: When I'm on Twitter, and Twitter is a place where
[11:26] Speaker 1: there's a lot of angry stuff going on. The moment
[11:29] Speaker 1: I see something and I'm minded to retweet it, to comment,
[11:33] Speaker 1: to share, I just hang on a moment, just notice
[11:36] Speaker 1: my own reaction to it, and then I may, of
[11:39] Speaker 1: course go on and share it. But I've already started
[11:42] Speaker 1: to spot the potential errors and the ways in which
[11:47] Speaker 1: it's not just that other people are fooling me, it's
[11:50] Speaker 1: that I am fooling myself. And I'm always going to
[11:52] Speaker 1: keep fooling myself if I'm feeling highly emotional when I
[11:56] Speaker 1: see these claims. I mean, you have talked about this.
[11:59] Speaker 1: We have talked about this many times on the podcast
[12:02] Speaker 1: Acts Us today, and I'm sure anyone who is even
[12:05] Speaker 1: a mild consumer of news is aware about the idea
[12:08] Speaker 1: of checking your sources right, checking your emotions. So I
[12:13] Speaker 1: think I wonder if you feel like that's just the
[12:16] Speaker 1: world that we live in now, where we have to
[12:19] Speaker 1: remember to be vigilant about all of these things, knowing
[12:22] Speaker 1: that people are probably exhausted of being vigilant about a
[12:24] Speaker 1: lot of other things. Yes, I mean, it would be
[12:28] Speaker 1: nice if every journalist, if everyone who ever posted on
[12:31] Speaker 1: social media did all that work for us, put everything
[12:35] Speaker 1: into context, gave all the sources linked us to complementary
[12:41] Speaker 1: or opposing points of view, so we could really sort
[12:44] Speaker 1: of evaluate everything. And the best journalists do the best
[12:48] Speaker 1: sources really do that. But if they're not going to
[12:51] Speaker 1: do it, you need to at least be aware that
[12:54] Speaker 1: someone is trying to get you to feel something. But
[12:58] Speaker 1: it's important to be vigilant and to be skeptical about
[13:02] Speaker 1: the news stories that we consume. I think it's just
[13:04] Speaker 1: as important to be vigilant and skeptical about our own
[13:07] Speaker 1: filters and biases, because you can consume a diet of
[13:12] Speaker 1: really excellent news and information, but if you're constantly processing
[13:16] Speaker 1: it in a very biased way, if you're really yearning
[13:19] Speaker 1: to each particular conclusion, you're still going to come out
[13:22] Speaker 1: thinking the wrong things. Can I end by just asking
[13:24] Speaker 1: what is the what is the one thing you want
[13:28] Speaker 1: people to take away from your book. If you are
[13:33] Speaker 1: curious about the world and you want to understand what
[13:37] Speaker 1: you're being told and how it fits into a bigger picture,
[13:41] Speaker 1: it's not that hard. Ask the right questions. Be open minded,
[13:46] Speaker 1: not too open minded, but be open minded and ask
[13:50] Speaker 1: whether what you're being told is making you smarter. When
[13:53] Speaker 1: you view information like that, rather than as a weapon
[13:57] Speaker 1: that might help you win some stupid argument, you're going
[14:00] Speaker 1: to be smarter about the world. Sim Harford is the
[14:03] Speaker 1: author of The Data Detective, which is out this week
[14:06] Speaker 1: in the US, and you can also catch him on
[14:08] Speaker 1: the Cautionary Tales podcast produced by our partners at Pushkin.
[14:12] Speaker 1: Tim thanks very much for being with us. I appreciate it.
[14:15] Speaker 1: Thank you, thank you.

Shows are listed from Apple Podcasts' charts and directory, and Podcast Index where it is used. Every show and episode belongs to its publisher and plays from the publisher's own feed; this site hosts none of them.