September 17, 2025 • 14 mins
How can investors find usable signal amidst all of the outrageous, algorithm-driven, clickbait? Noisy headlines can be a distraction from your long-term goals. Michael Hiltzik covers business for the Los Angeles Times, is a two-time winner of the Gerald Loeb Award and has authored numerous books on business. Each week, “At the Money” discusses an important topic in money management. From portfolio construction to taxes and cutting down on fees, join Barry Ritholtz to learn the best ways to put your money to work.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Bloomberg Audio studios, podcasts, radio news come on on the
US investor's face, a flood of noisy news, social media, TV, radio,
(00:31):
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 Pultzer Prize winning reporter Michael Hiltzik. He
covers business for the Los Angeles Times. He's a two
(00:52):
time winner of the Gerald Lobe Award, as well as
the author of numerous books on finance. Well, 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.
Speaker 2 (01:11):
Well, you know, it used to be said that that
newspaper readers know how to read their newspaper. You know,
they sort of, you know, assess what they see there,
you know, how it conforms to their own world views,
how it conforms to what they see in the outside
wide world of reality. And I think that's probably more
(01:34):
important now than it ever has been before. Newspaper reports
of data are always second order reports. Reporter who's looked
at the data, or an editor has dropped a page
or sent an email and said, you know, do something
(01:55):
on this report from this oud 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
(02:15):
number is it cooks up, and 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.
(02:37):
And I always ask, you know, if I'm calling a
lobbyists and saying, you know, you 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
they'll tell me. I just just one, you know, into
(02:58):
my email box, I think just the other day, and
I've asked but haven't gotten a reply. So that's that's
very important, and I think readers have to understand that
more than ever before. Certainly, you know more than in
my long career. Reporters are over worked. They don't have
(03:19):
the time to do their own work, 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
(03:44):
be able to do that.
Speaker 1 (03:45):
So that raises an obvious question, how do you tell
which sources are trustworthy? Who do you put on your
all star list? Who do you eliminate?
Speaker 2 (03:56):
Well, there are a few sources and economics sources where
are on my all star list? You know, you and
your folks you know because I quote you with some frequency.
There are other organizations that have shown, you know, through
the test of time, to have been to have integrity
and how they interpret data. Uh And and then there
(04:18):
are some where you just want to factor in what
you know about their ideology, their their their funders, their history,
and that just you know, those simple inquiries will tell
you a lot about how you want to assess information
that comes at you from all these sources.
Speaker 1 (04:41):
You mentioned reporters are pressed for time. So are investors.
You'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.
Speaker 2 (05:03):
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 an investment for you? And
(05:27):
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 col a little bit more closely
the next time. And I think that that's sort of
a good idea. More generally, you know, some reports will
(05:49):
be refuted or debunked fairly quickly, and some of these
sources will compile a record of inaccuracy or dishonesty, and
some will compile the record of reliability. And it takes time,
it takes attention, and I think investors, like readers and
(06:13):
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.
Speaker 1 (06:21):
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.
Speaker 2 (06:33):
How do you.
Speaker 1 (06:33):
Navigate through what is a compelling story? My Matthew friends
always say, and equals one? All right, so you have
not a data series, but that's one ancdote. How do
you manage that?
Speaker 2 (06:48):
That's right? And sometimes the end one is oneself? So yeah, well, look, basically,
I've always been sort of averse to men on the
street stories because you know, a man on the street
(07:09):
or a woman on the street that's that is that
is an an 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 of the last few years,
we saw a lot of interviews with families in which
(07:34):
they talked about how much they're spending on this or
that commodity or or product and got it totally wrong.
And 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 that's important to keep in mind.
(07:58):
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 were talking about, but sort of throwing in you know,
(08:20):
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. And we used to see that
when I was in Africa. You know, I could tell
you know, you know, the show for you know, sometimes
(08:42):
you know was labeled to hide. But yeah, so you
want to make sure that you know, if there's 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
(09:03):
own experiences, and that they sound plausible. So these are wrong.
You know, the sort of tests that we have to
conduct in our in our daily lives.
Speaker 1 (09:15):
What about social media? How do we avoid the worst
aspects of algorithmic height that seems to work its way
into mainstream media as well.
Speaker 2 (09:26):
Uh yeah, well, certainly mainstream media stories that rely on
social media sourcing very suspect social media. Look, you know,
I was always a fan of Twitter. I would I
still do, you know, I still am a fan. I
think Twitter, you know, for all its faults, still has
(09:50):
a critical mass that alternatives like Bousky just haven't quite reached. So,
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 my
(10:15):
tweet timeline and rely on sources on that platform that
that I had come to know. It's more and more
difficult now, and it's harder to uh sort of you know,
get rid of, you know, some of the straws. But
(10:36):
you know, there are websites that 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
you know, I get reinforcement where I need it, and
then there are some that I just ignore, you know,
(10:56):
I'm you know, I have more time to myself because
I'm not paying any attention to a lot of the stuff.
Speaker 1 (11:03):
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
(11:25):
stop spam and other junk stuff from coming through. All 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
(11:48):
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.
Speaker 2 (12:06):
Yeah, I should tell you that I am an AI skeptic.
I think, you know, 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 truth. Sure twenty five years ago now, and
(12:32):
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 to become better at at detecting AI creation or worse.
(12:52):
I think at the moment, there are giveaways that anyone
can see, you know, in the 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
(13:16):
craze in an 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, we're
going to say, what were we thinking? You know, why
(13:39):
did we spend any money on this?
Speaker 1 (13:41):
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 a and don't be afraid to follow people
(14:04):
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 Ridults. You're listening to Bloomberg's
at the Money
Bloomberg Audio studios, podcasts, radio news come on on the
US investor's face, a flood of noisy news, social media, TV, radio,
(00:31):
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 Pultzer Prize winning reporter Michael Hiltzik. He
covers business for the Los Angeles Times. He's a two
(00:52):
time winner of the Gerald Lobe Award, as well as
the author of numerous books on finance. Well, 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.
Speaker 2 (01:11):
Well, you know, it used to be said that that
newspaper readers know how to read their newspaper. You know,
they sort of, you know, assess what they see there,
you know, how it conforms to their own world views,
how it conforms to what they see in the outside
wide world of reality. And I think that's probably more
(01:34):
important now than it ever has been before. Newspaper reports
of data are always second order reports. Reporter who's looked
at the data, or an editor has dropped a page
or sent an email and said, you know, do something
(01:55):
on this report from this oud 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
(02:15):
number is it cooks up, and 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.
(02:37):
And I always ask, you know, if I'm calling a
lobbyists and saying, you know, you 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
they'll tell me. I just just one, you know, into
(02:58):
my email box, I think just the other day, and
I've asked but haven't gotten a reply. So that's that's
very important, and I think readers have to understand that
more than ever before. Certainly, you know more than in
my long career. Reporters are over worked. They don't have
(03:19):
the time to do their own work, 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
(03:44):
be able to do that.
Speaker 1 (03:45):
So that raises an obvious question, how do you tell
which sources are trustworthy? Who do you put on your
all star list? Who do you eliminate?
Speaker 2 (03:56):
Well, there are a few sources and economics sources where
are on my all star list? You know, you and
your folks you know because I quote you with some frequency.
There are other organizations that have shown, you know, through
the test of time, to have been to have integrity
and how they interpret data. Uh And and then there
(04:18):
are some where you just want to factor in what
you know about their ideology, their their their funders, their history,
and that just you know, those simple inquiries will tell
you a lot about how you want to assess information
that comes at you from all these sources.
Speaker 1 (04:41):
You mentioned reporters are pressed for time. So are investors.
You'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.
Speaker 2 (05:03):
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 an investment for you? And
(05:27):
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 col a little bit more closely
the next time. And I think that that's sort of
a good idea. More generally, you know, some reports will
(05:49):
be refuted or debunked fairly quickly, and some of these
sources will compile a record of inaccuracy or dishonesty, and
some will compile the record of reliability. And it takes time,
it takes attention, and I think investors, like readers and
(06:13):
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.
Speaker 1 (06:21):
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.
Speaker 2 (06:33):
How do you.
Speaker 1 (06:33):
Navigate through what is a compelling story? My Matthew friends
always say, and equals one? All right, so you have
not a data series, but that's one ancdote. How do
you manage that?
Speaker 2 (06:48):
That's right? And sometimes the end one is oneself? So yeah, well, look, basically,
I've always been sort of averse to men on the
street stories because you know, a man on the street
(07:09):
or a woman on the street that's that is that
is an an 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 of the last few years,
we saw a lot of interviews with families in which
(07:34):
they talked about how much they're spending on this or
that commodity or or product and got it totally wrong.
And 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 that's important to keep in mind.
(07:58):
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 were talking about, but sort of throwing in you know,
(08:20):
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. And we used to see that
when I was in Africa. You know, I could tell
you know, you know, the show for you know, sometimes
(08:42):
you know was labeled to hide. But yeah, so you
want to make sure that you know, if there's 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
(09:03):
own experiences, and that they sound plausible. So these are wrong.
You know, the sort of tests that we have to
conduct in our in our daily lives.
Speaker 1 (09:15):
What about social media? How do we avoid the worst
aspects of algorithmic height that seems to work its way
into mainstream media as well.
Speaker 2 (09:26):
Uh yeah, well, certainly mainstream media stories that rely on
social media sourcing very suspect social media. Look, you know,
I was always a fan of Twitter. I would I
still do, you know, I still am a fan. I
think Twitter, you know, for all its faults, still has
(09:50):
a critical mass that alternatives like Bousky just haven't quite reached. So,
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 my
(10:15):
tweet timeline and rely on sources on that platform that
that I had come to know. It's more and more
difficult now, and it's harder to uh sort of you know,
get rid of, you know, some of the straws. But
(10:36):
you know, there are websites that 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
you know, I get reinforcement where I need it, and
then there are some that I just ignore, you know,
(10:56):
I'm you know, I have more time to myself because
I'm not paying any attention to a lot of the stuff.
Speaker 1 (11:03):
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
(11:25):
stop spam and other junk stuff from coming through. All 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
(11:48):
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.
Speaker 2 (12:06):
Yeah, I should tell you that I am an AI skeptic.
I think, you know, 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 truth. Sure twenty five years ago now, and
(12:32):
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 to become better at at detecting AI creation or worse.
(12:52):
I think at the moment, there are giveaways that anyone
can see, you know, in the 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
(13:16):
craze in an 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, we're
going to say, what were we thinking? You know, why
(13:39):
did we spend any money on this?
Speaker 1 (13:41):
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 a and don't be afraid to follow people
(14:04):
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 Ridults. You're listening to Bloomberg's
at the Money
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