At The Money: Filtering Noisy News

0:00I'm Hannah Fry, and as we rely more and more on artificial intelligence in every facet of our lives and businesses, I'm on a mission to find out how we can build the internet that AI needs. Learn more later in the podcast.

0:40Investors face a flood of noisy news, social media, TV, radio, and more. None of it is tailored to you in particular, and much of it appears to be outrageous, algo-driven clickbait. What's an investor supposed to do? To help us navigate this, let's bring in Pulitzer Prize-winning reporter Michael Hiltzik. He covers business for the Los Angeles Times. He's a two-time winner of the Gerald Loeb Award, as well as the author of numerous books on finance. So Michael, let's start with this endless sea of noise. How do you navigate this? How do you prioritize what's important and what's not? Well, it used to be said that newspaper readers know how to read their newspaper.

1:32They sort of assess what they see there, how it conforms to their own worldviews, how it conforms to what they see in the outside wide world of reality. And I think that's probably more important now than it ever has been before. Newspaper reports of data are always second order reports. A reporter who's looked at the data or an editor has dropped a page or sent an email and said, you know, do something on this report from this side or the other. And I think you always have to assess the source as we've talked about. You know, if we're talking about a trade organization, well, a trade organization is basically a PR organization and it's going to put its own spin on whatever numbers it cooks up.

2:32And sometimes it puts spin on numbers even before they're cooked up. If a trade organization is citing a study from a supposedly independent group, I want to know if they commissioned the study or who commissioned it. And that's a mixture part of my assessment. And I always ask, you know, if I'm calling lobbyists and saying, you know, just cited this, you know, supposedly third-party analysis, you know, is it yours? Did you commission this? And, you know, if they're honest, they'll tell me. I just, it was just one, you know, into my email box, I think just the other day, and I've asked but haven't gotten a reply.

3:18So that's very important. And I think readers have to understand that more than ever before, certainly more than in my long career, reporters are overworked. They don't have the time to do their homework, so they will basically take a press release from some data source and parrot it, regurgitate it. So I think it's important for readers to do what I do, which is to check the source, and if they can, go to the raw material and make a judgment for themselves. Intelligent investors should be able to do that. So that raises an obvious question. How do you tell which sources are trustworthy? Who do you put on your all-star list?

4:09Who do you eliminate? Well, there are a few sources, economic sources who are on my all-star list. You and your folks, you know, because I quote you with some frequency. There are other organizations that have shown through the test of time to have integrity in how they interpret data. And then there were some where you just want to factor in what you know about their ideology, their funders, their history. And those simple inquiries will tell you a lot about how you want to assess information that comes at you from all these sources. You mentioned reporters are pressed for time, so are investors.

5:00You're kind of hinting at, hey, this requires some time, effort, and work in order to figure out what is a credible source of reliable news and what is a little more, let's just call it unreliable. Well, you know, I think I remember, you know, reading Andy Tobias's book, you know, probably one of its earliest incarnations, where he said, you know, what do you do if a broker comes to you, you know, cold call or someone you know, and pitches is an investment for you. And what his advice was to say, well, you know, don't invest in that investment, but see how it does. And if it's done well, then maybe you want to listen to this guy or Cal a little bit more closely the next time.

5:55And I think that that's sort of a good idea more generally. You know, some reports will be refuted or debunked fairly quickly. And some of these sources will compile a record of inaccuracy or dishonesty. And some will compile a record of reliability. And it takes time. It takes attention. And I think investors like readers and reporters need to do their homework. And we just see that being more and more difficult or just happening a lot less than it used to. I've been noticing what, at least to me, it seems like more than ever, anecdotes and one-off stories and narrative tales, they just seem to be increasingly popular.

6:47How do you navigate through what is a compelling story? my mathy friends always say n equals one all right so you have not a data series but that's one anecdote how do you how do you manage that uh that's right and sometimes the the n1 is is oneself so yeah well um look basically um i've always been sort of averse to man on the street stories because, you know, a man on the street or a woman on the street, that is an N equals one. And you really have no idea what, you can't really always tell what questions have been asked, what this person knows. We've certainly seen, you know, certainly during the inflation era under the last few years, we saw a lot of interviews with families in which they talked about how much they're spending on this or that commodity or produce and got it totally wrong.

8:00And so I think that people can sort of compare what they're reading to their own experience. And if it's really at odds, that's important to keep in mind. So I think, I mean, I've gone, you know, I've been assigned to do man on the street stories, but, you know, when they work, it's because you have a narrow subject and you are dealing with people who are in a position to know the answers to the questions you are talking about. But sort of throwing in, you know, somebody who's standing online or, you know, I used to say I was always suspicious of stories that quoted the driver who brought the reporter from the airport to the first class hotel in town.

8:50And we used to see that when I was in Africa, you know, I could tell, you know, the chauffeur, you know, sometimes, you know, was labeled to hide. But yeah, so you want to make sure that, you know, if there are interviews with individuals or families or couples, that there's more than one and that they seem to actually know what they're talking about. And they're talking about their own experiences and that they sound plausible. So these are all sort of tests that we have to conduct in our daily lives. What about social media? How do we avoid the worst aspects of algorithmic hype that seems to work its way into mainstream media as well?

9:41Yeah, well, certainly mainstream media stories that rely on social media sourcing, very suspect. um social media um look you know i was always a fan of twitter uh i i would i still do you know i still am a fan i think twitter you know for all its faults still has a critical mass that alternatives like um uh blue sky just haven't quite reached um so uh you know with with x as we call it, I think you can sort of wean out the wild nonsense. I always liked X because I could curate my tweet timeline and rely on sources on that platform that I had come to know. it's more and more difficult now and it's harder to sort of get rid of some of the straws.

10:49But there are websites that I go back to over and over again. They're not all economic websites. Sometimes they're writers who think the way I do. So I get reinforcement where I need it. And then there are some that I just ignore. I have more time to myself because I'm not paying any attention to a lot of the stuff. Yeah. I found on Twitter, curating your own lists on different topics. For me, it's the economy, it's data and analytics, it's behavioral finance. There are experts out there talking about subjects that I like. And at least it's, there's some filtering process by creating a list. It's not going to stop spam and other junk stuff from coming through.

11:44All right. So we're talking about social media. I guess if we're talking about news and problems, we have to discuss AI, not just the hallucination, but the risk that that news story you're reading is literally fake news, just something created by AI cheaply, how do we navigate a world where AI is cranking out a lot of artificial intelligence, is cranking out a lot of news that isn't exactly following the rules of journalism? Yeah, I should tell you that I am an AI skeptic. I think some large percentage of AI claims by developers and by clients is marketing in the same way that, you know, dot-com used to be the big marketing trope 25 years ago now.

12:46And so a lot of what is pitched as AI is not really AI and none of it is intelligence. I'm not sure, I'm of two minds about whether people are going going to become better at detecting AI creation or worse. I think at the moment, there are giveaways that anyone can see, you know, sometimes in the language that's used, sometimes in the images that are created. We see this over and over again, just, you know, clearly AI hallucinations. so you know right now there's an AI craze in in industry and including in the news industry and I think that's going to be a problem I think it's going to go bad and I think you know relying on AI is going to be something that you know when we look at it in the rearview mirror were going to say, what were we thinking?

13:54Why did we spend any money on this? So to wrap up, apply common sense to your consumption of news, figure out who's trustworthy, what sources are accurate, put the time and effort in to identifying who's worthy of your time and trust. Beware of social media, be wary of AI, and don't be afraid to follow people who have bylines that you trust rather than just blindly paying attention to any particular media source. It's worth understanding what you're consuming and why and staying on the right side of accuracy. I'm Barry Ritholtz. You're listening to Bloomberg's At The Money.