 This is Mises Weekends with your host Jeff Deist. Ladies and gentlemen, welcome back once again to Mises Weekends. Very happy to be joined this week with an in-studio guest, our own Jonathan Newman. Some of you know Jonathan as a fellow here at the Mises Institute, a recent Ph.D. graduate. So he's now Dr. Newman, one of the first people through the new Auburn Ph.D. program and also a frequent author and blogger for us. So this weekend we are talking science and scientism. Jonathan wrote an article called Neil Tye, The Scientism Guy just a couple days ago. And of course this all comes on the heels of the March for Science, which occurred throughout several U.S. cities last weekend. And also Neil deGrasse Tyson and Bill Nye, the science guy, have both been in the news quite a bit lately. The latter with his new Netflix show, ostensibly dealing with science. So it's very timely. I enjoyed the article very much. We'll post a link to it. So let's just kind of go back for a second and talk about this March for Science and all these things that are happening. There seems to be sort of a conservative versus liberal battle going on in the country where progressives are sort of implying that conservatives, particularly Christians, are scientific illiterates and that there is objective truth out there as opposed to fake news. And so your article is kind of bound up with what's happening in the U.S. right now. So talk a little bit about what prompted you to write it to begin with. Sure. Well the immediate or direct thing that really triggered me to write this article was a video by Neil deGrasse Tyson. And basically he was just summing up a lot of the things that we heard in the March for Science and other people. But yeah, you're exactly right. So there's this big crowd. There's this big, massive people who say that if you disagree with this set of policy, this set of policies usually on the left-hand side, then you're just an idiot. You just don't understand the science behind it, as if the science just sort of gives way to this set of policy recommendations. Well, you start out talking a little bit about scientism and economics. Some people seem to forget sometimes that economics is a social science and hence not necessarily applicable to the same scientific method that we talk about in physical sciences. Tell us a little bit about what Mises had to say about scientism, especially with respect to econ. Yeah, so this was a big issue for Mises. He definitely closely guarded the boundary between economics and other sciences. So Mises' position is methodological dualism that empiricism, the scientific method, doing experiments and making observations is especially suited for the natural sciences. So we can go up to the top of a building and drop a rock and we can test how fast it falls to the ground and we can do that over and over again and it's very repeatable and we can do it as many times as it takes to come up with some sort of general conclusion. But that method doesn't really work for the social sciences. So there's this big categorical difference between the way inanimate objects behave and the way humans behave. So humans obviously have this capacity to make choices and so there's no way to set up some sort of experiment where you could come up with this general constant relation that has to do with human choices. So that was Mises' view. But today, in a lot of PhD programs, I mean there's a lot of mathiness, right? There's a lot of emphasis on empiricism and testing of hypotheses. Is it wrong for economists to say, well, I have a theory, I have an economic theory, it's a hypothesis, I'm going to go out and test it and depending on what I find out empirically, I'll maybe revise it. Even Austrians see some benefit in empirical work. Yeah, you're exactly right. So the big difference is when we're constructing economic theory we use logical deduction or as Mises called it, we go through the logic of action or praxeology as Mises called it. But there's definitely a place for empiricism even when we're studying human behavior but the big question is what counts as economics and what doesn't count as economics? If you're just sort of looking at how much people spent on McDonald's during the last year, is that really answering an economic question? Are you constructing economic theory or are you just looking at some sort of historical fact? So the question is what is economics and what is economics not or what isn't economics and not necessarily whether or not we should be doing as much empirical work as we are. Ordinarily, you see academics sort of guard against mission creep by other fields and specialties into their own. It seems like economists have ventured into statistics and math and all kinds of data collection without much howling from some of these other fields. But I'm sure you've heard the criticism as I have that Austrians particularly suffer from excessive a prioriism that they're too focused on deductive truths that we can observe from human nature that don't necessarily need to be tested and that this hinders Austrian proponents in terms of real-world effectiveness. Yeah, there's certainly a level, there's an era of sophistication that comes with having a big graph behind you when you're giving an academic presentation. So a graph with a bunch of numbers, a lot of people say, oh, wow, that's great. So the Austrians definitely don't have that era of sophistication when it comes to these high-powered mathematical models. But the question is, which is closer to the truth or are we doing economics when we're doing it the praxeological way or are we doing economics when we're trying to do it the empirical way? But beyond just methodology if something is proper economics or not proper economics or perhaps some other field, how has scientism infected economics or how has it harmed it maybe? In my opinion, you can use statistics, you can use data to come up with any sort of conclusion that you like. So a lot of times what happens when we're doing economics we're sort of on the way towards a policy prescription. Maybe that shouldn't be the case, but when you're using stats, when you're using data, there are ways that you can twist it around to get whatever conclusion that you'd like. So in that regard, economics is certainly hard because we're not really doing real science. We've got this policy recommendation and then we torture the data enough until it tells us what we want it to say. Well, it's interesting. As a little bit of a side, Walter Block shared with me some email exchanges he had with the late Gary Becker, the Nobel Prize winner who had been an advisor to Walter, I guess, on his PhD. And he had similarly voiced this complaint that Austrians would benefit from more empiricism and more mathematical work. So Walter pushed back a little bit and said at what point would you accept as an a priori truth that all other things being equal raising the minimum wage reduces the demand for lower skilled workers. And so Gary Becker ultimately sort of acknowledged this point by Walter and said, I think I can agree with your a priori observation. But we don't have people asking in mathematics, for example. We don't continue to empirically test 2 plus 2 is 4. I assume no one's empirically testing gravity or certain laws of physics or thermodynamics. Yeah, or the example of an article with the Pythagorean theorem, that just doesn't happen. But for some reason everybody thinks that it's okay to try to do that in economics. But when we get beyond some baseline knowledge in let's say physics and we get to something that's actually very complex, like the fluctuations in the Earth's temperature over millennia, then we start to talk about settled science and politics comes into it and we start to get beat over the head by the Bill Nye's of the world. So talk a little bit about how you discuss in the article how politics plays a role in politicizing science. Well, I think everybody should sort of their skepticism should turn up a little bit whenever they hear this term settled science, especially when there's a policy recommendation right after it. Because I go through a few different examples in the article of where even government programs that had the backing of the scientific community and the backing of settled science, they had to backtrack. They went back on what they originally started doing. I go through the example with DDT, which was controversial with some of the commenters and with the food pyramid and a lot of the nutritional stuff. And also, since we just celebrated Earth Day, there were many different predictions that were made in 1970 that turned out to be just totally wrong. And so there are plenty of times where we've seen the scientific community has some sort of some conclusion and then the government connects some policy based on that conclusion and then everything has to go backwards. Everything has to be overturned. But it seems to me there's an inherent contradiction. There's a hypocrisy in saying that the scientific method is the way to go. Things are testable, verifiable, falsifiable. And then also saying, well, this is settled because if the scientific method applies, then new data can always come into play. Right, exactly. You know, the thing that worries me, Jonathan, this isn't just necessarily in public policy. It's also, unfortunately, what we have to call public health, which is there's a lot of government-funded research that goes on out there. And the Bill Nye's of the world would have more of it and less private funding, presumably. Does it concern you that government funding and then you start talking about settled science that is sort of narrows and mainstream research? In other words, if you have a really off-the-wall idea about cancer, you're probably not going to get funded by NIH or at your university. So it tends to maybe limit scientific advancement rather than furthering it. Yeah, you're right. So it'll limit it and also there's a question of whether it'll bias the results. So a lot of times if some, if there's a lot of money on the line to get some sort of result, then the researchers who are doing the science might be more inclined to get that result that they're being paid to find. And so, obviously, when there's a lot of money on the line and when there's a lot at stake politically, then scientists might be more inclined to fudge the numbers a little bit or they'll torture the data until it gives them the result that they want just so that they can please the people who are paying them. So yeah, it's going to limit the amount of science that's done but also there's a chance that will bias the science as well. Jonathan, what amazes me is that so much of what we see in social science is really decidedly unscientific. If you look at sociology or women's studies or feminist studies or even history, you'll often find that far from an objective framework or perspective, there's sort of some preferred results and the scientific research, the peer-reviewed articles all sort of try to reach that result. It's conclusory rather than truly scientific. Yeah, exactly. So the way science ought to be done is that you have some hypothesis that you're trying to test and so you proceed forward that direction but a lot of times what happens in some of these social sciences like you mentioned but also even in the natural sciences there's a conclusion first and then you're trying to get to that conclusion so that you can add your name to the list of scientists who have the same conclusion as everybody else. But how do we reach that? You've recently earned a PhD so you've been through quite a bit of higher education at Auburn which is not a left-wing bastion but not a right-wing bastion either. Talk about some of the ways that you saw this. How does this seep down throughout academia? One of my big things is being careful about the way we make causal claims in our papers. So in my dissertation I did use some empirics. I used some econometrics. I was looking at some old survey data about how reliable student responses about their own GPAs were and so I had to be... I was very careful about the way I would make causal claims so I didn't say that this impacted this because we have this regression that has this sign on this variable. So I think a lot of it comes down to just being careful of the way we word things and that when we say something causes something else then we have to be very careful about what's backing that up. One of the things that concerns me is that we're assuming that scientists and academics are necessarily well-intentioned rather than weaponizing science to use it as a bludgeon against us to forward certain public policy prescriptions and you talk about that a little bit here in the end of your article where you say that the end goal of these science marches is of this bigger government. People like Neil deGrasse Tyson would say how did we rise up from this sort of backwards country? Well, it's because of government funding and government research and that this is the path forward. There seems to be an anti-market bias in the march for science. You're absolutely right. So there's this worldview problem among scientists and I just got done watching a few episodes of Bill and I's Netflix show and you see it there as well so there's this complete denial of the market being able to produce anything or do anything of value. I think they had one small segment about can we actually go to space with private firms but there was this big question and I think they ended up with the conclusion that the private firms are going to have to work with governments so that they have the adequate resources to go to space and so yeah, there's this big worldview divide in these popular scientists like Neil deGrasse Tyson and Bill and I where they don't trust the market. They don't see the market at work for people. They don't see the benefits of free markets around the world and so there's this heavy reliance on government and on all of these government interventions to sort of give them what they want which is more government funding for their own science. Well, it's ironic that the people who are charged with finding objective truth are now apparently joining the chorus of people who are telling us to shut up and stop asking questions. Jonathan, thanks so much for your time. Ladies and gentlemen, have a great weekend. We'll see you next time.