1 00:00:02,520 --> 00:00:25,200 Speaker 1: Bloomberg Audio studios, podcasts, radio news come on on the 2 00:00:13,280 --> 00:00:31,200 Speaker 1: US investor's face, a flood of noisy news, social media, TV, radio, 3 00:00:31,480 --> 00:00:35,280 Speaker 1: and more. None of it is tailored to you in particular, 4 00:00:35,800 --> 00:00:40,520 Speaker 1: and much of it appears to be outrageous algo driven clickbait. 5 00:00:41,080 --> 00:00:45,280 Speaker 1: What's an investor supposed to do to help us navigate this? 6 00:00:45,680 --> 00:00:49,239 Speaker 1: Let's bring in Pultzer Prize winning reporter Michael Hiltzik. He 7 00:00:49,440 --> 00:00:52,479 Speaker 1: covers business for the Los Angeles Times. He's a two 8 00:00:52,600 --> 00:00:56,160 Speaker 1: time winner of the Gerald Lobe Award, as well as 9 00:00:56,200 --> 00:01:01,680 Speaker 1: the author of numerous books on finance. Well, Michael, let's 10 00:01:01,760 --> 00:01:05,600 Speaker 1: start with this endless sea of noise. How do you 11 00:01:05,680 --> 00:01:09,319 Speaker 1: navigate this? How do you prioritize what's important and what's not. 12 00:01:11,000 --> 00:01:13,720 Speaker 2: Well, you know, it used to be said that that 13 00:01:14,000 --> 00:01:17,120 Speaker 2: newspaper readers know how to read their newspaper. You know, 14 00:01:17,160 --> 00:01:21,280 Speaker 2: they sort of, you know, assess what they see there, 15 00:01:21,800 --> 00:01:25,000 Speaker 2: you know, how it conforms to their own world views, 16 00:01:25,520 --> 00:01:29,080 Speaker 2: how it conforms to what they see in the outside 17 00:01:29,480 --> 00:01:34,840 Speaker 2: wide world of reality. And I think that's probably more 18 00:01:34,880 --> 00:01:40,520 Speaker 2: important now than it ever has been before. Newspaper reports 19 00:01:41,720 --> 00:01:49,160 Speaker 2: of data are always second order reports. Reporter who's looked 20 00:01:49,160 --> 00:01:53,120 Speaker 2: at the data, or an editor has dropped a page 21 00:01:53,160 --> 00:01:55,720 Speaker 2: or sent an email and said, you know, do something 22 00:01:55,760 --> 00:02:00,160 Speaker 2: on this report from this oud or the other. And 23 00:02:00,240 --> 00:02:04,080 Speaker 2: I think you always have to assess the source. As 24 00:02:04,160 --> 00:02:07,640 Speaker 2: we've talked about, you know, if we're talking about a 25 00:02:07,680 --> 00:02:13,120 Speaker 2: trade organization, well, a trade organization is basically a pr organization, 26 00:02:13,200 --> 00:02:15,880 Speaker 2: and it's going to put its own spin on whatever 27 00:02:15,960 --> 00:02:18,359 Speaker 2: number is it cooks up, and sometimes it puts spin 28 00:02:18,440 --> 00:02:22,520 Speaker 2: on numbers even before they're cooked up. If a trade 29 00:02:22,639 --> 00:02:27,960 Speaker 2: organization is citing a study from a supposedly independent group, 30 00:02:28,560 --> 00:02:30,960 Speaker 2: I want to know if they commissioned the study or 31 00:02:31,000 --> 00:02:37,520 Speaker 2: who commissioned it. And that's a mixture part of my assessment. 32 00:02:37,880 --> 00:02:41,040 Speaker 2: And I always ask, you know, if I'm calling a 33 00:02:41,400 --> 00:02:44,640 Speaker 2: lobbyists and saying, you know, you just cited this, you know, 34 00:02:44,680 --> 00:02:50,799 Speaker 2: supposedly third party analysis, you know, is it yours? Did 35 00:02:50,800 --> 00:02:53,320 Speaker 2: you commission this? And you know, if they're honest, they'll 36 00:02:53,880 --> 00:02:58,000 Speaker 2: they'll tell me. I just just one, you know, into 37 00:02:58,040 --> 00:03:00,200 Speaker 2: my email box, I think just the other day, and 38 00:03:00,919 --> 00:03:04,880 Speaker 2: I've asked but haven't gotten a reply. So that's that's 39 00:03:05,040 --> 00:03:08,520 Speaker 2: very important, and I think readers have to understand that 40 00:03:08,800 --> 00:03:12,600 Speaker 2: more than ever before. Certainly, you know more than in 41 00:03:12,680 --> 00:03:19,880 Speaker 2: my long career. Reporters are over worked. They don't have 42 00:03:19,919 --> 00:03:23,239 Speaker 2: the time to do their own work, so they will 43 00:03:23,280 --> 00:03:28,919 Speaker 2: basically take a press release from some data source and 44 00:03:29,639 --> 00:03:35,560 Speaker 2: parrot it regurgitate it. So I think it's important for 45 00:03:35,680 --> 00:03:37,600 Speaker 2: readers to do what I do, which is to check 46 00:03:37,600 --> 00:03:39,600 Speaker 2: the source and if they can go to the raw 47 00:03:39,720 --> 00:03:44,040 Speaker 2: material and make a judgment for themselves, intelligent investors should 48 00:03:44,040 --> 00:03:44,680 Speaker 2: be able to do that. 49 00:03:45,200 --> 00:03:48,800 Speaker 1: So that raises an obvious question, how do you tell 50 00:03:49,400 --> 00:03:53,080 Speaker 1: which sources are trustworthy? Who do you put on your 51 00:03:53,120 --> 00:03:55,280 Speaker 1: all star list? Who do you eliminate? 52 00:03:56,720 --> 00:03:59,880 Speaker 2: Well, there are a few sources and economics sources where 53 00:03:59,880 --> 00:04:02,120 Speaker 2: are on my all star list? You know, you and 54 00:04:02,320 --> 00:04:06,200 Speaker 2: your folks you know because I quote you with some frequency. 55 00:04:07,160 --> 00:04:10,440 Speaker 2: There are other organizations that have shown, you know, through 56 00:04:10,480 --> 00:04:14,040 Speaker 2: the test of time, to have been to have integrity 57 00:04:14,120 --> 00:04:18,440 Speaker 2: and how they interpret data. Uh And and then there 58 00:04:18,440 --> 00:04:23,240 Speaker 2: are some where you just want to factor in what 59 00:04:23,320 --> 00:04:30,599 Speaker 2: you know about their ideology, their their their funders, their history, 60 00:04:30,880 --> 00:04:34,880 Speaker 2: and that just you know, those simple inquiries will tell 61 00:04:34,880 --> 00:04:38,080 Speaker 2: you a lot about how you want to assess information 62 00:04:38,200 --> 00:04:41,480 Speaker 2: that comes at you from all these sources. 63 00:04:41,160 --> 00:04:45,200 Speaker 1: You mentioned reporters are pressed for time. So are investors. 64 00:04:45,920 --> 00:04:51,599 Speaker 1: You're kind of hinting at hey, this requires some time, effort, 65 00:04:51,800 --> 00:04:55,039 Speaker 1: and work in order to figure out what is a 66 00:04:55,160 --> 00:04:59,560 Speaker 1: credible source of reliable news and what is a little 67 00:04:59,680 --> 00:05:02,480 Speaker 1: more let's just call it unreliable. 68 00:05:03,920 --> 00:05:07,640 Speaker 2: Well, you know, I think I remember, you know, reading 69 00:05:08,400 --> 00:05:12,920 Speaker 2: Andy Tobias's book, you know, probably one of its earliest incarnations, 70 00:05:13,640 --> 00:05:16,000 Speaker 2: where he said, you know, what do you do if 71 00:05:16,400 --> 00:05:19,040 Speaker 2: a broker comes to you, you know, cold call or 72 00:05:19,240 --> 00:05:26,880 Speaker 2: someone you know and pitches an investment for you? And 73 00:05:27,080 --> 00:05:29,760 Speaker 2: what his advice was to say, well, you know, don't 74 00:05:29,839 --> 00:05:32,760 Speaker 2: invest in that investment, but see how it does. And 75 00:05:32,839 --> 00:05:34,840 Speaker 2: if it's done well, then maybe you want to listen 76 00:05:34,880 --> 00:05:39,480 Speaker 2: to this guy or col a little bit more closely 77 00:05:39,960 --> 00:05:43,120 Speaker 2: the next time. And I think that that's sort of 78 00:05:43,160 --> 00:05:49,760 Speaker 2: a good idea. More generally, you know, some reports will 79 00:05:49,800 --> 00:05:56,840 Speaker 2: be refuted or debunked fairly quickly, and some of these 80 00:05:56,880 --> 00:06:02,599 Speaker 2: sources will compile a record of inaccuracy or dishonesty, and 81 00:06:02,720 --> 00:06:06,880 Speaker 2: some will compile the record of reliability. And it takes time, 82 00:06:07,080 --> 00:06:12,920 Speaker 2: it takes attention, and I think investors, like readers and 83 00:06:13,040 --> 00:06:15,440 Speaker 2: reporters need to do their homework and we just see 84 00:06:15,480 --> 00:06:18,919 Speaker 2: that being more and more difficult, or just happening a 85 00:06:18,960 --> 00:06:20,880 Speaker 2: lot less than it used to. 86 00:06:21,960 --> 00:06:25,039 Speaker 1: I've been noticing what, at least to me, it seems 87 00:06:25,080 --> 00:06:29,640 Speaker 1: like more than ever, anecdotes and one off stories and 88 00:06:29,800 --> 00:06:32,680 Speaker 1: narrative tales. They just seem to be increasingly popular. 89 00:06:33,040 --> 00:06:33,480 Speaker 2: How do you. 90 00:06:33,520 --> 00:06:39,359 Speaker 1: Navigate through what is a compelling story? My Matthew friends 91 00:06:39,440 --> 00:06:42,680 Speaker 1: always say, and equals one? All right, so you have 92 00:06:42,920 --> 00:06:47,440 Speaker 1: not a data series, but that's one ancdote. How do 93 00:06:47,480 --> 00:06:48,920 Speaker 1: you manage that? 94 00:06:48,920 --> 00:07:00,000 Speaker 2: That's right? And sometimes the end one is oneself? So yeah, well, look, basically, 95 00:07:02,120 --> 00:07:04,800 Speaker 2: I've always been sort of averse to men on the 96 00:07:04,839 --> 00:07:09,120 Speaker 2: street stories because you know, a man on the street 97 00:07:09,200 --> 00:07:11,080 Speaker 2: or a woman on the street that's that is that 98 00:07:11,200 --> 00:07:14,440 Speaker 2: is an an equals one, and you really have no 99 00:07:14,560 --> 00:07:18,160 Speaker 2: idea what You can't really always tell what questions have 100 00:07:18,440 --> 00:07:22,640 Speaker 2: been asked, what this person knows. We've certainly seen, you know, 101 00:07:22,760 --> 00:07:28,920 Speaker 2: certainly during the inflation era under of the last few years, 102 00:07:29,000 --> 00:07:34,160 Speaker 2: we saw a lot of interviews with families in which 103 00:07:34,320 --> 00:07:36,840 Speaker 2: they talked about how much they're spending on this or 104 00:07:36,880 --> 00:07:43,239 Speaker 2: that commodity or or product and got it totally wrong. 105 00:07:45,080 --> 00:07:50,320 Speaker 2: And so I think that people can sort of compare 106 00:07:50,480 --> 00:07:53,480 Speaker 2: what they're reading to their own experience and if it's 107 00:07:53,600 --> 00:07:57,840 Speaker 2: really at odds that that's important to keep in mind. 108 00:07:58,160 --> 00:08:02,120 Speaker 2: So I think, I mean, I've gone, you know, I've 109 00:08:02,120 --> 00:08:05,400 Speaker 2: been assigned to do man on the street stories. But 110 00:08:06,560 --> 00:08:09,080 Speaker 2: you know, when they work, it's because you have a 111 00:08:09,160 --> 00:08:13,320 Speaker 2: narrow subject and you are dealing with people who are 112 00:08:13,320 --> 00:08:16,320 Speaker 2: in a position to know the answers to the questions 113 00:08:16,520 --> 00:08:20,360 Speaker 2: you were talking about, but sort of throwing in you know, 114 00:08:20,480 --> 00:08:24,440 Speaker 2: somebody who's standing online or you know, I used to say, 115 00:08:24,480 --> 00:08:30,280 Speaker 2: I was always suspicious of stories that quoted the driver 116 00:08:30,480 --> 00:08:34,319 Speaker 2: who brought the reporter from the airport to the first 117 00:08:34,320 --> 00:08:36,319 Speaker 2: class hotel in town. And we used to see that 118 00:08:36,679 --> 00:08:38,680 Speaker 2: when I was in Africa. You know, I could tell 119 00:08:39,320 --> 00:08:42,400 Speaker 2: you know, you know, the show for you know, sometimes 120 00:08:42,440 --> 00:08:48,280 Speaker 2: you know was labeled to hide. But yeah, so you 121 00:08:48,360 --> 00:08:51,120 Speaker 2: want to make sure that you know, if there's if 122 00:08:51,120 --> 00:08:56,000 Speaker 2: there are interviews with individuals or families or couples, that 123 00:08:56,160 --> 00:09:00,000 Speaker 2: there's more than one and that they seem to actually 124 00:09:00,360 --> 00:09:03,679 Speaker 2: know what they're talking about and they're talking about their 125 00:09:03,720 --> 00:09:09,240 Speaker 2: own experiences, and that they sound plausible. So these are wrong. 126 00:09:09,440 --> 00:09:12,080 Speaker 2: You know, the sort of tests that we have to 127 00:09:12,120 --> 00:09:14,640 Speaker 2: conduct in our in our daily lives. 128 00:09:15,120 --> 00:09:18,400 Speaker 1: What about social media? How do we avoid the worst 129 00:09:18,440 --> 00:09:23,320 Speaker 1: aspects of algorithmic height that seems to work its way 130 00:09:23,360 --> 00:09:26,559 Speaker 1: into mainstream media as well. 131 00:09:26,760 --> 00:09:30,640 Speaker 2: Uh yeah, well, certainly mainstream media stories that rely on 132 00:09:30,720 --> 00:09:40,240 Speaker 2: social media sourcing very suspect social media. Look, you know, 133 00:09:40,360 --> 00:09:44,200 Speaker 2: I was always a fan of Twitter. I would I 134 00:09:44,280 --> 00:09:46,520 Speaker 2: still do, you know, I still am a fan. I 135 00:09:46,559 --> 00:09:50,480 Speaker 2: think Twitter, you know, for all its faults, still has 136 00:09:50,520 --> 00:10:00,080 Speaker 2: a critical mass that alternatives like Bousky just haven't quite reached. So, 137 00:10:00,600 --> 00:10:04,120 Speaker 2: you know, with with X as we call it, I 138 00:10:04,160 --> 00:10:08,119 Speaker 2: think you can sort of wean out the wild nonsense. 139 00:10:10,000 --> 00:10:15,320 Speaker 2: I always liked X because I could curate my my 140 00:10:15,679 --> 00:10:24,160 Speaker 2: tweet timeline and rely on sources on that platform that 141 00:10:24,160 --> 00:10:26,360 Speaker 2: that I had come to know. It's more and more 142 00:10:26,360 --> 00:10:30,880 Speaker 2: difficult now, and it's harder to uh sort of you know, 143 00:10:30,960 --> 00:10:34,480 Speaker 2: get rid of, you know, some of the straws. But 144 00:10:36,480 --> 00:10:40,000 Speaker 2: you know, there are websites that that I go back 145 00:10:40,040 --> 00:10:42,880 Speaker 2: to over and over again. They're not all economic websites. 146 00:10:42,920 --> 00:10:48,320 Speaker 2: Sometimes they're writers who think the way I do. So 147 00:10:48,720 --> 00:10:52,880 Speaker 2: you know, I get reinforcement where I need it, and 148 00:10:52,920 --> 00:10:56,800 Speaker 2: then there are some that I just ignore, you know, 149 00:10:56,920 --> 00:10:59,200 Speaker 2: I'm you know, I have more time to myself because 150 00:10:59,480 --> 00:11:02,960 Speaker 2: I'm not paying any attention to a lot of the stuff. 151 00:11:03,160 --> 00:11:06,880 Speaker 1: Yeah, I found on Twitter curating your own lists on 152 00:11:06,960 --> 00:11:11,800 Speaker 1: different topics. For me, it's the economy, it's data and analytics, 153 00:11:12,240 --> 00:11:17,120 Speaker 1: it's behavioral finance. There are experts out there talking about 154 00:11:17,200 --> 00:11:22,400 Speaker 1: subjects that I like, and at least it's there's some 155 00:11:22,480 --> 00:11:25,480 Speaker 1: filtering process by creating a list, it's not going to 156 00:11:25,559 --> 00:11:29,760 Speaker 1: stop spam and other junk stuff from coming through. All right, 157 00:11:29,800 --> 00:11:32,600 Speaker 1: So we're talking about social media. I guess if we're 158 00:11:32,640 --> 00:11:37,120 Speaker 1: talking about news and problems, we have to discuss AI, 159 00:11:38,000 --> 00:11:42,240 Speaker 1: not just the hallucination, but the risk that that news 160 00:11:42,280 --> 00:11:48,200 Speaker 1: story you're reading is literally fake news, just something created 161 00:11:48,800 --> 00:11:53,600 Speaker 1: by AI cheaply. How do we navigate a world where 162 00:11:53,800 --> 00:11:57,880 Speaker 1: AI is cranking out a lot of artificial intelligence is 163 00:11:58,160 --> 00:12:03,640 Speaker 1: cranking out a lot of news that isn't exactly following 164 00:12:03,679 --> 00:12:06,640 Speaker 1: the rules of journalism. 165 00:12:06,880 --> 00:12:10,280 Speaker 2: Yeah, I should tell you that I am an AI skeptic. 166 00:12:11,280 --> 00:12:16,160 Speaker 2: I think, you know, some large percentage of AI claims 167 00:12:16,280 --> 00:12:23,840 Speaker 2: by developers and by clients is marketing in the same 168 00:12:23,880 --> 00:12:26,160 Speaker 2: way that you know dot Com used to be the 169 00:12:26,200 --> 00:12:32,240 Speaker 2: big marketing truth. Sure twenty five years ago now, and 170 00:12:32,320 --> 00:12:34,440 Speaker 2: so a lot of what is pitched as AI is 171 00:12:34,480 --> 00:12:39,920 Speaker 2: not really AI, and none of it is intelligence. I'm 172 00:12:39,960 --> 00:12:44,240 Speaker 2: not sure. I'm of two minds about whether people are 173 00:12:44,280 --> 00:12:52,720 Speaker 2: going to become better at at detecting AI creation or worse. 174 00:12:52,920 --> 00:12:58,840 Speaker 2: I think at the moment, there are giveaways that anyone 175 00:12:58,880 --> 00:13:02,960 Speaker 2: can see, you know, in the sometimes in the language 176 00:13:03,000 --> 00:13:06,839 Speaker 2: that's used, sometimes in the images that are created. We 177 00:13:06,920 --> 00:13:09,760 Speaker 2: see this over and over again, just you know, clearly 178 00:13:10,120 --> 00:13:16,559 Speaker 2: AI hallucinations. So you know, right now there's an AI 179 00:13:16,760 --> 00:13:21,000 Speaker 2: craze in an industry and including in the news industry, 180 00:13:21,720 --> 00:13:25,760 Speaker 2: and I think that's going to be a problem. I 181 00:13:25,800 --> 00:13:30,120 Speaker 2: think it's going to go bad. And I think, you know, 182 00:13:31,280 --> 00:13:34,880 Speaker 2: relying on AI is going to be something that you know, 183 00:13:34,920 --> 00:13:36,600 Speaker 2: when we look at it in the rearview mirror, we're 184 00:13:36,600 --> 00:13:39,400 Speaker 2: going to say, what were we thinking? You know, why 185 00:13:39,480 --> 00:13:41,040 Speaker 2: did we spend any money on this? 186 00:13:41,360 --> 00:13:45,520 Speaker 1: So to wrap up, apply common sense to your consumption 187 00:13:45,679 --> 00:13:50,200 Speaker 1: of news. Figure out who's trustworthy, what sources are accurate. 188 00:13:50,760 --> 00:13:54,680 Speaker 1: Put the time and effort in to identifying who's worthy 189 00:13:54,800 --> 00:13:58,560 Speaker 1: of your time and trust. Beware of social media, be 190 00:13:58,720 --> 00:14:03,400 Speaker 1: wary of a and don't be afraid to follow people 191 00:14:04,400 --> 00:14:07,800 Speaker 1: who have bylines that you trust, rather than just blindly 192 00:14:08,360 --> 00:14:14,040 Speaker 1: paying attention to any particular media source. It's worth understanding 193 00:14:14,160 --> 00:14:17,320 Speaker 1: what you're consuming and why, and staying on the right 194 00:14:17,360 --> 00:14:21,960 Speaker 1: side of accuracy. I'm Barry Ridults. You're listening to Bloomberg's 195 00:14:22,520 --> 00:14:30,240 Speaker 1: at the Money