 Hey, OpenJS World. Thanks for tuning in to this session. My name is Chris Borchers. I am currently serving on the OpenJS Foundation Board of Directors as the one of the Cross Project Council representatives. And with me, I have Dr. Joy Leasy Rankin, who is the Research Lead at the AI Now Institute and Research Scholar at New York University. She's also the author of A People's History of Computing in the United States. And so I'm going to turn it over to Joy to kind of why don't you tell us a little bit about yourself and maybe how you came to write that book. All right. Thank you so much, Chris, for that introduction and hello OpenJS. I'm so excited to be a part of this conference. So I am a historian, but I am a historian by way of cryptography and ESL and the video game organ trail. I was a double major in college. I majored in math. I taught myself how to code. I wrote encryption programs, but I was also a history major. And after college, I worked in tech. I actually did a bunch of startups that were helping somehow connect education and technology. So one of those, for instance, was doing ESL online on a global scale. And this was sort of before voice over internet was common. We have proprietary software to do that. And after all of that, I finally at some point decided I really missed being in school myself and I went to pursue a doctorate. And as I was studying history of science and technology, which is my area of expertise, I kept reading about tech and competing from the perspectives of like founders and developers. And I had spent all this time working with, I mean, as a developer, but also working closely with users and seeing their creativity and imagination and how they never did exactly what we thought they would do with whatever tech we gave them. And I was looking for stories like that and not finding any. So when it was time for me to write my book, I decided to focus as much as I could on a sort of from the ground up from the user perspective of computing. And that led to my book, which is the People's History of Computing in the US. Very cool. So you mentioned sort of your inspired by in your experience of seeing some of the creativity of users of technology and I guess could you give us an example of some of that creativity that you saw in the past and in some of your findings? Absolutely. And also this lets me talk about Oregon Trail as well. So if I forget to bring that in, don't let me forget that. So, it also lets me talk about Minnesota, which is where I'll start because in the post World War Two decades, so we'll say from the 1950s to the 1980s, Minnesota was the Silicon Valley of the United States. And when I learned that, I was like, what? It's something we never hear about. It's totally forgotten now. But for those 40 or so years, especially based in the Minneapolis, St. Paul area, there was like a thriving, booming high tech economy. It was based with sort of five key companies, which were Control Data Corporation, Univac, Engineering Research Associates, Honeywell, and then IBM had a huge plant in Rochester. There was five companies, but also all of the smaller businesses around them that provided hearts, hardware, know how, created this sort of the state that was my colleague, Tom Misa, called it a digital state. And it was also something that was reflected in the community. So, parents and teachers were really enthusiastic for their kids to learn about computing, starting in the early 1960s. And so, around the mid 1960s in the Minneapolis, St. Paul area, different school districts formed a cooperative to give all of their students, all of their public school students access to computing. And what I think is really cool about this is at the time, time sharing was a form of network computing where you could connect teletype writers, which sort of looked like typewriters with printers attached to them. And you could connect a bunch of teletypes to one mainframe computer. And so in the mid 60s, a mainframe cost literally hundreds of thousands of dollars, whether you were buying it or leasing it. So it was a cost that no single school district could afford on their own, but Minnesota law enabled those school districts to form a co-op so that 18 or 20, and it started with about 20 school districts that grew closer to 50. They could all share the cost of the mainframe and then just put the teletypes in their school and the teletypes were connected to the mainframe by phone lines. They ran programs back and forth. All of the students and the teachers were actually connected because, and this is something that was often overlooked. They, because of the phone line connection, they could actually communicate with each other through the mainframe and share programs that way. So starting in the really the 1960s, Minnesota had this thriving creative computing community for public school students and they were writing programs. They were using basic, which is a programming language that was huge in schools from the 60s through the 90s at least. And just doing all sorts of amazing things. And as that was just one network in the Minneapolis area, there were similar networks that were sprouting up around the state and the state observed this and decided that it would be good for equitable reasons to have a network, basically a network of networks across the state to ensure that maybe kids who were in more rural school districts or less affluent school districts would also have access to computing. So the state organized something called MECH, the Minnesota Educational Computing Consortium to put together all of these networks and ensure public school computing from kindergarten through 12th grade as well as community colleges and universities. And that was in place by 1975 and within a year of its launch, something like 85% of students, public school students in Minnesota were regularly computing, which is phenomenal and it's something we totally forget. It's a huge success story. They were all not just doing programs but writing their own programs, writing programs to compose music and poetry as well as play game. So, and here we come to the Oregon Trail, which I am a big fan of, I think many children of the 1980s and 90s probably also grew up playing Oregon Trail. So doing the research for my book, I was so thrilled and surprised to learn that it had started, it had originated in the Minneapolis, St. Paul's schools in 1971 as a game written on a teletype by some student teachers in American history who wanted to teach their kids how to, how learning about the Lewis and Clark Expedition and so they programmed Oregon Trail and when MECH formed, that software became part of MECH software. It became popular across the state and then as Apple Computer came on the scene way back in the 1970s into early 80s, one of its biggest customers was school districts around the United States and all of these schools were looking for software for their apples and MECH because it had this huge software repository from like 15 years of Minnesota computing had all of these games and programs like Oregon Trail that they could, they actually did like a subscription service for public schools around the country. And voila, there we go. Very cool. No, I mean, I, yeah, I have fond memories of Oregon Trail. So, and even, I mean, I recently purchased like a little like handheld Oregon Trail like not too long ago that I was playing with, which was a lot of fun. Yeah, I've been, I mean, it lives on like when I go, I mean, talk to undergraduates about this or like at other colleges or universities like people have it on their phones they like, you know, there are different versions of it they played online with their friends. So, yeah, yeah. That's amazing. To, I guess, kind of bring us back to the, the title of this session. That obviously is a, an amazing story of increasing equity and serving as many people as possible I think you said some 85% right of those things. That's amazing. And were there other networks that perhaps we're trying to do the same thing and maybe had different outcomes or not so not so good outcomes that that you found in your research. Yeah, I did. I did. And this surprised me as well so I did my undergraduate at Dartmouth College, my BA, and Dartmouth was actually the home of one of these 1960s and 1970s networks, which I had known a bit about before I started researching the book but not as much as I know now. So, Dartmouth in the early 60s was men only it's now coed but then it was men only and it was almost exclusively white it was very affluent. And the two math professors one of whom we are became college president, John Kemeny and his colleague Tom Kurtz saw that there was interest in their students and computing. And they just thought it would be good citizen training actually they thought that computing would be so essential to life in the 21st century that all of their students should learn how to do it. So they fundraised and got grants and petitioned the Board of Trustees to build a network on campus initially. And it was a huge hit, perhaps not surprisingly to us now but like the network was launched in 1964 and as a side note, it was programmed entirely by undergraduates it was like a phenomenal coding thing to learn about, but launched in 64 by 6880% of the students, not only are regularly using the network, but they know how to write programs in basic so Kemeny and Kurtz had also created basic as the programming language to make it easy and accessible and faster to learn how to code using teletypes connected to excuse me connected to a mainframe. So, Kemeny and Kurtz see that computing is a hugely popular with their students, and there's interest around New England in from other schools like Oh, can we also do this. So Kemeny and Kurtz create a program that's connecting high schools and colleges across New England in New York with the mainframe at Dartmouth, and in particular there's a three year program that runs from 1967 to 1970, where they're working on about 20 high schools around New England, and some of them are public, some of them are private, some of them are in like rural, very rural farming communities, some are in elite boarding schools like Phillip Sandover and Phillip Exeter. And again, they think this is great we're going to increase access to computing, we're going to give more students opportunity. And on the surface I thought wow this is phenomenal like it looks amazing they have all of these schools with different socioeconomic levels, computing. And then I looked at the fine print and the fine print was that all of the private schools on the network had 72 hours a week of computing access and the public schools only had 40. So we'll say the private schools had about double the public schools for a number of reasons mainly though because they were residential in many cases they just could afford more teletype time. And I thought oh okay here's a class difference primarily. And I looked even further and most of those private schools are now coed, but at the time like Dartmouth, they were boys only or young men only. So what I realized is this meant that on the surface it looked like they were increasing access for everyone but because of the structures in place at the time around education, the boys using the network we're getting nearly double the access as girls. Similarly, it was sort of a amplified bias in a way because even though girls were writing programs like I found records of like one middle school young woman who wrote this a brilliant chess program apparently and there were a number of others but they were just forgotten, because there were so many more boys and sort of so many more boys in prominent schools who were given attention to so. And this was a case where like, it looked like everything was set for like tech to do good and like increase access, increased community connect people and it ultimately longer term had the opposite effect. Right, right. So, I guess that's definitely unfortunate. I mean it seems like the inadvertently boys were being given more time. But I mean, we're girls computing I mean were they doing things what did you find where girls were actually creating and and we're just, I guess, absolutely and not I mean this is not just girls but women as well so and girls on the network. Also it's important to I should note that there were all women's colleges like Mount Holyoke that were connected on the network as well, and their students were computing. And usually when I tell my like I've told my students this they're like what women were not in tech. And I'm like waiting to know wait actually in fact during the 1960s women had many jobs in tech like many programming jobs and the example that I find really compelling that I often share is specifically with the Dartmouth network there were women working at the computer center was called key which is where the mainframe was and they had public teletype terminals, but it sort of was the hub of computing life on campus. And there were women working there who were highly educated like with with college degrees in some cases with PhDs are working with two PhDs who were programming applications who were running user services who were doing their own research on computing so experts in the field and that was actually the norm for the 1960s. I think just like we forget that Minnesota used to be the high tech hub of the US I think right now we often forget that in the 60s actually there were many women who were working in the computing industry. And one of the reasons I think we forget this culturally is. So an example of this is john Kemeny who I mentioned before is one of the sort of co founders of this network he becomes president of the college. Not many years later in the late 60s early 70s and he's giving a speech about how phenomenal this network is and soon he expects everybody will have a computer in their homes. And it'll be so great because all of the housewives will be able to program their grocery lists and their chores to optimize their days and then their free time they can like take online courses for their like self improvement. And so he's giving this speech, which is both I find hilarious and sad because he's like predicting a future that's in some ways very familiar. But he's completely ignoring the fact that like his network is being run by women or at least we'll say the women are making significant contributions to its programming and success. And he's talking about housewives computing so sort of doing this like, oh, erasure of the work of women's expertise in science and tech. So absolutely, there were girls computing on this network there were women computing on this network as well as in Minnesota, as well as on other networks at the time but that work, often is sort of erased forgotten. Not given as much attention to in popular stories. Yeah. Yeah, I mean that's that's I think you put it really well and that it's I mean it's that specific story is funny but also just sad right I mean it's it's it's unfortunate and I'm sure there are many, many, many other stories like that. So, I hate to like cut us off but we are actually like almost at times so what what would be great I think for the audience is if you could kind of just I guess give us a little bit of info on how we can maybe learn more about these topics I mean obviously go get your book right. But in addition to that like for for people in the community that want to be allies and and sort of help fight these biases that are are clearly still present today. What kind of advice can you give on that front. All right, so as you mentioned my intro right now I'm a research lead at the AI now Institute at New York University. And we published a report last year called discriminating systems it was a lead offer by my colleague Dr Sarah Myers West. And we specifically give recommendations for improving in the report, improving workplace diversity or tech diversity because the report argues what we found is that often it is this lack of diversity in tech spaces whether it's gender diversity or having black people and brown people or people with disabilities. It's reflected in the kind of systems that get built and the code that gets written and even with the best intentions. If we're not sort of taking into account all of this diversity and the way that society is structured we end up replicating the bias so I would absolutely point people to the discriminating systems report. I'm going to read some of them and then I will also in case I forget I just there are a number there are some other books as well that I want to suggest that are just really good places to start but just some like basics for improving diversity is to publish compensation levels across roles and job categories broken down by race and gender to end pay and opportunity inequality especially for workers tents and vendors and I've been in the tech world you're all in the tech world you know there are a lot of people who are doing contract work and temp work and it creates a hierarchy about who's honored who's remembered how they're compensated and increase the number of people of color women and other underrepresented groups. Especially at senior leadership levels and we know like right all the research tells us it's not just good for the sort of practice of tech it's actually good for the economics of tech as well this actually like when you have more diversity you actually end up with more robust economics as well and then for academic spaces similarly ensure greater diversity in all the space that spaces where we focus on AI research but really broadly where tech is done where CS is done where engineering is done and including conference committees so those are just a few that we actually have many more recommendations but I also just wanted to suggest a few books as well. I would go pull them off my bookshelf but I but that also just go into a lot more depth about how the ways that I mean if some of this was eye opening to me just how biased that you don't you're not even aware of can see into sort of the spaces that we work in so one is algorithms of oppression by Sophia Noble. One is new Jim Code by Ruha Benjamin and then black software by Charlton McElwain and programmed inequality by Mar Hicks. So those are very like super well written and focused on the intersection of diversity and tech or we could say racism and sexism and tech as well and just, you know, learn more, try to be aware of, you know, wherever you have power, try to think about how it can be used to empower others. So, yeah. Awesome. Well thank you so much I mean that I'm like, I'm honored to have been able to have this conversation with you. I'm trying to learn every day as well so I really appreciate you taking the time to speak with us and yeah, everyone should, let me say go. Go get Dr Rankin's book and and the other books that she mentioned and and just learn be open to learning, listen. And yeah, we really appreciate you taking the time. Thanks so much Chris I, it was a pleasure. Thanks.