Hi everyone and welcome to course on equity and justice in technology policy. In today's video, I want to give you a little bit of an introduction to the course and I'm also going to give you an introduction to myself. My name is Shelby to Parthasarthy. I am a professor at the Ford School of Public Policy at University of Michigan where I also direct the Science Technology and Public policy program. So I have some background in this area and I'll tell you a little bit more about that. It's a bit of a complicated and interdisciplinary background in a minute. But first I'll talk a little bit about the course itself and why we thought it was important to have a course on this topic. So what is this course about? Well, I probably don't have to tell any of you after all, you're watching this video that technology is increasingly important in modern society. Like many of you, I can't live without my smartphone, my iphone to be specific. Of course over the last few years we've been incredibly dependent on covid vaccines and testing and it's really, really important. And most governments spend enormous sums of money funding technology. They do what's called push policies. And these push policies are based on what people call a linear model of innovation. That linear model of innovation generally means that we have public financial support, especially in the United States and europe, but increasingly around the world there's a lot of investment by the government in innovation. And that means research funding. It might mean development funding, choose using particular entrepreneurs to invest in who are working on projects that are of public benefit, but it also includes intellectual property policies, a subject that is near and dear to my heart because I've done a lot of research on it. And so the idea is that if the government funds a lot of research, then we will have public benefit. Usually they fund basic and applied research and to some degree, a little bit of technological development. But the idea of the linear model is that if we fund a lot of research, then that will lead to technological development which will produce innovation. And usually when we talk about innovation, we're focused very much on innovation for the marketplace that is market products and then social benefits will result. Now throughout this course, we're going to complicate that picture quite a bit. But I want to give you a sense of what that linear model traditionally is. You're probably accustomed to thinking about it in those terms. Now that focus on the linear model of innovation and that focus in terms of the government on funding a lot of innovation or supporting innovation in order to produce public benefit has produced a lot of benefit. There has been a growth in GDP across many countries. There is clearly a large scientific workforce. We have access to crucial new technologies like the vaccines that I mentioned a minute ago. But at the same time we are seeing increasing inequality and increasing injustice in all sorts of ways. So we know, for example that global inequality has risen and that global inequality has real impacts. So, for example, in the United States alone, the life expectancy for people in the wealthiest one person Category vs those in the poorest 1% category it increases. So people in the wealthiest 1%, men have a 10.1 increased life expectancy. And for women it's 14.6 years of increased life expectancy. That's quite significant. Right? So this global inequality has real impact. Part of the problem there is that access to technology itself is uneven. So to go back to the covid testing example, we know that people who were in wealthier and whiter communities tend to have more access to covid technologies than those who were in poor neighborhoods or neighborhoods where there were historically disadvantaged communities of color. We also know that technologies invariably reflect societal biases not just in the distribution of those technologies as I suggested a minute ago, but also even in the design itself. Now, that might be kind of shocking to you. But I'm going to talk a lot of about it over the next couple of weeks and you'll read a number of examples of that in the next couple of weeks. And I think you'll develop some tools to understand how that happens and also how to perhaps anticipate that in your own thinking and in your own work. And so the purpose of this course, really the central question is how can we rethink technology policies to maximize equity and justice And when we think about technology policies in that context, then we're thinking not just about innovation policies, but also about regulatory policies. And we'll talk about what those policies are, what the distinction is in the coming weeks. So I've already kind of hand waved to a couple of myths about technology, but I want to talk about the eight myths that we tend to have when it comes to technology. So the first is that technology benefits everyone that to put it perhaps in slightly different terms, that the benefits of public investment in technology ultimately trickles down and benefits everyone. But as I suggested already, in that covid testing case, it doesn't actually trickle down equally. Second myth is that by definition, innovation is in the public interest. We tend to not break apart these categories of either innovation or public interest and so ideas or results that suggest that actually innovation can in some cases reflect or reinforce even societal biases is surprising to us and perhaps hard for us to digest. Third myth that we can only enable or disable science and technology. That is that the primary lever that we have is that public support lever? Right? So we can only push innovation forward or not push innovation forward or we can only ban technologies or allow technologies. The fourth that science and technology evolved independently on linear, internally dependent path. So one of the important dimensions of this linear model, not just the first part. The public push is that line right from basic research to apply to technological development to innovation. If you look at that line, there's an internal logic there as though society is not part of that until the last piece, the societal benefit and what we're going to talk about in this course is how society actually shapes every dimension of the innovation process. Fifth myth that we can't really control technology or that there's a regulatory lag for technologies and that's why, you know, we're always running to keep up and this is often used as a reason why technology policies aren't really an adequate tool for dealing with some of the problems that technology creates, that we can't anticipate the implications of technology. We often you'll hear about unintended consequences and therefore we can't regulate them or shape their development in any kind of sophisticated way because we don't know actually what technologies are going to create. And then finally that the public fears about technology are irrational and that public's need to be educated so they can really understand technologies and understand. Generally speaking that they are beneficial. So you might believe some of these myths or you might know folks, your best friends and family might think, might be talking in these ways. And what I hope in this course is that I'll give you some tools by which you can think in a little bit more critical ways about the relationships between technology and society and the role that public policy plays so that in fact we can ensure that both technology and technology policy can really achieve social benefits and public goals. So the outline of the course is that in the first half we're going to be talking about and really understanding the relationships between technology policy and society. For this week, we're going to be talking about the role of social and political priorities and how value shape technological development and design. And then next week we're going to talk specifically about the relationship between technology and equity and how technologies can reflect or reinforce equity or inequity and injustice. The third week we'll talk specifically about the relationship between technology policy and equity. And then the last half of the course will be talking about tools to rethink both technological design and development and finally governance. So we'll talk about how we need to rethink expertise. We tend to think about technical experts as central to technology and technology policy. And I'm going to complicate that a little bit. Well, then talk about rethinking design of technologies themselves. And then finally rethinking policy. So our course content includes a variety of different kinds of insights from different fields, from public policy to social science to the humanities, to stem fields, science, technology engineering, Math, etcetera. We'll be reading some academic articles, some op EDS and public facing work blurbs from books. I'll expose you to some podcasts and videos that I think are going to be helpful in developing your thinking on these subjects. And just a content note, I host a podcast called The Received Wisdom that focuses on these subjects. You're welcome to take a look on your own time and see what the content is. I'll be including some of those pieces from the podcast in our course modules and then in terms of the assessments, they're a mix of quizzes, pair discussions, small projects that will hopefully give you the opportunity to not only learn the content and some of the lingo but also to really engage in thinking critically about technology and technology policies. So who am I? Well, as I suggested, I have a pretty multidisciplinary background which probably explains the multidisciplinary approach to the course. My own training is pretty varied. I have education in both the technical side and biology as well as in the social studies of Science and technology. And I have a pretty varied employment background in addition to being a professor in a school of public policy and training not only policy students, but also budding scientists and engineers, medical students, etcetera. I've also done a lot of work in the policy sphere. So I've worked for a White house advisory committee on human radiation experiments, worked for the national academies of Science Engineering and Medicine as well for rand that is a major think tank in the United States. I've done a lot of policy work outside of that based on my own research. So I've testified in front of Congress advised the Organization for Economic Cooperation and Development, the National Academies, the Government of India. And I'm kind of excited to say that my work has also influenced the Supreme Court even about a decade ago and my research spans a variety of topics from biotechnology to artificial intelligence. As I suggested before, I'm very interested in questions around intellectual property and innovation. More recently I've been doing research on inclusive innovation and international development and generally when I look at these topics, I'm interested both in how we can develop and govern emerging science and tech technology to serve public interest and social justice goals. But I'm also really interested in the politics of science and public policy and how policy environments shape the kinds of knowledge and expertise that we use to solve social and policy problems. So I'm looking forward to this journey with you on this course on equity and justice and technology policy. And just to give you a summation basically my goal is to really make you think and also to give you the tools to help ensure that technology is used to make the world a better place
