WEBVTT 00:00.000 --> 00:01.600 Hi, my name is Young B. 00:01.600 --> 00:01.920 Lim. 00:01.920 --> 00:14.740 I am a doctoral candidate at George Mason University and I'm also a Baltimore Underground Science Space Community Lab member and I am super thrilled to be here to give you this talk. 00:15.120 --> 00:20.600 I think that it's fairly apparent when you look at the title what I'm going to talk about. 00:20.600 --> 00:23.540 And that's about the dangers of assumptions. 00:23.700 --> 00:37.700 So let's get on with this talk about you know what they say when you assume So as a brief background about who I am, just from a professional vantage point, I'm clearly a guy that's into some style. 00:37.700 --> 00:40.980 I love glasses and I love wooden bow ties. 00:40.980 --> 00:46.160 I've been involved in national security and looking into it for about the past decade. 00:46.160 --> 00:51.360 Also, I am involved in community labs and community organizations. 00:51.360 --> 00:57.880 So I've been very fortunate the past few years to be involved with the Global Biosummit. 00:57.880 --> 01:02.180 Just so you know, Global Biosummit 4.0 is coming up. 01:02.240 --> 01:03.520 Biosummit.org. 01:03.520 --> 01:06.360 So go check it out and register while you still can. 01:06.360 --> 01:24.640 And like I mentioned previously, I am a doctoral candidate at George Mason University looking at DIY bio So the thing that I also wanted to point out because everybody is a multifaceted individual is I wanted to see what the internet would pull up When I decided to talk about, 01:24.640 --> 01:26.980 you know, things that are personal about me. 01:26.980 --> 01:35.800 So interestingly enough, these are the images that came up and the first one to the upper right should be pretty obvious. 01:35.800 --> 01:39.820 It's me hanging out with a friend of mine, Natalie Ma. 01:39.820 --> 01:43.040 This is actually at Santoka Ramen in Boston. 01:43.300 --> 01:45.580 So I'm a huge fan of ramen. 01:45.580 --> 02:02.500 In the bottom right hand corner, it shows me being involved in a community lab project called Barcoding the Inner Harbor, along with other members such as Syrah and also actually the founder of Bugs, Tom Burkett, in the photo in the lower right there. 02:02.560 --> 02:07.780 In the lower left hand corner, you can see that I think of myself, I guess, as a flamingo. 02:07.780 --> 02:14.000 I just thought this was a really fun picture because this photo was taken when I was traveling in Seoul, South Korea. 02:14.000 --> 02:16.640 I'm a person that really loves to travel. 02:16.780 --> 02:23.260 And interestingly enough, this focaccia bread picture popped up in the internet search. 02:23.260 --> 02:27.040 And so it seems to show that I have a real appreciation for baking. 02:27.040 --> 02:31.900 And for carbohydrates, which shouldn't be terribly surprising given the Robman photo. 02:32.200 --> 02:35.980 So, you know, that's a bit more about me, apparently, according to the internet. 02:35.980 --> 02:45.060 So I really want to now get into the meat of this particular talk, which deals with this idea of assuming. 02:45.060 --> 02:47.380 So you know what they say when you assume. 02:47.380 --> 02:52.620 And I think that Moira Rose does a fantastic job in this animated GIF of explaining that. 02:52.620 --> 02:55.920 Never assumed here, it makes an ass out of both of us. 02:56.480 --> 03:02.660 So what do assumptions have to do with kind of my talk and my life story here? 03:02.660 --> 03:06.660 Well, to get to that, we need to start with an origin story. 03:06.700 --> 03:10.360 So I'd like you to picture it, a la Sofia Petrillo. 03:10.700 --> 03:15.180 It's at George Mason University in 2015. 03:15.360 --> 03:17.740 That's when The Force Awakens came out. 03:17.740 --> 03:19.900 I just really liked that animated GIF. 03:19.900 --> 03:21.760 So I decided to put that in there. 03:21.760 --> 03:43.340 So when I was a PhD student at George Mason University in 2015, that's where I had my first exposure to these concepts of do-it-yourself biology, community labs, people doing the life sciences outside of conventional traditional areas like academia, industry, 03:43.340 --> 03:44.540 and government. 03:44.540 --> 03:47.860 And this was my first exposure to it. 03:47.860 --> 04:01.140 So if you look through any of these particular images, you can see that the image presented of do-it-yourself biology, community labs, amateur science is a pretty horrifying one. 04:01.140 --> 04:04.980 There's this idea that amateurs could create mutant viruses. 04:04.980 --> 04:12.500 There's this idea that these people are actually creating biosecurity issues. 04:12.500 --> 04:23.140 There's an idea that non-state actors could use these technologies that people are using in unconventional ways to exploit synthetic biology for terrorist purposes. 04:23.140 --> 04:38.620 And as more people engage in these types of activities, it's possible that, according to this 2018 New York Times article, that people will get hurt as they continue to do these DIY gene editing experiments. 04:39.420 --> 04:45.700 So my first impression of do-it-yourself biology and community labs is not terribly surprising. 04:45.800 --> 04:49.400 I think Archer explains it best here with welcome to the danger zone. 04:49.400 --> 04:53.240 Because it certainly feels like a danger zone type situation. 04:53.240 --> 04:54.660 You know, it feels very dangerous. 04:54.660 --> 04:57.560 It's about people that I don't understand. 04:57.800 --> 05:02.020 And, you know, that's the impression that I initially had. 05:02.020 --> 05:12.140 So clearly, I'm speaking to you here right now from the comfort of my own home during this virtual conference, and I've clearly had a change of heart. 05:12.400 --> 05:14.960 And how did that change of heart happen? 05:14.960 --> 05:17.460 Well, I think that there are three precipitating reasons. 05:17.460 --> 05:21.100 The first is, I'm a homebrewer. 05:21.100 --> 05:24.060 Starting in 2012, I go visit Korea. 05:24.060 --> 05:26.920 I try to visit once, sometimes twice a year. 05:26.920 --> 05:29.400 And I really got into homebrewing. 05:29.400 --> 05:32.020 They have a rice wine there called makgeolli. 05:32.020 --> 05:44.440 And if you listen to my interview podcast episode with Nina and Bo on white hats and lab coats, I talk a little bit about my homebrewing experience. 05:44.440 --> 06:00.540 But I kind of came to realize, and I use this book, I realized that sake is Japanese, makgeolli is Korean, but I kind of came to realize that homebrewing in itself is a form of, you know, doing biology. 06:00.540 --> 06:03.120 Outside of conventional spaces. 06:03.120 --> 06:14.860 And so, you know, that kind of got me open to this idea that maybe biology in unconventional spaces is not only something that's desirable, but it can be something that's delicious. 06:14.860 --> 06:39.760 So the second thing that kind of got me thinking about how biology in unconventional spaces could be a good thing was this idea that I was talking about myself as this kind of emerging tech, biosecurity expert, but the more that I got into the biology of it all, 06:39.760 --> 06:44.100 the more that I realized that biology is actually really hard. 06:44.860 --> 07:00.700 I kept having to go back through basic biology textbooks to just get a basic understanding of a lot of these very complex ideas and complex technologies that were coming down the pike that I was supposed to be able to understand. 07:00.700 --> 07:22.870 So I wasn't sure at one point if it was that biology is hard or that I'm just a horrible student, but I eventually realized that having community lab spaces as a place where people could learn biology at their own pace would actually be helpful to me from a professional and educational standpoint. 07:22.870 --> 07:36.690 And finally, the third thing that changed was I was very fortunate to get a research assistantship in California at Lawrence Livermore National Lab. 07:36.690 --> 07:42.170 And I met this gentleman in the upper right hand corner, Patrick Dessalier. 07:42.170 --> 07:52.550 He is a founder of one of the first few community labs in the United States, Counterculture Labs in Oakland, California. 07:52.570 --> 08:00.350 And he learned it through the grapevine at Lawrence Livermore National Lab that I was interested in do-it-yourself biology. 08:00.350 --> 08:07.330 And he at one point came up to me and he asked me, hey, so I hear that you're interested in community labs. 08:07.330 --> 08:08.830 And I said, yes. 08:09.050 --> 08:12.370 And then he asked me, have you ever been to a community lab? 08:12.370 --> 08:13.710 And I said, no. 08:13.970 --> 08:23.910 And so he offered me literally a life changing opportunity with an invitation very akin to Arnold Schwarzenegger in the lower right hand corner. 08:24.010 --> 08:29.390 Come with me if you want to live, or at least come with me if you want to learn more about community labs. 08:29.390 --> 08:42.230 So actually getting that initial introduction, actually getting that invitation to come and participate and observe was a really eye opening experience for me in 2016. 08:42.230 --> 08:54.470 And over the past five years, I think that it's really developed a number of changes in the way that I think about community labs and DIY bio that are very much with me to this day. 08:54.470 --> 09:00.890 So I know some of the people in the audience at this point are saying, you know, origin stories are great. 09:00.890 --> 09:04.090 But if you could get to the point, that would be great. 09:04.090 --> 09:05.810 So here's the point. 09:06.390 --> 09:12.570 This is often the situation, you know, there's a major problem when we assume things. 09:12.770 --> 09:20.670 So as much as we like to think that we know everything under the sun, that is not a true fact. 09:20.750 --> 09:22.190 That is fiction. 09:22.190 --> 09:38.010 There are the known knowns that we know of, but if we're not willing to push ourselves beyond the known knowns into the other areas, particularly in my case, in regards to DIY bio, the known unknown. 09:38.010 --> 09:47.670 So, you know, we know that there are like particular issues that may be existent, but we don't necessarily understand what this phenomenon is that we're observing in the first place. 09:47.670 --> 09:55.050 Unless we're willing to push ourselves to expand our idea of the known knowns, we often work off of assumptions. 09:55.110 --> 10:02.430 And once again, TLDR, remember what Moira says, it makes an ass out of both of us. 10:02.430 --> 10:15.270 So I just, you know, as the start to this whole entire talk, I wanted to get people to think about this idea of assumptions and understanding that assumptions aren't facts. 10:15.270 --> 10:16.890 Assumptions aren't truth. 10:16.890 --> 10:37.070 What we need to do as responsible citizens and responsible scientists is to, when we run into a particular situation that we don't know very much about, have the willingness to be curious and open minded and go into that new area, this kind of like, you know, 10:37.070 --> 10:39.250 this strange new world. 10:40.090 --> 10:53.050 With, you know, an open mind and be willing to kind of process information as we go along and allow that information to help inform us as we, you know, expand our knowledge. 10:53.550 --> 10:58.850 And arrive at particular conclusions and policy recommendations. 10:59.870 --> 11:02.870 So we are finally here now. 11:02.910 --> 11:21.710 My talk is on understanding the do-it-yourself biology and community labs scene, and it is a bit unusual, I think, in the biohacking village context, because a lot of you people are like incredibly technical people, and I would not be able to do half the things, 11:21.710 --> 11:27.270 actually even a quarter of the things that the people do in this audience on a regular basis. 11:27.270 --> 11:39.010 So, you know, testing vulnerabilities and various types of software, imagining, you know, all of these kind of like red teaming, like cybersecurity type events. 11:40.610 --> 11:41.970 That's amazing. 11:41.970 --> 11:43.570 It is amazing that you can do it. 11:43.570 --> 12:00.770 I really hope that you find this to be an interesting talk because social science, I think, is often referred to as a soft science and sometimes kind of pushed to the side, but I think there's real insights here that could be helpful, not only from a policy standpoint, 12:00.770 --> 12:02.410 but from a community standpoint. 12:02.410 --> 12:06.230 So I'm going to go forward with that kind of perspective in mind. 12:06.230 --> 12:08.530 So here we are finally at the main event. 12:09.930 --> 12:11.790 No crazy animated gif here. 12:11.790 --> 12:19.070 I just wanted to go over a few basic facts about the do-it-yourself biology community from my research. 12:19.070 --> 12:24.530 So there aren't very many reports about the do-it-yourself biology community. 12:24.530 --> 12:32.610 One of the main ones was from 2013 authored by Dan Grushkin, Todd Cookin, and Piers Millett. 12:32.610 --> 12:40.010 So in terms of its history, it appeared to emerge somewhere in the United States from about 2005 to 2008. 12:40.010 --> 12:45.650 It's now a global phenomenon with community labs popping up all around the world. 12:45.650 --> 13:08.910 A lot of people associated with the do-it-yourself biology movement in the early days include Rob Carlson, who built his own biolab in 2005 and he talked about, in a Wired article, how people could maybe start doing their own community lab work and learning community lab skills from the comfort of their own home. 13:08.910 --> 13:23.370 And then Jason Bobb and Matt Cowell in 2008, they were based in Cambridge, Massachusetts, and they had this idea of making biology more accessible and easier to do, particularly from the angle of synthetic biology. 13:23.550 --> 13:37.090 So having people, you know, providing people with the knowledge and the tools to be able to engage in biology and do some really fun and cool things, you know, from the comfort of their own home or from community lab settings. 13:37.690 --> 13:45.290 So the 2013 report discusses how this community started as a small online forum. 13:45.290 --> 13:48.210 It was an online Google group called DIY Bio. 13:48.210 --> 13:55.170 Current estimates estimated at 3,000 to 4,000 individuals associated with the movement. 13:55.170 --> 14:00.710 It's highly decentralized, consisting of actors ranging from individuals to regional communities. 14:00.710 --> 14:11.430 The individuals from that 2013 report, they noted that people tended to be more educated and younger than the general population. 14:11.610 --> 14:20.750 And these community labs and these kind of garage labs tend to be centered in highly developed urban locations with higher education academic institutions. 14:21.770 --> 14:29.570 So in terms of DIY Bio, in terms of its values and goals, it's very much about democratizing technology. 14:29.570 --> 14:37.950 And when we talk about democratizing technology, I see it as four separate but interrelated concepts. 14:37.950 --> 14:58.010 So there's increasing access to technology, increasing access to knowledge, so the internet, but also increasing access between people to have conversations, to talk about science, distributing scientific practices to a broader community, and distributing capability for a broader community. 14:58.010 --> 15:03.990 So broader in terms of the number of individuals and broader in terms of ways of usage. 15:03.990 --> 15:17.750 So I think that it's very much the idea of DIY Bio that people see the democratization of science as good news, as Professor Farnsworth clearly acknowledges. 15:17.750 --> 15:34.020 And, you know, this idea that not only do academics and, you know, industrialists and government have science, but we as citizens have science and should have access to science and should be able to do science. 15:35.250 --> 15:44.710 So in terms of my research, what I found in terms of DIY Bio activities were they encompass four general categories. 15:44.710 --> 15:47.470 So the first is exploration. 15:48.350 --> 15:56.770 People in the DIY Bio community like to explore, you know, everything from within themselves to their local and regional environments. 15:56.770 --> 16:03.910 So that's, you know, a vehicle that DIY Bio uses to enable people to explore their surroundings. 16:04.750 --> 16:21.350 He-Man, clearly with the, I have the power, indicates that DIY Bio also really believes in empowering individuals to be able to engage in biology and to be able to leverage biology for their own particular sets of purposes. 16:21.350 --> 16:29.170 In terms of another activity that DIY Bio does, there's a lot of education that happens in do-it-yourself biology contexts. 16:29.170 --> 16:38.370 So there are lectures, there are hands-on lab skills classes, there are casual conversations where people just talk about various topics. 16:38.370 --> 16:46.050 And before you know it, they've talked about this entire area of science that they're really excited about and really excited to collaborate on. 16:46.050 --> 16:49.070 And finally, there's an entrepreneurial element. 16:49.070 --> 17:11.210 So there are a number of community labs that function as early stage incubators for small groups and individuals to come in and maybe develop a proof of concept or get some data that hopefully they can then use to develop a product and very much in the style of Fry there, 17:11.210 --> 17:13.950 have people tell them to shut up and take their money. 17:16.610 --> 17:24.210 So question here is, how do national security professionals and practitioners typically feel about what I described? 17:24.790 --> 17:32.850 If you remember back maybe about 15 minutes ago, surprise, we're back to the danger zone again. 17:32.850 --> 17:45.850 There's this real concern that as people have access to these technologies that they can do all sorts of things with them and they're not necessarily benign things that, you know, people can do. 17:46.350 --> 18:16.410 So scouring through the WMD literature, especially as it relates to non-state actors, but, you know, the WMD context, I noticed three general trends or three general considerations that national security experts seem to be focused on when they think about the change in risk associated with the development of WMD and the use of WMD in the modern day. 18:16.410 --> 18:30.350 So in terms of capability, as capabilities increase, as people can do more things with the technology, that means that people are then able to leverage that technology to do lots of things. 18:30.710 --> 18:43.190 So if people are able to do lots of things, that increases the playing field of not only could they use the increased capabilities for good, but also for nefarious purposes. 18:43.890 --> 18:52.530 The second major trend that I noticed in terms of assessing WMD risk is increases in convergence. 18:52.530 --> 18:58.190 So there are lots of different players that are getting involved in science nowadays. 18:58.290 --> 19:05.530 And it's not just you know citizen scientists, but disciplines are also converging. 19:05.530 --> 19:26.350 So synthetic biology is actually a convergence between biology, you know, the traditional life sciences and the application of engineering principles to biology, trying to make it easier to design, easier to test, easier to build, making it easier to produce products with. 19:26.350 --> 19:36.030 So as these different groups and different communities engage with each other, there's less certainty about what the outcomes will be. 19:36.030 --> 19:41.090 And it's harder to predict what outcomes will come from what interactions. 19:41.090 --> 19:59.550 And so the lack of certainty also contributes to the sense of concern that, you know, as as more communities work together with each other or different disciplines work with each other, you're going to end up with this, you know, you're not, you're not sure where, 19:59.550 --> 20:01.650 you know, what's going to come out of those interactions. 20:02.270 --> 20:15.470 And finally, in terms of increased accessibility, technologies, you know, people talk often about how gene sequencing and gene synthesis prices are consistently falling rapidly. 20:15.470 --> 20:21.530 So that makes them financially more accessible to a broader audience. 20:21.530 --> 20:33.510 Technologies also are becoming more available secondhand, on secondhand markets, because there are a fair number of biotech companies that, you know, there's a high rate of failure in biotech. 20:33.510 --> 20:43.310 So when a company goes out of business, they often set things up so that they either donate their equipment to other people that, you know, are interested in them, they sell them on eBay. 20:43.790 --> 21:01.930 So as these technologies become more accessible to a broader audience, there's also this perception that there's a loss of control of the equipment, of the reagents, of all of these things, which then contributes to this idea that the risk of weapons of mass destruction, 21:01.930 --> 21:05.490 development, research, and use are increasing. 21:06.850 --> 21:13.330 And these are just some examples from the state actor perspective. 21:13.650 --> 21:17.590 So in the upper left hand corner, you have a 3D printer. 21:17.590 --> 21:36.690 The, you know, one of the concerns with 3D printing is as it becomes more capable, as we're able to do more granular things with it, maybe states or potentially non-state actors could use that granularity, that specificity, to develop nuclear weapons parts or parts for a nuclear centrifuge. 21:36.690 --> 21:42.510 In the upper right hand corner, we have, you know, a graphical image of CRISPR. 21:42.510 --> 21:44.610 So this idea of gene editing. 21:44.990 --> 22:07.110 And as, you know, gene editing becomes more prevalent, as gene editing becomes more accessible to a broader audience, it becomes not only harder to control the technology, but it also is just really hard for people to arrive at what would be approved and unapproved uses of gene editing technologies. 22:07.110 --> 22:12.410 Because as you broaden the pool, you know, you have an expansion of opinions. 22:12.410 --> 22:13.770 Opinions are like assholes. 22:13.770 --> 22:15.430 Everybody has one. 22:15.450 --> 22:23.310 And so, you know, it becomes harder to arrive at a consensus when it comes to technologies that become increasingly, you know, increasingly accessible. 22:24.230 --> 22:35.070 And then, you know, within the non-state actor context, here's that concern again about the use of weapons of mass destruction or the facilitation of uses of weapons of mass destruction. 22:35.070 --> 22:52.770 So as drone technology becomes more prevalent, it may be possible to use drone technologies themselves as a weapon of mass destruction in terms of, you know, if you have a concentrated number that's swarming, attacking a particular position that could, 22:52.770 --> 22:55.670 you know, result in massive, massive casualties and massive damage. 22:55.670 --> 23:10.450 We're looking at the fact that drones with swarming technologies may aggregate and be able to be used by non-state actors to do significant damage to infrastructure, to individuals, things along those lines. 23:10.450 --> 23:24.310 To the upper right hand, that image in terms of the non-state actor space, that was a sarin factory in Japan that was being run by a group called Amashinrikyo. 23:24.310 --> 23:43.350 The bottom image is in reference to Amerithrax, a domestic event that happened in 2001, largely believed to have been done by a single individual through the distribution of anthrax to the postal system. 23:46.090 --> 24:02.730 So with this, you know, with these three kind of considerations in mind, you know, these three relationships of what is driving risk, WMD risk, related to the life sciences, where does do-it-yourself biology fit? 24:02.730 --> 24:20.660 And I would argue that if you look through the lens of a national security person looking through this framework, that you could argue that do-it-yourself biology appears to mean a greater perceived WMD threat to the national security space. 24:20.660 --> 24:38.480 So, you know, you have people getting access to you know, use lab equipment that contributes to a diminished sense of control over being able to control the supply of equipment, reagents, things along those lines. 24:38.480 --> 24:41.360 You also have an increased convergence. 24:41.360 --> 25:00.340 So you have not only traditional people doing the life sciences, but you also have regular citizen scientists contributing towards, you know, various kind of life sciences projects, which means you're not necessarily sure how you know, what the outcome will be of the types of work that these people are doing. 25:00.340 --> 25:07.100 And, you know, technology is only getting not only cheaper, but more efficient, more capable. 25:07.100 --> 25:33.600 So as technologies become smaller, as technologies become faster, as technologies can do more things like gene sequencing devices that are, you know, tabletop gene sequencing devices or potentially even gene synthesis devices that are tabletop, we're talking about the potential to do more things as technology advances. 25:33.600 --> 25:51.620 So, unfortunately, it seems like do-it-yourself biology from a national security angle is a thing that deserves some concern and, you know, increases the potential for WMD threats from that perspective. 25:52.300 --> 25:58.440 And that is, you know, this typical perspective that you see in national security circles. 25:58.440 --> 26:00.340 So here are a few quotes. 26:00.980 --> 26:07.140 You can read through them, but mostly they're about how technology is becoming more accessible, specifically gene editing. 26:07.660 --> 26:12.340 People may be able to do all sorts of things with these technologies as they become more available. 26:12.720 --> 26:20.840 And, you know, these are communities that have traditionally not necessarily been involved in the life sciences. 26:20.840 --> 26:30.080 So there may be security and safety implications that go along with that kind of naivete, that amateur element. 26:31.240 --> 26:45.160 So, um, I saw this issue and I was trying to balance it with my perceptions and my experience being involved with the community for five years at this point. 26:45.740 --> 27:02.580 It was very frustrating, to be honest, to sit in and listen to people talking about do-it-yourself biology as this threat when I, from my personal observations and interactions, thought there was a more complex picture at play. 27:02.680 --> 27:21.500 So, you know, with the support of my committee, with the support of the do-it-yourself biology community, I developed a dissertation project looking to understand do-it-yourself biology community labs from a social science aspect, following very much in line with what Dr. 27:21.500 --> 27:26.360 Farnsworth recommends in terms of how to proceed with the scientific method. 27:26.620 --> 27:29.140 So I developed a one-year study. 27:29.140 --> 27:37.080 It looked at 10 community labs across the United States, as well as major spaces that are associated with community labs. 27:37.080 --> 27:42.640 So, for example, MIT Media Lab is a place that is not necessarily a community lab. 27:42.640 --> 27:46.260 It is a major convening space for community labs. 27:46.640 --> 27:51.500 In terms of the activities that I engaged in, I did in-depth interviews. 27:51.500 --> 27:58.720 I also actively participated in projects, classes, labs throughout that year. 27:58.720 --> 28:01.820 And I also did observations. 28:01.820 --> 28:15.100 So I gathered field notes and I highlighted observations over the course of a year to develop a very deep understanding of the community labs that I was able to associate with. 28:15.100 --> 28:19.060 So this study really focuses on four things. 28:19.060 --> 28:29.080 How people find out about community labs, what motivates people to participate in community labs, how they are organized, and how people learn and teach in these spaces. 28:29.840 --> 28:34.620 So getting to how people find community labs. 28:35.860 --> 28:43.540 Interestingly, actually not interestingly, because it's, you know, it's, I think it's a pretty obvious phenomenon nowadays. 28:43.540 --> 28:48.320 The most prevalent method that people find community labs is through the internet. 28:48.320 --> 28:53.720 As Homer Simpson points out, they now have the internet on computers. 28:54.200 --> 28:56.580 So that seems to be the most popular method. 28:56.580 --> 29:01.120 People are interested in finding lab spaces, and so they look online. 29:01.120 --> 29:06.940 People are interested in finding science spaces, so they look online. 29:06.940 --> 29:08.360 So that's a typical method. 29:08.360 --> 29:11.240 That was the most prevalent method from what I saw in the study. 29:11.240 --> 29:13.820 But other methods include interpersonal connections. 29:13.820 --> 29:17.140 So friends telling other friends about community labs. 29:17.140 --> 29:18.980 Professional connections as well. 29:18.980 --> 29:23.200 So individuals that are interested in, say, bio art. 29:23.200 --> 29:27.720 And they're like instructors of art at various institutions. 29:27.760 --> 29:34.560 They hear about community labs as these kinds of innovative spaces for bio artists. 29:34.560 --> 29:39.300 And then that's how they then go to these community labs. 29:39.300 --> 29:41.820 There's also direct community lab outreach. 29:41.820 --> 29:45.160 So community labs often have web pages. 29:45.160 --> 29:47.840 They have meetup sites, you know, things like that. 29:47.840 --> 29:50.340 And then sometimes it's just a roll of the dice. 29:50.340 --> 29:51.340 It's serendipity. 29:51.340 --> 30:03.760 So, you know, there were a number of people that I talked with throughout the process that said, hey, I was going to this one place because a friend told me about a poetry slam that was happening in this building. 30:04.140 --> 30:10.640 And then I looked around the corner and I found out that there was this lab that was in this building as well. 30:10.640 --> 30:13.160 So serendipity also does play a role. 30:13.580 --> 30:19.920 It's not exactly empirical, but I think it's just a really interesting little factoid to toss in there. 30:19.920 --> 30:21.300 Sometimes it's a little random. 30:22.460 --> 30:26.480 So what motivates people to participate in community labs? 30:26.480 --> 30:29.300 The main one is a passion for science. 30:29.300 --> 30:32.500 These individuals are very passionate about science. 30:32.500 --> 30:34.460 They want to learn about science. 30:34.460 --> 30:43.240 Maybe they want to engage in science, but there's this fundamental desire to engage in science. 30:43.240 --> 30:50.780 And that's what motivates people to not only start going to community labs, but continue participating in them. 30:50.780 --> 30:53.380 And then, you know, there are a number of other elements, too. 30:53.380 --> 30:55.960 You know, these are some just some of the top ones. 30:56.000 --> 30:57.240 Social interaction. 30:57.240 --> 31:01.100 So, you know, community labs, the word community is in there. 31:01.100 --> 31:02.940 Community members come together and they talk. 31:02.940 --> 31:08.200 So social interaction is considered a very positive motivation for why people go. 31:08.200 --> 31:13.180 People also believe in the mission of community labs and democratizing science. 31:13.180 --> 31:16.180 So there's an alignment of values with the organization. 31:16.520 --> 31:20.840 People also like to engage in community spaces because there's community engagement. 31:20.840 --> 31:27.420 You get to engage in community projects and work with community people to build things for the community. 31:27.800 --> 31:39.940 And another major one is just this idea that outside of a traditional institution like academia, industry, and government, you have access to an actual BSL-1 lab. 31:39.940 --> 31:44.880 So you can actually have hands on experience, rather than just read from a book. 31:44.880 --> 31:50.600 You can actually, you know, get your hands a little dirty and do a lot, you know, learn and do some science. 31:51.780 --> 31:54.780 So how are community labs organized? 31:55.060 --> 32:00.240 This is a blatant steal from Alex Perlman's Twitter. 32:00.240 --> 32:06.340 Alex Perlman is an amazing bioethicist who works closely with the DIY bio community. 32:06.340 --> 32:08.540 This was from Global Bio Summit. 32:08.540 --> 32:10.900 I believe 3.0. 32:10.900 --> 32:12.640 It may have been 2.0. 32:12.640 --> 32:14.060 Alex can correct me. 32:14.060 --> 32:17.360 I'm sure she's involved in Biohacking Village this year. 32:17.800 --> 32:29.220 But in this picture, David Kong at MIT Media Lab is presenting how he sees community labs being organized, which is as an armada of pirate ships. 32:29.420 --> 32:45.800 So this, you know, these pirates, they loosely associate with each other as a group, but they also kind of go their own path and their own direction, depending on their own particular whims and their own particular desires. 32:47.020 --> 32:56.640 The idea here, of course, is also that there is a loose organization, but it's not exactly hierarchical and entrenched in stone. 32:57.120 --> 33:10.380 So, you know, community labs are often organized this way, you know, not only from a community lab to community lab basis, like an organizational basis, but also just like within a community lab itself. 33:10.380 --> 33:16.160 So what are some of the advantages and disadvantages of having this loose organization style? 33:16.160 --> 33:20.080 Well, I see some of the advantages as being autonomy. 33:20.700 --> 33:22.260 People can do what they want. 33:22.260 --> 33:24.100 Individuals can do what they want. 33:24.100 --> 33:27.100 Community labs can engage in projects that they want. 33:27.380 --> 33:36.520 Also, many of these community labs are volunteer based, so they actually have a really incredible ability to operate with exceptionally low budgets. 33:37.060 --> 33:44.080 What often comes up in conversations with community lab leads and individuals is they run on shoestring budgets. 33:45.180 --> 33:56.820 And finally, with the autonomy element connected with it, community labs can engage in activities that are reflective of the unique local and regional communities that they're a part of. 33:56.820 --> 34:14.400 So in the case of bugs, for example, based in Baltimore, Maryland, they're really interested in barcoding or understanding what lives on a genetic level in the Inner Harbor, which is a body of water that is very significant to the Baltimore ecosystem. 34:14.920 --> 34:24.700 So some of the disadvantages, though, is because each group is autonomous and they're so distant, sometimes there are coordination difficulties. 34:24.700 --> 34:30.840 You can have issues with coordination across even the United States because there are time zone differences. 34:31.350 --> 34:40.150 You also have coordination difficulties within organizations in terms of this because of the fact that they're volunteer based. 34:40.940 --> 35:01.920 So the thing with volunteer based is while you have a lot of people that are willing to do work for no money, when there are situations that take precedence over your hobby of engaging in the community, that means that DIY bio activities won't always be a top priority. 35:01.920 --> 35:03.980 So things can fall through the cracks. 35:04.420 --> 35:11.880 And just as I mentioned that they're able to operate on shoestring budgets, there are severe resource limitations and it's not just financial. 35:11.880 --> 35:29.900 So a lot of community labs depend very heavily on the lab leadership to do a lot of the heavy lifting and that's usually one to two to three people that are essentially in charge of making sure that a shoestring budget organization continues onward. 35:29.900 --> 35:31.780 And that's a really large burden. 35:32.020 --> 35:36.440 There's a significant concern in the community for burnout. 35:36.780 --> 35:42.260 People that eventually get burned out because they've taken on too much for a long period of time and there's no respite. 35:43.940 --> 35:54.000 So in terms of, finally, how do people learn and teach in these spaces, um, I kind of divided out the activities as structured so versus unstructured. 35:54.060 --> 36:04.200 So in terms of how people learn in these spaces, there are the structured styles that actually reflect a lot of traditional academic teaching styles. 36:04.200 --> 36:11.000 So there are pure lectures, there are hybrid lecture and lab courses and there's project participation. 36:11.620 --> 36:30.020 Unstructured styles include, you know, just casual conversations, impromptu conversations, impromptu demonstrations, where people just engage with each other and then just kind of take things as they come and, you know, just explore things with each other in an unstructured fashion. 36:30.440 --> 36:37.740 And in terms of the style of teaching in these spaces, once again, it's very reflective of a traditional academic style. 36:37.740 --> 36:44.800 And the thing I want to emphasize here is the traditional academic style is not is not random. 36:44.800 --> 36:53.780 A lot of these community labs are run or founded by individuals that have advanced degrees from academia. 36:54.500 --> 37:11.760 So when you look at a board or a leadership of a community lab, more often than not, you will see individuals with PhDs in molecular biology, electrical engineering, bioinformatics, just, you know, these are highly educated individuals. 37:11.760 --> 37:24.920 And so it's not surprising that that traditional academic style bleeds into how they then structure the learning and teaching environments in, you know, in community labs. 37:24.940 --> 37:35.740 So, you know, in terms of like groups, they use traditional academic approaches like lecturing, small group demonstration and practice. 37:35.740 --> 37:40.860 And then you also have these mentorship one-on-one interactions. 37:40.860 --> 37:47.260 So when people are learning like a significant number of lab skills, they're really trying to beef themselves up. 37:47.260 --> 37:58.740 Learning from a PhD in, you know, in traditional science, then you get into more of these like hardcore mentorship relationships where they interact one-on-one. 37:58.740 --> 38:02.300 The person that is learning shadows their mentor. 38:02.300 --> 38:11.740 The person that's learning practices consistently and the mentor is there often in the beginning to monitor the progress of the individual. 38:11.740 --> 38:23.120 So I talked a lot about, you know, how people learn about these spaces, motivation, how people learn in these spaces, and how these places are organized. 38:23.120 --> 38:27.940 So is there an implication to these kind of like social elements? 38:27.960 --> 38:30.380 And I would argue, yeah, there is. 38:30.380 --> 38:41.960 Let's revisit that framework of perceiving WMD threat as it relates to, you know, from the do-it-yourself biology community. 38:41.960 --> 38:48.300 So does increased potential capability lead to a greater efficacy for do-it-yourself biology? 38:48.300 --> 38:51.310 Can you do more things as capabilities increase? 38:52.280 --> 38:54.540 And you know what, on the one hand, yes. 38:54.540 --> 39:04.540 So people can construct, you know, self-made Arduino board guided incubators for plants. 39:04.540 --> 39:06.400 So DIY constructs. 39:06.400 --> 39:20.860 People can engage in their own sample preparation and analysis and and people can even, you know, in high school through programs like iGEM engage in synthetic biology projects in a DIY biocontext. 39:22.340 --> 39:40.980 However, I would also argue that from some of the observations and some of the data that I acquired, it's not necessarily just because there's an increased potential capability does not necessarily lead to greater efficacy in the DIY biocontext. 39:40.980 --> 39:47.980 So in the DIY biocontext, like I mentioned, there's a lot of secondhand, third-hand equipment, self-made equipment. 39:47.980 --> 39:54.160 There's a lot of equipment breakages, which interferes directly with the ability to do science. 39:54.880 --> 40:03.700 Also, because DIY bioplaces are places of learning and of education, there are lots of errors that happen along the way. 40:03.700 --> 40:08.920 It's not just professionals doing the sampling and the analysis. 40:09.100 --> 40:16.580 It's people that are being taught as well by these professionals, by these, you know, knowledgeable people. 40:16.580 --> 40:17.980 And guess what? 40:17.980 --> 40:20.900 Those students learning, they make lots of mistakes. 40:20.900 --> 40:27.380 I can tell you for a fact that I made a ton of mistakes as I was learning how to just even basically pipette things. 40:28.260 --> 40:33.100 Also, community labs suffer from environmental contamination issues. 40:33.100 --> 41:00.010 We're talking about places where biology is being done in unconventional spaces, you know, whether it's in a warehouse or it's in, you know, a building or whether it's a place that doesn't have a separate room for your PCR machine that's being kept sterile so that you can get lots of environmental contamination that way. 41:00.320 --> 41:03.700 And then, you know, you just have issues with supplies and logistics. 41:03.700 --> 41:14.140 So there's this, from my understanding from the research, there's a very negative conceptualization of the term biohacking. 41:14.140 --> 41:18.840 So any place that refers to themselves as a biohacking place. 41:18.840 --> 41:30.480 So whether it has biohacking in the name or things like that, companies that produce reagents are very wary about sending reagents to such spaces. 41:30.480 --> 41:34.140 So, you know, that could be a limiting factor as well. 41:35.580 --> 41:46.340 So does also, you know, in terms of that second risk issue, does greater convergence lead to less certainty of outcomes in the DIY bio context? 41:46.340 --> 41:49.080 So on the one hand, yes. 41:49.500 --> 41:55.780 People engage in lots of really cool independent projects that you don't necessarily see in academia. 41:55.780 --> 42:06.760 So there's this really interesting, it's almost like it almost looks like a photo that they took on a leaf of a particular logo. 42:06.900 --> 42:15.600 I don't quite remember how they did it, but it looks like magic to me, but that's not something that I would expect coming out of an academic lab. 42:16.140 --> 42:19.520 Once again, there's that barcoding the Inner Harbor project. 42:19.520 --> 42:29.960 The open insulin project also is a really interesting example of having citizens get engaged in science. 42:29.960 --> 42:55.570 So not only is open insulin about finding ways to develop and distribute insulin, given the insulin crisis in the United States and across the globe nowadays, but it also sends a political message of saying that you know, big pharma is literally holding the lives of diabetics in its hands and trying to find a way to disrupt that. 42:56.020 --> 43:06.650 So yeah, you know, there are, you know, there is a certain type of less certainty that comes from an increased convergence, but on the other hand, no. 43:06.650 --> 43:13.850 One of the things that I found as I was doing my research was there are definite limiting factors. 43:13.850 --> 43:17.290 It's almost like a path dependence model for community labs. 43:17.290 --> 43:27.930 Where community labs are shaped by the environments that they exist in and the organizational factors that you know, that they have. 43:27.930 --> 43:44.130 So in terms of leadership expertise, the individual that runs the lab, depending on their expertise, may be more inclined or less inclined to do certain projects because they might not necessarily be comfortable with doing things that fall outside of their expertise. 43:44.750 --> 43:46.830 There's also the expertise of the community. 43:46.830 --> 43:54.270 If you don't have a particular type of expertise that you need to run a particular type of project, you're probably not going to pursue that project. 43:54.270 --> 43:57.550 There's also community interest and resources. 43:57.630 --> 44:02.790 So is there an interest in the community to actually do a particular type of project or not? 44:02.790 --> 44:09.550 And, you know, in the case of bugs, for example, like I said, they're really focused on that inner harbor. 44:09.950 --> 44:19.390 And so they're interested in doing projects that reflect the community, but they might be less interested in doing another type of project that does not reflect the community. 44:19.390 --> 44:36.210 And finally, there are a number of community labs that actually have higher education affiliations and being connected with these higher education affiliation, you know, these higher education affiliates, inherently because higher education, you know, 44:36.210 --> 44:42.930 affiliates tend to be a bit risk averse when it comes to interactions with outside entities. 44:42.930 --> 44:50.090 It, you know, inherently acts as a limiting factor to make sure that community labs don't just do whatever they want. 44:50.650 --> 44:57.450 If they want to participate and get kind of like the validation from higher education, they need to play by certain rules. 44:59.670 --> 45:06.930 And finally, does the increased accessibility of technology and knowledge lead to less control in the DIY biocontext? 45:06.930 --> 45:09.150 So yes, right. 45:09.150 --> 45:11.270 People can do independent research. 45:11.270 --> 45:21.210 People can learn how to do lab skills and techniques, potentially on their own, at least basic ones like pipetting, particularly through online resources. 45:21.330 --> 45:31.070 And, you know, there's readily equipment and tools available online for people that want to engage in do-it-yourself biology projects. 45:31.870 --> 45:51.220 However, I would also argue that the increased accessibility of technology, so technology and knowledge alone, they don't necessarily lead to less control because there are other factors to take into account than just these capabilities of like knowledge and capabilities of technology. 45:51.570 --> 45:55.790 So once again, community labs are limited by several factors. 45:55.870 --> 46:03.230 There needs to be a sufficient amount of scientific expertise in the community to be able to engage as a community lab. 46:03.250 --> 46:13.750 So, you know, a lot of this, as I discussed before, is addressed by the fact that a lot of these community labs are founded by people that are experts in science. 46:13.750 --> 46:18.150 So PhDs in molecular biology, things along those lines. 46:18.150 --> 46:22.390 But there also needs to be a desire or a need for a community lab space. 46:22.390 --> 46:26.590 So you're not going to find community lab space popping up literally everywhere. 46:26.590 --> 46:40.910 It's a little bit of an easier sell for a community lab space in Silicon Valley, for example, where BioCurious is based, or in Boston, where Boss Lab is based, or Baltimore, where there's a biotech hub in the Rockville area. 46:40.930 --> 46:58.770 But you're not going to, you're not going to, you're going to have a lot of difficulty finding a community lab space in, say, Cairo, Illinois, which is predominantly farmland, and there's not that much of a, you know, that much of a resource and interest in science. 46:59.290 --> 47:07.830 You know, and then there are a couple of other issues, availability of resources, and then there's networking communications issues, which I previously discussed. 47:08.250 --> 47:10.280 So what are we left with? 47:11.530 --> 47:20.350 So it's not like I'm saying that there aren't changes that happen with the introduction of do-it-yourself biology to the national security landscape. 47:20.370 --> 47:22.110 You know, the implications exist. 47:22.110 --> 47:32.070 There are potential risks on biosafety, biosecurity, cybersecurity elements, which I'd be more than happy to talk about during the Q&A. 47:33.610 --> 47:40.930 And, you know, the thing is, national security experts have a lot of things to deal with, with very little time. 47:41.530 --> 47:47.790 And so having a framework to be able to assess risk is very helpful. 47:47.790 --> 47:49.770 These frameworks are like heuristics. 47:49.770 --> 47:57.470 They're fast, they work as a mental shortcut, they can be correct, and they're based on the information available. 47:57.570 --> 48:01.930 That said, they may lead experts and policymakers astray. 48:01.930 --> 48:13.950 The focus may be diverted from more pressing issues and we may be missing opportunities by, you know, throwing DIY bio out with the bathwater. 48:14.270 --> 48:16.290 So don't pull a Ron. 48:16.590 --> 48:23.130 Don't get frustrated and throw your computer away just because you don't understand how your computer works. 48:24.890 --> 48:38.090 In terms of the opportunities that I think that we're missing by not fully leveraging DIY bio, one of them is grassroots education, community building, and science communication. 48:38.270 --> 48:51.750 I think that, particularly in an age of misinformation and disinformation, having a community based science resource could be very helpful in terms of dealing with misinformation and disinformation campaigns. 48:51.750 --> 49:05.570 Community labs can function as trusted sources of science information and hopefully communicate proper information that may be helpful in addressing those kind of misinformation and disinformation campaigns. 49:05.610 --> 49:09.150 I also see it as a supplemental education resource. 49:09.150 --> 49:21.390 So it's not a resource that is taking away from traditional education mechanisms, rather it is supplementing the things that people are learning in school. 49:21.390 --> 49:27.150 And in particular, the way that I see it being helpful is it offers hands on experience to individuals. 49:27.930 --> 49:32.590 Traditionally, when in academic institutions, they learn a lot of theory. 49:32.890 --> 49:36.790 And finally, I see it as an accelerative education resource. 49:36.790 --> 49:46.390 So community labs can function very well as places that can expose people that are younger to STEM and critical thinking. 49:47.590 --> 49:57.590 Providing individuals with opportunities to see if science is their passion when they're five or six, rather than having to wait, you know, until they're more in their teens. 49:58.770 --> 50:08.570 And the other thing that I think that we're missing when we don't highlight and lift up DIY Bio is its potential contributions to the bioeconomy. 50:08.570 --> 50:22.610 So there was a NASEM 2020 press release that said that the bioeconomy comprises 5% of US GDP, which when you crank the numbers out comes out to be nearly $1 trillion. 50:22.610 --> 50:27.990 It was $950 billion, but I think nearly $1 trillion just sounds that much more impressive. 50:28.910 --> 50:41.670 So, you know, given the large amount of money at stake, I think it's interesting that we aren't talking more about leveraging community labs as incubators for future biotech innovation. 50:41.750 --> 50:57.770 So we already have some proofs of concepts of this from several community labs, including the OpenTRONS project from GenSpace, which is automating lab technologies, as well as over 30 companies that were incubated at BioCurious, which is based in Sunnyvale, 50:57.770 --> 50:58.810 California. 51:00.590 --> 51:05.190 So in the context of the talk, what do I think we need to think about? 51:05.330 --> 51:08.490 And there are two main lanes that I think we need to think about. 51:08.490 --> 51:12.130 The first thing is addressing DIY Bio community obstacles. 51:12.130 --> 51:19.390 So we talked about how there is burnout and heavy leadership reliance issues, so bandwidth issues. 51:19.390 --> 51:30.150 DIY Bio, particularly being volunteer run, means that individuals have very little bandwidth to work with when they're, you know, in this context. 51:30.150 --> 51:36.110 So we need to be very cognizant and find out solutions to deal with those bandwidth issues. 51:36.110 --> 51:45.350 Also, just the resource issues, like I talked about, financial issues, access to good equipment, access to reagents, things along those lines. 51:45.350 --> 51:51.610 And something that I particularly want to emphasize is balancing the economic needs of the community. 51:51.610 --> 52:17.410 So understanding that economy is a very important element of making sure that community labs are available and are open and can operate, but also making sure that we don't lose track of its spirit, of its desire to not necessarily be all about capitalism and efficiency, 52:17.410 --> 52:23.850 but for it to be a place where people can explore and build communities, because I think there's value in both. 52:24.510 --> 52:39.090 And then finally, I think the other thing that we really need to look into is part of the issue with the DIY Bio image in the national security arena and other areas is I don't feel like it's had proper exposure. 52:39.770 --> 52:49.270 There's been a lot of hearsay and a lot of like media articles, rather than direct connections between the DIY Bio community and other life sciences stakeholders. 52:49.270 --> 52:59.450 So building those bridges, building that collaboration, I think it's incredibly important with members of industry, governance institutions, and public health. 53:00.730 --> 53:05.530 So if you survived this long, I first want to congratulate you. 53:05.530 --> 53:07.230 That was a lot. 53:07.290 --> 53:10.270 I hope that it was a lot of good food for thought. 53:10.270 --> 53:24.370 So I want to first, you know, take a moment to acknowledge the DIY Biology community members and organizations that really helped me out in understanding the community lab scene. 53:25.110 --> 53:29.410 I really see this as a community based project. 53:29.410 --> 53:38.910 I really see this as my contribution to DIY Bio by engaging in a community based project with community buy in. 53:38.910 --> 53:56.410 So I really want to make sure that I thank the community labs and DIY Bio members at BioCurious, Biodesign Challenge, Biologic, Biotech Without Borders, Boss Lab, Bugs, Counterculture Labs, GenSpace, Indie Lab, MIT Media Lab, and OpenBioLabs. 53:56.410 --> 54:02.590 I really do thank you from the bottom of my heart, and I used that RuPaul animated gif to show that. 54:03.310 --> 54:05.690 And then finally, you know, there's this other side too. 54:05.690 --> 54:32.050 Like I said, I'm a NatSec, a national security person as well, and my my thinking about the community and my drive to be able to engage with the community to fill what I feel is a very serious gap in the national security perspective would not have been possible without all of the people that are here as well on the security and safety side. 54:32.050 --> 54:39.810 So I really want to thank Nina, Bo, Nalja, Sidney, Josh, and everyone at Biohacking Village. 54:39.810 --> 54:48.030 I really do appreciate you giving me this platform to, you know, have these conversations, build connections, and see what comes out of it. 54:48.030 --> 55:06.310 I also really wanted to thank Gregory Copeland, Sonia Ben-Wahgum-Gormley, Trevor Thrall at George Mason University, Natasha Bajima at Nuclear Spin Cycle, Todd Quicken at NCSU, Seth Karras, Diane D'Ulis, Gerald Epstein at the Center for the Study of Weapons of Mass Destruction, 55:06.310 --> 55:12.510 Gigi Quick-Rumble at Johns Hopkins Center for Health Security, as well as Matt Watson and Crystal Watson and Michael Montague. 55:12.550 --> 55:23.390 And then a special shout out, a little shout out to my Friday LB night crew, Nicholas Evans, Emily Kelly, Mary Lancaster, Amanda Moody, Sasia Popescu, and Emily Ricotta. 55:23.990 --> 55:29.010 And with that, I'm sure that everybody has questions, comments. 55:29.010 --> 55:34.830 If you want to also even engage in a bit of old-fashioned trolling, I'm available for Q&A. 55:34.850 --> 55:38.810 You could have, you have my email right there, and you also have my Twitter. 55:39.150 --> 55:43.210 And with that, we are done. 55:44.270 --> 55:47.870 And I want to thank everyone for hanging in there with me.