29: Metascience, Economics, and Longevity with José Luis Ricón

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Hosted by
Will Jarvis

In this episode, we talk with José Luis Ricón about longevity, soviet economics, education research, metascience, and so much more. José blogs at nintil.com.

Some resources mentioned: Scientific Freedom by Don Braben.


Will Jarvis 0:04
Hey folks, I’m well Jarvis along with my dad, Dr. David Jarvis, I host the podcast narratives. narratives is a project exploring the ways in which the world is better than it has been the ways it is worse in the past or making a better, more definite future. I hope you enjoy it.

Will Jarvis 0:33
So Hey, folks, today on the podcast, we’ve got Jose Ricon, Did I pronounce that right? Yeah, that’s more or less, right? More or less. Right. Okay. Anyway, how are you doing today, Jose? Great. Thank you. Great to be here. So Jose, I just wanted to get started. Can you give us kind of a brief background bio, and just tell us the name of your blog, so people know where to go? Yes. So I’ve looked at this website called lintian.com. And I blog about various topics. Over the years more recently, I’ve been writing about science or the way science works with what some people call meta science. And that’s in my corner of the internet, we like to call progress studies. And I’ve also been writing about some specific aspects of one particular kind of science, that is longevity research and aging. I’ve also been writing about that. And in the past, I’ve written about economic history. And in particular, I wrote this very long series of blog posts about the Soviet Union and its economy. That’s great. That’s super. And I might end up asking you about longevity, I didn’t put anything in the in the outline. So I missed that one. So I just wanted to go ahead and get started with, you know, should we fund people or projects and science? So we had Don Braden on a couple weeks ago. And he was he was talking about scientific freedom and how things have kind of gone wrong. So yeah, at a super high level, people projects, which are more important, you know, VCs go back and forth on this all the time. And that’s for companies, but in science, which are more important.

Jose Ricon 2:01
Well, I guess the the lazy answer, although it’s kind of correct, it’s one of those, but right to get to ever need more context. And maybe we could start with what Brian is saying. So he, he, for example, has this notion, this idea of the planned collapse, this is Max Planck and other like I’m saying another bright physicists from from the 20th century, that literally, they were not funded by grants in the modern sense, they were just funded by universities, they had tenure effectively, and they could do research on whatever they wanted. They didn’t have to justify themselves periodically to maintain their their status. And so they could, just as the theory goes, they could think very long term and, and pursue whatever is that they wanted to without being worried at all in five years, I need to produce a piece of research to actually get the next grant grant, and so on and so forth.

Jose Ricon 2:46
Now, Braben, doesn’t say that all science has to be like that. It may be the the like, initially, it seems that that’s what he’s saying. But rather, he’s saying that we should go more in that direction. But Brian is saying that for a specific kind of science, that is for breakthrough science, or science, that it’s difficult to evaluate At first, the fun people approach might be the right one. There might be other reasons why so be the key reason for this is that, suppose that let’s say, the next Einstein comes to you and says, I just want to fumble around and think about, you know, physics and and what is, what is life? What is life? It’s very philosophical, assuming we have questions, as in, he doesn’t tell you, I’m going to stick this question a little bit. Our I went to med tech, Newcastle dragna. He’s like, I used to think about physics, you know, maybe we went somewhere not, that would be very strange in today’s funding environment, I was breathing would say is that if we, if we don’t have a place where people like Einstein, or people that will be funded, will be better suited for this fun people model? Then we’ll be missing out on lots of very interesting ideas. Yeah, and it seems like when we talk to Don, his, his big idea was like, used to be, you could if you were Max Planck, and he wanted to work on thermodynamics for 20 years, you know, you could get a small amount of money. And you could just work on that for a long time. It wasn’t, in other words, that there wouldn’t be a ton of money, but it would be enough to keep you going and kind of pursue your passions. And this is really important for basic research and creativity. Yeah, in implants, so implants on case my last post was, incidentally, I looked at appliance history supplies most famous, most famous for the idea of the condensation of energy, this is that energy. They’re like small packets of energy, the famous quanta.

Jose Ricon 4:30
And these can be used to explain for example, the, the progression of spectrum of Blackboard as a given temperature, that otherwise the equation doesn’t really fit with that CPM. We’re assuming that doesn’t fit with actual observed data. So Planck got his PhD around 1879. Wow. And then, and then, but the thing is, if you look at most things I’d most be, be very frank and things that he published, you find that he’s seemingly he’s he’s some he’s Muslim as well. These papers, I was going to say enough energy were from 1900. That is indeed. So when when braven says 20 years, he refers to the center years, 20 years from PhD, to doing interesting, recognized work now blank, blank did actually publish stuff in between. Here’s another place like just thinking he was probably, but the stuff he published about is so obscure that no one really pay attention to eat. And it’s not even in English. It says you have to learn German, to its obscure papers, but they exist or they are there. It’s just that, that if you were to judge plank, let’s say 10 years into his career, you would you say, Oh, this guy is not going anywhere, like the and yet, had you done that you might have missed out on the 10 years after actually he got a very interesting point

Will Jarvis 5:40
where he actually made real progress.

Jose Ricon 5:42
Yeah, now it’s it’s it’s a it has to be said that it’s not like he was thinking on the same brawler for 20 years, he was exploring various areas up until he found a very interesting problem to work on. So I guess in the more pessimistic case, the current system would have pushed plank towards a more safe and established areas of research. But you could conceive of another case where plank actually gets grants to quote, safe work, but on the side he’s actually doing and thinking that would be interesting and stuff. And indeed, this is what happens. This is very interesting blog post that my friend Alexei goosy, wrote, I think it’s a blog post, how life sciences actually work. And he describes the interview with a bunch of scientists, and this is what they do, they will ask for a grant to do X, but actually, they will do something else, they will just they will do the actual thing they were said they will do but on the side with some money, they will do their thing, they actually want to do a side thing, which is not ideal in that the ideally that is totally aligned with the researcher. But it’s an interesting workaround for this kind of if you want to still experiment within the system.

Will Jarvis 6:46
Right? Well, and it does seem like, you know, I’ve seen this a lot with my friends, I have a lot of friends that are research scientist and RFP comes out and it’s like, well, how can I fit my research into this RFP, you know, there’s got to be a way, right. And if you’re, if you’re a good salesperson, scientist, you can make that happen. My worry, though, is if you’re, you’re weird, and you know, you’ve got these different ideas, it’s hard, and you’re not maybe you’re not a good salesperson, you get end up getting cut out, and I’m one of the best people, you know, you end up kind of specializing you’re either a good salesperson or a good scientist. And we’ve kind of selected out that out of the equation.

Jose Ricon 7:19
Yeah, there’s there’s this very funny anecdote from the I think he was the research director at the Rockefeller Foundation, I think, perhaps prior around World War Two Anopheles before rafter. But basically, he wrote this brief handbook that he would use to train new analysts coming to the Rockefeller Foundation, the Rockefeller Foundation is the place that pioneer the frontopolar projects approach. So these days, people usually associate the idea with our huge Medical Institute, but the Rockefeller Foundation was also doing this kind of thing where like very hands on lots of interviews get to know that the researcher actually going to their to their house just to have dinner with them going going to their labs and really getting very personal with the scientists to really see their actually deserve the the funding. So when he spoke, he said his anecdote of this guy that he tells us, like very, very bright person, the smartest chemist, I know, but like, he doesn’t wear shoes, and like he smells fear. He’s a pretty strange person like he he would never collaborate with anyone or someone so forth. Yeah. Which, which I mean, just like honest, like he said, like he wouldn’t find this person in meaning meaning that that to some extent science also requires or in some context science requires of service even back then some of these salesmanship techniques and fitting system exactly that, that maybe it maybe it’s the case that some people require individualized, lifelong funding to their weird thing. I guess, one, one example would be this. The Surfer physicist Garrett Lisi, he’s in Hawaii surfing and doing physics research on his own, and the theory of everything he’s thinking about. And yeah, that’s right.

Will Jarvis 8:45
Yeah. Interesting. So it seems like it’s kind of this interplay. So what is the whole day? How they in principle, you know how to pronounce it? I don’t I’ve just read the Wikipedia entry.

Jose Ricon 8:58
Yeah, see how that how that principle is an idea, or, or an idea or value to inspire how science should be organized and vague. And well, that’s what it states and this seems to be a foundational principle in scientific organization and funding throughout the world. of the disadvantages in the UK, is that scientists should decide what scientists do not necessarily isn’t necessarily that that that I should start my research but my peers who judge me on scientific funding should be allocated with input from from scientists that is that that societal needs should not directly impose or constraints the research. This is kind of controversial for various reasons. Because possibly, society’s findings, a scientist, a lot of Sciences is done privately, but a lot of it, especially basic science is publicly funded by taxation ultimately. So ultimately, scientists are accountable to society in what they do, and scientists. They are not being paid to, to have to have fun and think about nature they’re having paid to produce. This is a really interesting philosophical question. What is science for what? What a society are we asking of science? Are we asking actually asking them to produce knowledge? Or are we asking them to produce useful knowledge that can be used for inventions? Maybe it is a probably a smarter people or people that are probably closer to making decisions or on science or bias towards the sign for a stick of science or military knowledge. I mean, like, me personally, I personally like to learn about like, Oh, this weird, this galaxy, black hole thing, right be useful for like having faster cars? Probably not. But it’s cool to know, now the most people care about those things relative to putting the money, let’s say on energy, or energy in his researcher or cancer research. Right. So so it’s it’s kind of Yeah, it’s kind of tricky. And unfortunately, politically, it’s kind of difficult to say, Okay, well look at your budget, your testing theories, because we do put this money on cancer research. And it seems that that bargain was achieved back then, whereby scientists said, Okay, well, if we’re going to do it ourselves, just like that. Politicians would like metal that. And that’s right, that’s exactly right, back and forth over the years. So to what extent should science to science govern govern itself, or where science is too important to be left to the scientist, and that we should actually impose more structure from the outside?

Will Jarvis 11:09
Right? It This reminds me I am in the middle of a book by Do you know who general groves was? Yes, the the Manhattan Project that he ran the Manhattan Project. So he wrote a book about the experience, which is quite good. And I really like East Tennessee. So you know, it’s all about high select the side needs, you know, building all this infrastructure. And it’s fascinating to me, because he knows, you know, he knows very generally how the science works. But he, what he knows what he really knows is how to get things done. And so he’s not he’s shoving the scientists in to these, that, you know, he’s like, I know you have these pet projects you love. But that’s not what you’re working on anymore.

Jose Ricon 11:46
Yeah. He He was an army guy, right?

Will Jarvis 11:49
That’s right, US Army Corps of Engineers, Brigadier General. And it’s really interesting how we selected Oppenheimer, like the intelligence agencies didn’t want Oppenheimer, because he was a socialist. Oh, yeah. I was like, this is the best guy. I don’t care what you say, in the entire book, you know, if there’s any takeaway, it’s like, wow, there’s something about kind of that two in the box leadership team, where you’ve got the scientist, you’ve got this, like, extremely competent manager. And they’re both making it work. So you have the technical lead, and the managerial kind of business side laid, but it is true. So what do you think about that it? Should it be scientists running all of this? Is it? Or, and you know, Manhattan’s a special case, right? Because we needed something? Great. There’s a clear problem. Yes. short timeframe we needed it on? And we could speed it up like that, in the short term.

Jose Ricon 12:35
Yeah. Yeah. Seems to be. So I was mentioning earlier that we’re not doing projects, funding projects or funding people, it depends on what you want the scene if if what you want is more or less well defined, let’s say you want a nuclear bomb, or let’s say you want a human genome, or you want a new avatar microscope or whatnot, then it seems that it’s easier to just define milestones and deadlines and and do some break management that of that, because ultimately, you know, the goals and you know, more or less the distance from your, from your to the goal, and you can express things more easily. And this, for example, what’s behind this, this idea that, you know, I don’t know if you know, that milestone. Well, so he, he’s working at ashmit futures. Now, he used to work at DeepMind. And prior to that he was working with your shirts and advice on on mapping the brain and other things for a while. And he has this idea of focus research organizations, the idea here being that there is a missing gap in it the same way that you could argue that we need more fun people we need to, for example, the physicist Lee Smolin says that, that we only need to find like 200 of the best physicists or just leave them alone. And with only those 200. Like, there, there aren’t enough people that you want to give that funding to, but you just set them aside and let them do crazy stuff. Medicine says, we also need to do that for projects as well, we need to find that there is an intermediate scale of projects that they’re there. They’re kind of like mini Manhattan projects that could greatly benefit science. But that cannot be done in the usual academic context. Because they either don’t require too much money or that require an aerial or an organizational skills that are more commonly let’s say, startups or or regular corporations. I guess I an example of an fo in the Bible, some sense would be either the Manhattan Project itself, or more recently, neural link, neural link. Ultimately, what they did was to take the state of the art across different parts of the BCI world, that and then they package them together and solve a bunch of integration problems they had. And that’s it. They didn’t create a new paradigm of BCI or any like, the objective was clear the technology was there at that last push that demo commercial. So yeah, so the the idea here is that you that there is also besides funding people there so products that are worth funding, and that will also be really good for for science.

Will Jarvis 14:47
Gotcha. That’s interesting. So it seems like you’ve got like, do you remember the Rumsfeld speech? He’s like the known unknowns, known unknowns. Yeah, so I like to think sighs about science planning like that. So there’s some things you know, we kind of know they exist. And we can see like an achievable roadmap and other things we just don’t know much about at all that maybe some curious people are interested in. And they need to be funded somehow. And then there’s like, you know, super concrete things. And there’s this whole range, and you kind of need to make sure each area is well taken care of, or because if you don’t have any basic research, you know, eventually, where are you going to get your tech from? In real application? I don’t know. Does that make sense?

Jose Ricon 15:25
Yes, but also vice versa. So there is this idea, this idea in economics of innovation, that’s the so called the linear model is the idea that you have basic research that feeds into applied research, and then from the plight we get into into applications, but sometimes it’s the case that applied research or tools or engineering is necessary to them as a researcher, for example, as an example, if you have a microscope, if you have a microscope, you can see it’s more things right. So, so so so for example, it could be that to be more basic research, you need, let’s say, new data sets new or new tools to actually go go back in a loop to do the basic research.

Will Jarvis 15:56
Gotcha, gotcha, that makes a lot of sense. So it’s all it all there’s a ton of interplay. It’s,

Jose Ricon 16:02
it’s like the conspiracy theories like to say everything is connected. I think that’s

Will Jarvis 16:07
right. That’s right.

Jose Ricon 16:10
Yeah, there’s something out one more thing, I guess, to say here, yeah. People have, like, there are various what we may call philosophical, or conceptual arguments, or perhaps even with some math, you can do some modeling about finding people or projects, but actually going and measuring whether or not funding people or projects works. It’s extremely difficult. And I guess right in, in one of my blog posts on I think the first one on this frontopolar predict series, I looked at the experience of the Howard Hughes Medical Institute, and to what extent because in, in, in the life science research context, the NIH in the US National Institutes of Health, typically fund concrete proposals, they do so for five years, four years ish. And they do it in a relatively impersonal way you submit your proposal, and then a committee reviews the proposal, and then they don’t meet you and they don’t know who you are necessarily, maybe your name but whereas htmi, they find you they actually get personal with you, they meet you in person, they discuss your abroad abroad, but alternative open ended research program, and they will find you for seven years with relatively more or less commitment to another seven years, unless you really fuck up. So you can like effectively 14 years of support to my two to actually not just think of the next five years, but to have like a 14 year planning horizon. And this paper tries to see, okay, these researchers that get this award, indeed, they actually do produce better research, but a better discipline or question better a bathroom as measured by how you buck citations and things like that, which may or may not correlate with actually being useful for design scientists that will cite it. But is this because they were really good to begin with,

Will Jarvis 17:43
right? Sorry? Because

Jose Ricon 17:45
exactly or is this because the extra time and budget they get enables them to those things, the author strike to some clever economic tricks to control for this, I think the results are not as clear as they make them seem. And I think that if I have like one thing to say or one thing to add to the conversation on urban science that hasn’t been stressed enough, is that we need more experiments we need we need more randomization we need that foundation. So yes, allocate money at random and yellow a little bit more instead of doing one thing works.

Will Jarvis 18:14
I love that I love that approach. Because that same the same really important because we don’t know a ton about it seems like we don’t know a ton about meta science and I am read deeply enough to know but it seems like there’s a lot more to learn.

Jose Ricon 18:27
Yeah, I think everybody’s camps and schools of thought with meta science some people will say peer review is the worst and it sucks in general

Will Jarvis 18:35
like Don’s like oh god peer review like your take it out back shoot it, you know, that’s Yeah,

Jose Ricon 18:40
I think that old i think i think he was in your podcast would have done says that. For for a lot of science peer review kind of work more or less fine. It is sort of breakthrough science that but some people take it even further. Like all peer review, it’s kind of not great. Or people will say not sure if the interview is fine, but it kind of works. Well, people will argue we should find scientists by lottery, we should just give you money at random because we have no one. Yeah, see, it’s like they don’t like various layers of epistemic nihilism that you can go into. It’s like, it’s like we don’t we don’t know anything about the world. It’s like, it’s like, rationally if you think that you know, nothing, the rational thing to do is a uniform prior, you find everything equally, right. Like, yeah, you’re gonna have you have any reason to, like, but but like, I guess my view is that there are some things that seem at least intuitive, more clearly universal, for example, if we truly believe that we know nothing about who is going to be doing more interesting, useful science to fund cancer research with the same amount of money as we would find a pathologist, or are like people that are studying ancient Sanskrit, which I have nothing against Sanskrit scholars, but it’s it’s it’s slightly It seems that people want more more cancer cures and not much Sanskrit scholarship. Right. And I think

Will Jarvis 19:49
that’s common sense, right?

Jose Ricon 19:51
Yes, although it does, indeed and has happened historically. There was one one interesting discovery in the in the life sciences that that that occurred because People who were studying magnification in Egypt, and we were studying at the Madison stuff. So it’s sure yes, in theory, yes, you can get discovery from the weirdest places that didn’t translate to unexpected places. But I suspect that if you find chemistry research, you will probably find more interesting chemistry findings. Right. Exactly. One.

Will Jarvis 20:16
Okay. One would hope so. Yeah. That’s great. So before we move on, you know, so when I think your sub tagline on Twitter is Make Science great again, which I love, are there any other policy interventions you would suggest you would be thinking about or anything you found that you find interesting,

Jose Ricon 20:32
that might help? I mean, there is the the experimentation side, there is also doing I guess Murphy’s more Estonian focus research organizations, kind of things I seen, or rather doing something that that that maybe it’s missing, it’s something that looks like a roadmap or a field that’s that says that lead said, imagine some kind of website, let’s say, maintained by an S, but maintained by NSF or something like that, that says, Here’s why this field stands, here are the bottlenecks, here are the open questions, right, provides an organized and coherent story for the field to organize itself around. And possibly you could use that either to find research on the bottlenecks are for people to think more about, okay, if you want to go here, let’s say mapping the brain, there are all these different avenues that we could pursue. And maybe we can see that these two or three ones are being under researched, or maybe they they’re worth funding more. And some of these might be with, with nuclear fusion research, that there are a bunch of open letters to nature published around the argument that funders have been focusing too much money on one or two approaches to fusion that is an ether at

Will Jarvis 21:38
just Toka max. Yes, yes, yes, yes, or something like that.

Jose Ricon 21:42
And maybe there are seven or eight other projects that are purchased a fusion that may be work, and they were they were, they were getting more funding back then. But then ether came in, it came in partly as a US Soviet Union collaboration thing to do for friendship and stuff and some science, but maybe we should have funded in a more diverse way back then. Or maybe had we had it more reasonable that actually they were that approaches there. Maybe you don’t have in the case that if you want to successful in classical physics, you have to go into these kind of approaches. Yeah, so this, this idea of roadmapping, about next, that’s something I think it should be there some kind of website kind of torque organizations. Another another crazy idea that I’ve been thinking about this, is this worthy, because Sure, I mean, there’s like the easy things. Everyone says, like, Oh, you could reduce, you could do some luxuries, you could say amount of hours, and grants. And you know, the other boring stuff everyone kind of already knows. But you could also pursue a project whereby you’re trying to see to what extent you can transfer genius to other people, or rather, what they sit about, about productive labs or important labs that makes them so good. It’s just like, even if they have a smart people, possibly many scientists are sufficiently smart, smart to understand and come up with the ideas. I guess, as an example. I guess in the case of let’s say, prime factorization, it’s simple to multiply two prime two prime numbers and get the number. It’s difficult to break an apple into into, into into different primes. Similarly, it’s easy for you or for us to understand your activity more or less, it’s difficult to come up with relativity in the first place. But which is implying that it’s not that you cannot comprehend the theory is that is that there is some creative spark that’s missing. So then the question is, is there a way to organize or systematize creativity and breakthrough generation such that not only crazy people in interesting labs can do it, but it’s more open to anyone that is like, suppose I give you a problem. And and then there is this rule set or frameworks to think through the problem. And that leads you to better insights about what which direction to pursue. And it’s extremely under studied, there is an interesting book on this that is really obscure. By this guy called Richard Bernstein, the title of the book is it’s a it’s called discovering, inventing, selling, inventing and solving problems are different theories of scientific knowledge. The book is out of print. But it talks about this idea in 1989, because of this idea of thinking in frameworks about science and creativity, and what make researchers great, and to what extent can we learn from that? Having like, systematizing creativity that because Because ultimately, we had science? Sure, like there’s like a money constraint constraint. But I think there is an idea a constraint as well, I think that unlocking or enabling people to have better ideas would be great. To what extent this can be done. We don’t know. But I think trying it will be an interesting exercise that they would like to see.

Will Jarvis 24:44
Definitely, it’s at least worth trying. Right. Absolutely. That’s super interesting. And I’ll put the link to that book in the show notes. That’s great. That’s actually a great kind of segue into Can you talk a little bit about the great stagnation, your thoughts around it? I know you’ve written a lot of good stuff. stuff on it that I’ve really yeah.

Jose Ricon 25:02
Yeah, so the, I guess, introducing the idea of the greatest tech nation. The idea here is that if you look at a chart of GDP growth and TFP growth, explained very normally, but tfbs. But GDP we got, I guess, we get an idea of what it is right? economic growth in general economic activity, the growth of that is it historically has been flat through history, then it speeds up greatly the natural evolution ran, then something similar happens in 1970. And then it slows down. That is, if you look at median, let’s say, median income in the US has been growing at a slower pace since then. So that is the great stagnation. Now, GDP growth, you can decompose it into three components. In various economic models, these three components are capital, labor, and the rest. This literally it’s it’s just how it works. You literally what you did that you tried to explain to VP VA distributors explain to the pivot by like, Okay, how much of you VP is because we have more or better, more educated people working on the problem? How much have you VPS because we have more capital equipment, more tools, more stuff, and how much is unexplained and that the theorizing that goes up this unexplained stuff, is what economists call that the factor productivity or productivity for short. This is not the same. And DFP has been kind of again, growing at a slower pace in since 1970. Now, the DSP in particular, is not technological innovation. DSP is a grab bag of everything else. So I guess it’s a mixture of, for example, institutional dysfunction, and potentially technological slowdown, but also sectoral rebalancing. So mind you in mind, you have two sectors in the economy. One has its relativity growing very fast, and another has its productivity growing very slowly. The sector in which you spend it with productivity grows pretty fast, let’s say that things become very cheap, let’s say let’s say for for computers, now you have to have a relatively cheap computer, that’s got a lot of things. So then you spend less on that, and just but then the other one gradually becomes more expensive. So then, these sectors, and then basically, at the end, your economy looks like the the local low production growth sector, it’s bigger than the other one, that in within each sector productivity rates in this in this experiment is growing at the same rate. So it happens that when the economy, the slow growth, one is bigger, but because it’s bigger, now it has a bigger impact. So the excellent so now that sort of growth in the bigger sector means that overall, you get a slower growth in the economy. And, and, and the economy of the US and other countries has seen a shift from sectors in which it’s easy to increase productivity, like on the functioning, I think the ultimate one politic, we have to make things productive is the assembly line is to modularize and make more of a thing. And yet the sectors that the economy is now more, investing more or putting more money on our people or personnel intensive services, like health care, education. You could even count research to some extent that this you can possibly underutilized seems to be things you can produce cars, let’s say 2x faster, you cannot move your arms twice as fast even assembled as a human. There are limits to human performance, that, that constraint those, there are ways that could be that we could pursue to overcome these and we could for example, try to push more on automation or process improvements. And other things. There are some interesting case studies of healthcare in India that the state of hospitals that they have basically built a surgery assembly line where you have one surgeon doing the same, the same operation over and over and over

Will Jarvis 28:30
the expert comes in to do his one part of you know, the heart surgery for you know, just like yes, it’s

Jose Ricon 28:35
it’s almost done and then it goes under the same operation. And I’m controlling for labor costs, this is cheaper than than the US model of head of surgery. And this thing is certified by by the US Healthcare Quality institution so it’s kind of like us level of quality. So it’s very, very, very interesting example that maybe we can link to because quite surprising that this exists by necessity. So so the elastic nation in this activity and GDP Israel, but from that does not follow that there is some stagnation or a great stagnation in technology, which is a different one. There might be some I might but the thing is it’s difficult to measure and DFP is not enough because we say this is a grab bag, I think I think I I am inclined towards the TF, the DSP nihilism v where I think some people are more or less prone to jump from DSP to technology, and I’m not very keen on is like I like to take in the real technologies and look at how they are developing over time. For example, if you take more, if you take more slow, or the increase of efficiency nuclear reactor, sorry, my steam boilers are in construction speeds are any orange because of batteries and solar panels. All the trends you could possibly find, do this show a change around 1970? The answer is no. Some I think were to do, but there is no nothing, especially with happiness in 1970 which I think should be some people some posts about whether or not it’s technology or not some People can argue that it’s it’s an actually I don’t claim that just because this is the case, it means that scientists are slowing down. Because because it could be that for established technologies, the ones you can actually measure and put in charge, those are doing fine, but we are getting less breakthroughs. And if we are doing so, then ultimately for established paradigms, you end up exhausting it as an example. For nuclear reactors, one way to increase the how much power you get out of one an extent one is to increase the capacity factor. This is a, let’s say that the nuclear power plant generates one gigawatt. And if it’s active hours, one one gigawatt hour, the capacity factor would be if you have one gigawatt plant, and you have so many hours in a year, how many of those hours is actually on versus maintenance and reserve capacity factors have been going up for like 70% of what back in the 60s originally to like 96%, these days, we have gotten better at the operation and efficiency. And that alone can squeeze more energy out of the same exact plant. But 100%, it’s 100%. Likewise, for for our internal combustion engines, there something might not be called limits, called the current efficiency as to how much efficiency you can get out of this. But then you can paradigm shift and use and have electric motors, which

Jose Ricon 31:22
I mean, sure at some level they have they’re theoretically constrained, but that the constraints are higher. So it’s not as much of a problem. So I guess to wrap up, it’s when when we it’s difficult to actually say yes or no to whether or not there is a thing or a stagnation. I am my preferred answer to this is to say, mu, or which is this, the questioner is explaining. So in Zen Buddhism, there is this this thing known as the moocow, on call and these comments, are these weird questions in in centralism, that are meant to make you reflect on things. So this one goes like this It goes a monk asked Joe to function, Chinese Zen master. And the question was, has a dog Buddha nature or not? And the master jobs you answer, whoo, or in Japanese mood? Now, what does this mean? He, the word the meaning of His Word is something like it can’t be translated translated as as nothingness or emptiness or something like that. But the point is, that he’s trying to answer the question, or rather to say, you should not think about this question or trying to say yes or no, you should actually focus on other questions, namely, looking at everything that’s broken in asking why x field is not being faster and focus on those problems and solving problems there. And I think that is an easier and more tractable and perhaps even more interesting, or engaging problem than trying to think what happened 1970 maybe, right? That’s right, is that nothing happened? Maybe it’s a bunch of trends that saw it happen that that got us lower growth in 1970. But But I say even if we could get TFP looking like the GameStop stock is going vertical. Even even even if we could do that, we could still keep asking the question. Sure. TFP growth is now faster, hypothetically, than press record 1970? Is that enough? answer is no, there are still problems to be solved, we will still should be looking at fields and say, why is field excellent making progress, they’re not going faster. So my my my goal is that instead of thinking about whether or not restart and stagnation in technology, we should just look at it field, see, why is it there is not broken, and try to come up with solutions. It may be that that there is a single cause for all of these problems. Some people for example, led rather on Twitter, he has an athletic one as well, that it may be better to as well there is this idea that there is a generalized complacency in society that we in general, were getting more complacent. And this happens in government and it happens in everyone General, right, that we are not We are not trying as hard as we used to, to fix things that we are not so easily annoyed at the inefficiencies of the world to go in and fix stuff, that might be true. I mean, we could discuss To what extent that’s true, but let’s say even if that’s true, there are many problems that still remain right and we should just go go forth and tackle them we should do this road mapping bottleneck finding exercise they are not plans and execute them that

Will Jarvis 34:16
that’s a great point. And I think you’re absolutely right and that it’s less important to figure out you know why and and why is often over determined but fixing it is the most important thing we can try and work on and go case by case because that’s that’s the way you can actually solve a problem. That’s right.

Jose Ricon 34:32
Yeah, I guess I guess like what one could see how it is intellectually satisfying to conceptualize and theorize agree the stagnation in technology and like think and and be able to say yes or no, right. But like some some questions are, are are some like more imposed on that than others? Some questions are harder to actually give an answer to, or even maybe even if you give an answer, the answer is going to be kind of vague and subject to lots of assumptions. So many assumptions that people will disagree with your assumption And then the question isn’t really answer, because it’s so self independent.

Will Jarvis 35:03
Right? That makes a lot of sense. That’s great. And that’s a great segue to you know, I wanted to move a little bit talk more about econ. And you know what people most misunderstand about the economy of the Soviet Union. I love reading these posts on your blog, because, you know, you just hear about in school, you know, Soviet Union playing economy and like, that’s it. That’s gos ever, right? Then you read the high IQ stuff, but you know, how well did it work? Did it work?

Jose Ricon 35:30
Yeah. So the maybe just some context about why I wrote these posts, which ended up being a small booklet published by the Smith Institute in the UK. So in in Spain, where I’m from, there are a bunch of communist parties, we don’t really have one we have, we have a bunch of them. We also have some fascist parties. It’s an interesting place compared to at the same scene from the from the US optics, it’s more diverse both ways. And, and politically, you see some propaganda for or like, you would call it reported propaganda, depending on what you think, from this part is arguing that actually, maybe somebody union was not as bad as you see, but but here’s the twist, they will. Back then, they had this video showing that the USSR was kind of great, but they use data, they use data from sources like the United Nations, or the CIA, they did not use solid data, because people was like, Oh, you know, the Soviets were kind of playing with their books and like, right, and, and that’s an interesting thing, right? Because you think that the United Nations and the CIA are for people who have incentives, incentives to get it, right. Yeah. So that so then I thought, is it real? Or is something going on a heat exchange going on here? So that was the starting point. Now, when people think about the USSR, they’re thinking, two or three things that that come to mind? One, one, I guess, is the supply economy, meaning that by and large, the economy, not 100% of the economy, but most of the economy was planned by the state. They were in everybody’s factories, and they had these very galaxy brain engineers trying to do optimization problems to optimally allocate resources across these industries. This fun book called read plenty that kind of goes over how some of these works

Will Jarvis 37:07
for Christmas, I haven’t gotten to yet but she said it’s really good. It’s already

Jose Ricon 37:13
there. There were this small particles called reinach. Yeah, I’m completely butchering the depression pronunciation, but they there is that people could try it, you know, like, like, like farm products, like very basic stuff. Like if, if if queueing for some time, you couldn’t buy like meat, you could go to the farmer and you could, there was a small amount of free market but by and large, it was it was a planned economy. And, and also the resupply economy after this is largely after Stalin’s time. Okay. Secondly, to the second point Soviet Union people come to mind Oh, Stalin, right extolling the gulags the the defines a holdover? Stalin. So my, my next episode union focuses on the Soviet Union, it is at its best that is on the post Stalin era. And the reason for this is that if we can share that the USSR was not so great. I just west, then by implication, at its worst, what’s even worse? And, and indeed, while I regarding food, I guess the first interesting thing that they found out is that well, first, there were no real food scarcity in the Soviet Union after the 1950s or so, in the data of the movies. People are starving. That that’s that’s true, but it happened during the earlier stages of the USSR. After that, do you have really the real struggle as much with with that, after after selling that? That is? But then the that’s maybe that’s where someone’s like, Okay, well, I mean, maybe it was not North Korea, it’s a little bit better than North Korea still. But then you wonder if you look at the United Nations, there’s this this entity within the UN called the Food and Agricultural Organization, FAO, FAO. And if you look at they have this time series, four calories per person day consumed are interesting. And seemingly the subjects were eating more calories than the US which seems difficult given the US people like to eat a lot of calories and you know, get good at it. Yeah, yes, it’s really good at like all other very nice food. Oh, the other three are not all that nice freedom. Yeah. But at first I first i thought well mighty political for Russia is calling on the US. Maybe they need more food for you know, because it’s called maybe it’s maybe the economics is less advanced. Maybe they’re doing more hard manual labor maybe. But I tried to look for some comparisons. That didn’t seem to be true. You can start Finland Did you look at other countries, the frequency is still very high it’s surprisingly interesting. So then I thought okay, what is it the data came from? What do we do get this data? Could it be that was like Soviet data that was scooped or something? Yeah, see, was there any of this data so suddenly got into this whole like rabbit hole of, of this very niche literature of people trying to do calculations based on like, how much so it said they produced and then tried to adjust for like, spoilage from the farm too much. To attract to actual people consuming it, and then trying to calculate how many calories and sweet potato and things like that. Because Because it’s different potato has a different amount of calories and things like that, right and so on. And I guess like TLDR, the what this goes is that the the FAO used us, they took the, I guess whatever context, Soviet data was published after more or less after Stalin or even during the later years, so it’s more or less restricted today to be relatively uncooked, it’s retro intrusive, and it’s, it’s organic, it’s not filtrated. So we can more or less, we can more or less trust the data, actually, a while, but the FAO at the same time, so the Soviets themselves, they had they have their own estimates of how many calories they were actually consuming. So there is this entity called ghost comstat. This is like a Soviet statistics agency. And their data showed that the Soviets were eating fewer calories compared to the US so so they they had their own set of coefficients to to convert from Soviet food to like American like, like a standardized calories. But the FAO said we’re gonna set we’re going to trust the their food figures, but not their commercial coefficients. So they took like the kilograms of things they were eating and use a standardized average coefficients that they use for other countries, and apply them to the US. And if you dig into that report, they say, this kind of wishy washy, but you know, we have, we had to do something and like, hey, here we go. That’s, that’s where that data came from. It’s like, deeply buried into it. And it’s like, if you if you just plot it, if you want to watch it and plot it, it looks like any other line, it looks like, like it’s slightly the graphics, same line as any other. But it’s each of these lines telling a story. It’s coming from somewhere, it’s coming from some random guys in the sand is arguing about potatoes and calories.

Will Jarvis 41:42
That’s amazing. That’s awesome. Just imagine that you’re one of these guys. And this is what you’re working on, you figured out. So

Jose Ricon 41:50
yeah, that’s that’s kind of the the for historical mystery of figuring out how many calories you’re actually consuming. Another one was finding out claims around the sun, people saying that if somebody union was actually more efficient than the US, intersection, see, yeah. And then again, this this is all sorts of various gear and niche, aka economics. But the the TLDR here, boils down to what do people mean by efficiency? Nowadays, there is one definition of efficiency, which some people call a static efficiency, which is if I give you a bunch of machines, some people, yeah. And then you can you can combine them and organize them think of the whole economy in different ways. What’s the URL optimal is typically efficient, if everything everything’s allocated to arrest us, that is that there is no rearrangement of resources such that as a whole, you are producing more. That’s the meaning of static efficiency, and dynamic efficiency. So that is this concept in economics call the name, the PPF, the production possibility frontier. So I guess you could see if you might have an economy that can produce, let’s say, cannons, or like, but like butter, and you can choose between both the decider is a curve. But he’s like, that’s their mindset, an exchange ratio between both and you can decide how much you want to reach. But there’s a curve of optimality, that you can choose different combinations of outputs and ultimate optimal. And there’s a set of points inside this curve that are this surface that are not optimal. So that’s what I said, if you rearrange the economy, you could produce more of more of everything kind of figure in that point. So so the dynamic efficiency and your hand and efficiency would be that you that over time, you’re actually growing this production possibility frontier that actually you’re able to produce more in general. Got it? And, and the research that seems to show that, indeed, the Soviet Union was very statically, efficient, interesting surprise, seems surprising at first. And when, when, whereas at the same time, they were their dynamic efficiency was low. And, and overall their, with their productivity, as we talked about in the in the end earlier sense. This TFP, that’s like a receivable of the of GDP, that was the slow the rate of growth in the SP was gonna flow. The explanation was that it’s an interesting quirk of what happens, what happens is, if as an economy, your technology doesn’t improve very fast, you get good at using what you have. Right? Yeah, see, I think if you if you use the same machines over and over for 20 years, you get good at using them and how everything should be allocated, there is no disruption going on that will force you to change and rearrange things, you can get good at optimizing the here and now instead of constantly changing things. So I need at least seem to be some inverse correlation between them are dynamically efficient you are, the less time there is for the economy to adapt and settled or statically efficient allocation of resources. So ironically, ironically, because they were not that innovative, they were particularly efficient.

Will Jarvis 44:45
While that’s like say

Jose Ricon 44:47
it’s there. And it’s like if you see the claim on its own free standing is the start was more if more efficient asterisk aesthetically than the US. It sounds kind of weird. It seems like like a scoring points for the USSR whereas actually It has to be put in its own context as to where that efficiency was actually coming from, which is not very flattering to the user.

Will Jarvis 45:08
That’s, that’s really interesting. And I want to ask you this question. I just had this thought, you know, what do lay people most misunderstand about the economy, the Soviet Union? You know, what would be your takeaway after doing all this research?

Unknown Speaker 45:21

Will Jarvis 45:24
just in the discourse, you know,

Jose Ricon 45:26
I mean, in the discourse, it is like one thing, it’s not necessarily the economy, but it’s the USSR as a whole. And if you ask people, what was bad, why was the USSR a problem? Right? Or what what did they What did they do wrong? People will talk about political political persecution and gulags and Stalin, right. And, and those things, and they will maybe like, not think much about the idea or the problems with it with a bland economic in the first place. on their head, perhaps like you have people that some somewhere who’s like, Oh, you Applied Economics, of course, that the collapse? Of course, it didn’t work. I mean, it, it kind of worked in the in the sense that that Russia was a very poor country, Russia was basically a feudal agricultural economy, that then Sterling took into something that could actually feed the defeat the Germans at World War Two, which is it’s something I mean, it doesn’t mean that you could have it couldn’t have been achieved by other means. And there’s some research in that, I think, what would have happened had Russia became a capitalist country instead of without having to go into communism. But yeah, they there’s something about as well. Although Even then, we could say that the one reason why they could grow so fast is that again, going going back to the, to the framework of thinking about growth, you have, you have people capital and productivity. So it’s basically this idea of a forced savings that is that you can force more people, you can artificially restrict consent, when you have a planned economy, you can force people not to consume and safe more, which is what they did, and then put all that into investment. You can insert like no, no more like fancy organic humans for you. To put this into making steel and concrete to make more factories and make more stuff. That’s, that’s how we got a lot of growth. But the thing is that there’s so there’s only so much steel and concrete you can manufacture to make more cylindrical factories, there’s only so much investment, the the the share of investment that you send us our GDP was kind of it was not that high. But even then, they were throwing that investment way more than the US I think they were 30, or 35% of our economy was investment in the us right now, it might be like 20 something percent, which means that you will get consumption for if you also coupled with the fact that the USSR, when trying to match the US military, they were spending, I think twice as much of GDP in military compared to the US, because they were a smaller economy. If you take the investment and military expenditures, during the Cold War, you end up with the actual consumption as in how much people are actually consuming, which is way less than that. Did you expect from this looking at GDP directly?

Will Jarvis 47:54
Gotcha. Very, very interesting. Very interesting. So I wanted to skip now and talk about Cuba. So you know, high Human Development Index in Cuba is a mirage. Is this a real fact? What do you think?

Jose Ricon 48:05
Yeah, so so I guess first which, which define what the HDI is the Human Development Index. So this is a this is an index that it’s basically a geometric mean, this is basically taking taking the the cubic root over the multiplication of three, three things, these three things being indices of letters, expectancy, GDP, and years of education as an on average, how many years people in society, get of education. Now, if I did a few years ago, if you looked at this elaborated by the UN, so it’s not like it’s done by some shady communist cabal is something that seems kind of rigid, and is something that people will typically use as an indicator to compare how well different countries are doing. It’s kind of like a physical CD or a scorecard under the premise that the well maybe some countries that have higher GDP just because they have oil or something. So you want to consider other things sorted and right. Now, the extent to which this weighting of these things throwing them in there, it’s reasonable, that’s perhaps some somewhat questionable, but it’s an index that is it’s out there. Now, three or four years ago, if you looked at the these HDI is from Latin America, Cuba was the second highest, which seems surprising given that Cuba has an interesting political system. That is it’s Yeah. And anyone there? Well, we’re just going from you said that is the kind of work is that they have they have something that we don’t know about health care and education and growth? Well, my, I guess, if you have like to, I think to use a framework that you have when thinking about economics, in general is what they call thinking thinking diamonds, basically is taking the country and compared with other countries around it. I didn’t think the country I think of the country in across time. So in this case, like okay, how the countries around Cuba doing how are they doing and also QA itself prior to a revolution, which was in in 1959. Yeah, how was he doing? Could it be that actually began in your sexual actually a very nice place to begin with and then it kind of cruised along. Yeah.

Will Jarvis 50:06
And that’s momentum.

Jose Ricon 50:08
Yeah. And and indeed that seems to be the case for for education and lifespan that even back prior to pollution, they were raised scoring extremely high on these metrics. These are these do the right variety of factors it may be maybe culture, I guess, in the same sense. For example, if you look at life expectancy of Hispanics in the in the US if you compare, if you compare, let’s say, Hispanic whites with Hispanics in the US, Hispanics are poorer than the average American but Hispanics live longer than whites. Even the thing that I think even even more than the research of richest of whites. Now, why is this? People are always it’s about like, how could we even if they have worse health care or whatever, like this, or that, or whatever? How could this be? So some people argue that maybe it’s something about culture, and maybe a combination of better diet and exercise and more better community in family relations? Who knows, but it may be that something like that may also be behind Cuba. But in any case, in any case, if you take, for example, something I did, which is to take Okay, 1955, prior to revolution, you take all these indicators for Cuba and a bunch of other countries around it. And then you plot, and then you take the same indicators in think 2013 or somewhere somewhere in here. And then you see, of course, countries that started from higher point are going to say more or less they have retained that that very high standard of living ish, instead of like, location and lifespan. And you look at your eyes, like that’s cute look special in this child’s comfort, Let’s fall in line. And lastly falls in line. Extend so that that could be used to explain healthcare, lifespan and, and yes, years of education. But there are things that are explained by that. One is one would be gdb. I never want to hear so many different anecdotes. Another one on one thing that in poor countries drags I think lifespan down is infant mortality. Got this like he started killing lifespan lifespan has been relatively low because it was very high child mortality early on. So Cuba as it happens, due to the way they do their statistics, they do not count deaths between second birth and a few and a few days. They don’t count. Gotcha. Yeah, the calculations is this they are not happy, then that appear there. Yeah, yeah. So that’s, that’s kind of like an interesting we check in. If you look at a table with data, you would think that it’s numbers coming from the same place, but not quite there that are like that, again, there’s stories behind each number by going back to the before. gap was also a tricky one. So GDP conceptually taking a grab bag of all the economic activity in an economy. But to compare it with B, let’s say it’s like, I guess this membrane divided competitively between two countries, what did you do, and let’s say the gated community before us, you could put then you could take, let’s say, the GDP of Cuba and vessels that are currency, and then converted using exchange rates to dollars and compared dollars, let’s say the US GDP in dollars, q1 GDP in dollars and compare them. That’s okay, ish. But you can do better than that. Which is why people use this approach Cisco, that purchasing power parity. Philosophically, the idea of this is that

Jose Ricon 53:26
one $1, or whatever $1 is in pesos doesn’t buy you the same amount of stuff, or to put it in in a in a different sense. $100,000, it’s the same in San Francisco, and it’s the same in the middle of Texas, but you’re gonna have the same life. In San Francisco, you will share a room and you will pay a lot of money. Whereas in Texas, you will have a very nice house, and three bedrooms for the same amount. So so people try to look at individual prices within each of these economies and try to use those to make corrections to make to see how they’re how rich they actually are, how much they can miss economics actually can code by with all these GDP. This again, this is constant, philosophically, more difficult to do than just doing using exchange rates. And, and because of these methodological problems, you again find very obscure conceptual disputes about what’s the best way of doing this. So again, back then looking at this HDI is looking at the GDP and was behind the number. I was like, Okay, well, what is this the CP numbers coming from so and you go into is very different, not at all this report from the world development bank that has that they were estimating they were they would explain the the methodology for comparing prices and applying these corrections to to GDP. And they said, you know, for Cuba, we are offering this number but but don’t take it too seriously, because we haven’t really settled on a good way like we cannot. It’s a plant. It’s a plant economy that are prices that they are not as comparable as they are in the market economy. So we have to do some more corrections. Here’s a preliminary figure but don’t rush it too much. But the United Nations do is like I just put the numbers HDI whatever. Yeah, it’s like, I mean, they learned. I mean, they I think the HDI changed. Recently, I think now is something the second highest, and probably the seventh or the ninth. So just went down. I think it’s right, they will still hide, right? It’s not like it’s super low. But again, it’s high, partly because of this pre existing set of healthcare and education, buddy. So that’s gonna be another case where one wants to look behind the story. That’s that that’s the data that that just because it’s on a table, and it syncs with everything else doesn’t mean it’s as reliable as your data. It was kind of like, like a fun. detective story, just go. figuring out where these numbers coming out coming from and seeing all these debates, people arguing about beaconing out all these obscure fears,

Will Jarvis 55:48
right? Absolutely. No, that’s really interesting. It’s a reminder, you always got to be careful. Right, you guys got to be careful. Interesting. I wanted to move on a little bit now. So last week on the podcast, we talked to Freddy de Boer. Have you ever read his blog? His book called Smart?

Jose Ricon 56:05
I have not. But I’ve I think I’ve heard a podcast with him. But more or less, outlines the ideas behind the book.

Will Jarvis 56:11
Yeah, yeah. He’s pretty interesting guy. Anyway, we talked about direct instruction and blimps, two sigma problem. Could you just describe it? And you know, how robust Do you think it is?

Jose Ricon 56:22
Yeah. So blooms two sigma problem, this idea that this, the circular is the Krishna secularist bloom that found that he was trying to find good ways of improving education of teaching in general, how do you get kids, not only kids at all levels, to learn more and better. And he found that once, the best thing that you could do is tutoring one to one individualized tutoring, having one person that understands how you think and what you know, and can give you individualized feedback on your homework, and, and so on. As of right, this leads to looking at test scores and exams to a to sigma improvement that you see right here is to do center deviations, which we can just interpret as a very large effect that two sigma, we can just take that to be as the big big effect problem. The it’s bigger than big effect problem, because in education research, if you look at randomized controlled trials of various interventions that people have tried most of them their exercises go to zero data yet difficult. It’s very difficult to build a location. And so the blue signal problem is very interesting in that it seems to show that there’s something that that seemingly increases education a lot. And so that is this aspect as measured by scores. Now bloom, he’s he said, like, Okay, can we replicate these two sigma, that we get from tutoring in a scalable way? Because, you know, giving everyone a personal tutor is very expensive, right? Can we do this in a cheaper way. So that was the two sigma problem. And he proposed that we could do it with various combinations of techniques that I think the most famous one is something called mastery learning, which is a technique whereby you really hammer down on concepts until they’re really appropriately acquired, and only then you build on and which more I guess, as an example would be, if you’re teaching, let’s say, summation, and then multiplication, you don’t just go go through and then if someone doesn’t really get how to do nine plus nine plus nine, just keep going to Junker. With mastery learning, you stop and test and test and test and preach and test until it is mastered. And only then you move on, that would constitute not solid, they’re difficult to then build on, build on and acquire so it’s less efficient, and people fall behind and so on. So I think the the the headline to sigma for tutoring, there may be something there, maybe it’s not two sigma, maybe it’s 1.6. Maybe it’s 1.5. But definitely, the idea that tutoring can greatly improve outcomes. It’s real. That’s definitely their mastery learning as well, I think again, not to sigma but to some extent, yes, it also works. The the way in which works are the channels through which it could work one when it seems simply repeated exposure to the same information over and over this is the the spaced Spaced Repetition effect. And this is when when you are in your for example, flashcards to learn a new language where you basically get yourself okay this award was in pain and then if you failed, you will see this card more often and so on. And another way in which this could work is something called as testing effect, which is merely by testing you even if I even if I don’t give you the answer that in itself finally helps you remember God think being first to to ask yourself and answer for yourself a pilot helps retention as well. Right? And probably guessed this conceptually, this idea the idea of building on solid knowledge helps us because cognitively if I give you a concept you understand that may that you may try to be too grounded in other things. But if those things are shaky you it’s difficult to know where it fits and maybe you have doesn’t require the or your brain will be like oh this thing doesn’t really make sense. I guess throw it away. Right? And just keep going. Didn’t really learn as as as much there are some suggestions to be some people have suggested using software methods to achieve these these effects. Famously there was this program that DARPA funded that is called data to the project. And basically, it was in the context of training US Navy. It technicians. Yeah, these are the data show it works not just in a high school setting or around a K 12. And they showed like very impressive effects, they showed that the the students in I think in half the time that the drag that regular core stakes were achieving scores way higher than anything that the regular students could achieve. Just kind of kind of cool given that software, which means that maybe it can be scaled that maybe you could greatly increase the efficiency of education, not in jail, in our country. Yes, with software, software you do, it may be difficult, and actually, in this literature of doing it in software, it’s a common theme that it’s very difficult to program this software because you need both knowledge about unity with a system that can model the student what they know how they learn, how have a bank of questions and to generate the right questions that they can

Jose Ricon 1:01:09
fill in the gaps they have. And also you need domain experts about math or physics or whatever, actually building that knowledge. But but difficult as it might be to do it once ultimately, the knowledge that starts in many contexts, it’s more or less, I think stable. And so you could possibly benefit from from that direct instruction. So you mentioned that there is the constructions that construction is technique, equipment technique typically practiced in the in an especial education context for kids with with mental disabilities that have slower rate of learning. And the idea here is maybe taking a step back first, to explain if we could say that there is a philosophy of education that one some people may think of as conservative in that the teacher knows and the student that basically the student is a vessel that has to be filled with knowledge by the doctor, right? It’s unidirectional, I’m more when we call progressive view of education. It’s a real it sounds like this digital age where students learn together that the teacher is a guide that the student uses to progress through knowledge, perhaps at their own pace, right, and in some cases, to explore areas of their own interest in a more in a less quote, authoritarian way. Their destruction is the extreme version of the first approach, in which you have a strong emphasis on things like rock memorization, repetition. There are videos of the construction on YouTube, and it looks initially a bit like like a gold. So you’d have like saying, nine, nine times nine is at one because like nine times nine is eight. too long for somebody to it’s, it’s, it seems very weird. But then it’s like, well, ultimately basketball. That’s the question. So they the construction guys, they they seem to be very interested in seeing if it works or not, I seen that they they try to when the curriculum would their concept gets implemented, they try to see how the school is just to get this and then they try to use that knowledge to then improve the construction method, and then send that knowledge to other I guess, in the same way that Tesla can gather video from all the Tesla cars and use it to improve the registration Institute, they try to use knowledge when they deploy the AI to improve the method. So base test that around for the same, I actually think the ultimate evidence seems to show that it seems to work. I mean, especially for the special needs a case that works very well there. And it works probably somewhat better than quote, this more carefree education, right, is that there is some debate as to in which way it works, right? Because I guess it’s easy to show that it works if you care about if allocation is about learning a bunch of facts, right, and you’re good to invest in those facts thing, if you test that I think that education is more likely to win. But then some people argue, oh, but what about creativity? And just like other other things that are more difficult to test? It’s difficult to measure indeed, and, and knows. But if, if you have like a more limited set of concepts that may or may will work. I think the and and the reason why the construction hasn’t been actually I think the USDA years first left decades ago, one night nationwide, huge trial for these different education systems, all the way from reconstruction to literally I think it’s decades and do whatever they want. I don’t know the name of this. It’s on my on my blog, this middle column, slats, Bloom sigma. And actually, it works as seemingly that this destruction thing seems to work. Now, a recent way, maybe it has not been adopted might be that culturally or politically, politically, politically around from a values point of view. The reconstruction is everything is everything teachers stand against, like this idea, I guess, their self image, they didn’t want to be Almost robots are reduced to just following a script. Because ultimately, I think their construction that they some features are better than others, they will try to get good teachers to write a script of what good teachers do and how they act. And then and then like, like actors, they will try to get teachers to act like the best teachers that they have found. The idea being that that acting like a good teacher is sufficient to be a good teacher. Now, some teachers find that this is humanizing that to some extent that we’re forced to do yes, play Act, or like LARP.

Unknown Speaker 1:05:30

Jose Ricon 1:05:32
being a teacher and is following this really great script. And they just don’t like it. They didn’t, like I said, job doing that this commission of that class, they are the philosophy underlying the AI, the AI, this idea that there is like throwing knowledge at kids, they like that concept they like, and I guess like, at some level, it kind of sounds nice in some way, this idea that you’re going to just guide them and they are your partner, Jordan, and you’re just not here. And you’re down there. You’re more of an equal to the hierarchy. Yeah. Yeah, I guess some people find that structure appealing, the are, are very satisfying to think of education in those egalitarian terms. But it just seemed to work. I think that, that that’s so sweet. I think it’s so it happens that ultimately, there’s a difference between doing what you think seems okay, or defined to you and and doing what works and? And it’s Yeah, and then it’s like, ultimately, I guess the meta question would be at which level in the in the in the, in the policy integration policy hierarchy Will you have to intervene in subsets to get these are with the teachers unions just just rebel against you, and you just want to do

Will Jarvis 1:06:47
top to toe? That’s, that’s really interesting. So I had one final line of questioning, and I want to ask you about longevity, longevity research. So it seems like it’s a field which is very prone to getting, you know, shall we say? quacks that, you know, it can be very muddy. So, where do you think we are? Right now? Like, as of today, as of February 10 2021. Yeah,

Jose Ricon 1:07:10
so, yeah, so I guess first, we don’t quite understand the question of what is aging bad remains certainly unsolved. There’s some, there’s some theories that I think they are better than the old theories. So welcome back a few years ago, people will talk about telomeres, for

Will Jarvis 1:07:27
example, those

Jose Ricon 1:07:28
are antioxidants. I think, years ago, everything was all about the antioxidants right. Now, those things have filtered out of fashion. And people are thinking more about the the opinion for example, or, or a condition of damage, or things like that they don’t like various schools of thought about what aging is ultimately, we know, we know that aging can be the things that we know that aging can be regulated, that is that that we it’s not fixed, that you can take a warm, let’s say, or a fly or a mouse, or mice mouse, and you can like play with these genes and make a leaf in worms 10x, longer, 10 times longer. Just by I think, knocking out this by inactivating two genes, you can make a worm lives that much longer. in mice, I think this is up to 50% longer than the target lifespan, which is not bad. And in monkeys, which is the closest to other thing was like maybe 10% increase in lifespan. In this case, the technique they use was, which again, be the most conserved and better than the best understood intervention with longevity, the thing that you see that has the same mechanisms, ingesting flies, in worms in mice and in humans, humans, we assume we feed the monkeys is those that centered around the circle. nutrient sensing pathways these are met routes are like sets of proteins that work together that detect nutrient availability, that is basically when you’re when you are starving. They they get response that’s such that ultimately, you end up going to some kind of maintenance mode where you live longer. And this, this mechanism seems to be very well conserved throughout the life in general. And there’s some evolutionary theorizing as to why is this the case in the first place? This is this is the logic behind for example, fasting, it’s this is this, this mechanisms?

Will Jarvis 1:09:20

Jose Ricon 1:09:21
And so that’s that’s one there is there are some drugs that have been proposed that can directly mimic what what is ultimately calorie restriction as improper conduct restriction can be mentally exhausted very difficult, right? if he’ll call you feel hungry all the time, right. And there is this drug called compromising that also seems to extend lifespan in in in everything. If you get tripped up from a hint to something. Everything gets better like in clinical trials in mice like Alzheimer’s and cancer, everything seems to improve. It’s kind of like it’s I guess, the the interest something that people will more or less point us to what is aging aging is a set of things, how they can teach There’s another set of things that if you touch if that affects everything else, more or less, that, I guess, I guess, for example, if you could I guess I’m the cause of let’s say cardiovascular disease is that a combination of cholesterol or excess cholesterol in your arteries, it looks arteries and so forth. But that’s just their cholesterol is not accumulating in your in your column or in your brain, right? But aging they do. So it’s a it’s very limited in its scope to the to one system, but aging seems to be the same mechanisms that can regulate maintenance, and repair or damage responds everywhere in your cells. That’s, that’s one way one way of thinking about aging. There is, I guess, one of interesting new developments in just like measuring a measuring aging, and that is, can we can we predict from I guess, if you give me let’s say a blood sample, can you predict how old the person is? Can you call it can you pick how long they have to live? So this is this is the theory behind this a goal methylation or epigenetic clocks? Right, he said, he said that, that we have this we have DNA. And then in the DNA, there are these, these small methods are mouthfeel. It’s basically I want carbon three hydrogens, if I have one more for it will be methane that may feel just for three that gets attached to the DNA. And that’s, that’s a methylation mark, it can be on or off in one given site. It’s like 01, kind of gotcha. And, and if you look, if you sequence, if you look at these methylation patterns, this case you take from the exam from desales, in in blood, typically, if you look at this, and you train, brain very simple or misleading regression models to predict Remaining Remaining lifespan or actual chronological age, you can do a decent job. And I guess an example of how this in this job is, well. Suppose that I could choose between, you might want to predict your lifespan. And I can choose between asking you two questions I can ask you, do you smoke or not? And or I can ask you give me your blood, I want to say you’re looking at the clock. I graduated blood. That’s the really interesting, this clocks predict more than than than smoking, non smoking status. Oh, wow. Which is quite interesting. Because then they mean, okay, this is methylation marks in the DNA. And this is, what do they mean, there? There are three schools of thought here that are currently they’re dishing out exactly to what extent each of them are, right. There’s, there’s some interesting work doing being done by Morgan live in jail on figuring out what the clocks mean, basically, there is three theories. One is, it’s noise that is random, we get, we get extra, or we get more or less of these mutilation marks, and that causes some kind of damage. Second theory is that those things that are just a damage response, actually, they are not causal, but actually there is damage accumulating elsewhere, and the body tries to switch on damage responses. And those things are the things that you’re seeing in the image below. The first one is it’s quite, it’s an interesting one. This one is what some people call the quasi program theory of aging. And when it goes is that at least aging stuff, it’s not that damaged accumulates randomly that your body wants you to age, but is that the same kind of processes that take you from being a child to being an adult also keep pushing you from an adult to actually eventually dying? This is interesting, this also goes goes by the name, the hyperfunction theory of aging.

Unknown Speaker 1:13:23
And interesting, which

Jose Ricon 1:13:24
is an interesting thing, because if aging is a regulated process, it means that maybe we can switch back these clocks. And just like if aging just means that this method may fail, so positions one and three, and then they are switched off. Why did you switch them on? What happens? That has not been done yet, but I expect we will see similar experiments to that at some point, we actually try to constantly intervene in the beginning to see what this inflation marks actually mean. Some other there’s some other interesting developments in the aging world like this used to go by the name of prognosis made popularized by the idea of blood boys, this idea that you say, yeah, the idea that you can take junk clothes and put them into old people, they get somehow better in some regards,

Will Jarvis 1:14:09
right? They

Jose Ricon 1:14:10
this was it was done in mice. So you can basically take like an old magic mice and literally connect them together and see them together. Like, say, like, like, science used to be that. There’s like a long list of Mad science experiments. This is not even the craziest one I’ve seen. There’s, there’s this crazy experiment like unrelated where they take this is gland called the thymus gland. We have our own here in the chest. And mice also have timers. And then these guys start to see Oh, what if we employed like 24 of his glands in one minute? intellect for 24 of them to see what happens? It’s like,

Will Jarvis 1:14:46
what are you doing? That’s awesome. That’s fine.

Jose Ricon 1:14:49
This is what happens when you find people or projects. Yes, go. Well, thanks, buddy. Yes, he was actually useful experiment. Yes. And we said last thing we actually discovered we are missing one Understand what why is it that this works? Why is it that that both are both taking blood out? That is that if you if you are relatively old and you donate blood, this actually seems to have a rejuvenating effect surprisingly, through radicals because it dilutes it dilutes potential misfolded proteins and things just accumulate in your blood that you cannot get rid of, maybe this guy, Robert bloodletting and leeches, maybe they are they’re

Will Jarvis 1:15:29

Jose Ricon 1:15:29
And conversely, or have argued that maybe you can isolate skola young blood plasma factors from things that are more abundant in junk blood, that not no problem and we can use those. And then just like figured out what they are, isolate them, produce them manufactured at scale, and then you could just get a simple injection of this fact that this is very cheap to produce all these others procedure, they’re very cheap. And that could potentially, there’s some experiments in mice doing this. And it also looks very promising. Got it? And yeah, so there’s that. I think also something that will probably begin to see at some point soon is the idea of combined intervention, there seems to be more and more cost to combinations. Got it? I guess, I suppose it would be here, this idea that if you could suppose you could cure cancer tomorrow, just like all cancer is gone? by how much would life expectancy increase?

Will Jarvis 1:16:26
Well, that’s a great question. How much would it

Jose Ricon 1:16:28
three or four years? Four years? Gotcha. So suppose you could cure cardiovascular disease, that’s very similar to four years, right? It’s just because of these diseases tend to occur at the same time. So if you have cancer, it will be your heart, because you have your lungs. Right, so. So basically, even if, suppose you can only die of cancer and of cardiovascular disease. Suppose that if you kill both you live forever, kind of in a very simplistic model. But even if that’s true, yes, curing one of them will show very small effects in lifespan. Yet, if you tackle many things at once, you will show you will see synergistic effects. Now, this is typically not done in academia, because it may be more expensive and difficult, more difficult to disentangle what’s going on tell story about the mechanism and get the paper published, maybe if you’re doing telomeres, maybe even want to do something in a different field and try this blood thing. But I think we will really start to see these combinations of them more broad approach to treating disease. For example, as a good example, if you take arthritis, and osteoarthritis, which is produced simply by the by the mechanical degradation of of cartilage in your inner joint, so just by by using them, right, this calculate is like soft tissue between bones. And then it’s worse off until you get bone on bone contact was Brisbane and arthritis. And you could reduce it, you could, for example, reduce inflammation, you could try to use some stem cell therapies to try to get the cartilage to grow again, that growth is impaired by inflammation. So, so maybe if you only do stem cells, students see match if you only the inflammation. But if you do both, maybe you sit Interesting, interesting, and, unfortunately, in pharma, partly because of the way clinical trials work doing outside of cancer in itself. And color is very rare for companies to do combination of intervention. So for example, if you wanted to this combine, let’s suppose you want to use analytics on synthetic targets, you think of senescence cells, which are thought to be behind versus diseases or contribute to various diseases like arthritis or, or macular degeneration in the eye. And if you wanted to use analytic, and also you said therapy, at the same time, the FDA will tell in your trial, you have to have a control with nothing, one arm for the cell therapy, one arm for symmetric and one arm with those two things. So it’s like a metal explosion of costs, right? So there’s the hope that maybe if these clocks, if we can produce more clocks and have better methods, or better predictors or easier ways to measure function and changes of this code, aging theorem, anti aging therapies, we are waiting 20 years to see what happens if we get that then we can run more and cheaper trials. I guess that’s one of the other focus areas for the aging field to try to find biomarkers that are cheaper and easier to measure so that we can have more and cheaper trials,

Will Jarvis 1:19:24
data that makes a lot of sense. How close do you think real in the field clinical therapies are?

Jose Ricon 1:19:31
I mean, they’re, they’re ready. I mean, in the actually at last year, one of them did a phase two trial and failed. So it’s that they’re slowly getting here. And that are probably scintillates analytics is one of them. There are a bunch of them in various stages of the pipeline. So BRSTV leaving push. So if they hadn’t appeared, they are not purely hypothetical. And also, if all this blood stuff turns out to be actually accurate, that that that that’s that that’s an FDA approved procedure is called plasmapheresis. And so it could be Use didn’t have to prove safety. It’s already safe just like donating blood. Right? So you can, yeah. So you can imagine, I think that that is the next maybe 1020 years, we’ll see lots of lots of these therapies coming into the market. Now, this does not mean yet that you can take let’s say, your eight year old and then do like after after a week, he’s looking like jack again. Yeah, we are. We are not there yet. But there are some there’s some very promising things in the in the pipeline. And and generally and in in the in trying to change the way we think about medicine to try to think instead of separate diseases, as more of they actually are very tightly connected. And we can actually target this this next so far of disease, because aging,

Will Jarvis 1:20:39
it makes a lot of sense, especially since aging seems to feed into all these other issues, right, like your risk for all Alzheimer’s and dementia and heart disease and cancer all go up as you get older.

Jose Ricon 1:20:49
Yeah. Or are going to COVID. If you look at the excess mortality for COVID. If you look at the under 30s. It’s like it’s as if nothing mostly as if nothing happened. Yeah. Whereas if you look at the elderly, you see way more mortality rates?

Will Jarvis 1:21:03
Definitely. That makes a lot of sense. Well, Jose, thank you so much for spending the time today. Where can people find you again? Can you plug your blog and where else you’d like to send people?

Jose Ricon 1:21:12
Yeah, so my blog is ninja.com. That’s n i n dil.com. And by Nick I’m also very active on Twitter on active Cal. That’s a RTR Ke Ke L. Er, yes, like search, search by name, which is very long, and there’s only one person with my name, so you will surely find me.

Will Jarvis 1:21:30
Awesome. Thanks so much.

Jose Ricon 1:21:33
Thank you. It’s great to be here by

Unknown Speaker 1:21:35
now. All right.

Will Jarvis 1:21:41
Well, that’s our show for today. I’m William Jarvis, and I’m Will’s dad. Join us next week for more narratives.

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