And talked about and consumed over the years. This conference is sponsored by the department of history at purdue university, is organized by one of our panelists. It is also by nikki. We are thankful to all of them to get into this and discuss how history is going to be taught in the future. My name is connie doebele. We are fairly new entity the, here at purdue, our goal is to help professors from across the country used the cspan archives, which is over 250,000 hours of american political history in their classrooms and in the research. We do some other things but thats what we are concentrating on at this conference. I tweet at c. J. Doubly we we hope that you will follow us. On twitter. We would be interested in following you as we reach out to, specifically history professors across the country who are interested in using the cspan archives in their classrooms and research. Here is what we are going to do, we have three excellent panelists who have different areas of interest under this topic. They are going to speak for five to seven minutes and then we are going to open it up and take a lot of q and a. We are going to start with Margaret Pugh omara, i hate to read introductions. So there is her introduction, you can read it. I do not need to read it for you. I will do what i am trained to do, ask you the questions that are not on their. Margaret, where did you grow up . I grew up in little rock arkansas. How did you make the move . Where did you go to school . Northwestern. I wanted to go to a big city. I wanted to be somewhere other than the south, and i got in. How did you choose history . One of the reasons i chose history is my high school is a little rock central high school. I was in my senior year, the 30th anniversary of the fall of 1987 of the crisis at central high. And it was a real, by the time i was in high school it was a time that we were all being made very aware of that history, at least certainly in the halls of the high school we are reckoning with that history. It may become a majority, minority diverse high school. Understanding my own personal connection to someplace that had such a significant role in American Civil Rights stories one of the reasons i did this. Last bio question. What teacher, no matter it was grade school, high school or university level, made the most difference in your career path . My graduate adviser, that late michael cats university of pennsylvania. Thats because we are the cspan archives, i was able to, find that all three of our panelists have appeared on cspan. Here is Margaret Pugh omara talking about the vietnam war and the protests. This is part of a program that cspan history does called lectures in history. They go across the country and look for professors teaching certain historical issues in their classrooms and they actually bring the cameras into the classrooms. 1960s is a time when the liberal left comes together, you have strong leftist movements. Both within and outside formal politics, a push towards more leftist solutions. But it is also the moment when the modern right is coming together. There are also young people on college campuses, young people in high schools, who have very different ideas about what america is and should be. This Margaret Pugh omara has a book called the code, this Silicon Valley and the remaking of america. It seems crazy that that is history now. I turn it to you. Thank you so much, thank you for organizing this. It is great to be on this panel with all of you and to be speaking to the people in the room and who will be watching this on cspan. I set to writing my most recent book, the code, and approached it, when i started about five years ago, thinking about it as a political history of Silicon Valley. It morphed into something much broader. But that political spine is still there. In the course of writing about the evolution of the high technology, computer in hardware and Software Companies on the west coast, from the 1940s to the president , particularly when you get to the last 25 years, it also becomes a story about media. Im intensely interested in, as scholars say, putting the state back into the story of Silicon Valley. A place which has for quite awhile portrayed itself to the techno libertarian paradise in politics and government should be avoided. Wind government got involved a just missed things up. Funny and of politicians of both parties had held up is this beautiful example of Free Enterprise and entrepreneurialism. But there is actually very critical government and political story that runs throughout. There is also a media story, or information dissemination story. Going to something that we see that is manifesting right now, you have these Large Tech Companies like alphabet google, and facebook, that are the media disseminators. We are so much information flows. Yet they are companies that do not think of themselves as media companies. Not only saying they are not in the business of media as if they were newspapers. But their whole self conception truly is one of being against traditional media and being something that media is like government, an old style institution. But when we look at this historically, we not only see how the culture of Silicon Valley in particular, Business Culture, that was based on growing fast at all costs, elbowing competitors out of the way, bringing products quickly to the market, the growth mindset of Silicon Valley is inundating how these very Large Companies are working today and why it is challenging, to create and change the Business Model. It was but also, a community that grew that i referred to as the galapagos, its a distinctive ecosystem that grew up in the fifties to the eighties, though very much connected to centers of finance and government on the east coast, notably through the flow of money through the military, which is why Silicon Valley came to be. But it was isolated enough, geographically and in terms of the people paying attention, if you read a story and the Washington Post for the New York Times that referred to Silicon Valley around 1980, that term comes up very rarely, and when it does it comes up as Silicon Valley. Even when you did have National News coverage like fortune, who are profiling entrepreneurs, it was eight this strange beautiful faraway species, a very different type. If we look back to the way entrepreneurs like steve jobs and bill gates were presented to the world when they first came to prominence, when their companies came to prominence, they were these shaggy haired, iconoclastic, disruptive narrative. One of the things that we discover when we look back is both, there is a very distinctive Business Culture that grows in the technology industry, an industry that has come under modern age to have an immense influence on politics and government and on media. It is very distinct of, yet it is deeply connected to old economy institutions, national government, state or local governments, old money, where did the money for the Technology Revolution come from. Where were the funds that that flew into the initial venture funds that started these iconic entrepreneur companies and Semi Conductors and personal computers and on and on . It was the rockefellers, the whitneys, it was where the money was. It was wall street banks. These Companies Like apple, which is some presenting itself as this counter cultural dream of a company, they think different, but why did apple break apart from the pack of other personal computer makers in the late seventies . They had a beautiful product and they also had a singular, the two steves, Steve Wozniak who designed the beautiful, powerful, eloquent motherboard inside the computer. And steve jobs who could tell a good story and understood how to present this device to the world. They also had management expertise from other companies that were traditional and well establish that took these two guys into a garage and turned into a real operation. We see it again and again. Recognizing a, that this whole ecosystem has a history. It is both singular and distinctive but it is a product of the last 75 years of american political history and American Social history. It is really critical to understanding and grappling with the immensity of these companies today. I will leave it at that. Thank you very much. Meredith is our next speaker. Meredith is from New York University and she has a book called artificial an intelligence, how computers misunderstand the world. I will put up your biography but ask you some questions like where did you grow up . I grew up in a small quakertown. How did you make it from philadelphia to nyu . The i was at pen before this, i was at temple them sorry . Oh the microphone. Just before i was at nyu i was a professor at temple and a professor at the university of pennsylvania. I studied Data Journalism it is the practice of finding stories and numbers to tell stories. New york is the epicenter right now of people who are working on Data Journalism and people who are working on major issues around ethics in technology, especially ethics in Artificial Intelligence, which is my other specialty. So what teacher move your life . One of the stories i tell in the book is about when i was in high school, and i was in a pro grab an Engineering Program for kids. The go ahead, do we need to start over . Absolutely not. I will just ask you to question again, what teacher changed your life. One of the really important educational experiences i had and learning to use technology happened when i was in high school, and Engineering Program for kids. We would get taken once a month to the are see a plant in the small town where i grew up. It was rumored that they were Building Nuclear weapons there, but actually what i did was go on this little bus to this Engineering Program and they gave a spare computer parks and said here, build a computer. I actually built my own first computer and it was great. So i learned from that. When i learned that i had the power to create technology, also that there are a lot of wasted spare parts laying around Tech Companies. Once that employ useful information. I learned about power and i had the power to build things. As margaret said, there is a lot of economic power behind building technology. That was really important knowledge that i took with me into becoming a data journalist. So looking for you in the cspan archives i found you in the yelp headquarters. And here you are. Technology is not going to save us from every social problem. Lets take homelessness for example, the fix for homelessness is not making an app to connect people with services. The fix for homelessness is giving people homes. So, we need to think about pushing back against techno chauvinism and using the right tool for the task. Sometimes that tool is a computer. Sometimes it is not. When meredith broussard. Thank you. I want to talk a little bit about today about understanding Artificial Intelligence. My book is about the inner workings and outer limits of technology. I started writing it because i was having a really hard time with people understanding what i was doing in my work. So, i build Artificial Intelligence systems for investigative reporting. I would say this and people would say, its like a robot reporter . And i would say, no. And they would say, it is like a machine that spits out story i. D. S . And i would say no. I realize that if i wanted anyone to understand what i was talking about and working on, there needed to be more of a basic understanding of Artificial Intelligence in the world. I started researching the book. I realize that we dont often get good definitions of ai. We talk about it a lot, but there is kind of this fog that descends when we try to talk more precisely about it. Theres a lot of confusion. When youre having a conversation about ai, one person is talking about the hollywood stuff with killer robots, and a computer that is going to take over the world, and the other person is talking about computational statistics. It is really important if we are going to have policy discussions about Artificial Intelligence, the role of technology in society, we should all be talking about the same thing. One of the things i do in the book is give a really concise definition of ai. I show readers exactly what it looks like when somebody does ai. Specifically i look at Machine Learning. It is a form of ai. Ai is a sub discipline of Computer Science, the sway way that is a algebra is that sub discipline of mathematics. Inside the field of ai there are a lot of other sub fields Machine Learnings, systems, natural language processing, and generation. This interesting thing has happened that ai is the most flip so this linguistics lip itch has happened. When people say i am using ai for business, what they actually mean is i am using Machine Learning for business. The two terms have become conflated. It is really important to keep that distinction in mind. Another point of confusion is that Machine Learning like ai, sounds like there is a little brain inside the computer. I was at a science fair for grownups, i was doing a demo of this ai system i had built, this undergraduate came over and said, oh you build and ai system. I said yes. He said is it real . I said yes. And then he starts looking under the table like theres something hiding under the computer, as if there is little brain in there. I realize that this linguistic confusion is really profound, we need to talk about the fact that real ai, real Machine Learning is not actually about sentence in the computer. It is a bad term. What must Machine Learning is, computational statistics on steroids. Well it is essentially making statistical predictions. It is amazing that it works so well most of the time. It is amazing that we can use math to figure things out about the universe. The but matt cannot tell us everything. Prediction can tell us likelihood but not truth. So we need to keep these ideas in mind and we need to think about hollywood. Because hollywood ideas about ai color are believes. And every student who comes into your classroom, and starts learning and start thinking about technology and history, is also simultaneously thinking about hollywood. Thinking about hollywood images of ai. We need to make that distinction, make the point that hollywood imagery of ai is totally imaginary. Researchers call it general Artificial Intelligence. That is the singularity that machines that think, the robots that are going to take over the world, it is all totally imaginary. Real ai is called narrow a i. Machine learning, even though it sounds magical is a kind of narrow ai and it is just matt. Another thing i realize when i was doing the recent search for the book was, that the confusion over ai is almost deliberate. Its that people have been using confusion about technology as a gate keeping methods to aggrandize their own importance, to make money, and to keep certain kinds of people out of the profession. When you really trace it back, all of our ideas about technology in Society Today come from a very small, very Homogeneous Group of people. There are mostly ivy league educated, white male mathematicians. There is nothing wrong with being a white male ivy league mathematician, some of my best friends are. But the problem is that people invent their own biases in technology. For example if you look at the way that we dont have women and people of color represented at the upper echelons in Silicon Valley, that is a we can draw a direct connection to the fact that women and people of color are not represented of mathematics. At the harvard matt department, one of the best math departments in the world, there are two senior professors who are women. In 2019 there are two. You know when they started . 2018. So there are Structural Forces outwork inside what fields that are extremely important but for people in technology fields, mathematics, physics, dont actually think that the social Structural Forces are important. They think is what matters is just the math. They think that solving mathematical problems, technological problems, is so superior to these pesky little social problems that they get a pass. This is the root of an idea that i call techno chauvinism which we saw in the earlier clip. It is the idea that Technical Solutions and problems are superior to other kinds of solutions. Using a computer is a superior technology, which is really about saying that math is superior, and it is really about a kind of bias. What i would argue is, again lets think about using the right tool for the task. Sometimes the right tool is a computer, other times it is something simple like a book in the hands of a child sitting on