In this episode we talk about the growth of data use in the media and the potential impact of misinformation on the public's trust in official statistics.

Navigating podcast host Miles Fletcher through this minefield is Prof Sir David Spiegelhalter, from the University of Cambridge; Ed Humpherson, Head of the Office for Statistics Regulation; and award-winning data journalist Simon Rogers.

Transcript

MILES FLETCHER

Welcome again to Statistically Speaking, the official podcast of the UK's Office for National Statistics, I'm Miles Fletcher. Now we've talked many times before in these podcasts about the rise of data and its impact on our everyday lives. It's all around us of course, and not least in the media we consume every day. But 'what' or 'who' to trust: mainstream media, public figures and national institutions like the ONS, or those random strangers bearing gifts of facts and figures in our social media feeds?

To help us step carefully through the minefields of misinformation and on, we hope, to the terra firma of reliable statistical communication, we have three interesting and distinguished voices, each with a different perspective. Professor Sir David Spiegelhalter is a well-known voice to UK listeners. He's chair of the Winton Centre for Risk Evidence Communication at the University of Cambridge and was a very prominent voice on the interpretation of public health data here during the COVID pandemic. Also, we have Ed Humpherson, Director General of regulation and head of the Office for Statistics Regulation (OSR), the official stats watchdog if you like, and later in this podcast, I'll be joined by award winning data journalist and writer Simon Rogers, who now works as data editor at Google.

Professor, you've been one of the most prominent voices these last few years – a fascinating few years, obviously, for statistics in which we were told quite frankly, this was a golden age for statistics and data. I mean, reflecting on your personal experience as a prominent public voice in that debate, when it comes to statistics and data, to be very general, how well informed are we now as a public, or indeed, how ill-informed on statistics?

DAVID SPIEGELHALTER

I think things have improved after COVID. You know, for a couple of years we saw nothing but numbers and graphs on the news and in the newspapers and everywhere, and that went down very well. People didn't object to that. In fact, they wanted more. And I think that has led to an increased profile for data journalism, and there's some brilliant ones out there. I'm just thinking of John Burn-Murdoch on the FT but lots of others as well, who do really good work. Of course, in the mainstream media there is still the problem of non-specialists getting hold of data and getting it wrong, and dreadful clickbait headlines. It is the sub editors that wreck it all just by sticking some headline on what might be a decent story to get the attention and which is quite often misleading. So that's a standard problem. In social media, yeah, during COVID and afterwards, there are people I follow who you might consider as - I wouldn't say amateurs at all, but they're not professional pundits or media people - who just do brilliant stuff, and who I've learned so much from. There are also some terrible people out there, widespread misinformation claims which are based on data and sound convincing because they have got numbers in them. And that, I mean, it's not a new problem, but now it is widespread, and it's really tricky to counter and deal with, but very important indeed.

So the issue aside from - those of us who deal with the media have heard this a hundred times - "I don't write the headlines", reporters will tell you when you challenge that misleading kind of headline. But would you say it's the mainstream media then, because they can be called out on what they report, who broadly get things right? And that the challenge is everything else - it's out there in the Wild West of social media?

Yeah, mainstream media is not too bad, partly because, you know, we've got the BBC in this country, we've got regulations, and so it's not too bad. And social media, it's the Wild West. You know, there are people who really revel in using numbers and data to make inappropriate and misleading claims.

Is there anything that can be done? Is it the government, or even those of us like the ONS who produce statistics, who should we be wading in more than we do? Should we be getting out there onto the social media platforms and putting people right?

It's difficult I mean, I don't believe in sort of censorship. I don't think you can stop this at source at all. But just because people can say this, it doesn't give them a right for it to be broadcast wide, in a way and to be dumped into people's feeds. And so my main problem is with the recommendation algorithms of social media, where people will see things because it's getting clicks, and the right algorithm thinks persona will like it. And so we just get fed all this stuff. That is my real problem and the obscurity and the lack of accountability of recommendation algorithms right across social media is I think, a really shocking state of affairs. Of course, you know, we come on to this later, but we should be doing something about education, and actually sort of pre-empting some of the misunderstandings is something I feel very strongly about with my colleagues. You've got to get in there quick, and rather than being on the backfoot and just reacting to false claims that have been made, you've got to sort of realise how to take the initiative and to realise what misunderstandings, misinterpretations can be made, and get in there quickly to try to pre-empt them. But that of course comes down to the whole business of how ONS and others communicate their data.

Because when you ask the public whether they trust them - and the UK statistics authority does this every two years - you ask the public if they trust ONS statistics, and a large proportion of them say they do. But of course, if they're not being presented with those statistics, then they're still going to end up being misled.

Yeah, I mean, it's nice to get those responses back. But, you know...that's in terms of respondents and just asking a simple question, do you trust something or not? I think it's good to hear but we can't be complacent about that at all. I'm massively influenced by the approach of the philosopher, Baroness Onora O'Neill, who really makes a sharp distinction between organisations wanting to be trusted and revelling in being trusted, and she says that shouldn't be your objective to be trusted. Your objective should be to be trustworthy, to deserve trust, and then it might be offered up to you. And so the crucial thing is trustworthiness of the statistics system and in the communications, and that's what I love talking about, because I think it's absolutely important and it puts the responsibility really firmly back to the communicator to demonstrate trustworthiness.

So doing more as stats producers to actually actively promote data and get people to come perhaps away from the social platforms, and to have their own websites that present data in an accessible way, in an understandable way, where people can get it for nothing without requiring an expensive subscription or something, as some of the best of the media outlets would require.

The other thing I'd say is there's no point of being trustworthy if you're dull, as no one's going to look at it or take any notice, and other media aren't going to use it. So I think it's really worthwhile to invest, make a lot of effort to make what you're putting out there as attractive, as vivid and as grabbing as possible. The problem is that in trying to do that, I mean, that's what a lot of communicators and media people want to do, because of course they want people to read their stuff. But what that tends to do largely is make their stuff kind of opinionated and have a very strong line, essentially to persuade you to either do something or think something or buy something or vote something. So much communication has to do with...

Communicating Statistics: Crossing the minefields of misinformation.