[00:00:15] Chris Freeland: We all do this. We offer up our email addresses to get into new sites. We do two-factor authentication by sprinkling our phone number around all kinds of spots on the web. We might even share our, personal biometric data with our shopping app to buy a new pair of pants. We're telling the machines everything about ourselves, but who all is listening?

Hi everyone. I'm Chris Freeland and I'm a librarian at the Internet Archive. I wanna welcome you to today's book Talk. In the Secret Life of Data authors, Aram Sinnreich and Jesse Gilbert explore the many unpredictable and often surprising ways in which data surveillance. AI and the constant presence of algorithms impact our culture and society in the age of global networks.

Today's conversation will be led by tech scholar Laura DeNardis, author of the classic text, The Global War for Internet Governance.

And now as we get started here today, I'd like to welcome Brewster Kahle, the Internet Archives founder and digital librarian.

[00:01:13] Brewster Kahle: Thank you, chris. And this is wonderful to be here. And this is the subject everyone is talking about is the AI opportunity, what's happening with our data and are we getting overrun?

And also sort of what are the roles that are being played by. Well large publishers and data miners and the like. So this is a completely timely talk and really wonderful to be able to hear this. I'm also would like to cite a book that is Open Access from Arm, that's from University of Massachusetts Press, the Piracy Crusade, which is unfortunately all old things are new.

Again, it's about the music industry lawsuits. So I am really happy to hear what's going on in this book. 

[00:01:59] Chris Freeland: Thanks Brewster. And now I'd like to welcome Dave Hansen, the Executive Director of Authors Alliance. 

[00:02:04] Dave Hansen: Thanks, Chris. Hi all. Welcome to the book Talk Today. I am incredibly excited about this book. I think when Authors Alliance and Internet Archive launched this book talk series, one of the goals that I had was to really find ways to educate creators, authors about some of the pressing issues with technology and policy that are affecting them.

And I think that this book really. Does a lot of that. It's an area where so much of how our data is collected and managed and processed is kind of hidden behind the scenes, but has a really big impact on day-to-day lives. Now I get to introduce our speakers, and this is kind of an all star cast as well.

First, I wanna introduce Dr. Laura DeNardis, who is Professor and endowed chair in Technology, ethics and Society, and director of the Center for Digital Ethics at Georgetown University in Washington, DC. Her book, the Internet in Everything, freedom and Security In a World With No Off Switch by Yale University Press was recognized as Financial Times Top Technology Book of 2020.

The book I know her most for is The Global War for Internet Governance, also published by Yale at University Press is considered a definitive source for understanding cyber governance, debates, and solutions. Professor DeNardis is an affiliated fellow. Of the Yale Information Society Project where she previously served as executive director.

And is a life member of the Council on Foreign Relations. Laura holds a engineering degrees and a PhD in science and technology studies and was awarded a postdoctoral fellowship from Yale Law School. So Laura is going to be moderating the conversation today with Aram Sinnreich, who is Professor and Chair of Communication Studies at American University.

Sinnreich's work focuses on the intersection of culture, law, and technology with an emphasis on subjects such as surveillance, critical data studies, intellectual property, remix culture, and music. He's the author of five books, of course, what we're gonna hear about today, the forthcoming Secret Life of Data.

He has appeared in a lot of publications that are familiar to you, such as the New York Times Billboard, wired Daily Beast, and Rolling Stone. He holds a MS in Journalism from Columbia University and a PhD in Communications from the University of Southern California. Our co-author with Arum is Jesse Gilbert.

Jesse is a transdisciplinary artist working at the intersection of image, sound, and code, creating flexible frameworks that are activated in live performance via networked interaction or. Installation settings. He was the founding chair of the media technology department at Woodbury University and has taught interactive software design at Cal Arts and UC, San Diego.

So as I said, we have a pretty All-Star group and I think those introductions gave that away. So I am going to turn it over to Laura. 

[00:05:04] Laura DeNardis: Well, thank you so much Dave, and hi everyone. It's just wonderful to join this discussion. Congratulations to Aaron and Jesse on the launch of your new book, the Secret Life of Data.

I thought it might be nice to start if you could read a little bit from your book. I was just drawn into the thesis and also into some of the tensions that are inherent in the book, in that opening story about Joseph DeAngelo. Would you mind reading a little of that? 

[00:05:29] Aram Sinnreich: Sure thing. Thank you so much. We're very excited to be here.

I'm gonna read from the introduction to the book. In 2018, a violent criminal who had terrorized California residents for over a decade was finally brought to justice more than 30 years after his last known crime. Joseph James D'Angelo, a former police officer, was arrested by Sacramento County Sheriff's Deputies and charged with a dozen murders attributed to an elusive figure, previously known only as the Golden State Killer.

After troves of genetic evidence were presented at his trial, DeAngelo pleaded guilty to 13 counts of first degree murder and was sent to prison for the remainder of his natural life. According to news coverage at the time of DeAngelo's arrest, the long cold case had finally been cracked thanks to technological advances.

Old DNA samples were analyzed using modern genetic profiling techniques and the results uploaded to an open source genealogy website called GDED match, where investigators honed in on the killer's identity by tracing his family tree through profiles posted by other users on the site. Data was hailed as the hero in this case.

Without the invisible strands of ones and zeros strung between our bodies, our identities, our markets, and our law enforcement system, justice would never have been served and the Golden State Killer would've remained at large. Even if tech, if genealogy websites weren't built for the purpose of aiding in criminal justice, outcomes like this have been trumpeted as examples of how new methods of data collection, storage and analysis could make the world a better place by bringing clarity and accountability to antiquated systems hindered by guesswork bias and obscurity.

It is fitting that today is National DNA Day District Attorney Ann Maurice Schubert said at a press conference announcing the arrest on April 25th, 2018, we found the needle in the haystack. Yet, while many rejoiced at DeAngelo, let's capture and conviction, not everyone found comfort in the investigator's methods.

As soon as the news broke technology, ethicists and civil rights advocates began to raise concerns about the broader implications of using ancestry databases to track suspected criminals. Should law enforcement have free reign to use DNA matching techniques? In all cases, even those involving non-violent crimes without adequate regulatory and judicial oversight, could techniques like this be used in a sloppy or even malicious fashion, potentially implicating blameless suspects?

Should users of open source databases like GED match be informed that their contributions might unwittingly make them genetic informants on their innocent family As attorney Steve Mercer of the Maryland Public Defender's Office framed it in a USA today interview. The legal and ethical waters became even muddier in 2020 when an Los Angeles Times investigation revealed that the official story about DeAngelo's identification and capture had omitted some important details.

For one thing, law enforcement investigators didn't collect data only from the open source GED match site. They also obtained data using a fake account on the private genealogy service, family tree, DNAA potential violation of the company's terms of service. Additionally, police collaborated with a civilian geneticist who used her personal account on another private service, my Heritage, to upload DeAngelo's DNA and explore his family tree without notifying the company of her true intentions.

None of this data collection and analysis was undertaken with a warrant. Which means that contra contrary to the pledges they'd made to their customers family tree, DNA and my heritage shared personal genetic information with the police even when they weren't required to by law. Despite these revelations, many people still believe the benefits of this foray into an ethical gray area were worth the risks.

As the daughter of one of DeAngelo's victims told the Los Angeles Times, she didn't mind that practices were bent because the unmasking of the killer justified any potential violation of privacy. And the truth is what's important. 

[00:09:29] Jesse Gilbert: Less than two years later, another breaking news story raised the stakes even further, leading many people to reevaluate the relative merits of truth and privacy.

In 2022, the US Supreme Court issued its landmark decision in Dobbs b Jackson, effectively ending half a century of safe, illegal abortion throughout the United States, and opening the door for numerous state laws that not only outlawed abortions, but treated women who sought them as Muslims. Privacy advocates and supporters of abortion rights immediately began to raise the alarm about the risks of online data, exposing abortion seekers to liability under these new laws.

Simultaneously, many news outlets and nonprofit organizations began public awareness campaigns aimed at showing abortion seekers how to protect their digital footprints and thereby minimize their potential exposure to law enforcement. These concerns were not mere speculation or hyperbole. Even prior to the Dobbs decision, there were dozens of cases in the United States in which people's online search histories, chat archives, and other digital traces were used to prosecute them for terminating pregnancies and even more such cases elsewhere around the world, especially in countries where abortions not legal.

In the wake of Dobbs civil rights watchdogs begin to look more closely at a newer set of risks for digital exposure, women's health tracking apps, and biometric devices such as menstrual calendars and smart watches. The same constellation of biotechnology, digital databases, identity tracking business models, and evolving norms about data privacy that had led to the golden State killer's arrest now threatened to expose millions of American women to prosecution for seeking a form of medical intervention they'd understood as a fundamental right throughout their entire lives.

These tensions inherent in these two recent news events between public and private, physical and digital, legal and ethical are at the heart of this book. Together they exemplify the double-edged sword of life in the 21st century, a potent mixture of possibilities and perils emerging in a data rich, globally connected society.

Armed with smart watches, home internet appliances, and an endless supply of apps, games, and streaming services. Billions of us now spend our days and nights enmeshed in webs of digital sensors, machine learning algorithms, and overlapping information networks, all designed to reduce the minutiae of our lives into discrete data points.

These data are then transmitted, stored, and analyzed for the purposes of predicting, evaluating, and influencing our behaviors in a never ending feedback. While these new data systems have likely improved our lives in countless ways, they've also presented us with a host of new conflicts and conundrums that we still lack the ability or even a conceptual language to resolve.

How can a my heritage user be expected to anticipate the risk? They, they may become a genetic informant on a distant unknown relative simply by submitting their own DNA to explore their family tree. How can a judge issue a warrant? Allowing police to investigate an individual suspect in a database for a specific crime without exposing all of the other people listed in the database to unwarranted surveillance.

How can a technology user confidently wear a smartwatch or install a health tracking app when a future court decision might turn their digital medical records into evidence against them? These are just a few of the many analogous challenges we explore in this book, though they encompass a broad range of settings, context, technologies, and cultures.

What unites them is a phenomenon that we refer to as the secret life of data. The basic premise is simple, though its implications are complex. There is no limit to the amount and variety of data and ultimately knowledge that may be produced from an object, event, or interaction, given enough time, distance, and computational power.

Even plainer language. It means that whatever we think we're shared, when we upload a selfie, write an email shop online, stream a video, look up driving directions, track our sleep, like a post, write a book, or spit into a test tube. That's only the tip of the proverbial iceberg. Both the artifacts we produce intentionally.

The data traces we leave in our wake as we go about our daily lives can and likely will be recorded, archived, analyzed, combined, and cross-referenced with other data and used to generate new forms of knowledge without our awareness or consent. This may be done not just once, but over and over by individuals and institutions we've never even heard of.

Using techniques that might not have been invented yet as technology and society continue to co-evolve over time. All of this adds up to something greater than the sum of its parts. Billions of us now live in a globally networked world, and our social structures and our personal relationships reflect this fact in innumerable ways.

This means every time any of us creates or collects a piece of data, even through casual interactions with everyday technologies, we have a responsibility to consider how the information derived from it might affect our friends, our colleagues, our compatriots, and billions of people we've never even met.

To borrow a phrase from a popular 20th century bumper sticker, we need to think globally whenever we act locally. 

[00:14:40] Laura DeNardis: Thank you so much. Yeah, it's a great way to start the book and so much comes up in this, but isn't the problem sometimes not that data is. Found, but that data is lost, you know, which is why internet archive is such force for moral good in the world.

Maybe someone is thinking, well, I cannot get to my thesis, which is on a punch card or a magnetic tape, or, I can't access something like a website that I used to be able to access or my data on Friendster or some old social media. Platform, or they might be concerned about the resurgence of proprietary formats that impede interoperability or have a loved one that passed away, and they can't easily access the letters that are in their locked up in their emails.

So how does the secret life of data also include that opposite and that opposite side of the coin of data being lost rather than found? 

[00:15:35] Jesse Gilbert: That's a great question and I'm glad we're addressing this. First and foremost, we're not saying that everything that's ever captured by a sensor or stored in a database becomes instantly available to everyone for all time.

We're saying there's no way to predict what will and won't be, and secondarily How the data that does get preserved and does get unearthed might be used in unexpected waves. So for instance, you know, there were papyrus scrolls that were burned when Mount Vesuvius erupted in Pompeii thousands of years ago, and those scrolls are now being scanned using these new AI assisted forensic techniques.

And new poetry that people have not known about for millennia is now entering into the public domain and interpersonal letters. Inscribed with CUNY Formm on clay, tablets are being dug up and reinterpreted and scanned with high powered forensic equipment. So you might not be able to recover your Friendster profile today, but that doesn't mean that somebody 50 years or 500 years from now won't be able to recover your Friendster profile.

And who knows what kinds of intelligence may be derived once they do. 

[00:16:42] Laura DeNardis: Fortunately, I never had a Friendster profile, so I should be good. But I was in, did climb Mountain Vesuvius recently and toured Pompei, so that's a very, very interesting example. Now, Chris started with a discussion and you also picked up on this of 

How we all share so much information, but what's really clear in your book is about how people who have never who, who don't share, they're not on social media or they don't, you know, promiscuously share information about themselves in other ways, but they're still affected by buying groceries or doing, carrying on other everyday activities.

Would you mind sharing a little bit about that? 

[00:17:19] Aram Sinnreich: Sure. I, I mean, I think it's an important point and one that we address in the book, which is really to say that, There isn't an opt out at this point for this process. We have to acknowledge a couple of things that are sort of precursors or presuppositions to the argument.

One is that we are all carrying, you know. Many computers around with us, many of us are, we are tracked via that for our location, for our interactions, for our purchases, for our likes and dislikes. And we are also surrounded by what we would call ambient computing, right? where we have CCTV camera feeds, we have visual tracking databases, we have.

All number of ambient devices that are actually recording and moving with us through our daily lives that are producing data out of the past that we take and the, the decisions that we're making. And I think that the bigger picture that is also raised in the introduction is that not only are the data that we produce being mined.

The information being pulled from that, but they're being correlated with others. They're being correlated with other people's movements. With other people's decisions, and that correlation is something which is in highly valuable from, a business case. But I think that it's also, it raises the questions, as we said in the text of how do you, you know, wrap your head around the implications of your decisions when this actually has much broader implications for even people that you don't know or that may have passed through the same space, or may have similar politics or, you know, buying habits or medical conditions that you do.

These are all questions that I think we have to ponder as we, we think about what has been created. 

[00:19:01] Laura DeNardis: Absolutely. And the stakes for privacy are so clear in the book, but there are other societal issues at stake that you raise in the book, and I was wondering if you could pick one of those and share it 

[00:19:13] Jesse Gilbert: Well, you know, we think of that in terms of scalar. So the secret life of data, because we live in this, as Jesse said, this kind of environment of ambient computing and, and ubiquitous networks. It affects our lives from the biological to the global. So we interview disability rights activists in the book who talk about how their insulin smart pumps change their relationship to their bodies.

And we talk to experts about the way that social media. Inserts itself into our interpersonal relationships such that we're always have kind of one eye on the likes while we're doing the business of liking one another. And it affects the institutions that we work for, whether our place of business or our schools, by inserting quantifiable metrics into the process of teaching and learning and reaching our productivity goals and self-actualizing our careers.

And it affects our democracies, you know, at the national level by deifying the process. Choosing our leaders and interacting with our elected officials and the people entrusted with the infrastructure of our society. And it affects our relationship to the environment at large. And there are these like global sensor nets that citizen scientists and professional scientists are using to keep track of ocean acidity and forest health and extraterrestrial objects passing through our solar system.

And all of these different scales are being fed into. Databases that correlate with one another and build these incredibly complex images of the world that we are interacting with on our daily basis. 

[00:20:49] Laura DeNardis: Excellent. Now. People may not know something personal about the two of you that I know. And that's that I think you met on the first day of ninth grade.

Is that right? In a New York City school for Science and Technology, and then you both came of age during the.com boom when there was a tremendous amount of excitement about technology and the internet in particular. I was wondering if one or both of you would tell us what has surprised you the most about how technology has evolved?

And I think people would love to know also, how did you embark on this book together? 

[00:21:24] Aram Sinnreich: So, yes, uh, we met at Stuyvesant High School in, uh, 1986, and we've been really engaged in this conversation in one form or another since that time. Obviously, we couldn't have predicted the, you know, development and the proliferation of global information networks at that time, but we did live through the birth of the internet, and both of us have made careers in one way or another, in relationship to that development.

I think that in response to the question of. What has been surprising? So there are a couple of things. I'll cover one of them, which I think, you know, as Aaron kind of alluded to, we interviewed dozens of experts that we brought through the process and really tried to get inside the way that they think about their discipline, their medium, and how they frame some of the problems.

And we. Decided at the a certain point to have a kind of, you know, rough script of that interview, where at the end of it we asked all of our experts to put themselves in the position of being a supervi and thinking about what it was that you know, they would do with the knowledge they had in order to affect maximum harm.

Which is probably not a typical interview question, and what we found was that actually a surprising majority of the people that we asked responded effectively with the response. I have never thought about that, or I'm not sure if I'm really, you know, that's not part of my. Disciplinary thought process.

And I think that after a certain point in our, you know, interview cycle, we kind of turned to each other and said, this is a finding. This is more than just a simple observation. This is, this is something which reflects some of the sort of, you know, utopianism, the optimism that is embedded within the tech.

Universe that we're really not considering some of the potential downsides. We're not putting ourselves in that position to think about what could be done with what has been created. And I think that although obviously we don't only reflect all of those negative use cases in the book, we try to balance it between some of the promises and the perils.

It was pretty surprising and significant that that was not top of mind for many of our experts. 

[00:23:41] Jesse Gilbert: A corollary surprise was that, you know, we talked to people across a really broad range of expertise and disciplines. So we talked to people who run data companies, we talked to anthropologists, we talked to artists, to attorneys and civil rights advocates.

And what was dismaying is that none of these people were speaking the same language. So. All of the, all of them were approaching the challenges that we described in the book from one angle or another, but they're so siloed in terms of both their purview and their framework of analysis that there's very little hope for any dialogue between those silos.

And that means that if we want to have the large enough conversation that we can invite everyday people whose lives. Profoundly impacted by technology into the discussion about whether and how to proceed with further data flying our society. If we can't even get the experts to talk to one another, what hope do we have to get every everyday people to be part of that conversation as well?

And that's really what the book is for, is to kind of take one step down that line towards opening up that conversation. 

[00:24:45] Laura DeNardis: The rise of artificial intelligence. I wanna ask you a little bit about that in reference to the secret life of data. This is certainly something that existed and was diff, you know, diffused into everything before you started the book.

But there's something about the sudden surge in generative AI that. Is raising some of those questions that you just raised, that we don't have a common vocabulary. There's a moral panic there. Intellectual property is a huge issue around this authorship. How does that relate? How does generative AI fit into the secret life of data?

[00:25:19] Jesse Gilbert: It's kind of like asking like, how does electricity fit into the process of building a society? Generative AI has so many potential applications that there's no, like any hot take that you hear about it, it's gonna be garbage 'cause it's gonna be ignoring 99% of those applications. So you mentioned intellectual property.

Obviously there are a bunch of lawsuits right now with plaintiffs like the New York Times suing Open AI for using their articles without permission or payments as part of the machine learning dataset. And you know, as a scholar of copyright and intellectual property, I don't actually know what to think of this because there's very persuasive case law that says that, well, there's a thing called fair use.

And if Google has fair use to show snippets on Google Books, then. Open AI should have fair use to not show snippets, but just kinda use them to inform a chatbot. But on the other hand, there's this massive transfer of wealth where the people who generated all of this valuable cultural information aren't being paid for it.

And these, you know, hyper evaluated AI companies are just stocking up billions and billions and billions of dollars of valuation and potentially making very lucrative contracts to use that tech and not. Paying any of it back. So that's like one tiny sliver. But you know, generative AI also has these.

Kind of second order consequences in terms of the role that they play in our civil society, which maybe Jesse can speak to. 

[00:26:43] Aram Sinnreich: Yeah, I think that's part of the challenge of the book, right? We're trying to talk about tangible, everyday use cases and then shift the focus a little bit to what can come. We're actually seeing that, if you think about the power of generative AI combined with the desire to misinform the public, that is a very put.

Potent combination where you know, the, obviously there are many, you know, benign use cases of generative ai, but we can point to this and look at that. Then tied to, for example, our current election cycle where we're seeing images being generated that are, you know, effectively not only falsifying, you know, the bonafides of a given candidate, but actually also serving to muddy the waters about.

Where the truth actually lies. And I think that is something which is a very interesting longer term, second order type of effect that generative AI can have. Because I think that once we've undermined the idea. That an image or a video has a kind of inherent truth to it, right? And that we can do that at scale and produce these images with complete dexterity and make them incredibly, you know, realistic and lifelike.

I think that it really is a slippery slope for us as a society of, you know, how do we. Relate to how do we talk to the public about how to have skepticism about images? How do we as individual citizens navigate this media landscape where the truth itself is being undermined through these practices?

[00:28:15] Laura DeNardis: It's really amazing if, if someone hasn't had a chance to read the book yet, and what you'll notice, and I say this for any academics that might be here, the conceptual framework that you develop is so important and such a unifying theory for so many different things that are happening right now, and the diversity of topics and cases that you go through that fit within that are so important here, you get into biometric.

Identification, the internet of things, ai, how all apps are Trojan horses. It all fits in here. The thing that doesn't fit as much with the others in my mind, but perfectly fits in the conceptual framework and really stands out, is genetic information. And I was wondering if you could talk a little bit about some of the moral issues around genealogy data.

You know, just tell us a little bit about the moral considerations and if there's something that you wanna say to people about what they can or can't do. 

[00:29:10] Jesse Gilbert: Sure. It's actually really well captured in the contrast between the, the story we told and the introduction about that Joseph James DeAngelo, the Golden State Killer, and another case that we profiled in the book, which is about a graduate student who found out that she has a sibling.

That she never knew about her father before she was born had fathered a child. The mother didn't inform him and moved out of town and cut off all relations, and it was only because the daughter whom we interviewed, uploaded some information to one of these genetic databases that she found out she had the sibling.

Now, the father himself had not. So he was put into this no-win situation where he had never consented to be genealogically profiled, but all of a sudden he was confronted and he was a deeply religious person who has very strong, uh, spiritual feelings about out of wedlock, childbirth. And he was just informed out of nowhere that he had done precisely that thing 30, 40 years.

Prior. And so the, our interviewee, the, the young woman who found out that she had a sibling, went through a really interesting process of grappling with that ethically. Like at first she was kind of overjoyed to find out that she had a new family member and there was love in her heart. And then she felt kind of bad for her father for being confronted with this moral and ethical dilemma.

And then she felt really proud and happy for her. Brother who was able to track his birth parents through this genetic database. So there's not, it's not like there's a good guy and a bad guy, or like a good side and a bad side. We are presented with these conflicting visions of the good. Through our Inable connection, through these databases, and we don't have a conceptual language to reconcile.

How do we weigh one person's good against another person's risk or cost? And as it turns out, what Jesse and I realized as we were working on the book is that it's a very clear case when it comes to genetic information. But the same thing applies to all data because all datas have the same kinds of familial relationships and networks.

So when we reveal. By taking a photo on our iPhone, there's exif data that shows exactly the GPS coordinates in it. And there might be a passerby in the photo who did not consent to being photographed. But now once we upload it to a social media platform, anybody who's looking can do a facial recognition and identified that this person was in this place at that time.

And so the sense of obligation to think about what the secret life of our data might be. Is clearest when it comes to the genetic information, but is really a theme that runs through the whole book. 

[00:31:57] Aram Sinnreich: And just to add briefly to that, to build on the photograph example a little, we're at this point in the society where we have to make some collective decisions about our, you know, shared ethics around this.

So, for example, we know now that all of the photographs that have been posted to social media sites for many years have been fed through a missing children's database. Not with our informed consent, we, it's just something that the company's decided to do, so that if a missing child is photographed in the background of an image that's uploaded, that they can be identified and potentially found, and we might then.

As a society say, well, that is a valid use of facial recognition, or the type of, you know, aging algorithms that would say, what would this child look like, you know, 10 years after they went missing because we think that we're addressing a potential societal harm there, but. It is an ethical, legal gray area.

I think as to whether or not those companies had an obligation to inform us, we might give them the pass on this one, but where does that line exist with any number of other decisions that are being made about the data that we upload, that that's a, you know, a dramatic example of one where we might say, we're okay with this invasion of our privacy, but what others are there that we might not be.

[00:33:15] Jesse Gilbert: Well, then there's like the third order consequence, right, which is, so they build the infrastructure both technologically and institutionally to scan social media photos for missing children and to age them up so that they can identify what they might look like today. And then those same technologies are sold into law enforcement agencies.

Which create based on genetic evidence left behind at a scene, a projected phenotype profile of what a suspect in a crime might look like. And then they apply that profile to facial recognition algorithms and scan historical footage of public events. And you know, that's another step down the slippery slope that couldn't have existed without the kind of legitimized usage in the public interest that Jesse just described, but that a lot of us would feel a lot ickier about, especially as.

You know, things that we previously thought of as moral and legal and ethical, like say safe and legal abortions become outlawed and potentially cause for criminal prosecution. 

[00:34:15] Laura DeNardis: Absolutely this gray, this ethical gray area that you describe is not only external and about our relationships with society and law enforcement and each other, there's also an internal, a deeply intimate and internal concept that you raise in the book about how we see ourselves differently through the devices that we use and the data.

And you came up with this really interesting name for it, algo vision. Can you tell us what you mean by algo vision? 

[00:34:46] Aram Sinnreich: I think that the term really is reflecting the idea that, you know, we have begun to articulate a language, as Aaron mentioned earlier, of doing it for the likes, right? Understanding how we're going to be viewed in the eyes of an algorithm, and then incorporating that into our own self-conception.

And I think that this has, you know, again, we're on a knife edge with this because there are behaviors that you could say we're optimizing our lives or. Whether we have a a fitness tracker or we're thinking about a social media presence, there is a level of participation that, you know, we could say is healthy.

That is encouraging. But then we've also seen, for example, the pressure. If you think about the popularity of plastic surgery in relationship to our ubiquitous presence on streaming conferencing platforms such as this, that there's actually a significant finding that many plastic surgeons have reported that their incoming patients are actually requesting plastic surgery because they don't like the way they look on these.

Type of platforms, and I think that we need to, again, I, I think we're just repeating sort of some of the same rhetoric here, that we need to think as a society as to what are those healthy boundaries and lines. We live in a world where we, we've also, you know, anthropomorphized algorithms, right? Whether it's.

You know, Siri and Alexa. But now even just the idea of communicating with an algorithm or thinking of it as a presence that you have to modify, you know, gaming the algorithm. This is something, you know, I've been programming for a long time. I've been in this industry for many, many decades by now. I don't think that those of us who are involved in the early stages of computer culture.

Could have anticipated that this would be part of our, you know, shared language and dialogue. This is far scaled beyond what I think we could have anticipated. 

[00:36:43] Jesse Gilbert: Even science fiction images of the role of artificial technology in, uh, artificial intelligence in the future. Like didn't account for that, right?

Like. In 2001, Dave doesn't get awkward around hell's ubiquitous eye, right? He just kind of goes about his business, picks his nose, eats his food, you know, washes his socks. And even in that forward thinking vision of the role of AI as a ubiquitous presence in human culture, it doesn't include the feedback loop between the human kind of self.

Conception and the way that we see ourselves refractive through the lens of these systems. But I also want to like Les, we sound too dooming bloom. Jesse and I throughout the book, take great effort not just to kind of ring our hands and raise the alarm, but talk about the benefits of some of these technologies and the ways in which the unexpected uses of them can actually confer positive social effects.

So Avision is a great example. Because there are all kinds of ways in which people's alga visual capacities, their ability to think about how they're gonna be seen through the eyes of the algorithm, actually builds political power and cultural power and increases people's sense of self-efficacy. So one example, for instance, is there was a great app called Uber Cheats.

As it turns out, you know, the Rideshare Company, Uber was cheating drivers by kind of like lying about what the distance from their source to their origin was. And somebody developed an app called Uber Cheats that allowed drivers to kind of compare their actual trip on a map. To the Uber's algorithms version of what was on their map and see exactly how much they were being shortchanged.

And that was put out for free and downloaded, you know, thousands or more times. And it's this kind of communal resistance to the algorithmic gaze that can only happen through internalizing that gaze that makes Avision into both a vulnerability but also kind of a super palette. And we take great pains to show both sides of that coin in the book.

[00:38:37] Laura DeNardis: Think you do. And why don't we invite Dave in. 

[00:38:39] Dave Hansen: Yeah. Thank you both. This was a phenomenal conversation. We are getting close to the end. I wanna turn to Laura. Thank you so much for moderating this conversation. If you have any last concluding thoughts, or questions, I'd like to invite you to go ahead.

[00:38:53] Laura DeNardis: I wanna end by congratulating Aram and Jesse for this incredible contribution that is not only a major academic and scholarly contribution, but also one that is very accessible and I think it's gonna be widely read, including by policymakers, so it's extremely accessible and the end on a positive note in their chapter on data and democracy.

And I will just leave it at that. To entice people to read it, but I appreciate their raising critical issues, but also giving us some hope in an environment where people seem to be on this wild pendulum swing between dystopian and utopian views of technology and society. So thank you for that and for all of the many accessible things in the book and ways that we can change and be part of the change and congratulations. 

[00:39:44] Chris Freeland: A big thank you to our authors, Aram and Jesse, for writing the book, for putting such an interesting content together and joining us for the conversation today, and really helping us understand, you know, the reality of what happens in our networked world and the data that we're consciously or unconsciously sprinkling around.

Thanks also to all Laura for facilitating this conversation and to Dave Hansen and to Authors Alliance for co-hosting our session today. Thank you all. Have a great day.

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