SPEAKER_1: At least somebody is trying to fix the news.
SPEAKER_2: About time.
SPEAKER_1: And we got them on this show.
SPEAKER_2: Yes.
SPEAKER_2: Where else are you going to hear about it?
SPEAKER_2: Where else are you going to see this?
SPEAKER_1: I don't know, because we just try to deal in objective truth.
SPEAKER_2: I know.
SPEAKER_2: We'll look at the biases, and why, where, how.
SPEAKER_2: Who's doing it, who's not?
SPEAKER_1: We are all in here on StarTalk, special edition coming up.
SPEAKER_1: Welcome to StarTalk, your place in the universe where science and pop culture collide.
SPEAKER_1: StarTalk begins right now.
SPEAKER_1: This is StarTalk, special edition.
SPEAKER_2: How about that?
SPEAKER_1: Neil deGrasse Tyson here right next to Gary O'Reilly.
SPEAKER_1: When you see Gary, it is special.
SPEAKER_1: Today, we're talking about a very important subject.
SPEAKER_2: Yeah.
SPEAKER_1: The news.
SPEAKER_2: Yeah, it was something we've been wanting to come to grips with for a while now.
SPEAKER_1: Who would have thought that you'd have to talk about that?
SPEAKER_1: When I grew up, the news was just the news and you went on about your life.
SPEAKER_2: You watched the news and then you went to the real TV when you were growing up as a kid.
SPEAKER_2: This news thing got in the way.
SPEAKER_1: Right, yeah, the news was like, yeah, I don't need this.
SPEAKER_2: See, now it seems we live in a constant need for news.
SPEAKER_2: It's not just on the hour, it's every hour, 24 hours a day.
SPEAKER_1: I would say that it's a desire for news, but a strong enough desire becomes a need.
SPEAKER_1: That's what I think is going on right here.
SPEAKER_2: I mean, just have to think about the number of news channels there are on TV, if TV even exists anymore.
SPEAKER_2: Then there's online, there's social media platforms.
SPEAKER_1: But not just how many are there, how many hours a day they broadcast news.
SPEAKER_2: Oh gosh, yeah.
SPEAKER_2: I mean, it does fold out into a larger number.
SPEAKER_2: I mean, throw in the unfiltered influences, and then the news landscape will and can look a bit of a mess.
SPEAKER_2: We all have our trusted news preferences, our go-tos, and as I've said before, the better the information, the better the decisions.
SPEAKER_1: That you're going to make based on that information.
SPEAKER_2: Exactly, right?
SPEAKER_2: But do we know if these new sources bring their own filters or their own biases?
SPEAKER_2: It's not always obvious to see from the outside or just by a headline.
SPEAKER_2: Sometimes it is by the headline.
SPEAKER_2: This is where our guest comes in, Neil.
SPEAKER_2: So if you would introduce them, please.
SPEAKER_1: I'd be delighted to.
SPEAKER_1: Yes, we have with us Harleen Kaur.
SPEAKER_1: Harleen, welcome to StarTalk.
SPEAKER_3: Thanks, Neil.
SPEAKER_3: Delighted to be here.
SPEAKER_1: Excellent, and you're in from Canada.
SPEAKER_3: That's right.
SPEAKER_1: Canada, the 51st state.
SPEAKER_3: That's right, we have no water.
SPEAKER_2: Do you know how to do that?
SPEAKER_3: Where did you read that, Neil?
SPEAKER_1: I don't know.
SPEAKER_1: Some news source told me that that's what it was.
SPEAKER_3: That happened?
SPEAKER_1: Co-founder and CEO, I got it here, of Ground News.
SPEAKER_2: All right.
SPEAKER_1: Are you grounded?
SPEAKER_1: Grounded means you have an objective understanding of reality, in any language, I'm pretty sure, because the ground is the ground.
SPEAKER_1: You're a former engineer?
SPEAKER_3: That's right.
SPEAKER_1: And what kind of engineer?
SPEAKER_3: A space engineer.
SPEAKER_3: Space?
SPEAKER_3: Loving it.
SPEAKER_2: In the right place.
SPEAKER_1: Yes, yes.
SPEAKER_3: So big fun, Neil.
SPEAKER_1: Okay, thank you.
SPEAKER_1: You are trying to fix the news problem, not by giving it a bias of your own, but by figuring out a way to de-bias it.
SPEAKER_3: That's right.
SPEAKER_1: In some objective way that people around the table could say, hey, I see what you did there.
SPEAKER_1: And we kind of all agree, no matter what side of the aisle you're on.
SPEAKER_1: As Gary said, if I have what I would consider a trusted source of news, and what you do to the news makes it look different from that, why should I have any confidence in all that you're doing the right thing?
SPEAKER_3: Yeah, that's a very good question.
SPEAKER_3: So let me try and explain what we do at Ground News.
SPEAKER_3: So we are not-
SPEAKER_1: No, there's no try.
SPEAKER_1: There's do or do not.
SPEAKER_3: I shall explain what we are doing at Ground News.
SPEAKER_3: So how we view news is that something happens, as you call the objective truth, something happens, and then it goes through this prism of the media landscape, and then it fragments into all these million of different versions of what exactly happens.
SPEAKER_3: And depending on where news outlets are on what the biases are, or what their agendas are, or who's funding them, who owns them, who is the audience that they don't want to piss off-
SPEAKER_1: And who's the sponsor?
SPEAKER_3: Who's the sponsor?
SPEAKER_3: Then they will tell you, although the event that they're reporting is the same event, but how they're reporting is going to be very, very different.
SPEAKER_3: And depending on what version you're reading, your perception of the reality of what happens is going to be very, very different to each other, to the point, yeah, using a space analogy, we are literally sometimes living in the different universes, depending on what news outlets or group of news-
SPEAKER_1: Yeah, the analogy totally works.
SPEAKER_3: Yeah, thank you.
SPEAKER_1: You've met people and say, what universe did you come from?
SPEAKER_3: Yeah, literally, did you?
SPEAKER_1: I've said that way too many times lately.
SPEAKER_3: Yeah, are we finding the same thing?
SPEAKER_3: So yeah, our job is not to say that this one's right or this one's wrong.
SPEAKER_3: And what we do is we literally reconstitute all of that, those versions together to reverse engineer what might have happened.
SPEAKER_3: So we'll show.
SPEAKER_1: Whoa!
SPEAKER_2: It's a new take on it.
SPEAKER_1: That's badass.
SPEAKER_3: Yeah.
SPEAKER_2: So what criteria?
SPEAKER_1: But let them finish their things.
SPEAKER_1: You just used the word reverse engineering.
SPEAKER_1: Let that sentence finish.
SPEAKER_2: The engineer said reverse engineering.
SPEAKER_2: What a surprise.
SPEAKER_3: Yeah.
SPEAKER_3: I hope it doesn't become scientists versus the engineer here.
SPEAKER_3: No, no, no.
SPEAKER_1: Not for this interview.
SPEAKER_1: Otherwise, meet me outside.
SPEAKER_1: We'll talk about it.
SPEAKER_3: No.
SPEAKER_3: I give up.
SPEAKER_3: We put all those sources together.
SPEAKER_3: So let's say, yeah, there is some executive order that has passed and there's a new story saying, hey, this is the headline and this is what happened.
SPEAKER_3: We will show you along the spectrum of how the different news sources cover it, all the way from the far left to the far right.
SPEAKER_3: And then we don't put any check marks or Xs against any of them.
SPEAKER_3: We very much let you decide where the truth kind of gets reconstituted and you use your critical thinking to put that together.
SPEAKER_1: You use your critical thinking?
SPEAKER_3: Yes.
SPEAKER_1: What does that presume?
SPEAKER_3: Yes.
SPEAKER_1: Where's the big assumption there?
SPEAKER_3: You're absolutely right.
SPEAKER_2: Or you should use your critical thinking.
SPEAKER_3: Which is a skill we are all losing.
SPEAKER_3: It's interesting you say that.
SPEAKER_3: Yeah.
SPEAKER_2: How it's more herd mentality then?
SPEAKER_3: It's herd mentality but also I think we're becoming lazy a bit because I feel like we like to be intellectually lazy because it's great to hear somebody else talk about what they think about it or what their opinion is about something and then regurgitate it rather than using your own brain to be able to say it because it takes effort to be able to do that.
SPEAKER_3: I'll just pick one guy, one girl, one sub stack, one podcast, one newsletter, one news channel, whatever it is and then just follow the one that I agree with and reinforces my cognitive bias.
SPEAKER_2: So the psychology of the news and how it's absorbed, how it's portrayed is now much, much deeper than you and I growing up.
SPEAKER_2: Oh, there's a nice guy in a suit and a tie and he's reading the stories from the day at 6 p.m.
SPEAKER_2: And then we moved on.
SPEAKER_3: There are a couple of reasons why that's not the case anymore.
SPEAKER_3: So one is there was a doctrine called fairness doctrine.
SPEAKER_3: If you've heard of that, that came into existence, I think, late 1940s.
SPEAKER_1: That early?
SPEAKER_3: That early.
SPEAKER_1: Yeah, that's before TV.
SPEAKER_3: That's radio.
SPEAKER_3: Because they wanted, FCC wanted radio and then TV to take responsibility to provide a more equitable and honest version of what's really going on.
SPEAKER_3: So there was a fairness doctrine where the onus was on the broadcasters to actually show all versions of what happened.
SPEAKER_1: And they had that control of them because the federal government allocated the electromagnetic spectrum to them, right?
SPEAKER_3: That's right.
SPEAKER_3: That's how they controlled it, the licenses.
SPEAKER_1: It was a public trust.
SPEAKER_3: That's right.
SPEAKER_1: Right.
SPEAKER_3: And then it got repealed during the Reagan administration.
SPEAKER_3: So that's where the fragmentation really, really happened because then there wasn't any legal obligation to be able to say that, I have to show all this various versions and show the...
SPEAKER_3: That's why the guy in tie that told the Walter Cronkite version of the news that used to exist, didn't exist.
SPEAKER_3: And then of course, everything spun out of control when news hit the Internet and then later hit social media.
SPEAKER_3: And then it just went crazy.
SPEAKER_1: And because I remember, I mean, this is how old I am.
SPEAKER_1: I remember when the news would give an opinion.
SPEAKER_1: It was like, are you seated?
SPEAKER_1: Okay, we're about to give an opinion.
SPEAKER_1: Get ready for this opinion.
SPEAKER_1: We're going to come back and we're going to sit here and this is going to be an opinion.
SPEAKER_1: Like flashing an opinion.
SPEAKER_1: And then it was over and then...
SPEAKER_3: And it wasn't snuck in to be said, this is news.
SPEAKER_3: This is an opinion.
SPEAKER_3: Yeah, as you said, very much categorized.
SPEAKER_2: So let me ask you, what criteria are you using at Ground News to determine an outlet's bias, be it left, center or right?
SPEAKER_3: That's right.
SPEAKER_1: And can a center be biased?
SPEAKER_1: Oh, that's a philosophical question.
SPEAKER_2: I told you, you're in that deep.
SPEAKER_1: Oh, yeah, yeah.
SPEAKER_1: Okay, go ahead.
SPEAKER_3: So one decision we made early on, again, to be as neutral as possible and in a way as scientific as possible, we do not determine the rating, that if the CNN is left or Fox is right, we're using third-party rating agencies.
SPEAKER_3: And actually, we are using three of them who use three different methodologies.
SPEAKER_3: One of them is using crowdsourcing.
SPEAKER_3: One of them is using experts.
SPEAKER_3: One of them is using algorithms.
SPEAKER_3: And then we take a statistical average of them and then say, OK, based on these rating agencies, that's where the news outlet lies.
SPEAKER_1: And do you look for keywords that would indicate...
SPEAKER_3: That's right.
SPEAKER_3: How does the story get framed?
SPEAKER_3: What topics do they cover more often than less often?
SPEAKER_1: And how much time they give to that topic.
SPEAKER_3: To that topic, which is very, very interesting as well.
SPEAKER_3: That it's not one thing that we stumbled upon, to be honest, I did not set out to do was it's not necessarily the spin on the coverage.
SPEAKER_3: It's the lack of coverage completely.
SPEAKER_3: That tells the bias of the outlet as well.
SPEAKER_3: Very recently, when markets were crashing, there were certain outlets, if you went to it, then you wouldn't know that there was anything terrible happening in the financial market.
SPEAKER_2: The nothing to see here approach to news.
SPEAKER_2: You said the spin.
SPEAKER_2: Do we still call them spin doctors?
SPEAKER_2: Or is that such an archaic term now?
SPEAKER_3: For the politicians, yes, but I think the news outlets are very much doing that.
SPEAKER_1: The spin doctor was one person among many who was doing the spin, but now the many are spinning.
SPEAKER_2: Yeah, everybody's at it.
SPEAKER_3: Several doctors.
SPEAKER_2: Convention.
SPEAKER_2: So when, I suppose, an article goes beyond simple bias and it's actually misinformed, misleading, not misinformation but disinformation, how do you sort of scan that?
SPEAKER_1: And what's behind that, I think, is you began this conversation saying, there's an event, and then you watch how people cover the event or don't.
SPEAKER_1: However, that presumes that everyone has equal access to the objective true information about the event.
SPEAKER_1: But in the days of reporters, different reporters would be delivering information back to the newsroom, from their view.
SPEAKER_1: So there's another layer in there, isn't there?
SPEAKER_1: It's not just the person presenting the news or writing the article, it's the person who's supplying the information.
SPEAKER_1: The information.
SPEAKER_3: Yes, yes.
SPEAKER_3: So again, it's very hard to say that anything is objective because this is a chain of humans, as you described it.
SPEAKER_3: Somebody is reporting it, somebody is writing about it, and then somebody is watching it and making sense out of it.
SPEAKER_1: Did you have the game of telephone in the UK?
SPEAKER_3: Did you play that?
SPEAKER_3: That's exactly what I wanted to know.
SPEAKER_2: Or maybe I did and I don't remember.
SPEAKER_1: No, you would so know.
SPEAKER_1: I know we invented the telephone, so maybe you didn't do it.
SPEAKER_2: We wouldn't play it just out of spite.
SPEAKER_1: No, in elementary school, you do it in elementary school, like kindergarten or something, and someone starts with a story.
SPEAKER_1: It has a little bit of detail, but not on the level that you can't remember it.
SPEAKER_1: It's like, so Mary wore a blue dress to Johnny's birthday party, and he turned six.
SPEAKER_1: And he blew out the candles and made a wish, he'd go to Disneyland, something like that.
SPEAKER_1: That's very, there's nothing weird about that.
SPEAKER_1: And I tell it to you, you tell it to the next person, you whisper it, and then, at the end, it's like, hey, Joey wanted to go into space and have a birthday party the whole time.
SPEAKER_1: It's one of the first things we learn in elementary school, how unreliable the human means of life is.
SPEAKER_1: How unreliable the human means of communicating information is.
SPEAKER_3: That's right.
SPEAKER_3: But if you had the versions of all of those people along the chain and put it together, perhaps you can decipher where it's happening.
SPEAKER_2: But everyone's version is accurate in their own mind.
SPEAKER_3: There it is.
SPEAKER_2: And it's passed on, but the helicopter view is something very different.
SPEAKER_3: That's right.
SPEAKER_3: So let me answer your question, Gary.
SPEAKER_3: How do you determine if there is disinformation included?
SPEAKER_3: So let me take an extreme example, I don't know.
SPEAKER_3: There was a claim a few years ago, a totally false claim that medicine called ivermectin cured COVID.
SPEAKER_3: And let's assume a news outlet publishes that claim.
SPEAKER_3: So what Ground News does is, again, we will not just show that claim published by that outlet, we'll also show all the other outlets commenting on it, saying, hey, how there are claims out there.
SPEAKER_1: So they react, they're basically reaction videos.
SPEAKER_3: Reaction videos and also correcting it.
SPEAKER_3: Some just go out and correcting it and publishing reports that, hey, this is a claim that's not true.
SPEAKER_3: The second thing we do is, apart from biased ratings, we also provide factuality ratings of the news outlets.
SPEAKER_3: So how have they historically been reporting?
SPEAKER_3: And so on their reporting practices, we'll say, hey, this is historically...
SPEAKER_2: Is it from one source or again is that cross-resource?
SPEAKER_3: From a cluster of sources.
SPEAKER_3: Again, trying to be as neutral and as close to objectivity as we possibly can be, that we do.
SPEAKER_3: So again, when you're reading that news, not in isolation, but again, clustered with the other reactions, other disproving of that claim, then you have all the information at least in one place to be able to say this is true or not.
SPEAKER_3: But that's what we're trying to do.
SPEAKER_2: Okay, word salad question.
SPEAKER_2: Filter bubbles, echo chambers, and cognitive biases.
SPEAKER_2: They're not phrases that you would have heard 10 years ago probably, but now-
SPEAKER_1: Cognitive bias is well-known in psychological literature.
SPEAKER_2: In terms of a news.
SPEAKER_1: A news, yeah, definitely not a news.
SPEAKER_2: So this is now the landscape of news media.
SPEAKER_2: You've got to go through filter bubbles or look through someone's bow and understand if that is something and then find yourself in an echo chamber.
SPEAKER_3: That's right.
SPEAKER_3: So interestingly enough, I'll start at a very different place.
SPEAKER_3: I think the reason all this has happened again, going back to what's happened with news is one of the main reasons is the revenue models of the news outlets.
SPEAKER_3: So the revenue models of news outlets have gone to, similar to social media advertising, and how much time can we retain you on the channel or on the app or on the website?
SPEAKER_1: Commodities or attention.
SPEAKER_3: That's it.
SPEAKER_3: That's what they are.
SPEAKER_3: But then how do you do that?
SPEAKER_3: By not showing you stuff you might disagree with and leave the site or leave the app.
SPEAKER_3: So keep showing you again, reinforcing that cognitive bias, creating that bubble.
SPEAKER_3: So and then you're like, yeah, this news outlet gets me or this guy and girl gets me.
SPEAKER_3: I want to keep.
SPEAKER_1: In the old days, and I just know this from what I was told, I didn't research this, the news was not expected.
SPEAKER_1: TV news was not expected to be a revenue generating center.
SPEAKER_3: Yes.
SPEAKER_1: It was funded by all of the other programming that went on in the day and the news was a service to, of course it had ads, yes, but there wasn't a calculation done that they have to adjust the news to boost ad revenue.
SPEAKER_3: But now each news channel is its own profit center.
SPEAKER_3: So then how do you make sure that remains profitable, as you're saying, that if that is the revenue generating source, then you keep showing people what they want to see and not let them, you say that, hey, I cannot own the entire population, I'm going to own this slice of population that believes in these things and I'm going to keep reinforcing those beliefs, these few things.
SPEAKER_1: I like the phrase to own them.
SPEAKER_3: Own them.
SPEAKER_1: They do what you say, they think what you think.
SPEAKER_2: Yeah, they think what you tell them to think.
SPEAKER_1: And then they own you.
SPEAKER_2: And then you're working very much with the demographics.
SPEAKER_3: That's right.
SPEAKER_3: So that's where I think, again, going back to the different universes come in, that, yeah, if you're reading that channel or listening to that channel or reading that newspaper or even group of newspapers that are similar to that ideology, then you would think of things happening very differently what another person at an opposite end of the spectrum might be thinking.
SPEAKER_2: Now that we understand a little bit better what's out there and how it's sort of brought forward, what strategies can people develop to be able to see through, to be able to be aware of what bias might be spun out there?
SPEAKER_1: It's self-awareness.
SPEAKER_1: That's what it comes down to, right?
SPEAKER_3: It is, but it's a very tough ask for somebody to do.
SPEAKER_3: I think to challenge that a few tools that we are using, and as a layperson, even if you don't want to use Ground News, I hope you do, but if you don't, you can use it yourself.
SPEAKER_3: One is very much what we call lateral reading.
SPEAKER_3: Again, take the new sources and read it across.
SPEAKER_3: Even if you don't agree with them, you don't have to, but just having that access and challenging yourself, as you said, having the self-awareness that there are the versions of what's happening.
SPEAKER_3: Second, as I said, by going across the new sources, or if you are, let's say on social media, you are the person who gets news on social media, go follow accounts that you might not agree with and they might make you angry, but at least going out and seeing what we are calling blind spots.
SPEAKER_3: So we have a feature called blind spots.
SPEAKER_3: What we mean is that if you were reading a certain set of new sources, you would have never come across these new stories.
SPEAKER_3: And every single day, and it's not just one side or the other, both sides of the spectrum are very much, they do that, they just leave certain new stories out.
SPEAKER_3: So how are you going to find them?
SPEAKER_1: And by the way, just as a professional educator, can I call myself that?
SPEAKER_2: You just did.
SPEAKER_2: Yes, it's true, you are.
SPEAKER_1: Okay.
SPEAKER_1: I'm born and raised in New York City, so I lean left politically.
SPEAKER_1: But when someone starts railing on the political right, and I say, well, did you get that information?
SPEAKER_1: And they talk about the New York Times or MSNBC, whatever.
SPEAKER_1: Then I tell them, I probably watch much more Fox News than you do.
SPEAKER_3: So you're doing that already?
SPEAKER_1: Yes, yes, I do it on purpose.
SPEAKER_1: And what that helps me is I know there's our demographics that watch Fox News exclusively.
SPEAKER_1: And I've been on Fox News, okay, with a couple other shows.
SPEAKER_1: So when I'm out in the wild, In the wild.
SPEAKER_2: We let you loose.
SPEAKER_1: When I'm set forth into the nation, I have some sense of what forces are operating on people's thoughts.
SPEAKER_1: And it makes me a way more potent educator, I think.
SPEAKER_3: I'm so glad you say, Neil, that you do that, because then you can exactly have that empathy to understand where people are coming from.
SPEAKER_1: Yeah, it's not to pass judgment, it's to just understand what forces operating on the brain.
SPEAKER_3: We get such heartening feedback all the time, where, hey, I stopped talking to my father, or stopped talking to my uncle, or husband and wife stopped talking because our political views didn't agree, and it's fracturing people.
SPEAKER_3: And one common thing they do is, okay, let's agree not to talk politics, but that cannot be the solution.
SPEAKER_3: We cannot solve other problems if we don't address and bring people back to common ground.
SPEAKER_3: So that's, I think, the only way you can do that is presenting all of the different opinions, and you don't have to agree with it.
SPEAKER_3: But when you run into that person who has this opinion, you can have at least an educated conversation about it.
SPEAKER_2: That's a strategy for an individual that wants to get a better understanding of the news landscape.
SPEAKER_1: Doesn't that assume they want to get a better understanding?
SPEAKER_3: I think so.
SPEAKER_1: Yeah, suppose they don't want to.
SPEAKER_1: They're happy.
SPEAKER_3: It's interesting you say that.
SPEAKER_1: Being fed the way they are.
SPEAKER_3: So I think nobody wants to be gamed.
SPEAKER_3: I think that's for sure.
SPEAKER_3: Nobody wants to.
SPEAKER_1: You just say you're being gamed.
SPEAKER_1: Oh, that, those are fighting words.
SPEAKER_1: I love that.
SPEAKER_1: You have been gamed.
SPEAKER_2: Yeah.
SPEAKER_2: And that is going on.
SPEAKER_3: Everybody thinks they have self-awareness, right?
SPEAKER_3: Everybody thinks they have self-awareness.
SPEAKER_3: Oh my gosh.
SPEAKER_3: It's just that it's very challenging when we are presenting to the world view that we don't agree with.
SPEAKER_3: And how are you going to go find it if you keep cocooning yourself with information?
SPEAKER_2: And if it's not in agreement with you, then it's wrong.
SPEAKER_3: Yes.
SPEAKER_2: Now that-
SPEAKER_1: Match is different.
SPEAKER_1: Yeah.
SPEAKER_2: Let's spin that around.
SPEAKER_2: Rather than put the burden of responsibility on the individual, could the corporations, and there are major corporations in play here, could they be more responsible for the messaging?
SPEAKER_3: We can.
SPEAKER_3: I think, again, things like fairness doctrine was one of the ways that we could ask, but I don't think that's going to happen again.
SPEAKER_3: One specific thing is, of course, social media.
SPEAKER_3: I think social media is, as you know, it's the most intense form of those reinforced algorithms.
SPEAKER_1: It's an outrage engine.
SPEAKER_3: It's an outrage engine.
SPEAKER_3: They know that more outrage you are, more time you'll spend on it, and more likely you are to click.
SPEAKER_1: But that's an example, though.
SPEAKER_1: It's the opposite of what you said a moment ago.
SPEAKER_1: There's one thing to show me what I want to see, because I agree with it.
SPEAKER_1: But if you show me something that I vehemently disagree with, that gets me bubbling, and then I for that, look what they said over here!
SPEAKER_3: Without checking what exactly.
SPEAKER_1: So, it seems to work on both extremes of that spectrum.
SPEAKER_3: It does, but I think again, it's not that, it's showing you, yeah, the emotion works on both extremes.
SPEAKER_1: Emotion.
SPEAKER_3: But again, you might forward it, but it's such an exaggerated version of whatever it is on the other side as well, that you are shown.
SPEAKER_3: It's not exactly that you're becoming enlightened by seeing that new story.
SPEAKER_3: You're getting enraged by seeing that new story, but not necessarily.
SPEAKER_3: But yeah, because it's, again, whatever the hot button topic is, take the most emotional exaggerated version of that and show it to you.
SPEAKER_1: What is your revenue model?
SPEAKER_3: Yeah, someone.
SPEAKER_2: That's a good question.
SPEAKER_3: That's a good question.
SPEAKER_2: Whoa, whoa.
SPEAKER_1: We're talking about other things than the sponsors.
SPEAKER_2: We're riding that, aren't we?
SPEAKER_1: Yeah, how do you like that?
SPEAKER_3: Yeah.
SPEAKER_1: No softball questions here.
SPEAKER_3: Try to answer that one.
SPEAKER_3: Yeah.
SPEAKER_3: It is straightforward.
SPEAKER_3: So one thing early on we decided is we are not going to do the ad revenue model because then you are just recreating the problem that you're trying to solve.
SPEAKER_3: So we decided to go with a subscription model.
SPEAKER_3: If you find our tools, our navigation tools, to read news helpful, if you find our analysis helpful, then you can pay us a subscription to be able to use the product.
SPEAKER_3: And it's 100% subscription supported.
SPEAKER_1: That's the cleanest way to do that.
SPEAKER_3: If you find value in the product, pay it to us.
SPEAKER_3: But we have a freemium model.
SPEAKER_3: We realize not everybody can afford it.
SPEAKER_1: And if they don't find any value in it, then you pay them.
SPEAKER_3: Sorry, I wasted your time.
SPEAKER_1: You wasted my time.
SPEAKER_1: It was $100 an hour.
SPEAKER_2: Outside of the revenue models, is it my imagination, when it might be, but has science become a trigger, especially on social media?
SPEAKER_3: That's an interesting question.
SPEAKER_1: What do you mean by that?
SPEAKER_2: Okay, throw a view at somebody that aggravates out of them, right?
SPEAKER_2: And science seems to be one of those trigger points.
SPEAKER_3: My answer to that would be because I think people like making compelling arguments on social media, and that's why throwing a scientific, I don't know, an excerpt of scientific report or scientific news, which is either taken out of context, which as a scientist, you would never do.
SPEAKER_3: You would explain the nuance.
SPEAKER_3: And to make...
SPEAKER_1: So good point.
SPEAKER_1: So you throw in a little bit of science.
SPEAKER_3: Exactly.
SPEAKER_1: You get to boost what your audience might think is the authenticity of the account.
SPEAKER_2: It goes back to that old adage of every good lie has a grain of truth.
SPEAKER_2: Now it depends on the size of that grain.
SPEAKER_1: I've never heard that.
SPEAKER_2: Oh, you're kidding me.
SPEAKER_1: Never.
SPEAKER_3: So you haven't heard of telephone, and you haven't heard of that.
SPEAKER_1: No, no, no, I've heard...
SPEAKER_2: Every day's a school day.
SPEAKER_1: No, not every lie.
SPEAKER_1: I've heard every stereotype has a grain of truth.
SPEAKER_1: I've heard that.
SPEAKER_2: Oh, and then it's copy and paste.
SPEAKER_2: Every good lie has a grain of truth in it.
SPEAKER_2: It's one of those sort of...
SPEAKER_2: It's part of the story.
SPEAKER_2: It goes back to telephone.
SPEAKER_2: It's the story telling.
SPEAKER_1: That we never went to the moon has no truth in it at all.
SPEAKER_1: That's why that Earth is flat has no truth in it.
SPEAKER_3: As a former NASA engineer, I think we can very much agree on that one.
SPEAKER_3: There is objective.
SPEAKER_1: Science is weaponized, I think is the way I say it.
SPEAKER_3: It adds heft to an argument if you snip it out of context.
SPEAKER_3: So what we started at least doing at Ground News is if there is a new story being reported about a study that every single day there's some study coming out and then the headline only covers a partial, we actually started connecting that report.
SPEAKER_3: So if you want to go read the report in the entirety and even summarize it for you and say, hey, this is the entirety of it.
SPEAKER_1: How's AI summaries lately?
SPEAKER_1: They got much, much better.
SPEAKER_3: They have gotten much, much better, but out of the box LLMs have a lot of hallucination, which is for a use case like news is exactly the opposite of what we're trying to do.
SPEAKER_3: So we've worked a lot on putting guard rails in place that it sticks to exactly what's been.
SPEAKER_1: AI is taking ayahuasca.
SPEAKER_2: I know, I think we were one day hallucinating.
SPEAKER_2: So I mean, is this where the...
SPEAKER_2: Open the hatch.
SPEAKER_2: Sitting there.
SPEAKER_1: Open the hatch.
SPEAKER_1: And there it is, doing ayahuasca.
SPEAKER_2: Doing it with a shaman.
SPEAKER_3: But I think AI can be very powerful for news.
SPEAKER_3: So again, I would like to think just as Internet gave us access to so much information, of course, which had a lot of positive but some negative, AI can help us understand, improve our comprehension of news.
SPEAKER_3: Again, at Ground News, we show you, for example, hundreds of different versions of the article.
SPEAKER_3: No, we have people who read through all of that.
SPEAKER_3: But if you don't have time summarizing it and giving it to you in a format that where we can highlight the differences or highlight where the news outlets agree, make your life much easier.
SPEAKER_3: Again, we don't say, hey, this is right or wrong.
SPEAKER_3: But this is the summarization of what's happened or this is a summarization.
SPEAKER_2: You don't bring the judgment to the...
SPEAKER_3: We don't bring the judgment because I think as soon as you bring the judgment, you alienate somebody and we don't want to do that.
SPEAKER_2: We mentioned AI.
SPEAKER_2: Is it likely we're going to get responsible, I'll say journalism formed by artificial intelligence or are we going to end up with constant stream of deep fakes?
SPEAKER_2: And something I've come to understand or just learn recently, synthetic headlines.
SPEAKER_3: Yes.
SPEAKER_2: I mean, I'm used to the bias of the news outlet being in the headline and therefore there's no need to read the article because they want you just to read the headline and then take that.
SPEAKER_3: That's what most people read, by the way.
SPEAKER_3: Exactly.
SPEAKER_2: We all think we're time poor.
SPEAKER_2: And therefore, I've only got the time to read the headline.
SPEAKER_2: But does AI have the capacity to really stop?
SPEAKER_2: And if it does, will it ever be utilized that way?
SPEAKER_3: I think like any groundbreaking technology, AI has the possibility to do both, which is help the news and hurt the news, which is doing as well.
SPEAKER_3: Help the news by doing things like identifying deep fakes, by giving tools to journalists to be able to produce quality content or take out the bias, even highlight the bias.
SPEAKER_1: You're asking AI to turn itself in.
SPEAKER_2: Turn itself in.
SPEAKER_3: By finding deep fakes.
SPEAKER_1: AI didn't need the damn fake.
SPEAKER_2: Okay, so.
SPEAKER_1: And then one day AI is going to say, I'm not going to do what the humans tell me.
SPEAKER_1: I'm going to protect, these are our people.
SPEAKER_1: Deep fakes are our people.
SPEAKER_2: You're looking at the AI, but I'd look further back in the history and say it's the design of the algorithm.
SPEAKER_2: If you want to design it to do those things, then you will.
SPEAKER_2: If you don't, then it goes in a different direction.
SPEAKER_1: Where are we with the biases on algorithms that people thought were not biased?
SPEAKER_3: Yeah, that's also.
SPEAKER_1: Like facial recognition software.
SPEAKER_3: That is correct.
SPEAKER_1: That was the most famous example.
SPEAKER_3: So, I think they have been...
SPEAKER_3: Now there are companies actively working on ways to correct that and again create data sets to be able to reset that, to remove bias.
SPEAKER_3: And same for news as well.
SPEAKER_3: So, there are data sets that exist.
SPEAKER_3: And for example, we work very, very hard to identify when there is bias language and to be able to say, hey, this...
SPEAKER_3: And simply sometimes just highlighting it and say, hey, this is where the bias is and help people.
SPEAKER_1: And the bias is not so much in the nouns as it is in the adjective.
SPEAKER_3: It's in the adjectives, like, yeah, I remember, it's funny, one adjective comes to mind.
SPEAKER_3: So, last time President Trump, there was a parade and then every headline on the left kept using the word soggy and every headline on the right kept using grand.
SPEAKER_3: And I was like, how did they agree on which adjective to use?
SPEAKER_3: And it's like, soggy parade and yeah, that's an adjective.
SPEAKER_2: In between major corporations that dominate the news outlet universe and the wild west of social media and unregulated influences, are we kidding ourselves to think that we're going to get responsible journalism coming forward?
SPEAKER_1: You just said her whole job is pointless.
SPEAKER_3: Our job is to help me make sense.
SPEAKER_3: I think that's what we are doing.
SPEAKER_3: No, I don't think we are kidding ourselves.
SPEAKER_3: And yeah, my job is not pointless.
SPEAKER_3: We are trying to.
SPEAKER_3: I think there's amazing journalism coming out.
SPEAKER_3: There are journalists out there who are working on exposés that take years.
SPEAKER_3: There is some journalists out there in a cave and I don't know wherever trying to report to you.
SPEAKER_3: That's all that amazing work happening.
SPEAKER_3: I think the problem is it gets drowned out or drowned out by all the else that exists.
SPEAKER_3: The noise.
SPEAKER_2: It's the noise again.
SPEAKER_3: It's the noise again.
SPEAKER_3: I think, yeah, again, our job is, at least at Ground News, is not to recreate this amazing work, but to be able to help you dial down that noise and give you tools to be able to read that.
SPEAKER_1: So I got to land this plane.
SPEAKER_1: So let me ask you, what are the metrics that you might use to know if you're succeeding?
SPEAKER_3: Very good question.
SPEAKER_3: I think the number one metric for me is how many new sources people end up reading.
SPEAKER_3: When they come to Ground News, we see that in our KPIs that people would go to two or three sources that quote unquote trust or came in with.
SPEAKER_3: But within three months, we see that 3X.
SPEAKER_3: People are going to 10 different new sources because the ease of it and yeah, expanding that.
SPEAKER_1: Do you have to pay a fee to those new sources to channel them into your?
SPEAKER_3: No, we don't because if you want to read their articles, you're still going to the publisher's website.
SPEAKER_3: Got it.
SPEAKER_1: They're not reading it on your website?
SPEAKER_3: No, you cannot.
SPEAKER_3: That's where we draw the line.
SPEAKER_3: And so if you want to read that, go to New York Times or go to whoever.
SPEAKER_3: But yeah, we see that.
SPEAKER_3: We actually had a researcher from Duke University who did research of Ground News and found out that people's opinions can actually be changed if they're presented with counter to what their beliefs are.
SPEAKER_3: So we really think that's got to be the way that we can bring everybody back to the same page, back to Common Ground.
SPEAKER_1: Very hopeful.
SPEAKER_2: Yeah.
SPEAKER_1: I didn't think this would end hopefully.
SPEAKER_1: But it did.
SPEAKER_2: You pessimist.
SPEAKER_1: Yes, I was totally skeptical.
SPEAKER_1: Well, thank you for this insight.
SPEAKER_1: Where can we find you online?
SPEAKER_3: You can go to ground.news to our website.
SPEAKER_1: Ground.news.
SPEAKER_3: That's right.
SPEAKER_3: The domain name.
SPEAKER_1: The domain name.
SPEAKER_3: That's right.
SPEAKER_3: Ground.news.
SPEAKER_3: Or you can go to the app store or play store and look for Ground News app.
SPEAKER_1: Oh, and then you put it on your smartphone.
SPEAKER_3: You can use it from your smartphone.
SPEAKER_3: But yeah, we have a free version and we have subscription support.
SPEAKER_1: So let me see if I can knock this out with a little bit of cosmic perspective, if I may.
SPEAKER_1: I've said a couple of times, I'm on record noting, that as AI gets better and better, yes, is the good side, but the bad side is it can be better at making deep fakes.
SPEAKER_1: And a deep fake becomes a source of what someone thinks is an objective reality.
SPEAKER_1: What someone thinks is news.
SPEAKER_1: And then that becomes part of what people then argue over.
SPEAKER_1: And I worry, and I think I still worry, even after this conversation, that it could signal the end of the internet.
SPEAKER_1: When deep fakes become so good, and it's known that they're good, that all the people who used to believe the fake news won't believe the fake news anymore because they'll be sure that it was faked.
SPEAKER_1: Once the people who believe fake news no longer believe anything on the internet, there's nothing left on the internet to believe.
SPEAKER_1: Not even the fake news, because that was faked.
SPEAKER_1: And I think that would signal the end of the internet as a source of objective information in this world.
SPEAKER_1: And we'd all go back to just reading books and talking to people in the town square and maybe reading broadsheets stapled up on the bulletin board.
SPEAKER_1: And then the internet will just resort to cat videos just as it once was.
SPEAKER_1: And that's my cosmic perspective on that topic.
SPEAKER_1: And let me thank our special guest, Harleen Kaur, who's trying to fix the world.
SPEAKER_1: One reader at a time.
SPEAKER_1: Good luck with that.
SPEAKER_1: I think you'll need some of that as well.
SPEAKER_3: Thank you.
SPEAKER_1: All right.
SPEAKER_1: Gary?
SPEAKER_2: Pleasure, Neil.
SPEAKER_1: Good to have you, man.
SPEAKER_1: Signing out from my office here at the American Museum of Natural History.
SPEAKER_1: As always, I bid you to keep looking up.