Be Like A Sage

This podcast is supported by the Icon School of Medicine at Mount Sinai, an international leader in research, education, and patient care. The Medical and Graduate School is part of the Mount Sinai Health System, one of the largest academic medical systems in New York City. Ranked among the top recipients of NIH funding, researchers at Mount Sinai have made breakthrough discoveries advancing the health of patients. Here, clinicians and scientists push the boundaries in cardiology, cancer, immunology, neuroscience, genomics, geriatrics, environmental medicine, and artificial intelligence. The Icon School of Medicine at Mount Sinai, we find a way. Hey listeners, we released a second episode of our short run series, The Normals on Tuesday. Be sure to check that out, and our last episode in that series comes out on Tuesday. This is a science podcast for April 16th, 2026. I'm Sarah Cressby. First up, new tech for keeping quantum computers cool, without depending on a rare helium isotope. We hear from freelance journalist Zach Sivitz-Gee for that one. Next, the potential harms of commercialized prediction markets with research nerd Needson Packen, and finally, a bonus segment with a working life author on how podcasting changed one PhD student's life. [Music] This weekend science freelance science writer, Zach Sivitz-Gee talks about the latest in ultra-cooling technology. Hi, Zach, welcome back to the podcast. Hey, Sarah, nice to see you. So there are a few drivers to getting new cooling technologies online. One is that quantum computers are going to be getting bigger, and they need to be cold. And our supply of helium three, which is kind of the main element behind keeping things ultra-cold, our supply of that is getting much smaller. Zach, let's take quantum computers first. Why do they need to be so cold? All sorts of quantum technologies are very sensitive. They rely on very cold temperatures in order for the effects that make them interesting. So in this case, the colder the environment is the quieter the background voices. So for these effects to take place, the quantum computers run on. We want it to be as quiet as possible, which means as cold as possible. And they're getting bigger. How big is a quantum computer? So the computer itself is just a little chip, like the size of a baseball card. But when you see images of quantum computers online, what you're really seeing is the fridge that cools that chip, which is about the size of a person. It's this large, gold, elegant, chandelier looking device. When you say a quantum computer is the size of a playing card, that's an experimental one, not one that's actually set up to do the operations that we want them to do. Quantum computers will get bigger because they need more cooling, not because there's more qubits in there, which are obviously subatomic, right? It's really the number of qubits, which is the quantum equivalent of a transistor, essentially, that's going to increase significantly in order for them to grow in the way that people are talking about. The computing power is expected to get much larger. And so therefore, they're going to produce a lot more heat. Right now, we have like a couple of hundred qubits up to a little over a thousand qubits. And some companies think that they'll need around a million qubits in order for them to do practically useful computations. So that is significantly larger, but we're not talking about the chip itself suddenly being the size of a room. The chip itself is much more powerful. And so we need more powerful cooling technologies. So how big would, if we're using the technology that we have today for cooling, how big would the cooler be if we had that enormous number of qubits? So to give you a sense of scale, delusion fridges, which are the refrigerators that cool quantum computers primarily. The traditional ones are roughly the size of a person. And when I was at Blue Forest, which is one of the leading companies building these fridges, they showed me their next generation fridge, which is built for today's largest quantum computers of around a thousand qubits. And it's more like the size of an elevator car. So it's significantly larger. It sort of powers over you. The capacity is like somewhere between six and 12 people. For an elevator. Yeah, exactly. Exactly. So you can just imagine like as these devices get significantly more powerful, in theory, they could have to get much larger. But what's more pressing is the idea that they'll need more of this ultra rare, ultra important gas, which powers the coolers, which is helium three. So this is the other driver. We're running low on helium three. It's a super rare isotope of helium. Helium was also not that easy to come by these days. Actually, just your basic balloon filling helium. So where do we get helium three now? And like how low is our supply? Much of the world's supply of helium three actually comes from nuclear weapons, believe it or not. Since the Cold War, governments have added this other gas to nuclear weapons called Tritium, in order to make them more destructive. And that Tritium slowly decays into helium three. And that provides much of the supply for global helium three. But that's kind of politically sensitive, I would say. Totally, yeah. Working with whoever's stockpiling nuclear weapons, getting some some byproduct of that process might be tricky for research scientists. Yeah, so much of the world's gas is controlled by the US and Russian governments. It's subject to geopolitical drama, as you might imagine. We're also not quite sure how much of this gas there is for this reason. You can sort of, if you know how big a government's helium three stockpile is, you can sort of infer the size of their nuclear stockpile. That was actually a big quest for me. And the story was figuring out a rough estimate of how big the US stockpile is, because that's very important information for figuring out the future of these cooling technologies. And whether they're going to have a big problem. I did come across a document from 2021 from what looked like an internal presentation that gave a reference which seemed to be referencing the size of the US stockpile around that time, which put it around 90,000 liters. Okay, 90,000 liters. Did DOE decline to comment on whether that actually represents the current size of the stockpile of this gas? But the website does now seem to be offline. So this is, I think, the best estimate that we have. And it's worth mentioning that when I talk to Blue Forest, which is this company building these fridges about how much of this gas we would need to power the size of the devices that they're talking about, they estimate that it could be tens of thousands, you know, around 40,000 liters. And that's to power one device. How many quantum computers do we need, Zach? I mean, do we just need one? Or do we need two? Let's answer this way. There are dozens of companies around the US who are working on building their own quantum computers right now. There are probably hundreds of companies around the world who are working to build these. And so if we only have the gas to pull one or two of these devices, there seems to be a mismatch in expectations going on somewhere. How is it involved in making things ultra-cold in these delusion fridges that are used for quantum experiments and quantum computing? If you think about how a normal, like, your refrigerator at home works, you have this series of tubes, and they all pump this refrigerant around. And that refrigerant expands and it compresses. And in this process of undergoing these phase changes, it sort of sucks out heat from inside of the fridge and it dumps out it out in the back of the fridge. Delusion fridges are doing the same sort of thing, but with a different refrigerant here. And it goes through a different sort of phase change. And so rather than this liquid that's pulsing through your refrigerator at home, it's using a combination of helium 3 and helium 4 isotopes. And something very special happens with these helium gases, which is that below a certain temperature, which is very cold, around one Kelvin. Should I explain what Kelvin is? Should I tell Celsius? So absolute zero is zero Kelvin, which is minus 273 Celsius. Below around 272 degrees Celsius, something very strange happens that helium 3 and helium 4, that this mixture of gases will separate sort of like oil and water. And then you can get the helium 3 on top to dilute into the helium 4 layer essentially. And this process is endothermic, which means that it takes heat and it does this very efficiently and so it's able to get things to very, very low temperatures. That's the basic premise of how delusion fridges work. You're a fraction above absolute zero. This is the coldest kind of place on Earth. It's the coldest place in the universe actually. It's hundreds or thousands of times colder than the vacuum of deep space. That's just kind of mind blowing. I mean, really, so this is kind of the standard everyone is trying to meet when they're looking for alternatives to helium 3 as the kind of basis of the cooling technology. But before we kind of go into those other technologies, is there another way we could be getting more helium 3? We could just get a lot of it and then we can keep making bigger and bigger fridges. So this is something that a lot of people are looking into given the potential future shortage of helium 3. So there are a couple different routes that people are taking. Companies who are building delusion fridges are looking to optimize their fridges to use less helium 3. That's one option. Others are looking for new sources of helium 3, which could include building new nuclear fission plants, which have Tritium as a byproduct and that decays in T3. They could also repurpose other plants to produce more helium 3. There's also this other more out there solution of flying to the moon. Yeah, the moon for some reason has a lot of helium 3 on it. So we can just go mine on the moon. That's the thought? Yeah, it's a pretty simple idea. Like Keeling 3 is in the universe. It's not very rare. It's actually quite common. It's one of the most abundant isotopes in the universe. And it's produced in the sun of all places. But because the earth has a magnetic field, the supply from the sun gets deflected, but because the moon doesn't have a magnetic field, some people suspect that it piles up there. We're not totally sure about that, but people seem to be rather confident. So guess we got to go back. I got to go back to the moon. So let's talk about some of the alternatives to the dilution fridges that are powered by Helium 3, or the cooling is generated by Helium 3. One that I thought was really interesting, especially because of the size aspect that we're talking about is doing on chip cooling. So building into these chips, the ability for them to cool themselves. How would that work? What kind of technology or physics goes on in there? There are a couple of ways that people are trying to build fridges without relying on Helium 3 altogether. Some of these involve cooling on the chip directly itself. And there are a couple of ways to do this. So one that I talked to some researchers who are trying this is they essentially create a trap for the heat in the chip so that they sequester all of the heat to one side of the chip. Now when we're talking about heat on a quantum chip, there are two important sources of heat. So it's the energy of the electrons in the chip and it's the vibrations of the chip itself. One idea that people have is you can use a certain combination of materials that basically traps the hot electrons. So it gets them to jump from one material into the other material only if they have above a certain threshold of energy so that filters out, you know, only the hot electrons are going to go over there and then it gets them to stay there basically. And then it also happens to reduce the amount of vibrations that's happening in the material. So it has this double effective cooling basically. We really need to get into the very basic physics of heat in order to understand how to do this at such a small scale with such tiny things. It's really interesting. So how far along is this on the chip cooling technology? Is this something people have built or are they like close to under one Calvin cooling with that? I would say this on chip, what we call electronic cooling is sort of an approved of concept fees where they're really demonstrating the basic principles of this working. It's still very much the academic setting they've managed to show they can do this at various temperature stages. Now they're working on putting those stages together in order to get a streamlined process that cools in, you know, all the way through the pipeline and they're trying to build a platform that that can get you basically from the entire range where helium three is needed. So that one is we're calling it electronic cooling, but there's also this other one that kind of relates to LEDs, which I think of as like, oh, you know, it's flow energy lighting supply. This really blew my mind to think of it. LED is basically a heat pump. Can you talk about that one? The basic idea is that like you said, we think of LEDs as being very efficient. The idea here is that they can sort of be in some very specific sense, they can be more than 100% efficient. And what I mean by that is that if you're thinking about the efficiency of light as how much electricity you put into it versus how much light you get out of it, imagine for a moment that for this LED, you need five watts to power it. If you supply the LED with a little bit less than five watts, say, whatever, four and a half watts, the LED can actually suck up the remaining half a lot of energy from the heat in the environment and use that to glow anyways. And so in this sense, it is actually pooling the room around it. And so the general idea here is that you're going to use this effect to get additional cooling. My LED lights are not cold. Yeah. I'm touching one right now. Yeah. So there must be a lot of other stuff happening. But when you're at the quantum level, this is something that you can observe. And it would actually be meaningful when you're trying to squeak down under half a Kelvin. Yeah, I mean, I should say they actually haven't even conclusively demonstrated this photonic cooling effect yet. They have some indirect evidence that happens. Some people seem pretty confident that it is in fact a thing. But you know, exploiting that for actual commercial applications is another story. Theory's there. The math might check out, but getting the materials assembled and operational is still on the horizon. Yeah. Okay, very cool. All right. So we're going to move away from on-chip cooling technology to a different kind that actually is available now. And this is magneto-choloric cooling. And this is something that you could get. It doesn't necessarily get all the way down to quantum computing temperatures. How does that one work? And how has it been implemented for getting things super cold? Magnetic cooling has been around actually before dilution refrigerators. It's been around for a long time. There are certain types of materials called magneto-choloric materials where when you put them in a magnetic field, they will heat up. When you put an object in a magnetic field, what happens is that basically the atoms inside this material have their own little magnetic fields. You can think of them as little arrows. And so when you apply the magnet, all those arrows align, the material gets magnetized. When we put this material in the magnetic field, all these arrows align, the material heats up. And then we take that heat and we dump it away. The arrows in the material will naturally disorder and start to misalign. That process requires heat. And it's going to suck that heat from the environment around it. And that's what gives us our cooling. How has this been implemented to cool down quantum experiments or quantum computing? The hold up with this, the reason why this hasn't been in place for a long time, is that you could basically do this once. It's neat, but once this process happens, then you've done the cooling. And what companies like Qtra and Germany are starting to do is they figured out a way to do this continuously, which is essentially you just take two of these cooling devices and you attach them both to the same device simultaneously. And then when one of them is actively cooling, the other one is disconnected and it sort of resets. And then you can flip between the two of them and then get this continuous cooling. And so all you need for that is the materials and some electricity to get things cold. You don't need helium three and the magnets and the magnets. Yeah. But no helium three. Yeah, importantly. And so that's cold enough right now for people who want to do quantum experiments, who want to do it in the lab. It's mainly at this point, it doesn't get quite as cold or have quite as much cooling power. So this ability to keep things cold as solution projects do. But it is proving useful for characterizing quantum devices sort of testing them as they're being built. But at the current stage where they are, we couldn't use this to run a full quantum computer. But they have hopes that they'll get there one day. Is anybody looking into just like not having quantum computing being so cold? Is that an area that people are exploring? It's kind of like a big technological hurdle to get your computer to work if it has to be really close to absolute zero. This is definitely something that people are looking into. And there are some modalities of quantum computing that are supposed to work at much higher temperatures. The caveat here is that well, for one, we don't have a quantum computer at the size of the scale that we want. So it's unclear which one of these is actually going to scale. Some of these that do require very low temperatures, they're going to keep on pushing ahead. It may be that those are the only ones that prove scalable. And then we need these low temperatures. But also even many of the ones that say that they can operate at much higher temperatures. When you consider all of the wiring and all of the components that go into the computers, they end up needing much more cooling power than they say they're going to. And so it may be that they end up needing more heating through than they say. I've been told what's going on with quantum computing. We haven't actually checked in in a while. Zach, like, where are we? Are we making quantum computers? Have we solved some of these really big problems like error correction and all that stuff? Again, it always really depends on who you ask. Companies are still promising functioning quantum computers by the end of the decade. A lot of researchers in the field still express low skepticism that we're going to see practical applications of these devices in the near term future. But I will say there has been real progress on showing practical applications of these devices. I mean, just in the past week or two, there was a series of papers out that shows how one of the big potential uses of quantum computing, which is cracking modern encryption codes, that this is actually feasible without a lot fewer qubits than they thought we would need before. So it really raises the stakes on this quantum computing race. Definitely. Oh, that's very interesting. I'm glad we got to talk about. All right, Zach, thanks so much for talking with me about this. Always a pleasure, Sarah. Zach Savisky is a freelance science journalist based in Berlin. You can find the future we talked about at science.org/podcast. Apply today for a chance to win the Science and Sign Life Lab prize for young scientists. This annual prize recognizes outstanding doctoral research in life science, including cell and molecular biology, genomics, proteomics, systems biology, ecology and environment, and molecular medicine. Apply today at science.org/prices for a chance at the $30,000 grand prize. Submissions closed July 15th, 2026. Submissions for the Ependorf and Science Prize for Neurobiology are now open. The prize for neurobiology recognizes outstanding young researchers, age 35 and under, for exceptional neurobiological research conducted in the past three years. The winner receives $25,000 and publication of their essay in science. Apply now at science.org/prices before the June 15th, 2026 deadline. Also on the other side. On the site this week, freelance science writer Hannah Richter wrote for the news side about the Pacific Coastal Fog Research Project. This is a big initiative looking to better understand fog, which turns out to be a vital water resource that could be lost in a warming world. From the journal side, in science advances this week, a Bayward Dina and colleagues report that not all naked mole rat queens take over violently when the old queen is removed or dies. They observed in a captive colony a peaceful succession in these U-social mammals. In the science commentary section, there's an expert voices column by Aud Belaard. She writes about robots that can transition between forms of locomotion, swimming, rolling, flying, all while manipulating objects and the major advancements that have enabled these types of designs. Stay tuned for a chat about prediction markets as a public health threat. This week in science, Needson Packen wrote a policy forum on the potential harms of the rise of prediction markets and how they can be studied and potentially addressed. Hi Needson, welcome to the science podcast. Hi, thanks for having me. Just a note on transparency here, my brother-in-law is the chief legal officer for one of the big prediction markets. But we really haven't talked about his work very much, which you'll be able to tell as soon as I start asking these really basic questions right now. So Needson, can you walk us through an online commercial prediction market experience right now? Prediction markets are a way to kind of place your guess in a way or forecast or bet on whether a certain event is like it to happen or not. This pretty much can cover anything under the sun from Taylor Swift's wedding date to who's going to win a major sports event to even wars and of course financial events. Who picks what you can place money on or what you can forecast or buy a contract on? How does that get into the platform and who sets the parameters for it? They vary. There are a lot out there and they could be created automatically using AI, different types of bets, people interested in something could initiate as well. And you can based on the odds, make a nice amount of money and we've seen some of those play on an in-use recently events that no one really thought were going to happen in some of them speculation about insider trading also took place after because no one really could see it coming supposedly. So have you spent some time yourself on these prediction markets trying it out? I have to say I very much enjoy just looking at the different types of categories and the different types of things around things giving. There were all sorts of bets going on as to which Turkey would the president pick as the official. I saw some bets yesterday on eggs the other times it's more interesting and revealing about the financial markets or about geopolitical events that are very much integrated in two mainstream media. It's interesting to follow. There's this idea in academia that crowdsourcing information like this predictions about the future forecasting can yield very useful results. And then surveying people or asking experts this has shown in certain kinds of settings to yield useful information about the future. Now that these prediction markets are getting commercialized they're just getting a lot more scale, a lot more people involved. What's changed that has made these so much more popular and active? Their origin sort of started with that and what happened in the last few years is that everyone found out and wanted to participate and there's also significant commercial aspects to these platforms. It has become a super accessible kind of an exercise in which we've seen following the presidential action in the US in 2024. It's a big sporting events that the public has fallen in love with for the prediction markets and everyone wants in and of course money could be made. This is a big business now. We're talking about billions of dollars a week are moving across these platforms and you call out in your piece that at this scale the risks for a population harm should be evaluated. An interesting thing that we sort of started analyzing my co-author and I who's an addiction expert. So this is her expert. These the addiction world and some of our analysis is also based a lot on addiction literature. We focused on three main threats that we would like to be further studied so that the use of prediction markets could be dying to say for a way. And so the first one is really the democratic threat. It is a threat because these markets are very broad include everything. A super ball event is one that attracts a lot of money but some of the specific events are narrower in terms of participation. So for example, if you have a very thin market it's fairly easy for bigger investors to invest not that much and be able to kind of tilt the result or dominate the market. Does there betting heavily on one side or the other can influence what people see as a forecast? When you watch CNN or read Reveiter's news you see about online but it doesn't tell you how many people have participated in that specific market markets which might have seen our liquidity in which less money much less money could tilt or influence or impact more the result that you're seeing. The other thing is we've all been reading about insider trader type of information and even though this is not governed by securities laws because we're not talking about securities we're talking about event contracts. Some comparable have been drawn as to what type of regulation we would want to see and of course the platforms themselves have been stepping up and emphasizing how critical this is and how mindful they are of these bets are event contracts and therefore not under the SEC but under the CFTC's supervision. That's the commodities in future trading. That's like oil and corn and that kind of stuff. And they do have regulation and they are mindful of market integrity but it is not under the same type of regulatory schemes that are much more developed that the SEC uses for insider trading. So in the last couple of months we've seen all sorts of congressional initiatives and different lawmakers saying we need to create different types of rules that would more strictly address these types of conducts in non-securities like products such as event contracts. If you think about sports betting there's really clear like you're not supposed to throw a game. You're not supposed to change the outcome. It's supposed to be independent of how the betting is going but if there's this crossover and someone is like I'm making a decision in my government role and there's money on the line that I could have access to that's very different. And not just access to when we're talking about like geopolitical markets and actors and the way the public perceives this and then a public pushback or tilting in a public opinion those could be different. Right. And so for example in the US you cannot have foreign money flowing to sponsor candidates but you can bet on certain countries elections even if you're not from that country and if it's a thin market and then liquidity means that you can sort of influence what the results look like to the people in that country for example then you can already start maybe potentially manipulating a little bit. We should mention there's another layer here with the fact that cryptocurrency is acceptable in these markets and so that means it anonymity is maybe a little bit easier to obtain because you are not using banks to move this money around. Not all but some prediction market that's also used crypto and so while it does increase access to some extent it does cause or could resulting issues associated with an anonymity or enthemenaging things like that. We talked a little bit about the threats of democracy foreign money influencing what predictions look like people inside of government releasing information. Another aspect that you address as a potential harm is that there's a lot of similarities to gambling in these prediction markets. What parallels do you want to talk about? So this is not a very easy comparison anyways because the two industries are obviously defect but what we kind of look at in prior work is that there are certain gambling mechanisms in disguise that are to some extent in play here. We kind of broke it into three different layers. The first one is the addictive behavioral level. We looked at some of the platforms and definitely some of them have featured all sorts of addictive design mechanisms that are familiar to addiction scholars from the literature and those include things like cow dung timers and street bonuses and leader board, even loot box style rewards. There's a similar toolkit that is being utilized. And then the second level we looked at is the cognitive motivational level. We said that there's an artificial progression of systems that are exploiting users need to basically show that they belong, be part of that community feel related, feel that they're competent. We see things like personalized avatars, creating an illusion of autonomy, you know, foam o fear of messing out. Yeah. Neural level. We've seen things that kind of resemble the schedules that activate the same circuits, slot machines or infinite events, dreams that eliminate stopping points, algorithmic targeting of rapidly resolving markets. And even though this is different from casinos, right? None of this comes with things that we do see casinos like deposit limits for ability checks, mandatory breaks. These are the rules that they have in those places. And even though some of the same things are happening over here, none of that's being applied at this point or it's not being applied evenly. Yeah, I mean, it's not being applied because it's not the same industry. It's being branded and being perceived as a different industry and there are differences. And also, by the way, unlike online sports betting prediction markets don't necessarily derive their addictive potential from rapid resolution. As you said before, some contracts are pretty long-term, but we do see things that kind of make it still very comparable and concerning. Studies have not been done on prediction markets per se, but they could be relevant. And that's a main part of our claim. We're not saying this is prediction markets, it's going to make per se, but we're saying there are comprehables. We should study this so that we can design a more safe ecosystem for prediction markets. And the last thing is really, we see all these push notifications and these strict bonuses and discontinuous stream of action that we all have gotten so comfortable with in the digital era, whether it's Netflix or just scrolling on your feed. And this is ongoing all the time. So even if one contract is not coming up anytime soon, you have all these other things that are filling you up with excitement. So getting into the specifics of the harm here that's possible, is it mostly from like this along the same lines of if there is something bad happening? Is it related to gambling addiction? So a few things, one we do know that the World Health Organization has recognized gambling as mental health disorder, gambling addiction. Right. That requires attention. And we see that online gambling is a big part of it. The numbers are much higher. Not every single person that is going to place a bet on a sportsbedic platform. And certainly not everyone that is on a prediction market is going to get addicted, right? But it's a game of numbers. It's a game of scale. We've created this opportunity for very large number of people to go on and use these platforms. If we even stick with the traditional low number, even if we go with the 2 to 3% of users to develop behavioral disorders, if you scale it up to, you know, dozens of millions of participants, these numbers become significant. The larger the police, the more people could be impacted. And when we talk about people that suffer from addictions, each individual like that impacts six people around them. So whether it's financial or family, mental, and this is when you cross over the clinical threshold, then there are a lot of people be awake, right? That suffer from all sorts of other harms. And so, you know, we invoke this prevention paradox that the biggest public health costs are hidden in plain sight. But we really want to be mindful of them and understand them and address them before it becomes a big problem. You know, one thing you call out in the piece, I think, is really interesting is the idea that that people may not think of this as gambling as they're doing it, even if it has some of the same addictive qualities, people are able to kind of like keep themselves distant from that label because of the way this is presented and sold to them. Yeah, so actually that's a very good point. As it is, no one wants to come out and say, I'm addicted to something. A lot of this is being reprinted as forecast, rather than betting or gambling. And we see this terminology being used across the board in financial markets now, you know, event contracts also sounds very financial. And it is true that many of these events on which we're placing predictions are of financial nature. But Gaston made how many times you know, in Musk, he's going to tweet a certain word by tomorrow is not necessarily something of economic value. We kind of we brand all this is just one big forecasting type of a system, but really, we should differentiate between the different types. And because of this, it's harder to raise awareness. And even if users would have a problem, they would delay help seeking, even if financial or psychological damages do accumulate. And at least in one of the platforms that we examine, at some point, they could have placed up to half a million dollars without a single safeguard. But the point is we're also mindful of the fact that it would be harder for people to understand this to be an issue. What kind of studies do you see that it being necessary in the space to better understand potential harms here? We should do more work really trying to understand and gain some, you know, scientific accountability as to what could be the consequences and how we could create more guardials to enable this industry to present these advantages and exist, but also minimize any potential risks or harms. And so for example, we really need to better understand how the interface design standards mitigated addictive features and enforce certain elements or how to create guardrails that would minimize any potential harm. You know, a lot of studies have been done in the financial context with traditional traders and they traders and all sorts of financial activity to understand what their boundaries should be or what type of regulation he's needed. What is kind of the status of the regulation here in the US? We're in the midst of a federal state battle of sort, right, where different states are are saying, you know, we are the ones with the authority to regulate and enforce gambling and the federal government basically saying this is an event contract and as such, this is a financial product that we regulate. We've seen like more than, you know, I think 20 states in which we've saw that tension play out in courts and interestingly enough, some district courts or federal or state courts have gone different ways. Some legal experts are predicting that this would maybe end up in the Supreme Court next year. Thanks so much for talking with me about this has been really fascinating. Thank you. I appreciate it. It's great being here. Needs on packing. It's a professor of law at the Zickland School of Business, Baruch College, City University of New York and the University of Haifa faculty of law. You can find a link to her policy forum at science.org/podcast. In our final segment this week, we are podcasting about podcasting. This week we have a special treat. We have a science podcaster, Philippo Delar Malina. Philippo is a co-host of neuropod cases. This is a neuroscience podcast that covers basic research and translational medicine. He wrote a work in life column for the magazine this week and I really enjoy these these essays. Basically, just give a little snapshot of a scientist's life, what they're doing, what they're thinking about in a very personalized way and they're pretty well read because that's a lot of our readership much of the time and of course this is very close to my heart because it's about starting a podcast as a scientist. Let's get into it. What inspired you to write this piece now and you know to send this in as a work in life column. The moment that really inspired the article that I wrote for science came when one of our guests forwarded me a message from a listener overseas. They had just been diagnosed with a small brain tumor and after listening to our episode, they reached out to ask about possible ways to get involved in research and clinical trials and I was in the middle of a frustrating stretch in the lab. So reading that email made me pause for a second. It was a sudden reminder that science doesn't just exist inside the lab or in the papers. It can reach people and have a real world impact as well. So that moment really shifted my perspective and shaped how I approached both my research and science communication in general. So how did this come about? How did you decide to take to the airwaves? Everything started out of this phase in my PhD at the very beginning where I was struggling to see the long-term effects of the work that I was doing every single day in the lab. I've always been a very avid podcast listener. I would usually listen to a couple of episodes per day. I realized that I wanted to do a little bit more science outreach. So I had volunteered at the Museum of Liverpool, the World Museum. It was a science event for children that were basically showing them a few instruments, researchers using the lab. I realized that I really enjoyed that by the same time there were a lot of gaps during the day where we were just not doing anything because people were not coming along and during that time I was listening to podcasts and that's when I had the idea of starting my own thing. At the beginning it was just an idea that I had and I didn't not expect it to become anything serious but then I pitched the idea my friend would then became the co-host. And you managed to join a podcast that was already in production, which I think is really smart because starting from zero is very difficult in the world of podcasting. It was great to be involved with something that was already out there, especially because I knew what my audience was already and so I could target exactly the sort of questions and answers that people wanted to hear. You're now interviewing researchers about their clinical, is it experiments or results or what do you focus on? Yeah, so what we usually do is reach out to clinical researchers or basic researchers who are doing experiments or who have just published work that has major translational applications. So we obviously care about the applications of research. We think that there's potential behind every single research project that we bring onto the recording stage. So it's very science-focused, but we obviously want to bring in the potential of what the research is actually bringing to the table because if you're studying us very specific neuromuscular disease that is very rare and no one really knows about it, there are people out there who are affected by that disease and obviously we want them to know that there are people working on this problem. There may be clinical trials currently taking place around the world. The overall idea is to spread the word. I see how that can fill the gap you are feeling early in your PhD where you are at the bench or in the lab scraping away at a tiny detail and then to be like, well, here I can actually tell people about things further along, things that may translate to their lives. It sounds like it would be rewarding for that period of your life. Yeah, absolutely. I was at a stage where I didn't really see where the experiments were taking me. And so I didn't really see what the potential of the beginning of my PhD could be or would have been. And so it was really helpful to see senior researchers who said that they felt, at some point, in their career that they were at the same stage that I found myself in. And the fact that they had gone through that phase means that it was just a phase. And over time, things could have changed. And I could have found results that were very interesting for my own PhD project, which is what later happened. Especially thanks to one of the guests that we had on the show, who suggested that scaling up sometimes is the solution. It was in my case because I was studying interactions inside the cell, but very specific ones. And once we had scaled up the number of things that we were looking at at at the same time, then the methodology changed as well and the pipeline improved. And that's what later became the biggest chunk of my PhD. And also later on reached publication. And you got that from my guest? And I got that from a guest. So I was very satisfied. And that's what actually changed my PhD, I think, from a position which I found myself in this stalling phase to a position where my PhD felt actually successful. And that's probably what a lot of PhD students feel at the beginning of their academic journey. Part of training is conveying your research to your peers and sometimes to the public. Do you feel like doing that on a podcast, asking people questions and helping them convey what they're doing? Does that change the way you communicate about science? It's absolutely did. I remember that after hitting record on the first episode and after having that first conversation, I felt a lot more confident about talking but other people's science and other people's research. That I think is the key thing that when PhD students go to conferences or when they attend science festivals and they want to do networking and they try to reach out to people, but they just feel shy because they know they're in a junior position. And then interviewing live and following the conversation along with my co-host and with the guest also improved how I asked questions in the lab meetings. I was more precise, more confident and I was just on the flight. And so the conversations just became story telling over time and so they just felt like friendly chats. And I felt a lot more confident about talking about other people's work and then also talking about my own work with our guests and then other people at conferences. I find there's like a balance between over preparing and under preparing for an interview. If I read the paper front to back, do a bunch of research. I'm a little bit too in the know and I end up not asking a bigger questions or not as much as comes from the guest. Do you find that there's kind of this like you could know too much to ask good questions? Yeah, sometimes for sure. I noticed that some guests were just as nervous as I was. And they were very beginning and so they were quite happy with redoing some takes or with recording some parts again. It wasn't just me. It was everyone who the fact that you have to talk in public or the fact that you know that other people who will be listening to this can kind of make you shy or make you feel less confident about the way that you definitely know how to phrase things. I find that it's always a little bit of a delicate issue when someone has English as their second language. You know, they're already doing something amazing. They learn a second language, they're doing science in it, they are publishing in it. Now you're asked them to talk about it live on the air and people can resist that. But I think for our show, it's really important to like demonstrate the internationalness of science, how many people all over the world are doing this and working really hard to communicate with other scientists in the public. The fact that English is my second language did feel like a struggle at the beginning for sure. And it was one of the things that kept me from doing it right away. And that's why months went by before I had pitched the idea of podcasting to my friend and to the uh, neuropod cases team. But it didn't stop me in the end. I realized that there's a lot of people in research from a variety of countries and from a variety of nationalities. And the fact that English is my second language should not have stopped me there. If anything, it kind of gave me some situation a little bit of an advantage because I had to stop twice before saying something or I had to think twice before asking a question that some people were missing just because it took me longer at the beginning to phrase exactly what I wanted to say. And so yeah, for sure. I do think that sometimes not really understanding or knowing what's going on is helpful for the guests. Like if I don't really know what's going on because it sometimes happens, I think I understand a paper, I come in, I ask questions and I'm like, Oh, I miss this really key point. And that gets them more excited to explain or like they're like, I got to go to the basics here. I'm like, yes, please go to the basics because sometimes I don't know what's their target. Yeah, absolutely. And it helps. It helps. It definitely does help. And I'm so glad that you're saying that because this means that my co and I haven't had a very isolated experience. But you've seen this as well. We did actually do this one past where in an episode, I didn't really know much about the topic, but I was very intrigued by the potential of the research from a clinical point of view. But my co and I didn't really know much about that topic. And so obviously what we usually do is spend a bunch of time reading the papers, the publications and educate ourselves before obviously hitting record and getting into the conversation with the guest. But what we did this fun time, we just showed up with no knowledge whatsoever of what the background was. And I think it was one of our mostly listened episodes so far just because we needed to ask the guest obviously to slow down a little bit and to just give a wider background to everything. You know, people that were also experts in that area will listen to the episode and they will probably still enjoy the introductory bit. But it's everyone else who is just missing out. And so I think that's a very important part. It sounds like you really benefited a lot in your scientific career in the PhD process. From doing this podcast, do you feel like it had benefits outside of that for your personal life? Yeah, absolutely. So at the beginning, it felt overwhelming, but in a wonderful way. I mean that in a really wonderful way, because I felt hope for science and a deep sense of connection with my academic colleagues. And I had lost that. I have to be honest with myself and with everyone in the community. I definitely had lost that. And if you were, I was stuck in the lab worrying about minor technical setbacks. And suddenly I realized that something that I had been doing was making a tangible difference in someone else's life. And so it reminded me why I became a scientist and why I'd retrubually matters in the first place. I definitely had this turning point during my PhD emotionally and professionally. I've always been interested in other people's research outside of my PhD and outside of my education and my background. And so making that a hobby and then a profession as well, I had not seen that coming, but doing that was definitely one of the best decisions I've made in my life. Are you recommending everyone start a podcast? Or is there some more general advice that you could share for other people who might be in your position? I think the general lesson here, the general advice that I can give is to find up any project outside your main area of interest and your research that keeps your curiosity alive. You may not have encountered the same problems that I have at the very beginning of my PhD, but in general, in science, it's I think it's always good to have a side hustle or a side project that involves science and research. So let's be honest, people who do research are people who are passionate about science in general. Chances are it'll show up in your hobby. Yeah, exactly. So having something like that that will show up as a hobby would be great. I'm not saying that once you start a podcast now, so it could be just general outreach at museums or volunteering or mentoring someone or even just talking about your science with someone outside of your field or with your friends. So these experiences can teach you skills that you want to learn in the lab, I think, like communication and perspective and above all confidence. And they can actually feed back into your research in surprising ways, maybe later on in life. Like it happened for me. Thank you so much for talking with me. This has been wonderful to hear about. Thank you so much for bringing me on the show. It's been a pleasure. And that concludes this edition of the science podcast. If you have any comments or suggestions right to us at [email protected] to find us on podcast apps, search for science magazine or listen on our website science.org/podcast. This show was edited by me Sarah Crespie and Kevin McLean. We had production help from Poddagy. Our music is by Jeffrey Cook and Wenquay Wen. On behalf of science and his publisher Triple S, thanks for joining us. [Music]