with Spencer Greenberg
the podcast about ideas that matter

Episode 091: The science of addiction (with Crystal Dilworth)

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February 11, 2022

Why do people get addicted to cigarettes? Should people use nicotine as a stimulant (without smoking it, of course)? What percent of people have a hard time quitting smoking once they start? What genetic factors predispose a person to nicotine addiction? How addictive is alcohol relative to nicotine? Is vaping less addictive and/or less negatively impactful on cardiovascular health than smoking? How can we train scientists to be better leaders? How valuable are graduate students to their advisors, mentors, and departments in various fields? How can researchers tell better stories about the data they've collected? Why are there fewer girls and women in science? Why can educators do to encourage more girls and women to work in scientific fields? Will increasing diversity in science improve science?

Dr. Crystal Dilworth is a neuroscientist, dancer/choreographer, and television host on a mission to help others better understand themselves and their world. Saturday Mornings you can find her on CBS as Mission Unstoppable's "Dr. Brain" or weekly on Voice of America as the host of VOA-Tek. Behind the camera, the Caltech-trained neuroscientist coaches both public and private organizations in how to foster meaningful communication and understanding within internal teams and externally to the public, and she loves leveraging her unconventional background in the performing arts to creatively produce large-scale public events championing science and technology. Dr. Dilworth is an AAAS IF/THEN Ambassador for STEM and lives in Jakarta, Indonesia with her husband and two cats. Find her on Instagram at @PolycrystalhD.

Further reading:

JOSH: Hello, and welcome to Clearer Thinking with Spencer Greenberg, the podcast about ideas that matter. I'm Josh Castle, the producer of the podcast. And I'm so glad you've joined us today. In this episode, Spencer speaks with Crystal Dilworth, about the chemistry of nicotine addiction, how scientists can be better leaders and the peer-review process.

SPENCER: Crystal, welcome. It's great to have you here.

CRYSTAL: Thank you so much for having me. I'm excited to be here.

SPENCER: So the first thing I want to ask you about is why people get addicted to cigarettes.

CRYSTAL: Wow, that's such a huge topic. But really, I think about addiction to cigarettes, it's like two different ways. So one is sort of like the behavioral learning and memory components. So the reason why people will say, "Oh, I'm not a smoker, I only smoke when I drink," but they're actually a smoker. And then there's the chemistry side of it, which is sort of what I've spent a lot of my time trying to understand, which is actually how nicotine influences the chemistry of our brain. And actually, the proteins that the cells in our brain are creating to increase that positive feedback loop that we call addiction.

SPENCER: So I have some friends that advocate people use nicotine as kind of a stimulant, like not through cigarettes, but maybe through some other mechanism, like vaping or something like that. And to me, this is a terrifying idea. And the reason it's a terrifying idea is because I have two friends in particular, that started smoking at a young age, and just have found it just so difficult to quit, and there's watching the kind of torment they go through attempting to quit, and kind of months of like trying to get off of it, and be constantly throughout the day like thinking about smoking, and just constantly interrupting what they're doing. And then when they're in a stressful situation, they kind of get fixated on it. And eventually, usually, inevitably, they go back to smoking after giving up after three months. So like having watched two people in my life go through that. I'm just like, oh my God, why would you ever take that chemical? So I'm curious to hear your reaction to that.

CRYSTAL: Yeah, I mean, there's the clinical behavioral aspect of addiction, right, which is like, but it's a clinical addiction, it's really interfering with your personal, professional life, like your ability to function is dependent on the thing that you're addicted to. On the chemistry side, though, what we're really talking about is rewiring your biology to function in the presence of that chemical. And actually, nicotine as a compound in humans can work as a cognitive enhancer. So I know people that know a little bit of science, and they're chewing nicotine gum to get themselves through the day because they don't want the negative cardiovascular impact of smoking or vaping. But they do want that little acetylcholine boost and dopamine boost that you get when you're exposed to nicotine. Some people are genetically more predisposed to be dependent on nicotine than others. You do hear about the people that say, I used to be a smoker, and now I'm not and I quit cold turkey 18 years ago, and I never had another cigarette. And then there are those that say, oh, yeah, I am not a smoker, I quit five times, you know, the actual success rate of decrease in addiction is like 12 to 20%. And a lot of that is environmental, but also genetics.

SPENCER: So one thing I've wondered about is what sort of percent of people that if they were to like smoke daily for let's say, a few months, would just find an incredibly hard time quitting versus what percent? Would it be like, no big deal, I just stop and you know, maybe I feel bad for a few days, but it's all good. Do we know the answer to that kind of thing?

CRYSTAL: I can give you some numbers. But honestly, in most population studies, what we know is mostly centered in white western populations. And in order to really be able to answer your question, I would need to know more about the impact of genetics in Asian and African populations. We actually know that there are differences. Actually, a colleague in the lab that I worked in, Brandon Henderson did some really interesting studies on why African American populations tend to smoke more menthol cigarettes than conventional cigarettes. And that actually has to do with their genetic profile and that menthol cigarettes actually increases the positive dopamine reaction to exposure to nicotine.

SPENCER: There's some good interaction between genetics and the kind of chemical compounds in menthol versus regular cigarettes.

CRYSTAL: Yeah, and it doesn't just have to be like these additive compounds. So I study a particular amino acid substitution and a particular subunit of a particular nicotinic acetylcholine receptor. This is a mutation that's found in some Caucasian populations. And if you have this amino acid substitution this mutation in your DNA, you are more likely to become dependent on nicotine if you're ever exposed to it. So it can be in the composition of the proteins. And it can also be additional reactions to additives in the cigarette itself or in the vape juice.

SPENCER: So if someone starts smoking or they start, you know, you to take nicotine gum or vaping, they're kind of rolling the dice with their genetics, like they might have genetics that makes it so that they're less likely to be addicted. And they might have genetics where they just find it incredibly hard to quit. Is that accurate?

CRYSTAL: Yeah, absolutely. The majority of the population is going to find themselves dependent on nicotine. What we do know is that when you're exposed to nicotine, whether that's through gum or patch, or smoking, your body responds to that exposure by changing the types of nicotinic acetylcholine receptors that it makes in certain neurons in your brain. And that is one of the first signs of chemical dependence. So it's changing the sensitivity of those receptors so that it can increase its response to nicotine. And that creates the increase in all of those feel-good molecules that tells your brain hey, this is good. I want it again. And then that's how the feedback loop starts.

SPENCER: Some people I've heard say things like, well, but if you know, you're just choking, you're just to nicotine gum or vaping. What's the big deal with being addicted? You can just do it whenever you want. But talking to friends of mine who have been addicted, it sounds like one of the worst things about it's kind of fixation. It's like, imagine if every half an hour, you just felt like you had to have something and if you didn't have it, you would feel frustrated or, you know, you have negative emotions, that that actually seems kind of terrible. Is that your understanding of why would he like, because otherwise, you know, when nicotine gum, no big deal, right? Like, what's so bad about that?

CRYSTAL: Yeah, I mean, if you think about withdrawal, like when we think about like, really detrimental chemically, like addictive drugs, like usually we're thinking about heroin, and street drugs, [they] absolutely ruin your life. Methamphetamines, for instance, have terrible withdrawal symptoms -- you feel like insects are crawling all over your body, your brain, you know, is like really firing, it's terrible. But honestly, those negative symptoms for meth or for heroin only happen for a short duration. And you can actually withdraw from those drugs easier than you can from a drug like nicotine. That doesn't have severe withdrawal symptoms, but the dependence lasts longer. And because you have nicotinic acetylcholine receptors in regions of the brain that are responsible for fear, anxiety, and cognition, when your brain is really craving that nicotine, it's impacting a lot of those emotional regulation centers. And that's why you get the agitation, the fixation, you know, and that that need to smoke.

SPENCER: Yeah, and I've heard people say, when in times of stress that that desire comes out much stronger to smoke, that sort of like goes both ways. The lack of nicotine makes them feel negative, but then negative emotions make them crave the nicotine.

CRYSTAL: Yeah, it's really amazing. I mean, they were looking at the amygdala, which is one of the brain regions that everybody talks about when they're talking about fear and anxiety and emotional regulation, because it kind of coordinates a lot of that, and the behavior that comes out of that, and how soldiers coming back from combat engagements tend to smoke more. And possibly, it's because they're attempting to self-regulate activity in the fear center of the brain, we see similar behaviors. And this isn't having to do with anxiety and fear. But in schizophrenia, there is actually a genetic mutation that's found in the schizophrenic population that has to do with a small duplication substitution of what we call the alpha seven nicotinic acetylcholine receptor. You don't need to know alpha's numbers, it's irrelevant. But the point is that schizophrenics have very specific pattern of smoking, they change smoke, they smoke their cigarettes, all the way down to the filter, it's as if they're trying to suck every last molecule of nicotine out of that cigarette. And we think it's because they're actually attempting to self-regulate the expression of that particular nicotinic acetylcholine receptor by increasing the concentration of nicotine that they're exposed to. So you know, it's pretty crazy.

SPENCER: So let's contrast that with something like alcohol because I so I'm very far from an expert on these topics. But the way it seems to me is that alcohol is occasionally addictive to people and when it is, it can be absolutely devastating. In other words, like many, many people drink once a week, and it's no big deal. And then a small percentage of people it just kind of completely ruins their life. Whereas nicotine, it seems to me is actually addictive for a much wider range of people, it tends to have much less depth stating the facts when it is addictive. Is that roughly accurate?

CRYSTAL: Yes, I would say that that is roughly accurate, I would say that there is a percentage of the population that is genetically or environmentally predisposed to addictive behaviors. And genetically, I mean, exactly that. Like there are mutations in your genetics probably in parts of your dopamine reward circuit. That means you're just more sensitive to the release of dopamine, which does happen when you drink alcohol. And environmentally, I can mean that you're starting to use alcohol or other things that you're addicted to as a coping mechanism. Or perhaps it's a learned behavior. So that increased exposure to whatever you're addicted to can happen in the case of alcohol for those two reasons. But for nicotine, it definitely is a gene transcription, biological mechanistic change that happens when you're exposed to nicotine.

SPENCER: I think it's interesting to consider like a hypothetical drug acts, right, that could have different properties where, on the one hand, it could be addictive to nobody, like 0% of the population will get addicted to it. On the other hand, it could be like so addictive that if you just tried it, once, you're just addicted immediately, right, you can imagine a full spectrum of addictiveness. And then you can imagine another axis, which is like how damaging it is, when you get addicted to it, right all the way at one extreme, it could be like, well, even if you're addicted like it's really no big deal. You just have to use it once a day, and it has no negative side effects. At the other extreme, it's like if you're addicted, it basically just sort of automatically destroys your life. Right? And so you'd imagine like every drug, you kind of place them on this to access system from like, what percentage of people who try it will become addicted and how bad is it to be addictive? And it seems like alcohol and nicotine fall very different points than those with alcohol being a smaller percentage of the population get addicted to it. But it's much more devastating. When you're addicted to nicotine, a higher percent of people who try it will get addicted, but it's less devastating. And then you can imagine hypothetical drugs everywhere on this two-axis system. Right? I just think it's interesting to think about from a policy perspective. Like how bad does a drug have to be on these two axes before we just say it should be banned? Like it's just too high of a percent of people will get addicted as to harmful for them? When they do maybe crack is is an example of such a drug? Do you have any examples of drugs where you feel like their profile is so bad on this kind of two-axis system that it's just kind of a no-brainer that they shouldn't be allowed?

CRYSTAL: Well, I guess it depends on what you mean by bad. Like, if chemical dependence is how we're defining bad, then we should ban caffeine because I cannot function without my coffee, right?

SPENCER: Well, I don't really mean adjust to being dependent on it. I mean, like, it ruins your life, like destroys the things you value, you know, your relationships, your ability to be productive, whatever it is you value, you know. So you can imagine the kind of worst possible drug where 100% of people who try get addicted, and it ruins their life entirely, right? That drug would just be like a, you know, landmine just sitting there. And anyone who tried – their life is ruined, and clearly should be banned. So I'm just wondering, are there other drugs that you feel like fall at different points in the spectrum where it's sort of obvious that they should, should be banned? Or not necessarily?

CRYSTAL: No, I honestly believe that use is context-dependent. And from a policy perspective, that's really hard, because then you get into a philosophical discussion about who should have the authority to make these value judgments. And I don't actually have answers for those, like sort of bigger, existential questions about authority and judgment. But you know, I don't agree with opioids or methamphetamines being used recreationally, because I think that it is too easy to slide down the path of behaviors that start to destroy your social support and your ability to function within society. But in a certain medical context, you know, like, I want our kids with ADHD to be able to have low doses of amphetamine so that it can balance their brain chemistry, and they can pay better attention in school and actually fit into society. So I think we're really considering your ability to fit within a societally defined norm, as you know, sort of that sweet spot that I think you're trying to describe.

SPENCER: So let's talk about vaping for a moment. There's an interesting debate going on about vaping. On the one hand, people say, well, vaping is actually great, it's saving huge numbers of lives. Because when people who are smokers switched to vaping, you know, it's probably safer. We don't necessarily know the full safety profile, but at least it doesn't have some of the things we know are really bad for you in it. On the other hand, people say, well, actually vaping is just a way to get more people addicted. And you know, it's popular among young people. And so it's sort of like the next smoking in some sense. And also, you know, there may be additives in there or just other chemicals, and we're not really sure that they are say, so I'm curious what your perspective is on vaping.

CRYSTAL: So my perspective and it was one that was shared by the lab that I worked in that did research on nicotine-dependence and nicotinic acetylcholine receptor specifically, I mean, I don't think any of us really saw vaping, when it first hit the market in what the early 2000s as a smoking cessation device. That was definitely how it was being marketed when it came out of China. But none of us looked at that and said, "Oh, that's clearly going to work for smoking cessation." You know, all of us just kind of accepted that this was an alternate nicotine delivery device, that sure you're not getting the obvious carcinogens that come from combustion, which is probably a really great thing. But there are other things that we don't know or that we are currently doing research on to indicate that nobody can really call vaping. Healthy, all we can say is that it might be healthier than conventional cigarettes.

SPENCER: I see. But wouldn't at least probabilistically, wouldn't that be a win? Like, if a smoker switches to vaping? Can we think on average, that's probably a good thing, and they're less likely to have a negative health consequence?

CRYSTAL: I do. I mean, if you forced me to pick one or the other, I would certainly pick vaping over smoking. But you know, there, there were some early studies that were really interesting, showing like sure, you're not getting the carcinogens that we know come from combustion, but the heating coil that heats up the propylene glycol juice in your vaping canister is made of metal and heavy metal particles get vaporized when you breathe in the vapor and that sticks in your lungs and can cause cancer and tissue damage and all of these other things. So you know, it might just sort of be out of the frying pan into the fire.

SPENCER: Personally, I'm worried about vaping leading just to a lot more people addicted to nicotine than would be otherwise. Because it seems like smoking was kind of falling out of fashion and seems like fewer and fewer people were doing it at least in the United States. And now you know, vaping is just this huge phenomenon, you know, we get a whole new generation of people addicted to nicotine seems like that's probably not a good thing.

CRYSTAL: No, it's like the perfect, attractive, shiny, sparkling toy for the adolescent population, right? Adults, I'd like to believe are responsible for making their own judgment calls about their health and wellbeing as long as they're not endangering other people by doing so. But adolescents that are, you know, their brains are still developing, they're still learning how to shift gears in this brain hardware that they've been given exposure to drugs of addiction, like nicotine can actually alter the way that their brains choose to develop, they can make regions of the brain that are more susceptible to nicotine, or to cannabinoids, for instance. Actually, those brain areas can develop larger, you know, with more receptors ready to accept those drugs. And, you know, I'm not here to say if that's a good thing or a bad thing, but I think over developing regions of the brain that are part of the dopamine reward slash addiction cycle can probably lead to repetitive potentially addictive behaviors downstream, that would be difficult for adult function.

SPENCER: Yeah, I guess my stance given what I know now is that if someone's smoking cigarettes and they're unlikely to stop, I'd rather they switch to vaping. Because I think on average, there's a better chance of it being less bad for you. However, if someone's not smoking, I definitely don't think they should start vaping unless, for some reason, they have really good evidence that they're the sort of person who just is not easily addicted to nicotine, they could easily quit whenever they want. But it's hard to really know that that's going to be true about you. So anyway, I think that's where I land. Do you think this is a kind of a nuanced, tricky topic? Because you really can argue both sides of it, because there on the one hand, maybe it's better than smoking, but on the other hand, maybe it's not great if lots more people get addicted.

CRYSTAL: Yeah, I mean, but like with nicotine, you can do things like add menthol, or you know, you have clove cigarettes. These are things that people have been doing for like hundreds of years to try and make tobacco more palatable. But when you're talking about vaping, you have the colors and the flavors that everybody you know, has been so up in arms in the media about that truly do make the vaping behavior more exciting than more exciting, more pleasurable, you're getting more dopamine, even if you're getting less nicotine, and in some cases, like green apple flavor, specifically, actually sensitizes your dopamine receptors so that you have a more pleasurable response when you're vaping. Green apple flavored versus something else.

SPENCER: You're saying there's like some kind of molecular interaction there between some flavors and the dopamine response?

CRYSTAL: Yeah, actually, my colleague Brandon, who I mentioned before, who did the research on the menthol cigarettes, also started investigating some of the main compounds in artificial green apple slavering and found that they create a larger dopamine response in the brain than just nicotine solution alone.

SPENCER: There's also an interesting thing about vaping that we didn't talk about, which is that you can do it more easily in more places because it creates vapor rather than smoke and you know, smoke kind of hangs in the air and you have to use fire often, whereas with vaping, you can often like get away with doing it all kinds of places, but also, it's very easy to get to kind of higher and higher doses and nicotine vaping because it's just sort of like you can buy whatever dose you want, as I understand it. So my sense is that people who vape can tend to get, like more addicted even than people who smoke. Do you think there's anything to that theory?

CRYSTAL: Oh, absolutely. And not just that, because of the lack of quality control in the vapes vaping juices that you buy. Even if you think you're buying one concentration, it might be another. So it's very difficult for the consumer to know how much nicotine they're actually exposing themselves to. And then you can buy pure nicotine off, you know, Alibaba, and make your own juices in your garage. When we think about exposure to nicotine, we think about the concentrations as inverted U-shaped. So as the concentration goes up, our desire for it increases to a certain point, and that's like kind of the top of the inverted U, and then as the concentration goes up, things start to, you know, get bitter, our heart rate starts to increase, you know, in a way that doesn't make us feel good, we get nauseated, and we start to have these adverse effects that really high concentrations that make us voluntarily stop administering it. Now, if we were to vape pure nicotine, we wouldn't have time to experience the adverse effects to tell us to stop. And if you're exposed to enough nicotine, because you have nicotinic acetylcholine receptors at all of your neuromuscular junctions, you would probably experience seizure and or convulsions.

SPENCER: Okay, I don't I didn't actually realize that there was actually acute health risk from it.

CRYSTAL: Yeah, actually, I was covering a story on electronic cigarettes really early on, and it's an explosion into the US market. And I was at a convention at the Anaheim Convention Center. And it was basically one enormous hot box of nicotine vape. I mean, you know, you couldn't see to the other end of the convention center because of all the vape in the air. And I studied nicotine and nicotinic acetylcholine receptors, but I have never smoked a cigarette. I think that was the most exposure that I've ever gotten through secondhand vaping to nicotine than I have ever gotten to nicotine in my whole life. And I became nauseated, I had a racing heart, I got lightheaded, and I had to ironically leave the convention center and sit in the smoking section outside so I could get fresh air.


SPENCER: So changing topics – the next thing I want to ask you about is how do we train scientists to be better leaders?

CRYSTAL: Well, studying nicotine, you know, really working sort of at that interface between science and academic research and public health and public knowledge. And so I really sort of saw firsthand the importance of communication and leadership in being able to translate what the world of science knows into a format that can really benefit the rest of society. And so I had already started thinking about that. I will say that my graduate school experience wasn't exactly the most fun that I've ever had.

SPENCER: Oh, really, all the PhD students say now we're just having a wonderful time.

CRYSTAL: Really, what PhD students have you been hanging out with? As I'm sure you know, and maybe you can share some of your own experiences. You know, we train people to get PhDs and we train them to be amazing scientists and be really good at data and do all these other things. But what we don't do is train them to be good at managing people and money. And unfortunately, once you get a PhD in a job, you stop doing science and you end up writing grants, managing people and money.

SPENCER: Right. So when you talk about turning scientists into better leaders, like what is the leader means to you, in that case.

CRYSTAL: Leader means thought leadership, leader means mentorship, leader means manager. It really means thinking not just about the thing that is the goal, but also about the people that are needed to get there and managing those resources in a humane way.

SPENCER: It is interesting how little training you got in a PhD for any of those things you just mentioned?

CRYSTAL: Yeah, absolutely. I mean, like, when I was in graduate school, I definitely did not have the sophisticated mindset that I was actually the CEO of my own education and project. You know, I felt that I was a cog in a wheel and at the mercy and the whim of the big man on the mountain, my PI, and my professor, Principal Investigator. And I think that if we had received more training and support in leadership, and in management, I would be able to have applied those principles to my own behavior and life much earlier. And I would have definitely benefited from them. And it would have made me a better scientist.

SPENCER: So what would you like to see scientists doing differently? Like, imagine that they do get this hypothetical training to be better leaders, better managers -- what would that look like in practice?

CRYSTAL: Well, I think it's sort of two things. So one, I think we need to let go of the idea of command and control being the only effective or meaningful way for leaders to show up, because science in and of itself is quite dynamic, quite collaborative, and requires a lot of different types of leadership approaches. It's not just “do as I say,” or there will be consequences, right? And then I think that it's important for us to train scientists to think of themselves as leaders, both in science and society earlier on. So the idea that a scientist is a data drone that works alone in a lab and makes discoveries by themselves, has been very romantic and attractive in the past. But even then, it wasn't actually true. You had your lone scientist, then they had all of these anonymous, unnamed workers and aides and assistants that were working to support them in their projects. So scientists have always been leaders, they've never been alone. In a lab, we've always been talking to colleagues passing letters across oceans to share data. And so I really think that collaborative leadership, how to communicate with others, how to how to share information in a way that sort of improves the quality of the group's goals is definitely something that academia could think about, although, as you know, none of the incentive structures are set up to support that.

SPENCER: Now, one interesting distinction I've heard about between different academic fields is how valuable a PhD student is. Because for example, from my own field of applied mathematics, you're coming in as a PhD student, I feel like I have no almost no value to my thesis advisors, right? It's like, they know so much more mathematics than me, I'm just like beginning to dig into the subject to try to eventually hopefully get to the kind of edge where I can make a contribution. But like, when you first land there, you have very little you can contribute to their work directly, eventually, maybe you could start publishing your own papers, and they can be on the papers, and maybe that has some value to them. Whereas in like biological sciences, my understanding is, there's a lot more like helpful things someone could do right away, like, you know, working in the lab, or, you know, just logistical things, all kinds of stuff like that, and sort of kind of creates a different system where you have like a lot of lab workers like doing, you know, maybe not the stuff they expected to do when they became a scientist. Maybe they're like pipetting fluids or putting these refrigerators or whatever. Do you have any comments on that?

CRYSTAL: I mean, I guess you've been thinking about it that way, but in biological sciences, you at least have another set of hands or you know, an intern that can like make buffers, as long as they're capable of following a recipe. And then they're kind of like providing benefit for the lab instead of just taking resources I think like even first-year, graduate students are able to function as TAs. Sometimes the innocent question in the lab meeting is the one that needs to be asked, and only the early-stage graduate students are the ones dumb enough and innocent enough to ask the question. So I think there's even an intellectual contribution that can be made early on, but I want to ask you, was there a turning point for you where you realize, oh, I'm a colleague now, or oh, it's not everybody else knowing more than. Like, when did that inflection happen for you in the course of your graduate career?

SPENCER: I think it's really when I started deep diving into very specific problems. And then for those particular problems, I wouldn't be spending many hours a week thinking about that, just that thing. Whereas, you know, my thesis advisor would be spending, you know, half an hour thinking that in a week when, when I would talk to him, so there, you know, I started feeling like, okay, I know the ins and outs of this problem in a way that nobody who just doesn't spend many hours a week think about it does. And so maybe for me, that was that inflection point about for yourself?

CRYSTAL: Yeah, I think it's when, for me, I had a thesis committee meeting and there's like combined over 100 years of scientific career on one side of the table. And then on the other side of the table, it's like me, and I've got four. And we were talking about a problem in some of my experiments. And I realized that the suggestions that they were making didn't make any sense and were like, actually irrelevant to my actual problem, because they were so far removed, but either from the technique that I was using, or from the actual system that I was studying, and that's when I was like, oh, I know more about the nuanced details about this, then they do. That was for me, was the point. I was like, oh, this is gonna work, I might get out.

SPENCER: Make a contribution with that level of understanding. Yeah. No, that makes no sense. It's just someone who's just on the ground trying to do the thing has a huge advantage over someone who's sort of like looking at it from afar and trying to understand it.

CRYSTAL: Yeah. And I think that that's something that I wish that more people knew like I speak with some people sometimes that are talking about science and scientists like it's this impossible to reach like unattainable thing, oh, all these scientists are in their ivory towers, and we can't interact with that community. And that community doesn't have anything to do with us, they just publish their papers and talk to each other. And I wish that more people knew that the definition of science and scientists and how you can contribute to the growing body of knowledge that humanity has of our universe, you know, doesn't have to be done only through academic research. But it can be through participating in citizen science projects, you know, or interacting with the process of science in ways that don't require you to have a degree or to spend time in a lab or on a computer.

SPENCER: Know, well, the whole academic system of publishing in journals, I feel like it hasn't done a great job of including the public, in part, because a lot of those papers are actually locked behind paywalls. Increasingly, they've been opening up, you know, now it's easier, it's become easier and easier, especially the last few years to find papers without having to have some academic system you subscribe to. But I feel like that was a major barrier to people engaging with science.

CRYSTAL: Yeah, absolutely. I mean, at least in math and physics, you guys have the archive, right?

SPENCER: Oh, yeah, the archive is amazing. It's for those who don't know, now in mathematics, people often post their papers to the archive before they get them published in journals, and basically, archive, anyone can read it, it's free. It's online. And you will have other mathematicians like emailing you and commenting on what you wrote, you know, and then maybe like a year or later, the thing actually comes out in publication. But at that point, you've already kind of gotten the comments and feedback you want.

CRYSTAL: Yeah, it's a more responsible type of peer review. I think in biology, you know, we're very concerned about being scooped, I think, and few people really would want to pre-publish in that way. It's quite competitive. And it's unfortunate, but I think that we have seen with COVID-19 on the biology side, more journals, publishing COVID-related articles, open access, I think we can talk about whether it's a double-edged sword because there have been some experiments that have been rushed to publication because we think they have meaningful results. And then maybe there's a downside to that. But I'm hoping that we see that findings that have a huge human impact. It's a kind of ethical and moral responsibility that we have to be able to make that data accessible to the people that need it as soon as possible.

SPENCER: Yeah, absolutely. I'm curious to hear about your experience with peer review. Would you say you've generally had a good experience is when you're going to publish papers, bad experiences, like, what has it been like for you?

CRYSTAL: There's always that one reviewer. I don't know, it's cliche to say, but it's like when you're doing experiments in -- we use mouse models in my lab -- there's always that one mouse like it's always an outlier. And you're always like, why won't you make my error bars work? And that mouse is like, "Screw you. I do what I want." It's exactly the same. I think with peer review, I think this is something that we're going to need to think more broadly about because I in my PhD was doing quite interdisciplinary work. You know, you have the human behavior side of nicotine dependence you have you know, for me, it was the chemistry, the fluorescence microscopy side of my work, then you have electrophysiologist that you're collaborating with. And so that's physics and, you know, computational neuroscience. So when you have a paper-like all the papers that came out of our lab -- you know, that require expertise, and all of those more sort of more specialized techniques in order to truly review and understand them, we didn't often get editors that would be able to send the paper to that diverse of labs. Because my field is, really small, like the nicotinic acetylcholine receptor field isn't that big, we pretty much know everybody in the field. So it was rare when if you showed the review to my PI, he wasn't like, "Oh, I know exactly who that is."

SPENCER: Yeah, I had a number of kinds of funny experiences with peer review. One of them, I feel like they barely read my paper. Like, I just had this impression that there was essentially no process by which they reviewed it.

CRYSTAL: It's so insulting.

SPENCER: Yeah. And then another situation I was in was even worse, where it was pretty clear that one of the reviewers was like, "Oh, this is fine. Here's some, you know, here are some reasonable edits." The other reviewer was just really angry about something. And I suspected they had like a vendetta against one of my colleagues, because for some bizarre reason, a lot of times the reviewer knows whose paper they're reviewing, but not the reverse, right? So the reviewers are anonymous, but the submitter is known. And so they just attack our paper on completely, like spurious nonsense grounds. I think we ended up having to request like the editor to get involved and be like, this person saying things that make no sense. And they're just trying to get our paper blocked. That was rather weird and disturbing.

CRYSTAL: I'm so sorry that you had that experience. But yeah, this is the academic game, right? Oh, no, our competitor is trying to publish on something similar to the paper that we wanted to put out quick, "Let's tie them up in review, well, try and get our paper published somewhere else." I mean, these are the different ways that scientists or academics can shoot themselves in the foot.

SPENCER: It seems like a really bizarre system where the person submitting is known, it seems like that's gonna create all sorts of biases when evaluating their paper about like, oh, this person is considering authorities, the papers probably good or this person's low level, and like, it doesn't matter if you know, they're obnoxious to them, or, you know, all these kinds of another kind of situations you can crop up.

CRYSTAL: Well, the community that's using this system, which, which is like that one-directional information about the authorship wouldn't accept data that didn't come from double-blind studies, especially when you're talking about drug development or something like that, right? They're like, this is ridiculous, the effect could be placebo, we need both parties to be blinded to what version of you know, but yet, in this case when it could potentially benefit them. It's just one of those antiquated artifacts of you know, the origins of the academic system like we still defend our theses. Like, it's no longer a fight to the death, but like, you know, you're in fight or flight mode, when you're up there giving your presentation, it feels like a diet anymore.

SPENCER: Oh, for sure. You're like, "Okay, I'm pretty sure I'm gonna pass because my advisor says I'm gonna pass but like, what if they just failed me and I still get my PhD?" You know.

CRYSTAL: Yeah, and still it could still end badly.

SPENCER: Exactly. There was this really interesting paper where what they did is they, they took a bunch of other papers that had already been published in journals and resubmitted them to the same journals to see what would happen. And it was fascinating because some of them got detected as this has already been submitted. But a bunch of them got rejected, even though the Journal had already published, like the exact same paper, as you know, for all kinds of, you know, different reasons or reviewers said, "Oh, this is not publish-worthy." So that kind of study and others have convinced me to believe that basically, well, peer review does get rid of some garbage, like some really bad papers or are getting rejected because of peer review, which is a good thing, that there's actually a huge element of randomness. In other words, you might have a really good paper and it still might take you three submissions to get published somewhere, because there's just so much to carsickness. And like, who happens to be reviewing it based on when exactly you submit and what exact field it's in. So it actually also, in addition to getting rid of some of the garbage, it just creates this huge cost to everyone where they end up having to resubmit things over and over.

CRYSTAL: Yeah, I agree. I mean, cleaning up the peer review process will probably take the next 50 years of concentrated effort. But you know, I think that that's true for any peer-review process. Like I'm also thinking about job applications, you know, which is basically candidate's suitability is subject to peer review, right. And they've done all these experiments where we submitted the exact same resume with a different name on top and you know, the results were different. And I think that we're seeing technology and some forms of automation trying to level the playing field, if you will, to eliminate some of that cost and the excess sort of energy that happens when you're dealing with the unpredictability of human behavior. But that's sort of far off in terms of widespread use, I think,

SPENCER: Yeah, and some of the technology might reduce these kinds of biases in the selection, but some of them might even enhance it. For example, recently I'm reading about AI that like you submit a video for a job of you talking and it analyzes like the way you move and the way you talk and gives you a score as you on this to help screen out people. And it's like, really, we want an AI to like, make superficial measurements about how someone comes across in like a one-minute video and use that as selection criteria? You know, maybe for sure, in jobs where like a job is all about presenting yourself really well, that makes sense. But like for the vast majority of jobs, it just seems like optimizing for entirely the wrong thing.

CRYSTAL: Yeah. And who's choosing those measurements? And how universal are they, right? That's always the question. I mean, I think that I personally, just because of my personal philosophy, and like belief, and like, the uniqueness of the human spirit, it sort of makes my skin crawl when I think about myself being subjected to the allegedly objective measurements and my suitability and value being assessed by artificially intelligent machine. But I think that the next generation is a little bit more comfortable with that the same way that they're more comfortable with, with loss of privacy. And hopefully, it's because they're building the technology, and that's why they feel better about it.

SPENCER: I think they're just used to it. Oh, yeah, of course, all your stuff is online forever and owned by you know, social media companies. That's just normal. All right. We're just it's like boiling the frog, right? It creeps up on you. And if you grew up that way, you're just never think about it. Yeah,

CRYSTAL: That might be true. I recently had to, and I like embarrassed to admit this, but I recently had to create a TikTok account profile.

SPENCER: Oh, so now China has your data, is that what you're telling us?

CRYSTAL: Yes. And like, as I was downloading the app, I was like, okay, China, here's literally all my (inaudible) here you go.

SPENCER: I don't know too much about it. But I read a blog post from like security analysts about how the app basically steals every type of data it can possibly steal from you and kind of uploads it to some server in China. Maybe now with the negotiations with the US government, they're clamping down on I'm not sure.

CRYSTAL: Oh, I'm sure not this is exactly the same reason, like the same way I got on Facebook. I never wanted Facebook, when it was a thing. I managed to escape the entire years of Facebook when you needed an edu email address to have an account. And I finally joined once I started doing more public-facing things like I was in the PhD movie, if anybody knows, like PhD comics, like I worked with Jorge Cham, the creator, and we like made this live-action independent film. And like when that came out, everyone was like, "You need a Facebook account." And I was like, "No, I don't want people knowing things about me." And they're like, "Well, they can't find you online. They're gonna try and find you at your house. And I don't think you want that." Now. It's like, "You know, I'm making a Facebook account right now. I mean, I check it like once a year, but at least it's there."

SPENCER: Yeah. Well, you know, I think there's an interesting question about to what extent can you get by without these accounts, right, like when all your friends are on Facebook, and that's where like the event invites are occurring, suddenly, not being on Facebook, you're gonna be excluded from the events of the people, you know. So at some point, we cross this threshold where the cost of not being on some of these systems actually, you know, goes up and up.

CRYSTAL: This is true. I have been the last person to know that friends have gotten engaged.

SPENCER: Like "Wait, but we told you. We post it on Facebook."

CRYSTAL: Yeah, exactly. In my car. Like, "How have you been engaged for six months, I never knew?"


SPENCER: So another topic I want to discuss with you is the kind of interpretation of data when it comes to science. So I would love to hear some of your thoughts about that.

CRYSTAL: Data are data. I mean, like as a mathematician, you know, that like, you can't really dispute whether or not the data exist, you collected it. But how we interpret it, how we tell the story about those data, how we ascribe meaning to patterns, or the lack of pattern in those data is 100%, up to the human brain. And in some cases, all of the collective human brains are going to agree that yes, that is the pattern that is the meaning of those data. But that's not always the case. Because you know, we're coming at this pattern of information with different priorities with different areas of expertise with different strengths. And so I think it's really important for people that don't work with data on a regular basis to understand that the story that we tell about data is just as important as the data themselves and that some person is telling the story, and is telling you what those data mean. And that can be a really good thing when I would much rather have my infectious disease information coming from experts in infectious disease and having them tell me the story about the data that they're seeing, as opposed to me with little to no expertise in infectious disease, trying to interpret the data itself. But I do want to be able to understand it. As a science communicator, you know, I'm really invested in this idea of the way that we tell stories about what we know, it's really perhaps the most important part of the scientific endeavor.

SPENCER: Yeah, I think that's a really great point. And I think people really underestimate the extent to which there are choices to be made in analyzing data. And then fundamentally, these questions arise from the fact that you have to compress the information you have, you can't just be like, "Hey, we're all I did a study. Here's a matrix of numbers." That's like, you know, nobody can do anything with that information. You have to say, "Hey, I collected this big matrix of numbers. And here's what it means," right? That's really the scientific paper is trying to interpret the data was collected. So just as an example, if you collect 50 variables on 200 people, or 200, mice, or whatever it is, that's 10,000 numbers. Okay, that's like way too much information for the human brain to process, okay, what is interesting about these 10,000 numbers is what can you draw from? What can you conclude? And I think a really interesting example of this was a project where they gave the same data set to many different researchers, I believe it was a dataset that had been collected on referees in soccer, and whether they gave people like red cards, and there's sort of the question was it were they showing prejudice of some kind, and the way they gave people red cards, and basically, what was fascinating about it is that there were many different decisions made by different teams working independently about how to analyze that data. In other words, it wasn't like everyone's like, Oh, here's the data. Okay, we're all gonna analyze the same way. The different teams actually made a bunch of different design decisions and tried to answer the same question, which sort of shows that there really are choices to be made about how you tell the story.

CRYSTAL: Yeah. And the hardware that you're bringing to that in that interpretation process can be different, as well. If you and I, for instance, were analyzing the same data set, I can only analyze that data set by comparing it to my past experience and things that I have heard about and techniques that I know, which are very different than you know, your background. So even ignoring any sort of personality impact or implicit bias, if we were just trying to apply the best of our purely platonic knowledge to that data set, we would probably most likely come up with completely different interpretations, or possibly the same interpretation. But we would have arrived there in very, very different ways.

SPENCER: Yeah, absolutely. And I think there are at least four ways that people could come to different conclusions from the same dataset. The first is that they might just be asking different questions about it. And that can be very, very subtle. Like, it could even sound like they're answering the same question, but there are subtle differences to the exact question they're trying to answer. The second is different skill levels or training, right? Like, you know, someone could just know about technique X, and that person knows about technique Y or one person uses technique improperly, then there's an incentive issue, which is that you know, we humans tend to rationalize things. And if you have, like, a huge incentive to get a certain answer, it's gonna be very easy to say, "Aha, this isn't what I expected. Oh, wait, I should remove these two outliers. That seems reasonable. And then now it looks better. Okay, I'm happy." And really feel like that's okay. Because we have an incentive, we generally, if the sound of strong enough, can find a way to justify our behavior and not feel too bad about it. And then the last thing is that they're legitimately difficult choices that are debatable what the right way to do them is like, there is this kind of fundamental questions in statistics or in how to conduct science, where very reasonable people really don't agree. And it's just kind of a matter of like, philosophical position at that point. So you know, I think there are quite a few reasons why we could tell different stories from the same data.

CRYSTAL: Yeah, absolutely. And that's why -- to bring it back to academia like that's why we need more than one research lab working on the same or similar questions because we kind of look at the overlap in the Venn diagram of what everybody thinks that they know. And we sort of say, okay, at least we, you know, agree in this common area. When we're talking about the story that we tell about data. You know, like, originally, maybe we weren't to collect those data, we thought we were answering one question, but nature doesn't actually work that way. So we have to think, okay, we have these data, what actually are they telling us since they're not telling us what we thought that they would say? And then we get to tell a story about what actually is, as opposed to how we thought things worked. And that's why every academic paper, at least in my field, that you'll read is like, "We totally knew what we were doing. We had this hypothesis, we ran this experiment, the data showed this and we conclude that." But when really half of them are like, "We're trying to answer this other question. The data came about wonky, we didn't know why they were wonky. Turns out it was because of something cooler that we didn't think about before. And that's why this paper exists."

SPENCER: When you go read a paper, it gives such a false conception of the way science is done. It's sort of like reading a math proof. Because as a mathematician, usually, you'll have some intuition about a problem, like you think, "Ah, I think it's probably true." And you kind of has an idea about why it might be true. And you'll like try to work to prove it, and you're like, your first 10 attempts won't work, and you'll hit a wall. And then one day, you know, you'll have a stroke of insight, and maybe you'll get through and actually prove it. But then the thing you put in your paper is just this like the final thing. It's like that final proof, it looks like you just wrote it down right from your mind. And it usually doesn't give really any explanation of why did you even think that thing was true? What was the intuition that was driving this? So you spent 100 hours trying to prove this thing? And how did you even think of that proof in the first place? And that's all missing? It's just like, it's this very sterile, very fake version of events, basically, is what you read.

CRYSTAL: Yeah, I think what's missing is the human part of science, right, like a normalizing failure, normalizing being wrong, and reveling in it. Because it turns out the universe works in a way, that's way weirder and cooler than the way that you thought it did. And having that be a good thing instead of being wrong, means that you're stupid and not actually good enough to be a contributing member of scientific society.

SPENCER: I don't know if you'll agree with this. But now having run lots and lots of studies in the social science space, I've come to think that it's so hard to just sit in your armchair and like, guess about reality, that in order to actually make progress, you generally have to run kind of exploratory studies just to like, get your bearing to know what bigger studies to run. And so often, I think starting with like some rapid-fire, like, okay, let's just poke at this thing to just get our bearings. And then we're going to learn enough that we actually can conduct a real study. That's really essential. But that first stuff, it doesn't fit into sort of the standard narrative of what science is because you don't necessarily know what you're gonna find. You don't necessarily have a clear hypothesis. You're just data gathering to understand the topic.

CRYSTAL: Yeah, I guess I don't know why. But it made me think of the early experiments in neuroscience, like in my field, hey, we don't know what this brain region does. Cool. Let's ablate it and find out. So like, we just got rid of the hippocampus. Wow, this person or this mouse can't remember anything. Cool. That's what that does. Hey, oh, yeah. Oh, this person's prefrontal cortex. Oh, now they have no emotional regulation. And they're behaving irrationally. Great. We know what that part of the brain does.

SPENCER: Was that actually done on humans?

CRYSTAL: Yeah, so the prefrontal cortex one was like a railroad accident, where a railroad spike actually went up through somebody's jaw and took out just the prefrontal cortex region.

SPENCER: Those are Phineas Gage's story, right?

CRYSTAL: Yes, exactly. Phineas Gage's story, like super famous, and their personality totally flipped. And that's when, you know, scientists sort of -- this is the story that's always cited in terms of like the example for why you need that executive function of the prefrontal cortex region of the brain. But yeah, they were absolutely doing those types of ablative experiments, mostly in rats, not always in people. But you know, we have to admit that neuroscience psychology, neurology has a really horrific history of human experiments, both on slaves and on humans that were in asylums, you know, all of these early experiments that were being done allegedly to help the mentally ill or people that were incarcerated in asylums. You know, it's not the prettiest history that you know, my field is based on but those were some of the hey, let's perturb the system and find out what happens. Some of those experiments were done before you had to fill out Lots of forms to do experiments on humans.

SPENCER: Yikes, that's quite disturbing. One thing I would ask about it. So I've heard that Phineas Gage's story was called into question and that it's been doubted whether his personality changes really were permanent. Do you have to know anything about that?

CRYSTAL: I can't imagine that they wouldn't necessarily be as drastic as they have been described. I think it's like a legend now, like Paul Bunyan, or Davy Crockett, in a way. Um, so I would, it wouldn't surprise me if there was historic evidence of it not being perhaps as dramatic of a Dr. Jekyll, Mr. Hyde situation as the tale that we tell to undergrads. But in the absence of executive function in the prefrontal cortex, that type of temper and unpredictability is absolutely something that we have seen and more just that one case.

SPENCER: So Crystal, my understanding is that you do some work directly related to training scientists to be better leaders. Can you tell us about that?

CRYSTAL: Yeah, I mean, I'm maybe traumatized from my own graduate experience and realizing that one of the things that I think holding science back is the lack of leadership training. I started to think about how we perceive scientists in general and the fact that scientists are not necessarily seen as leaders in society, or at least they weren't until the pandemic hit. And now suddenly, we have a lot of scientists and leadership positions that were paying attention to, which is great. So I'm on the board of a nonprofit organization called The Plenary, and one of the projects that they run is a project called I am a STEM, or I am a scientist. And the purpose of this is to get an educational standards-aligned STEM curriculum that shows diverse faces and stories of real-life scientists into classrooms around the country. So the curriculum is aimed at elementary middle school, but it can also go as high as high school, there's a bit of flexibility there. And it shows pictures of diverse scientists. It tells the human stories of those scientists. And it's really trying to diversify the narrative and the idea of who does science and what scientists do. And understanding that I would really like to train the scientific leaders of the future. I'm working with the plenary, and I'm a scientist to create another set of educational standards-aligned curriculum that approaches STEM topics. And the examples that they use are scientists in leadership positions. And that doesn't necessarily mean in government positions. But that means scientists that use their scientific knowledge to go into science diplomacy, to go into conservation, that is working in nonprofit spaces, different ways that you can really lead change socially, through the application of scientific knowledge. And I'm really excited about the development of that curriculum. And I'm, like really hoping that we can sort of change the function that we think scientists should have in society.

SPENCER: So would that be a curriculum for PhD students?

CRYSTAL: We're targeting it originally, actually, at middle school age students.

SPENCER: Oh, that's much younger than I expected.

CRYSTAL: Much younger, yeah. And this is an antiquated language that we're not supposed to use anymore, but I'm going to use it because it's sort of what everybody knows to talk about, right? Like this idea of the leaky pipeline of women, specifically, in science, you know, there are different places along the career trajectory that you just see, like, larger amounts of fallout, and middle school to high school transition is one of those places. And when you look just at girls, and why they say that they don't want to pursue science, it's because they don't view science as a collaborative effort. And you know, this is when sociality is starting to be really important. Your role in your peer group is starting to be really important in terms of the developmental stage that you're in. And science just doesn't seem to be like a people-centered endeavor. And also girls report that they don't see science as having a positive impact on humans, and they want to turn their attention to something that's more human-focused in general.

SPENCER: That's interesting because it has such a huge impact.

CRYSTAL: Yeah, absolutely. But if you think about what science education is, at that time, it's people memorizing facts and spitting them back on tests, for the most part, right, preparing you to learn about the complex system of science later if you make it there. And so what I was really hoping to do is to kind of catch girls or anyone at that stage where they start to think about their impact as individuals and to start to think about how they are going to connect as an individual identity to their community and show them how they can use their personal interests to contribute through science and showing them means hands-on classroom exercises, as well as real-world examples of working scientists who might have a personality like them, and hopefully give them role models to look up to.

SPENCER: Hmm, interesting. So if we think about why there are fewer women in any branch of science, or the I guess, not all branches of science, but in many branches of science, you can imagine going back to the, I guess, the pipe model, there's a number of places where they could drop out of that pipe, right? There's maybe early on when they first take their science classes, maybe they just don't find that interesting or that exciting. Or maybe they think, oh, you know, science isn't really for girls, for boys or, or whatever. And just, they're not sparked in that initial interest. You could also imagine there'll be you know, somewhat, later on, there might be conceptions of people who may be accepting applications for these two roles. And there may be bias against women. You could also imagine other things like maybe women have fewer opportunities to do science, like, I know that my mom growing up actually, I don't think she was allowed to take science or there was just standard that the girls didn't take science and the boys did, which is just mind-bogglingly insane today, but that was just the way it was and her school. So you know, there are all these different points. And so I guess it sounds like you think that this intervention point of like if you can get girls interested in middle school, that that will have a strong causal effect. And like, even if there are these other forces acting that that will be enough to kind of like increase the rate of women going into science. Is that right?

CRYSTAL: Yeah, I mean, at least trying to address the issues, that science doesn't have a direct impact on people or that science isn't in and of itself a social and collaborative endeavor, because there were such strong studies sort of indicating that those were some of the things that girls weren't seeing, to engage their interest in the pursuit of STEM, hoping to be able to give examples of how that is not true. And to show them how who they are developing into because you know, just starting to develop the identity of yourself as an individual and what your strengths and weaknesses might be, how both your perceived strengths and your perceived weaknesses can still be incorporated into the idea of a scientist.

SPENCER: So it's interesting because it seems like the theory of change, it bakes into this idea that women are more interested in certain types of activities at that age, like more people-centric activities, and interested in maybe more in like social impact -- is that your understanding?

CRYSTAL: The project itself is framed in a gender diversity context, because of the grant that I got, in order to be able to pursue this project. But my personal philosophy is that we limit ourselves in lots of different ways. And one of my first forays into the public domain was a TEDx Youth talk that I gave at Caltech in the late years of my PhD program, where I was just kind of talking about the way that we represent scientists in the media and women scientists, and just like, look, you know, I'm a dancer, I do art, you know, I was a rhythmic gymnast growing up, I have all these diverse interests, I don't see anyone like me represented and the images of scientists that are projected at us, you know, I became a scientist, despite who I was not because I thought that who I was, was well suited for science. And I would just love for everyone to know that you don't have to fit into a single box, in order to be a scientist, you can be an effective contributor to the scientific process, who you are right now is enough. That's really all I want people to know. Science is cool.

SPENCER: Yeah, and I've seen that (inaudible), I thought that was really good. And I thought you did a good job of pointing out how a lot of representations of female scientists sort of like even when they're representative, or very stereotypical, right? Like, usually the side is the man in movies and stuff, but when they're not like, it still doesn't necessarily give us a feeling that, oh, you know, lots of different women could become scientists or, or isn't necessarily that encouraging of women to go into that. And I also, I just want to mention, I'm reading this book now called The Secret of our Success, about cultural evolution and sort of how culture shaped humanity, and kind of the back and forth between culture and biology. And one of the theories put forth in that book is that humans have a natural like imitation instinct and that this has served us really well because you know if you're a child, and you're like, looking at your parents' behavior, there's so much you can learn from that about survival, right? Like, you know, what to eat, what not to eat, you know, imagine you're, you know, living 100,000 years ago in a tribe and you're like, trying to figure out, you know, what is safe? How do I collect food? All these things, and you essentially copy parental figures. But he also suggests that this copying instinct actually is stronger than more similar review someone is being to ourselves. In other words, we naturally will mimic people that we think are like us. And so that would suggest that if there were more female role models in science. If this theory is true that girls will look to me like, "Oh, they're like me. And so I should, like imitate their behavior." And that without that, you know, you just don't you know, you just don't get the idea in their minds that like, oh, yeah, maybe I could be a scientist.

CRYSTAL: I mean, I can't speak to the validity of that hypothesis. But from my personal experience, I think that that certainly rings true. I mean, I grew up homeschooled the first school that I ever went to was in junior college, I was 11. Everyone, always when they find out that you're homeschooled, they're like, "Oh, my gosh, but you appear so normal and socialized. How did that happen?" Yeah, everybody's worried about socialization. But because I didn't have the broader social community of people my own age, in that formalized school setting, I think I do a lot of mimicry in order to like, understand the social rules that are governing, whatever situation that I'm in, and then trying to adapt those cultural conventions. And I maybe I'm more conscious of that because I've been doing it for so long.

SPENCER: Yeah, and I mean, we all do this to some degree, right? Like, imagine that you're going to an event, and you've never been to the type of event before, you're going to wonder like, well, how do you dress that event? Is it formal or informal? You know, we're going to try to mimic what other people are doing, because we feel like out of our element. And you know, when you're a child, you obviously don't know much about much, except the things you've had personal experience with. So you're kind of forced to just copy what other people are doing until you kind of figure out things for yourself. So imagine, that could be a good intervention point.

CRYSTAL: Superficially, I think we know that that is true, even for science. The Scully Effect is a documented impact that just Scully on X Files, like a million years ago, had on the number of women that were interested in going into certain scientific fields. We also see the CSI effect, I don't remember the name of the TV producer. But suddenly, there were fun, funky criminal investigators that were experts in forensic science on TV. And they had a huge increase in the number of women that were applying for forensic science, education, and eventually jobs. So I think that there really is something to the if she can see it, then she can be it just a lot easier to imagine yourself doing something that somebody like you is already doing.

SPENCER: In terms of the long term impact of this, you know, some people would argue, I think, quite reasonably, that there's just sort of as an end in itself, we want a diverse range of people to be in a diverse range of positions in society. But I imagine there also might be a more pragmatic argument that there might be benefits to having more women in science, like do the second or consequences of that. So I'm curious, your thoughts on that? Do you think that science would be different? And would it produce different outcomes? If there were more women in it? Or do you just view it more as it ended in itself to have more diversity?

CRYSTAL: I think that science generally benefits from the diversity of people, and I mean, background, education, cultural experience, all of these things, right? Because if we are truly allowed to pursue the questions that are interesting to us as a holistic individual, then and that knowledge is able to be contributed to the whole, then we actually learn collectively in three dimensions instead of in two, because of the diversity of inputs that are going into, you know, that collective understanding,

SPENCER: it seems to me that diversity of thought and science is incredibly important because it helps check our assumptions, it helps discover more things and that different factors like gender, I expect to be at least somewhat correlated to the diversity of thought. In other words, like, if everyone is imagine, demographically I expect that to produce a more narrow range of thinking as well.

CRYSTAL: Diversity in that sense, it's really true. I mean, we're looking at, I don't remember how this came across my feet. But it was looking at the medical practice of dermatology and how we know so much about certain skin diseases on Caucasian skin, and very little about how it presents in skin types that are like higher up on the Fitzpatrick scale or darker-skinned people. And that's just because of the lack of diversity of people that are doing the research. Like you don't think about other groups of people that don't look like you unless you're trained to do so. We have all of these gaps in our understanding, or in other cases, my fiance actually is a biologist, and he is on this really important paper where they helped to classify a new species of primate and new species of earning a team. But when the PR on that discovery, you know, went out scientists discovered a new orangutan, yeah, really, really upset. Because look, the end Did you notice population that was living in that region of you know, Sumatra knew about this orangutan -- the generation, they just didn't care. So it wasn't like white scientists go to Indonesia to discover an orangutan, it was like Western science finally caught up with indigenous knowledge.

SPENCER: That's funny.

CRYSTAL: Yeah, right. So, knowledge exists in other places, and having that tested and validated and having the scientific method applied to its understanding so that it can be structured for inclusion in the collective pool of scientific like academic scientific knowledge can only benefit society.

SPENCER: Crystal, this was a really interesting conversation. Thank you so much for coming on.

CRYSTAL: Oh, my God. Thank you so much for having me. You took me through almost all of my favorite topics. I hope I didn't ramble too much. This was really enjoyable.





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