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Bald Ambition
Kent Anderson and Joy Moore: How Science Hijacked Your Attention and Lost Your Trust
01:23:52
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- [00:00]
A
Hello and welcome to the Bald Ambition podcast with your very bald host, Mookie Spitz. And the ones with all the ambition today are Kent Anderson and Joy Moore. They are the co authors of how the Internet Disrupted Science, coming out August 4th. Consider this a launch party. Welcome aboard. And Joy, thanks Mookie, much.
- [00:27]
B
Yeah, thanks for inviting us.
- [00:30]
A
You guys are veterans in the publishing industry as I understand it. So you have an insider's view as to some of the biases that have warped science. Now, most of us understand science as an evidence based discipline. It's one of the foundations, the bedrocks of our society in terms of getting at the truth. And we all endured the pandemic and the whiplash from COVID merely reinforced skepticism around the sciences. And now I think it's fair to say that as a society, we're living in a culture that increasingly distrusts what used to be this foundational institution. How do we get here? How does it progressively seem to be getting worse and not better? And how does your book set it up and describe the predicament that we're in right now?
- [01:34]
C
That's the perfect way to frame it. So the book tells us how we got here. It connects a lot of dots. When Joy and I started in scientific publishing, it was just prior to the commercial Internet going mainstream. And so we know what it was like back when journals were carefully curated and focused on scientific communities and used to inform public policy. And then the findings given to a robust scientific journalism profession that would interpret it well for the public. And what we saw over the. What we've seen over the past decades, because it has been a long term problem. And Covid really catalyzed a lot of problems. But what we've seen over time is that the incentives changed. And the reason that we use the Internet as something that disrupted science is because the information wants to be free. Politics of Silicon Valley. The cyber libertarianism of Silicon Valley crept into the sciences and the belief that more information is axiomatically better and that information should be free to the user. So in order to make the information free to the user, someone had to pay. And the business model flipped in a lot of cases so that the producers pay, and they pay on a per piece basis rather than there being a recurring revenue subscription basis. And so what happened is that volume and scale became the incentives for scientific publishing. And you made money when you accepted a paper. So all of a sudden editors had a price tag on a rejection. You knew it was going to be $5,000, that you were turning away or Something like that. And so a lot of those incentives then allowed predatory publishers and paper mills and a whole bunch of people with commercial angles to start flooding the scientific literature. At the same time, a lot of things were deprivileged, like peer review was deprivileged. So you had preprints. And we can talk about preprints specifically and how those have been used by various people with various agendas. But essentially the biggest flip was the incentives. It went from trying to make the best information for a specific community of scientists to getting out the most information for technology platforms and to make the most money.
- [04:14]
A
A tsunami of content for the sake of monetization. That sounds familiar, but I think many of our viewers and listeners will be a little bit surprised to hear that it's become endemic within the sciences.
- [04:31]
B
Yeah, publishing is so important to career scientists. You need to publish the findings, you get a grant, you do your research, and then in order to stake a claim and get credit for it, you publish a paper and that goes into the record and you, mookie published the first. You were the first one to find this bit of thing. And so anyone who builds on that has to cite you. And so that's how it started out. And there was a closer link between scientists using the papers as their dialogue. Right. You can go back into the literature and then you continue to build on it, but by breaking it apart, you know, basically ripping the spine off the journals as a package. Right. And if you, if you didn't do a good job as a journal editor before, people could cancel your subscriptions and your publisher would shut you down. Now it's flipped, where every single paper is paid for up front and no one can cancel it because it's already out there. And it's going to be out there in most cases forever. And so like Kent said, when you change the incentives, you change the behavior. And so on the, you know, kind of on the good side, a lot of scientists thought, well, this is great because more people are going to have access to my work and this is going to create, you know, a lot more innovation. But, you know, there's a larger majority of people across the globe who said, hey, there's cash there in them papers. And so we've seen an explosion of journals, of papers. There's, there's too many to count right now. I think the latest is there's somewhere between 25,000 and 50,000 thousand scientific journals out there available to anybody who wants to publish anything and anybody who wants to find a paper that will prove
- [06:50]
A
Anything sounds like a cat is chasing its tail. The cat is the publishing industry as you've described it, with shifting incentives, focus on monetization, and now this tsunami of publications and content that often has very little to do with the inherent quality of the work. You also mentioned how the motivation behind this is endemic within the scientific community where it's published or perish. And now it's flourish or perish.
- [07:26]
C
Now it's one of the things that
- [07:27]
D
people say now it's publish and perish. So the. But to your cat analogy I would say, I think what the publishing industry has allowed itself to do is to chase the laser dot of Silicon Valley around the room and slowly be. Be worn out and exhausted by doing that. And that dot is based on the attention economy, on the producer pays economy and you know, publish and publish or parish existed before, but it was a very. Both those words had were especially the publish met was meaningful. Right. It was a big accomplishment to publish a paper in a good journal because you had to go through multiple layers of expert review and you could make a career from a single publication. Now you have to publish 20 papers in order to even compete on volume with other people in your field. And those papers are typically vanilla. A lot of. But then it's also enabled grifters especially. There's a whole track that gets us into the Maha movement and how that, that on the wellness community and all of those people have used this kind of this flood of papers to hide out and bury claims that they use then to sell us things.
- [08:55]
A
Yeah, and the other tale I was thinking of was the scientific community itself. You mentioned how Covid precipitated an increase in the distrust of science foundationally. And we've had other trends throughout the sciences, including one of its most sacred domains, fundamental physics, where some of its key opinion leaders, where some of the habits of fundamental physics and even some of its theories have fed into this negative feedback loop. So specifically one example, string theory has dominated fundamental physics for decades and it operates off of some of these similar biases. So I'm wondering if what you're describing in terms of this Internet disturbance of science has precipitated or fed into putting certain theories above others. Some of the inherent biases within certain scientific communities are being encouraged, if you will, to erupt and promulgate and create their own implicit and explicit biases.
- [10:19]
B
Well, there's certainly the attention economy. Right. So you're gonna. Now anyone can be a celebrity, especially if you have a PhD at the end of your name and you can create your own YouTube channel and you can host a podcast and you can get like minded people to follow you and you can push these views out and at the same time you could start a substack and you could. But you could also, you know, publish some papers in any manner of journal and the people within your discipline who don't agree with you will just ignore you for the most part. But as we've seen the celebrity culture kind of come out, those tend to take on a life of their own and then that will turn into public opinion and in some cases policies.
- [11:23]
C
Yeah, you raise an interesting point though about the, the effect of the physics community on scientific publishing during the Internet age, especially the early portion and setting precedence in that. So the first major preprint server was arXiv. You probably read papers on that and so on and so forth. Right. So that was a sensible solution to a problem that came about or an opportunity actually that came about because of machine readable telescopes, data from telescopes. They couldn't process it fast enough through the journal system. So they said, well, let's put all the papers we can get out of the data there and then we'll pick the best for the journal system. Right. But you can still look at the data and still have access to it. Made sense for high energy physics and theoretical physics. Other people then took that model where there's not peer review over the science being put out into the public sphere and push that into other areas, chemistry, engineering. Again, not things that are really going to affect the average person on the street. And then in 2014, I think the first biomedical preprint server came about, modeled specifically on arXiv. And that's where a lot of the misinformation during COVID was placed and where there was a, There's a huge section of the book about this where a lot of the mythology that's still being used by the Make America Healthy Again group and the wellness community and all of these people really started to boil up because there was no peer review on those preprints. And we. Other studies have found that white nationalists, alt right and people like that love to use those papers to push eugenics and transhumanist beliefs that are coming out of Silicon Valley into popular culture. So there's a, there's a. It's all related to the fact that this scientific community, the scientific communication environment, has been aimed at the public. And that's not what it was. It's meant to be for scientists to talk about. Here's an interesting thing. Let's Try to figure out what that means as we try to ferret out what's true and what's not. That's where the scientific communication space should be. When it's aimed at the public, it gets weaponized far too often,
- [13:58]
A
most definitely. But there's a dynamic tension between institutionalized science with certain gatekeepers who are the arbiters of truth, and this ability to disseminate information in a way that's more democratized. I think that's been the dynamic tension that's going on here. And whereas I understand that opening up the floodgates and making peer review almost an afterthought creates its own set of problems. But there were also problems prior to this with the entrenched system. So you've had peer review, which was more cloistered. You've had many theories that were reinforced and proved to be wrong. So you bring up the Maha movement and eugenics. But on the political left, there's been controversial ideas that have been backed as well. So the right isn't the only side of the equation that we could point a finger at for manipulating science in the manner that you describe. And I'm just wondering about both of your thoughts as to before and after, where there seems to be this tipping point between an entrenched system, which most people trusted, and the wild, wild west we're in right now of tens of thousands of publications circumvented peer review. You've got. One of my favorites is Avi Loeb, I believe that's his name, the Harvard astronomer who's every five minutes, he's on his YouTube, he's on his sub stack, and he's talking about the aliens are here, and it's unsubstantiated and it's clearly sensationalist nonsense just to get the eyeballs and asses. So I completely concur with your assessment that it's gotten totally out of control. But part of my point is that it was out of control before, too.
- [16:07]
B
I would argue that there has always been bias and nonsense in the scientific literature, but. But that has been part of the process. Right, and so journals. Correct. Over time it was much more linear. Journals appoint different editors for set terms, and communities change over time. And so there was never the sense, you know, the belief that everything that was published is encapsulated in a paper was true, but it was part of an ongoing dialogue and continued research and rebuttals. And, you know, there's always been people going back and forth, you know, with differing views on different things and over time, it would play out, you know, who was ultimately closer to being right and who was. Was missing the mark. The difference now with it being a total free for all is that you don't have that structure in place. And so by the time we were just, you know, we're looking at papers all the time and. And once something, the cat gets out of the bag, you know, to continue with the cat, you can't put it back in anymore because it's. It is immortalized. When we first put journals online, we got so much blowback from editors and authors and societies because they were afraid that somebody could pull the plug and things would disappear. It's the opposite. You can't get rid of it. Once it's out there, it's there forever and people are going to build on it.
- [17:55]
C
So a couple of points to that. One is Enjoy was instrumental in bringing online peer review systems and submission systems to life for a lot of publishers. And one of the things, you were right, journals were cloistered, but they were on an improvement trajectory with those systems because instead of having to have every editor and editorial person inside a beltway so they could come in for weekly editorial meetings or something like that, you could have them now much more far flung. You could have them working internationally. So journals were, at the beginning of the commercial Internet, were actually addressing a lot of the concerns about representation and books, both in the communities, the locations, the regions they were representing, all of those things. They also were able to work more quickly and also were addressing things like disclosure and statistical review and things like that. So all there was a. What's kind of frustrating looking back is we were on an improvement trajectory in the late 1990s and early 2000s, to the point of how entrenched things get and how the attention economy keeps them entrenched. And this is another effect of the Internet, but also a subtle effect of search engines. People don't understand that search engines are not only discovery tools, they're preservation tools. Right? So you can go. You can find things that are very old or have been rated very high over a very long period of time. And it kind of keeps us stuck around certain concepts or certain bits of misinformation. And people can use that to find ways to attach to those things with other bad papers. I was just talking to Joy earlier today about how I was trying to verify a certain thing that we talk about in the book and just finding all of the main term had been, you know, there were all these remoras that had attached themselves to it. That were parasitical to it. And it took forever to find the real science in that. And that's where we see scientists talking about the scientific information space now being
- [20:11]
D
a, you know, a dangerous workplace. Right, because it's an unsafe workplace because the information has become so polluted that they have, they don't even, they can't tell truth from fiction. They don't know which way is up.
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C
And it.
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D
That's a different, and I think a
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C
worse problem than occasionally having, you know,
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D
a paper within a community or an idea within a community go to a certain extent and then be shot down.
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C
Right, that's different. And also because now it's publicly available, you have a lot of people who
- [20:48]
D
don't have expertise with opinions about things that they don't have expertise in. Right.
- [20:56]
A
What about artificial intelligence? This is a great bridge point to introduce what's now ubiquitous to the point of cliche. But I think central to this conversation in terms of the evolution of the Internet that you're describing. And that has impacted science, science journalism and journaling. So the bots are aggregating content. They're chopping up the entire Internet. At first it was entirely through the pre training of the models and now they're accessing through search in real time, tons of information and prompts. From what I could tell, and I'm a science geek, I do a lot of chatting with Claude and ChatGPT on science topics. From what I can tell in my areas of interests, the bots so far are doing a pretty good job of filtering out the signal and noise. What's your feeling about how these frontier models are handling all of this information and then in a sense regurgitating it to scientists and the public in a way that, based on your opinion, is either in the box of what we would consider the canaan of science across the different specialties, or are they going out there to pull from these myriad and oftentimes erroneous sources of information?
- [22:36]
B
Well, they're pulling from everywhere. And so before anybody even knew what was happening, we've got all these beautiful prepaid free papers everywhere. There's no barrier to entry, to access. These years ago, we had to spend a lot of time and money to make our content discoverable to Google. Believe it or not, the publishers paid the bill so that Google could index our content while we could still maintain subscriptions. And now that's kind of, you know, coming back. Some publishers are all for it and they are doing licensing deals and they're saying anthropic, you know, ChatGPT take our content and, you know, because we have the best. But there's definitely. They're ingesting everything they can get their hands on. A savvy user like yourself can probably put in a prompt that's going to get you what you are looking for, and you can probably ignore some things that aren't relevant. And it depends on the question that you're asking. And it depends on kind of how far down you want to go in terms of refining. And so there's been a lot of talk about, you know, AI literacy and the work that you need to do, understanding that there's going to be hallucinations, understanding that there's going to be mistakes. But if you're a savvy enough user, you're going to be able to get something good out of it. When it comes to biomedical and medical information, I have no tolerance for that because it's. That content has never been designed to be a definitive answer that would change somebody's mind or change somebody's practice. And so to have LLMs trying to do the work of parsing clinical medical information in a way that would replace the human beings who've been doing it is very worrisome.
- [24:56]
D
Yeah.
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C
And, Mookie, I'd add one of a few things to think about next time you're using one of these tools. First of all, they are developed to sound confident and to reassure you that whatever they're saying is right. Right. They will never say, I don't know. And they're also meant to keep you engaged. So they will have, you know, do you want me to do this now? Do you want me to do that now? And that's part of the attention economy as well. The other thing is that there are more and more studies finding that a, they're generating fake citations themselves. I was just reading something where 43% of chat of GPT 3.5 and 24% of GPT 4s papers contained the papers that. That they say they cited were actually fake. And so they're citing things that don't exist because they're just. They're stochastic parrots. Right. They guess that these are the words that should appear here. This is the journal title that I'm going to compile from a bunch of words that sound journal title. Ish. And so it's going to sound confident. It's going to try to make you sound like you've learned a lot. It's sycophantic at a certain level. Right. It's like, oh, that's a brilliant question. You know, that's. You're so insightful. And we, we've. You've read those stories of AI psychosis, right, where the people are convinced that they've created some new thing that FedEx is going to want to buy off of them for a billion dollars because it's a logistics solution that FedEx never had any access to or, you know, things like that. So, you know, that's. These tools are not built to be reflections of reality. They fog the mirror of reality and they do it so you can write on it whatever you want. And that's a bit of a. A problem in my mind when it comes to scientific inquiry.
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A
Yeah, I agree. LLM sycophancy is well documented, often through the LLMs who are being sycophantic when they're talking about their sycophancy.
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B
Yeah, you're right. I'm terrible. Go on.
- [27:13]
A
I'm sorry.
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C
Yeah, you caught me a lot.
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A
And I do understand this idea that all the information is being basically sliced and diced into tokens. It is a stochastic parrot.
- [27:28]
C
It's an important point, I think, from the point of view of two scientific publishing veterans. So there are things that scientific publishers and editors need to do occasionally with papers. Right. They need to correct them, they need to amend them, they need to put an expression of concern on them, or they need to retract them once they're in an LLM.
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D
You can't do any of that because the LLM has broken the paper apart.
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C
It has lost track of where every word has come from. And so the only way to retract a paper from an LLM is to
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D
rewind the system to before the publication date, which no LLM provider is going to do. So there's a basic incompatibility between these systems and the way the scientific record
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C
needs to be managed in order to reflect realizations. And a lot of times, you know,
- [28:21]
D
retraction is not a negative thing. It's been stigmatized, but there are a
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C
lot of authors who will retract a
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D
paper because they're like, oh, my gosh, we didn't realize that this computer had thrown out this thing.
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C
Or we used the wrong table here.
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D
And so a lot of times retraction is a positive thing that scientists do in order to correct the scientific record. But these LLMs are completely blocking that
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C
because of how they're designed.
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A
Yeah, I need to push back a little bit. Just from a technical point of view. The LLMs don't just chop up all information pretty much indiscriminately and aggregate it together based on the weighting and the matrix math. So for example, if a paper is retracted, there's a breadcrumb trail on the Internet too. And the LLMs aren't just relying on the pre trained modeling. They're now pulling from the Internet in real time and they're cross checking and they're cross checking citations and the dilemma that you're describing. Whereas for you know, GPT3, four hallucinations, they're all getting better at trying to be more accurate, hallucinate less and keep this information together. So I do agree with you that it's been a problem. From what I can tell from a technical and applied vantage point, it's less of a problem. And all the frontier models are now more, way more conscientiously trying to keep things veridical, at least in terms of source, source content and even citations. So I think just for the sake of objectivity and fairness, to dismiss the LLMs as this shake and bake of random content with no way to retract or change information is, is not, is not fair to the technology that is evolved.
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C
Well, I'll, I'll push back to your pushback which is we've talked with experts who build, who know how these systems are built and know how they process content and they have confirmed that the, really in their opinion the only way to you a correcting an article is one thing.
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D
Right?
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C
So a lot of times the way a correction is put up by a journal publisher is Table 4. This number should be 17.8. Right? There's no way an LLM and it's a, and it's an image. There's no way an LLM knows how to handle that.
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B
Right.
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C
So they can check all they want, but there's, they can't handle that. Then a retraction again from what we've, we've talked with experts about this. They, the elements in an LLM gain weighting, right? And that weighting has a, is of material interest to the transformer engine in the LLM. And if you, you can't just go out and process search results raw from the Internet without reflecting that weighting system. And so if you retract an article, you're going to have to retract it and take all the weightings away from it. The, the other thing that I would point out is that part of the other thing that the Internet did. So the Internet's a distributed architecture, right. Which back when we started with this, the idea was that Everything would point to a version of record. So it's single claim and it would be a single paper.
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D
Right.
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C
What's happened though is there are now we can find within days of a paper being posted on a preprint server, seven versions of that paper, right? And then it gets published. So there's another seven or ten versions of it through this, what we call the automated box of confusion. And then this one in particular that we looked at had a correction put on it five weeks later and that went through the automated box of confusion. So now there are 21 versions of this paper, right? One is one set of seven, let's say, just for the sake of argument, is from a preprint before editorial review and refinement. Another set of seven is from edit is the published version and another set of seven is the corrected version. Now how is an LLM going to reconcile 21 versions on 21 websites and 21 templates with 21 different. You know, you can see the problem and this is why we're so concerned about, especially when it comes to biomedical information, but also other scientific information, and why scientists are feeling so confounded by what's going on with the tech industry and how it. It just seems incompatible with looking at nature without interference.
- [33:21]
A
I can't disagree with most of these points. What I wonder about though is the inevitability of our time and place and the inevitability of the transformer technology to change how we're interacting with information. Full stop. The train has not only left the station, but it's blazing. And there's a tremendous amount of utility. I work in digital health as a consultant, digital health communications as the, as the day job. And I see physicians and many specialists who have very much embraced the LLMs as a valuable sidekick and tool. To your point, you still need to be discerning, you still need that human decision maker, especially when human lives are at stake. But we're really talking about a matter of degree and a matter of utility. And with increased citations and maybe better training and more caution, the the tipping point between utility and benefit and risk seems to be shifting more toward the pragmatic end of using LLMs and the transformers more and more and more within healthcare, as a diagnostic tool, as an assistant, as a transcriber during point of care interactions, et cetera. So I understand your concern and all of this is on point, but there is that line when utility and even convenience supersede the status quo and what we considered unacceptable risk.
- [35:18]
B
I'll take your point on that. And I have a background in working in point of care content for physicians and nurses and practitioners. And so within a controlled environment, when you are totally controlling the content that is coming in and it's in the workflow and then you can use LLMs within an appropriate context that's linked to the practitioner's needs. Those are pretty good and they are only going to get better. And I agree with you, using LLMs like that in order to improve and speed ability is only going to get better. Where we have a problem is this uncontrolled clinical trial on the public that says now everybody can do your own research. That's very different and that's where this stuff gets out of control. But there are a lot of companies that are doing things very responsibly and I think to the openness part of it, the thing to keep in mind is they are not invested in you getting the right answer. They are invested in you using their product and them knowing who you are. And that's very different than signing into your ehr and accessing up to date or dynamed and doing your job.
- [36:56]
A
I think that that's a great point. Which leads me to my next question. What do we do about all of this? You mentioned this idea of siloed walled gardens of content where we know what we're dealing with and we're actually using the powerful engine of the transformer to heighten efficiency, to do stuff that otherwise we don't want to do or is a waste of time so we can concentrate on what we're good at. Quality time with the patient doing real time diagnostics that could be really impactful. Relying on information presented in a way that is really effective. Right on. And then you've got the local LLMs that are starting to spring up as well rather than relying on data centers and the frontier model. So even the, the LLM model, artificial intelligence as we know it is a work in progress. Billions in capex. It's transformed everything. So you're pointing to a significant problem. What do we do about it? How can we make the LLMs safer and more effective? And then going back to the publishing industry to the point you made earlier, the cat. The cat has left the bag. You've got all of these independent publishers, you've got a really hard time determining what's authoritative and what isn't. And you've got this public insistence on the democratization of information in general and science in particular. People have distrusted institutions for decades and now it's acute. Who are you? Who Am I. Who is anyone to say who is the arbiter of truth? I think that's a deep, fundamental issue that, not just something that I worry about, but the public is actively engaged in it and it's become the centerpiece of political discourse.
- [39:08]
C
Yeah, I mean, there are a lot of things in that. That question. So, you know, an arbiter of. I don't think any scientific editor set themselves up as an arbiter of truth. What they set themselves up to do is to run a publication for a specific audience and to give them the best information to that audience of expert researchers or practitioners. So because what the public wants or they want the benefits of science, it's like, I want the benefits of farming. I don't want to read everything all the farmers are dealing with. I don't want to watch the farm report every morning. I don't want to, you know, see your crop reports and your fertilizer bills and all that. I just want fresh food, safe food, all of that.
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D
Right.
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C
And so I think part of the reason that the public has been drawn into the battle over science is because there has been a battle over science created is because there's a purpose to that. Right. You have to ask, what is the incentive? Why would somebody do that? And part of the reason is that there is in Silicon Valley and Adam Becker wrote a great book about this, More Everything Forever. There's this idea that technology is more important than science.
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D
Right.
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C
The technology can subsume everything, that everything is going to go into computers. Whether it's your intelligence, which nobody even can define, whether it's your identity, whether it's our science, everything's going to go into computers. And through that computerization, we're going to reach a singularity. Right? And so that's where the inevitability narrative comes from. And I think it's, frankly, I think it's purposeful because they are. This is a group of people who now have become addicted to power. And so LLMs are centralized because that creates power.
- [41:17]
D
Right.
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C
That's why it's good to have like
- [41:20]
D
you were talking about the models that
- [41:22]
C
are, you know, machine learning on a little, you know, computer in your office,
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D
you know, to run an experiment and to track it. It's good to have that kind of stuff.
- [41:32]
C
It's the same reason that we need
- [41:34]
D
to have a decentralized communication space so you can compare outcomes and compare observations. Because science isn't about.
- [41:42]
C
Is kind of about the pursuit of truth, but it's really about the pursuit of discovery.
- [41:47]
D
And there's there probably. If you, and you probably know your quantum physics well enough to know that there probably is no truth.
- [41:56]
A
Well, that, that, that I just have to push back. That's one of the mythologies behind quantum mechanics, that it's just inherently random and doesn't make any sense.
- [42:06]
C
I love it. But it's a great place to put your mind once in a while though. It's kind of fun. But I think that, you know, we have to look at the incentives of the publishers who are getting paid to publish papers. That one's pretty obvious.
- [42:21]
D
Right.
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C
You're going to publish more papers. You have to look at the incentives of people in the wellness community selling bovine colostrum powder and peptides about why they're sprinkling their papers in pay to publish journals. You have to look at the incentives of open evidence and other LLMs about why they're collecting NPIs from physicians and selling ads. Because that's an incentive system. And so I think it all comes down. What is the incentive of Silicon Valley trying to put everything into a centralized computerized belief system and not. And it's about power ultimately that's their incentive. They want to be the feudal overlords,
- [43:04]
D
basically funding all the science, deciding who gets what running society. And they showed up at the inauguration for a reason, Right?
- [43:16]
A
Yeah. Talk about sycophancy. Yeah.
- [43:20]
D
I couldn't tell who was kissing whose butt on that one, frankly.
- [43:23]
A
Kissing the ring. But this is not just a problem for science, this is a problem for journalism as well, for all information.
- [43:33]
D
And we just wanted to write the book to let everybody know it's also a problem in science.
- [43:38]
B
Yes. And that some of the problems that we're seeing outside in, in society have their roots in scientific publishing. Because most people don't know about the scientific publishing industry. It's a strange platypus of business models. There's not a straight line from, you know, for, for payments and the person who buys it isn't the person who reads it. It's, it's just, it's a, it's a specialty area. But to your question of what can be done, you know, the easiest thing that's not going to happen would be for the incentives to change for the publishers. It used to be you spent most of your money rejecting papers. Right. So that you only published the most valuable content that was going to get you the best return that's flipped. And there are huge multinational corporations whose shareholders are invested in them, continue to scale and continue to grow. And so unless something catastrophic happens in that industry and it could, with some of the changes and pushback on how things are getting funded up front, they could be at risk. But are they going to go back and only charge subscriptions and contain and edit out more? Probably not anytime soon. Is the, is the Internet's appetite for, for content related to science, things that kind of evoke emotions and get them to purchase things, is that going to change? No. If people don't agree with what's going on, what a certain journal is publishing, you can spin up a new one. You know, you can break off from the main society and create the alternative society for this and that. And, and so the, the, the, the platforming and the incentives are all geared toward continuing on this road. But we do address in the book are things that, particularly societies, academic organizations who are representing their communities and running their own publishing programs, things that are within their control would be to unplug, right? You know, don't play along, you know, go focus on how to use technology to best serve your community, your constituents, make sure that your scientists members still have jobs and that have the best resources that they can get and try to weather the storm rather than throwing up your hands and say, well everybody else is doing it, we're going to do it too.
- [46:45]
A
That's tough because on the one hand you've got institutions, research facilities being doged, and on the other you've got the clickbait incentive of pure garbage getting eyeballs and asses online. So proof to all of your points is just browsing on a social media feed. I'm a science geek, so I've been targeted to get science related articles. I'll get Popular Science and various magazines and news sources that used to have at least an iota of credibility back in the day. They were vetted, they were peer reviewed, they tried to be authoritative. It's unbelievable the garbage that I get in my feed from once respected institutions. I'm a science fiction writer as a hobby and these articles are pure fanciful science fiction bullshit which are being thrown at the public as if they would be the next wave of Einstein's field equations. It's absolutely tragic what's going on.
- [47:58]
B
Well, and this is what we also call the worst advertising model. Scientific publishing right now is the dumbest advertising model ever. So somebody pays 500 bucks to publish a paper and they get a DOI and they get a citation and it looks important and um, it's probably not important enough for anyone to care about to argue with so that, but it's got a sexy headline right and so then it gets picked up by these trash newsletters that run on advertising. And so the publisher just got paid once, 500 bucks. Then the newsletter gets paid whatever they get paid. And then it gets picked up by somebody else and it gets posted on Facebook and they get paid. So everybody is getting paid.
- [48:48]
C
Everybody gets their beak wet, but the publisher only gets their beak wet once, which is a dumb ad model if you're a publisher.
- [48:55]
D
But I, you know, I think that the. These papers then get ingested by LLMs and they get perpetuated in search engines because they're clickbait, like you said. And this gets back to the core problem of the attention economy.
- [49:11]
B
Right.
- [49:12]
D
So science doesn't care about attention. Right. Science isn't more.
- [49:18]
C
Right.
- [49:18]
D
Because, you know, more, More people know about it. It's either right or it's wrong or it's either, you know, helpful or useful or it's not whatever is being described. And so the attention economy is a real misfit with science, but it's one that now, because the Internet is. Has its paws all over science, scientific information is, you know, there's just. It, it's being misused to drive businesses that really don't understand what the purpose is and are misaligned with the purpose here.
- [49:54]
B
Yeah, they don't care. I mean, content is. Content is content. Right. And if, especially if the, if the headline is Harvard study shows that, you know, you should drink red wine in the morning and eat dark chocolate before you go to bed. Right. Like they're gonna pick that up and
- [50:14]
A
they've been picking it up for decades.
- [50:16]
B
Yeah. Yeah. There's nothing. It's. It's just faster and more, More pervasive.
- [50:24]
C
Yeah. So one thing we, we like to say for your listeners is if you are finding yourself targeted by quote, unquote, science, you have to ask why. You have to look at the incentives. Right. Because we actually trust in science and scientists has not fallen that much. People still trust their physician. They still trust a val. A plausible scientific expert that they see in a. And describing something in a reasonable way. Just a survey out that they, you know, that the, the. It's been politicized so much that trust is now politicized, which is a, which is a different problem. And there's a whole history to that which we talk about in the book. But the. I think you have to just look at the incentives like I was just looking at. There's something. There's a company called Armor, which they sell bovine colostrum powder, and they have all these citations about the science that backs up their claims, 83% of those were published pay to play. And they paid for those papers to be published. So the incentives are clear, right? For like Joy was saying, for $20,000 in marketing or $40,000 in marketing, they can get, you know, a few dozen papers published and a few dozen citations they can list and they get all this, you know, perceived credibility, and then they can sell $2.1 million worth of product. So the ROI on that is insane. And. But why are you seeing this? Why is somebody targeting you with scientific claims?
- [52:12]
A
That rationale is central. Unfortunately, most people don't think that way because they're an entertainment mode. And this idea that even science and journalism and the news is entertainment rather than essential information for humane and just egalitarian society is out the window. And I think that's what fuels the attention economy. And the attention economy fuels that sentiment as well, which I think a lot of what you're talking about.
- [52:49]
C
Well, I don't know if you're familiar with Neil Postman, but back in the 1980s, he had a great book called Amusing Ourselves to Death where he predicted that the all information would be viewed as entertainment before too long, and at that point we would stop being serious people.
- [53:10]
A
One person who instantly comes to mind, and I think this is a showcase for our conversation, is Mr. Elon Musk. For $44 billion, he basically bought the world's largest and most expansive social media platform, so he could be the world's biggest troll. And he has been successful at it. Now, there's two sides to him. The one is the bloviating extremist troll who's designed to build attention and a following through outrage and owning the libs at this point. And then you've got the Elon Musk, who can land rockets, who can launch satellites, who has brought the Internet to the world and is now the world's first trillionaire, not because, or even in spite of this other side to him, but because the science works. At the end of the day, the rocket is going to take off or it's going to explode. The satellite is going to work or it won't, we're going to have a base on the moon or we won't. So I'm just wondering if the public is able to make a similar kind of bifurcation that Wall street is making that is really the underpinning of a lot of what we're talking about, which is there's good science and then there's bad science. There's and there's stuff we need to succeed. And going back to the raw utility and pragmatic aspect of good science, it's either an accurate reflection of nature, in which case we can do amazing things technologically with it, or it's wrong and we can't.
- [55:08]
C
Right? So one of the few interesting things
- [55:10]
D
about Elon Musk, right, so all of the science that he is using, the batteries in the Teslas and the, the assembly lines for manufacturing them, and the rocket technology and the satellite technology, it's very much like Tim Cook and Apple. It's all technology that came out of government research, government funded research. And Elon is simply a very good investor. I don't think he's Tony Stark. I don't think he understands most of the physics or, or any of the things that go on in the science. I think he's just a good, smart investor and he has, you know, and I don't think, I don't think Twitter X has been a good investment for him. He's lost a ton of money. He just wanted it, right? Yeah, he just wanted his soapbox. But he's a good investor. He hires, you know, the scientists and the science leadership of, you know, the satellite company and the rocket company. They are, they are very solid operators. Right.
- [56:15]
C
Tesla has not innovated in a long time and they're going to be shoved aside. But that was an interesting initial investment for him. But he's an investor and so that's one thing to keep in mind. He's not a scientist. And the science that he's invested in is pretty proven science. Battery technology, Satell, rocket technology, gps, all of these things have huge scientific legacies and a lot of government investment and hundreds of years of science behind them. The, the downside of him is what he did in Doge with USAID and the thousands of deaths that are indirectly linked to the cuts that he pushed through in order to wield his chainsaw in the government. The government funding is exactly what got him the technologies he's using to make all of his money. And then he goes into the very heart of what fed his vision and cuts things for other humans. I can't, I don't know how you can get into a headspace where any of that makes sense.
- [57:28]
A
It's not about reality, it's about perception. There's the schizophrenia that's there when we're perceiving science, entertainment, publishing and research. And I think he embodies that.
- [57:45]
C
I think you're right.
- [57:46]
D
Yeah.
- [57:46]
A
Wall street has no problem with that. Schizophrenia. They know this guy is snorting K and doing Nazi salutes and hanging out with the right wing party in Germany of all. And there's no reputational problem there with this guy running, which is now valued as the world's biggest company, at least on paper. So what, What I'm trying to get at is this sensibility that's now become pervasive. It's not just Wall street that there's an acknowledgment that this guy is a troll and he's often full of shit and he's an extremist. But at the same time there is an acceptance and understanding that he's displayed amazing competence to your point, when it comes to his investment decisions and the companies that he's ostensibly created and as a foundation for this, the companies that he's created are based on science working. So I'm trying to get at the zeitgeist of 2026 and you guys wrote this awesome book as a heads up as to everything that's wrong and that's really dysfunctional about science publishing. And I categorically agree with you. It's hard to argue your points. But what I am trying to get at is, is the ground shifting out from all of us that the legacy standards of what's considered authoritative, definitive, foundational truth, even science, is it giving way to this schizophrenic breakdown of attention, entertainment? If it works, it works. If it doesn't, it doesn't. And you know what? We're tired of the government, we're tired of institutions telling us what we could and should read. I want to be the gatekeeper. And I might not have the bandwidth to be good at it or the intellect to do it, but the freedom needs to reside with me, not with you. And everything we're talking about over the course of this hour is an expression of this extreme democratization of information. I'm not saying that it's good or the results are positive, and you and your book have highlighted both the problem and its implications. But I'm just wondering where we go from here and if the two sides can't in a sense, if not reconcile, then coexist in a way where we're entering a new world of attention, information and even science.
- [60:33]
B
We definitely are. And the consolidation and the move to more privatization has led to, you know, just the other day I think it was Scott Atlas was, was it Scott Atlas who was saying, you know, we don't need the nih, you know, let's just get rid of this and and let's privatize science, right? So Elon Musk has got plenty of money to give to science. Mark Zuckerberg gives money to science. A lot of billionaires create their pet projects, whether it's in or the CEO of Patagonia deciding to invest in conservation. And so when you talk about democratization of science by letting a few people decide what gets funded as pet projects, that's not democracy. And so I think that's the part that most of the public don't understand is that those, those nerds in Bethesda who've been deciding who to give a couple hundred thousand to a million dollars, you know, ever since, since the 1950s, have been working on our behalf. And what they're deciding to fund is, is at the outset, not known whether it's going to be successful or not. But it's an investment in the, in America turning into products, turning into cures, turning into discoveries and things like that. And so that's what I'm worried about. I think you're right. You know, we are on new ground. We're not going to be able to say, oh, sorry, all science is just for nerds. You know, you can't come in, that's out there. But I think letting people know the potential downsides, and those are going to be generational downsides, is the best that we can try to do.
- [62:41]
C
Yeah, and I'd want to pick up on the word democratization a little bit because we haven't interrogated that word sufficiently. So a democracy is an institutional construction, right?
- [62:52]
D
It has separation of powers, it has voting, it has representative government, it has laws, it has a constitution, it has all of these things. One of the things that the cyber libertarians of Silicon Valley want to get rid of is copyright, even though it's enumerated in the Constitution as a natural right of a creator, of someone who does a creative work to hold copyright on that for a span. And then legal treaties and all these other things have been democratically arrived at, right? By representative government, by voting, by all of that, you get into the institutions of the NIH and all and cdc. These are all fellow citizens, right? And this is one thing we have to, we have to undemonize the institutions because that demonization of institutions. My dad used to work for the government in the Forest Service and the Department of Interior.
- [63:45]
C
He always felt like he was represent doing what was best for the American public, for American citizens. He knew he was a civil civil servant. Right? These are civil servants. They're, you know who they are. They're named. You have, you can look them up. You, they're identified. They're. It's all transparent. You get into these other funding sources. You get into these other media sources. We don't know who is adjudicating information on Twitter. We don't know who is adjudicating information on Facebook. We don't know who is adjudicating funding decisions at Czi Chan Zuckerberg Initiative, which is an llc, by the way, which operates for profit. We don't know these things. They're very opaque. So that's very undemocratic. We don't, you know, even, even the, you watch the current administration in the Health and Health and Human Services, they squirm under democratic scrutiny because they're very uncomfortable with it. Right. Russell Vaught is trying to make it so that politics will drive decision making. And there's a historical precedent for this, which is Lysenko in Russia, who in a matter of a few years set back Russian science by decades. And they've never caught up because this kind of stuff was going on. And so I think I am a big fan of actual democratization, which means representative government, adherence to laws, respecting the institutions we've established to operationalize things that we've prioritized as a society, transparency about those things. I think FOIA needs to be revised because that's become undemocratic, but that's a whole different subject. But all of these things need to be. We need to. The word democratize has been appropriated by people who really aren't. Are anti democratic at their heart. They want to get us off balance. They don't respect the institutions, they don't respect the democracy. They're undermining the democracy. They want to put themselves above it and outside of it.
- [66:01]
A
Yeah, it's. It's like you hire an arsonist to burn down an institution because the institutions corrupt. But then you got an arsonist hanging
- [66:16]
C
out in your, in the fire station. Yeah.
- [66:20]
A
Burning down all the other buildings with it.
- [66:22]
D
Yeah.
- [66:23]
C
We're going to a fire like being
- [66:25]
A
married to the mob. You know, you're getting extorted by one institution, so then you hire another authoritarian institution. Institution to get rid of them. And you're basically just swapping one warlord for another. And I appreciate the point both of you are making, which is power gets centralized.
- [66:45]
D
I think the scientific institutions of the
- [66:47]
C
US have been generally quite effective. We are, we have, we are the end. We have been until recently the envy of the world when it comes to the technologies that we're able to produce the science we're able to produce the findings we're able to produce, we've dumped. And economically, every dollar spent on Science Returns 5. So it's a great investment as well. And we need to keep track of the fact that societies invest in science
- [67:22]
D
because it gives them advantages.
- [67:24]
C
And you need scientists doing the science.
- [67:28]
D
And again, having it made opaque in
- [67:31]
C
the hands of a few powerful techno authoritarians is not a good idea.
- [67:38]
A
Agree. But going back to that idea of perception versus reality and how we started this conversation was really the COVID pandemic. And that by any stretch of the imagination, created fissures in the public's trust of institutional science, especially health science, the cdc, the way we responded to the pandemic, the way we're communicating the pandemic. And I understand there was a certain administration flip flop that happened throughout the pandemic. There was a lot of unknowns, and science learns as it goes, it can change its mind. But frankly, there was a lot of bias, there was a lot of lying, and there was a lot of miscommunication. So whereas I agree with you that institutional science going back to the Library of Alexandria is the greatest human accomplishment ever as far as learning and research and growth that way, I think it sucked in terms of public relations and communicating with the public. And I'm not trying to blame the victim here. I'm merely saying that this didn't come out of nowhere. And I know the Internet, as you described, was instrumental in the polluting of science and the mess right now. But I think that the institutions that you describe and justifiably consider hallowed have been deeply flawed in terms of how they communicate with the public. And the COVID pandemic, pandemic in particular, was a moment where they really, really dropped the ball in terms of handling the pandemic and also communicating with the public. So if there's a silver lining in any of this, we're talking about what can we do to fix this? And you and Joy have talked about many specific things that publishing industry can do to disincentivizing this mess. I think those are great best practices. But the science community and the institutions that we respect need to take a good, cold, hard look at themselves. Joy, just like you acknowledge this is the moment where, you know, it's a brave new world. And I think part of that transformation has to come from within.
- [70:01]
D
And we agree.
- [70:03]
B
I think. And to your point, the pandemic shined a huge spotlight and. And the cockroaches had to scatter Real quick, you know, because science and these institutions and the scientists who've been, you know, slaving away at the bench, who, who take, who took decades to develop the technology that have the vaccine. They were operating in their own, in their own world. And we only knew what scientists did when something good or bad happened. And there's a lot of stuff that goes on in between. And what it's, what it's supercharged is this idea that science should be happening faster. We need more results. You know, we've got to dump more money on why haven't we cured cancer yet? Why haven't we done this?
- [71:00]
C
Why did I wake up this morning and there's not a solution?
- [71:03]
B
Right. Yeah. And so, so, and so that's because we were all at home. We were, you know, we had a captive audience who's like glued to the screen and reading what we can and,
- [71:17]
C
and, and the attention economy was in hyper, right?
- [71:21]
B
And then the, and the publishers are like, well, we got to make everything free just in case someone can figure out something faster. And so that is, that is, that is something that has set, you know, that ship has sailed. And I think our scientific communities are going to be continually compared to somebody else's promise of a better solution, whether it's an alternative treatment or if it's, you know, it's a private lab that's going to do something that's created this appetite and it's this distrust in, in the methodical process of science. Again, never been perfect, it was, never will be. But, and so this is a challenge. And so there's, there are organizations who have, have sprung up in the last couple of years trying to figure out how to be better communicators of real science and especially public health to the public. This is a job that didn't exist a couple of years ago. And there are a few, you know, bootstrap organizations with really dedicated people who are trying to permeate the attention economy in even a fraction, with even a fraction of the success that the pseudoscience anti science people have already have. They have a head start. I would say that it's a challenge.
- [72:55]
C
The COVID period, and we go into it a lot in our book, but that was basically a lot of the open movement, opened a lot of gas cans in the garage and the fumes were building up and then Covid was the match and everything blew up into a big infodemic.
- [73:14]
D
Right.
- [73:15]
C
And the institutions were rocked by the explosion too.
- [73:19]
D
Right.
- [73:19]
C
They, they, they didn't they. And that we, I kind of wish we'd written the book before the pandemic because they didn't appreciate what kind of information economy they were operating in. They thought it was still 1995.
- [73:32]
A
Right, great point, great point.
- [73:34]
C
And, and so they were caught off guard. And then you had the first Twitter president who was using social media to, you know, every night to get in front of the experts and throw them off balance further. So it was just, it was, I'm not sure. I think the institutions need to. And part of the reason we wrote the book was to pull the alarm cord and say this is an information environment that's very different than the one you thought it was and you need to behave differently in this information environment if you're going to do what science does.
- [74:11]
A
Love that central thesis and an adjunct to that is the not the cat but the elephant in the room, which is education. In America, we complain that there's a lack of civics education which precipitates part of our polarization, our inability to do any critical thinking whatsoever. There's no such thing as a nuanced political discussion anymore. And conversely, where's the science education? What do people really know? Do people even know, going back to Covid, what is a virus? How's the virus different from a bacteria? How does transmission take place? MRNA? What the hell is that? How can you criticize a new technology when you literally don't even know what you're talking about?
- [75:03]
B
Well, you don't have to know what you're talking about because other people are shoving their interpretations into your feed and directly into your brain.
- [75:15]
A
I'm a science geek. I could be a little discerning. I can call bullshit. You need to train people to call bullshit for themselves. That's the core issue.
- [75:27]
D
So I, I'm encouraged. I, I interact with young people for a variety of reasons as, you know, as a teacher and, and otherwise. And I'm very encouraged by the fact that they grew up with the Internet and they have really good bullshit detectors now. They, they generally. And they're also very committed to being offline there. I was just listening to a podcast where the hosts were talking about how it's the 36 to 65 year olds that are the trouble spot because they still think the Internet's cool And anyone under 35 thinks the Internet's a drag because they saw their friends struggle with it in high school. They saw the damage that they saw. You know, somebody committed suicide or somebody had to, you know, was doing self cutting or whatever. They saw the downside of it and they saw their parents on the phone, you know, ignoring them when they were growing up. And so they, they are, you know, going to, you know, to sporting events and to gyms and they're meeting each. They're living in meat space and much more dedicated way.
- [76:36]
C
And they also know. I was talking to a physician a couple of weeks ago who uses one of the LLMs, and she said, ah, you know, sometimes I'll use it to, you know, to kind of just get my mind, you know, provoke a thought, see if, you know, if, if I'm missing something or if I, you know, just, just to get my, you know, because I'm busy and I'll just take a peek. But she, she says, I know that they're selling me, you know, my information out the back door and I hate it. So, you know, these people are very hip to the games that the now elder statesmen of the Internet think are so clever and subtle. And I think the next generation is going to, you know, gradually make these things less relevant and insist that they're good.
- [77:22]
B
We do talk to a number of professors from time to time, and it's interesting one we were talking to a couple weeks ago, young ones. Yeah. Who said the difference between the freshmen over four years, the freshman sophomore class as they graduated versus the next one is night and day. It's like there's like a hard line between, in terms of their adoption of AI and even wanting to use technology at all. And so the ones who are coming up behind seem to be more curious and more invested in their own agency. So let's just keep.
- [78:09]
D
Encourage that.
- [78:12]
C
Go, kids, go.
- [78:13]
A
Always the human hopeful default, right? Which is what Churchill said about America. America will do everything wrong until it finally does the right thing. So something like that, right. And I think as a society, we succumb to that, but at the same time that that's our parachute, hopefully that every action has a reaction, that this tsunami of bullshit might have a silver lining, which is creating a younger generation who's more discerning and has had enough
- [78:47]
C
of it and who have read our
- [78:49]
A
book and read your book Full Circle, which is. Thank you, thank you for your book, which is how the Internet disrupted science, which is the more we know, the more power we have and the more we realize how manipulated we are. And that's an opportunity to push back. I do want to cite the Austrian philosopher of science, Paul Feyerabend. He wrote a book called Against Method. Way back, I think in the 90s, and it was all the rage in the academy for A while. And his idea was that when you're, when you're seeking that paradigm shift in a Thomas Kuhn kind of nature of a scientific revolution, where you're at an acute point of crisis and then you need something new, you got to break the mold, you got to break the model to really make that quantum leap. So if you believe in Einstein automatically, Newtonian classical mechanics isn't just evolved, but it's wrong. It's a different model of reality. My additional hopefulness is that out of all of this nonsense and distrust and the breakdown of institutions, that we could reformulate how we share information, how we conduct research, so that it can be truly democratic in the sense that you described, Ken, that we learn some of the lessons of this moment of crisis and we can break open how we do science to be more open minded, to suffer less from the implicit biases that frankly have been holding science down. And perhaps some new and amazing innovation can come out of this train wreck when we finally are shaken up to the point where we reject the nonsense and embrace new ideas we otherwise might never have. Yep.
- [80:48]
D
And just make sure you, like you
- [80:49]
C
said, educate the, the young ones and fund the scientists.
- [80:56]
A
Absolutely. And draw a distinction and educate yourself.
- [81:01]
B
Yes.
- [81:02]
A
At the end of the day, it's all on. The individual power of democracy rests with its citizens. And we all need to take personal responsibility to better educate ourselves and not succumb to this attention deficit disorder that is the Internet and is now AI.
- [81:20]
D
Yep. Well put.
- [81:22]
B
Question authority. I mean, one of the problems that has gotten us here with this, with within the scientific publication community is that they have been marching to, to meet the same metrics over the last 30 years when everything else has changed. You know, why are we doing that? Why are we trying marching this way when the world is going this way? So we're totally with you. We've got some ideas. You got to break things sometimes to start.
- [81:51]
C
Remember that the two words that start every great scientific discovery. That's weird.
- [81:58]
A
I think that's a great way to cap it. Which is at the heart of the wonder of childhood. That's weird is looking around at nature and our universe and saying, wow, we're sentient beings in a three dimensional space that's maybe 100 billion light years across from what we can tell. And wow, this is really something.
- [82:29]
C
Truth is stranger than fiction.
- [82:31]
A
We've lost that wonder, we've lost curiosity. And if we stay curious, we're way more capable and excited about calling out bullshit and embracing not truth, but at least a more viable pragmatic and effective path to getting us there.
- [82:52]
C
Totally agree. Well put.
- [82:54]
A
Thanks so much for your book. Ladies and gentlemen, Kent Anderson, Joy Moore, the co authors of how the Internet Disrupted Science and It's coming out August 4th. We're going to get this up and out as our own little launch party for you and if you're not watching us already on YouTube wherever your podcasts are found, like subscribe, comment in this information attention starved economy, at least have a message like this percolate up through the noise because this book is important and I think it could help get us where we need to go, which is cutting through all the nonsense. Thanks so much Kent and Joy for joining us and I'll put the link to your book and bios and a little synopsis of our conversation in the description below. Thank you.
- [83:48]
D
That's awesome.
- [83:49]
C
Mookie. Thanks for having us.
- [83:50]
B
Awesome. Thanks so much.