Engelberg Center Live!


Episode Summary

On today's episode, Engelberg Center Fellow and CUNY Law Professor Sarah Lamdan discusses her new book Data Cartels with MarketWatch Enterprise Reporter Shoshana Wodinsky. It was recorded on November 10, 2022.

Episode Transcription

Announcer  0:02  

Welcome to Engelberg Center Live!, a collection of audio from events held by the Engelberg Center on Innovation Law and Policy at NYU Law.


On today's episode, Engelberg Center Fellow and CUNY Law Professor Sarah Lamdan discusses her new book Data Cartels with MarketWatch enterprise reporter Shoshana Wodinsky. It was recorded on November 10, 2022.


Sarah Lamdan  0:28  

So hi, everyone, and thank you all so much for coming to this fun time book party. I have a few thank yous before I introduce Shoshana winsky, who I'm so excited, it's with us today. So first, I want to thank everyone at the engelberg center on innovation Law and Policy at NYU School of Law right here for putting on our for putting the fun in fun time book party. I often say that data cartels are the friends I made along the way. And everybody in the angle verts is part of that sentiment, Michael and Katrina, thank you for creating such a vibrant community of scholars and practitioners. And also, thank you library futures. Now affiliated with engelberg for a being awesome and amazing, but be also making these relics don't do it shirts, it's a librarian in joke if you don't get it yet. After you read the book, you'll get it. However, if you want your own relics, don't do it shirt. Library futures is not only making these for the book launch, but it's also part of a fundraiser for library features and for library causes. So


yeah, find either me or Jenny afterwards, Jenny, and you can you can you too, and they're not really they're not really crop tops, my child. Yeah. Made that so that the real version is longer, though, you know? Yeah. And I, I also want to thank my home institution Sorenson Center for International Peace and Justice at CUNY School of Law. Yeah, CUNY. Yeah, Camille and Arpita. The work you do to make our school a hub of public interest in human rights activities, enriches all of our work. And you are awesome. So thank you. And I also want to thank all the students who work on topics and data cartels, including the intellectual property and entertainment law society here at the law school and writes over tech here at NYU. So thank you all.


And now I'm going to introduce Shauna. So when Michael and Camille and I started talking about this event, they asked me if I could choose anyone to be in conversation with who it would be. And that person I didn't even have to like pause it was Shoshana winsky. When I set out to learn about how Lexus worked, there wasn't a lot of information out there. Because Lexus IS contracts and work are notoriously opaque. And there aren't any transparency laws that can force the information about how they work into the public. So I depended on the work of a few journalists who were able to shine a light into the murky, weird world of data analytics companies. Shannon's work was critically important to this book and to everything that's come since. And her work provides clear detailed glimpses into how these companies operate. And most importantly, her writing also manages to be super entertaining and funny, it is hilarious, which makes it a joy to read because data analytics by themselves, this might be a shock. They're not very interesting. So yeah, making data analytics delightful is a major skill Joe Szanto possesses. So I'm thrilled to be here today with MarketWatch, investigative reporter Shoshana winsky. Her work explores ad tech and data use on major platforms from how tick tock rings its creators to Metis ad tech empire. She wants tracked a targeted but pajama ad to its creepy source, which is a great piece of journalism. I encourage you all to check out. So before Shoshana arrived at MarketWatch. She reported on platforms and privacy for Gizmodo, and she's also the mom to two adorable cats. And I'll briefly introduce myself my name is Sarah Landon. I am the mom to two adorable children and also two adorable dogs. One of the dogs is more adorable than the other but both my children are equally in an infinitely adorable. I'm also so I'm a longtime law librarian and a newer law professor at the City University of New York CUNY and I'm really excited to be here today to talk about data cartel.


Shoshana Wodinsky  4:37  

I'm really sorry, just one Oh, god. Is this this thing working? By the way, spoiler alert, if you're wondering where that sexy Buck pajama ad came from, it turns out it was China. Anyway. This is a great book y'all are in for a treat. I I just have to say, I read everything except the last chapter because I didn't want to be spoiled. And we're going to figure it out on stage tonight, your real time. So just to kind of kick things off, you know, I began privacy reporting kind of in the wake of Cambridge Analytica, that kind of happened late 2018. And in the years since we've seen privacy reporting, kind of, I don't want to say mutate, mutate a server on word, but it's changed shape. Now, we're not just talking about cops surveilling protesters, we're also talking about companies like like Rolex, and and the way that they kind of fit into things. So why did you want to? Why do you think things are changing? And why did you want to write this now, of all


Sarah Lamdan  5:51  

times? Well, there's no time like the present to talk about all the problems that Elsevier and LexisNexis bring into our information ecosystem. No, but really, like, it was it was kind of, I think we're all coming to a point like, I think the reason it's like, the idea of privacy. And how we think about privacy is mutating is because we're realizing I'm borrowing your word. It's, it's, it's morphing. At the same time, we're realizing how deep the problem goes, right? Like, it's easy to look at police surveillance be like, Oh, well, that's not the best. And we see some problems with that. But then when you start to trace the lines from police surveillance back to the companies that kind of supply the data and do all the work, that to make it possible, like fuel, the data, analytics, build the data analytics, you see that it's all kind of smoke and mirrors. And also, it is really problematic. And I don't think like the way I came to this was actually, I didn't, I didn't intentionally set out to write about relics. But organically figured out that relics was a problem. Should I tell them should I do this story? I feel like I do this story. Also. I was a librarian at CUNY School of Law, just doing my librarian things my desk had I was saying this earlier, like, like my desk had like Westlaw stress balls on it, you know, I had my Lexus tote. I was I was, you know, a librarian, like we all are, well, not all of us. But those of us who are librarians, we're all librarians. But, um, so yeah, I was, I was just doing my library and stuff. And some I don't remember how I found it. But there was an article about the companies vying to build ices extreme vetting program. So Donald Trump had just passed an executive order, I guess sometime before it passed an executive order or issued an executive order, sorry, that directed ice to start building like an a very intensive data surveillance program and infrastructure. And some reporters FoId a list of companies that attended their investor day. So an investor Day is a day basically, where companies interested in getting in on this work go in and they learn about how they can be involved, right, how they can make money and work with ice or whatever agency. So on the list of attendees in ISIS investor day for the extreme vetting program, there were representatives from both LexisNexis and Thomson Reuters. Thomson Reuters is the parent company for Westlaw. And here I am, like sitting in my office, just like with piles of printout of like Westlaw or Lexus cases, and my little stress balls and decoration, you know, my Westlaw rep, like sitting outside doing their office hours. And I was like, wait, wait a second. What exactly is what's not like? What are these companies doing with ice because this was also in 2017, when there was, ice was always in the news for, you know, kind of getting, getting a lot of attention for human rights violating activities. So I wanted to know, more, I guess. So I wrote an innocent blog post for the American Association of all libraries with the app and took our marker to I'm totally embarrassing right now. So I, we wrote a blog post, and we, we we didn't like it wasn't an offensive like, wasn't especially incendiary. It wasn't it was just like, hey, this seems weird. Should we like why librarians should we care about this? And they posted it on the American Association of law libraries blog. And within two minutes, the association took the blog post down and said, This is censored, like by the advice of counsel or something or at the best advice of counsel, and we were like, we are, this is the this has been removed. And I said, Wait, this is censorship. Like librarians are kind of censoring us right now, I guess. And I was so annoyed by that. I guess. Then I started digging to by myself to figure out exactly what was going on. And I started asking our Lexis and Westlaw reps like hey, what's going on? And they couldn't really explain to me what the what what these companies were doing with ice. So I started researching myself and reading work like Shawn does work. And I realized that yeah, this is the UK bad. Yeah, you can track the underwear ad to China, you can track LexisNexis to eye surveillance and Thomson Reuters Westlaw to I surveillance. And I also like in doing that, I also realized, because I didn't even know that LexisNexis was under the same corporate umbrella as Elsevier, like that wasn't even a thing that was common knowledge. I don't think at the time, so I decided that it was such a big topic. And we think they should write a book so that librarians and other you know, and people like you everybody would know about how this these two companies work. Wow.


Shoshana Wodinsky  10:50  

You know, I kind of joked earlier that like I it is kind of the story about like, how you got respects, is against the


Sarah Lamdan  10:59  

law librarian. Yeah. Because it's


Shoshana Wodinsky  11:01  

funny because like, you know, there's always people that are like, oh, like, why should I care about privacy? Why is it an issue and you present this really kind of strong case for like, right at the start of the book, you're like, I love to data analytics companies, I like use their product I had their stressful do you solve their struggles?


Sarah Lamdan  11:18  

No, I don't have any more guys. None. Okay, good.


Shoshana Wodinsky  11:23  

And then you learn this, like one fact about them. And suddenly, everything starts to unravel. And the more you pick it apart, it's just like, the more the more different it is, in suddenly, by the end, like at the end, you suddenly realize like, the companies that you've been dealing with for years are nothing like what you signed up to work with, which is typically what happens in the space. But, you know, I, I have to ask also, again, when we talk about these sorts of companies, companies like Facebook, Google, Twitter, Tiktok, those are tech companies. Relics is not a tech company, is it?


Sarah Lamdan  12:06  

Yeah, that's a really great question. So that was kind of one of the other things that really surprised me, because when I was a librarian, I thought of Elsevier and LexisNexis. As publishers, publisher, like when you walk into a law library, all the books on the shelves are web publication, or their LexisNexis. Bender, what have you, Elsevier, you think of journals. But what I learned really quickly, and honestly, this was one of the things that prompted me to write the book is, they both reframed themselves as data analytics companies, all of the publishers relics, and Thomson Reuters no longer call themselves publishers, and they've even change their like, market description of who they are from media service, aka publishing, to data products and business solutions, which is data analytics. So they're not even doing the same publishing business that they used to specialize in.


Shoshana Wodinsky  12:58  

So there's Seriously there's kind of like a straight line between Hey, we're a product that like we we partner with, like lawyers and librarians, and suddenly it's like, no, we mostly partner with banks. Now. It's, it's kind of a straight line. Absolutely.


Sarah Lamdan  13:11  

Yeah. I think I mean, I don't know, like what I observed as librarian, which I realized might be slanted, because I only have this one person perception is it was tough going for publishers, when things started becoming digitized. And we kind of went online, right? Like, we weren't buying to two copies of all of the, you know, constitution, like our sorry, all of the US Code. And we like weren't buying we used to buy all every law review bound and paper. We weren't doing that anymore, right. And we probably were also we're buying all the Elsevier journals, and paper, some. And so paper publishing their traditional business model, and their traditional business fair was suffering. But they realized that going that there were new markets and new opportunities in digital, I hated data analytic analytics, right? So they they went on like, exactly. And I think it was, I don't know if you see it this way. But I feel like it was this gradual move. So firstly, figured out how to make fun data platform. So or informational platforms like Westlaw and Lexus, where they're like, Oh, this is cool. You can link you can like link all the statutes inside this case, and then, you know, like, we hyperlinking is cool. And organizing data by database is cool. And it like it really did kind of morph, like it mutates mutated, they're like, Wait, we could also take this data and put it together this way. And that, like, turned into data analytic.


Shoshana Wodinsky  14:33  

Admittedly, I've got like cosmic horror stuff on the brain because I've been watching a bunch of movies lately, but we can talk about that later. So you're saying it's kind of like it's kind of like the the frog in a boiling pot of water thing. Like it didn't happen all at once. It was suddenly like they rolled out one platform and another platform and another and another and they suddenly realized, like, oh, everyone needs data. And there's some industries that are willing to pay a lot way more money than libraries are at And that, that's just, that's just kind of how it worked.


Sarah Lamdan  15:02  

Yeah. And it's interesting because I do, I think it was Amanda Levandowski. Like, was like librarians warned us or librarians tell us this would happen. She posted something like that earlier this week that I, I liked a lot. But we could have told you librarians noticed, like, maybe 15 years ago that our vendor relations started kind of going downhill, right? Like, vendors used to really cater to us and give us all sorts of like freebies, and really be like, they were with us, they had like special library relations vendors who weren't like our buddies, right. And that's really changed a lot of things that I initially thought some of it was like, because of 2008, there was a market crash, and they kind of changed their business model. But what I really do think happened is they realized, Oh, we can make a lot more money from like, ice and cops and insurance companies. And they just now it's like, I always describe it, like we used to be in the front of the line of people they cared about. Now we've been like, shuffled all the way to the back.


Shoshana Wodinsky  15:57  

What's funny is that you actually, you do see this in the advert because I covered the digital advertising industry, mostly. And like, you definitely see that to where you have these companies that were collected, like, with, like, offer apps analytics, so like app creators could like offer free apps to make money. And suddenly they realize, oh, wait, there's a ton of data here. And no real rules governing this. I'm gonna make a quick buck. And you know, to 2022 Here we are cops by this sort of data to like surveil people. So it is kind of funny how these two kind of disparate industries kind of met in the middle because money was


Sarah Lamdan  16:34  

that is where the new pot of money was start. Yeah. And


Shoshana Wodinsky  16:37  

like, you know, I was planning, I was planning on asking this later. But sometimes the data that they buy the data these companies collect, and they collect so much of it from so many different you don't really quick, where does relics get its data from relics that


Sarah Lamdan  16:53  

claims in Thomson Reuters both claim that they get their data from over 10,000 unique sources. There is no listing of those sources anywhere. You can't know.


Shoshana Wodinsky  17:02  

Have you tried asking really nice. We've tried to bring it bring your kids.


Sarah Lamdan  17:07  

We both tried asking really nice. And then also foiling all of the agencies that have contracts with Westlaw and or with LexisNexis and Thomson Reuters. And the only thing that we've learned from those FOIA requests about this part of the question is that not only will they not tell us, the LexisNexis puts non disclosure agreements into its contracts with ice that prohibit ice from even talking about how they work with LexisNexis, which I don't even think is like, according to Boyle laws, I don't understand even exactly how that works unless you're using like some sort of national security loophole or exemption. But yeah, they they are not only are they not allowed to tell us what the 10,000 sources are, they aren't even allowed to say that they do work with LexisNexis. Okay.


Shoshana Wodinsky  17:59  

Now, I know what you're all thinking in the audience here, you're probably thinking, oh, there's 10,000 different sources of data. They have a ton of data on me, my parents might grandmas neighbors friend, that data is probably going to be super accurate, because there's so much of it.


Sarah Lamdan  18:15  

Yes. You know that a firehose of unvetted data is always super accurate. Yeah, no, and I so the actually the story about how LexisNexis and Thomson Reuters got into this business, I feel like it's telling and interesting. There's actually another reporter named Mackenzie funk, who's writing a whole book. Yeah, he's writing a whole book about Hank Asher. Cool, okay, Hank, Asher is the grandfather of data fusion. And he was basically this guy who's like a reformed drug smuggler. Like he, we've all been there. Yeah, he used to he, like, flew helicopter, he had a very exciting like, movie, five movie style lifestyle. And then he got cut. And he started working with the government. And then he realized that he could buy people's data from like DMVs. And from other kinds of public offices for pretty cheap like it was he saw it as like, untapped real estate. Like, there's all this data out there that these government offices are collecting about us. And you just buy it, like for a few 100 bucks, you can just get it. So he started buying it. And then he also figured out how to connect together databases, and how to fuse the data, and then how to kind of do like the first data analytics operation, he would connect a bunch of servers together and like, figure out how to mix and match the data to make to pull up new data and to make readily identifiable data. And this he he created a program his he and everybody who does I don't know if you feel this too, but everybody who does government data surveillance work always says it's because of human trafficking. Yeah, that they're trying to protect children and prevent so his quest To protect children involve collecting, buying all of our data from government offices that he could get and running these systems and he would sell these databases to police that would help like it only if you have a part of somebody's name or part of social security or somebody's social security number, or only if you have their license plate number, you could kind of mix and match that data and it would pull up the person's name, right. And that was very helpful to law enforcement. So he started making money off of that. And then after 911, the White House was desperate to figure out a way to surveil Muslim communities right and to figure out, you know, how to track people. So they invited him to the White House, and I believe they offered him like $8 million for his services. And then shortly after that, I feel like within the same few years, he sold the entire operation to LexisNexis. And then when he did that, the FTC intervened and said, Yo, you this will make you a monopoly. For I think they call it like government records, data services or something, some market that they they made up the name for, and they forced LexisNexis to divest some of their product to the product was called choice point. So they forced LexisNexis to divest some of choice point two. To Thomson Reuters, the part of choice point that they force Thomson Reuters to divest is called clear today, Thomson Reuters surveillance products are called clear. It's the same it all is sourced from Hank Asher's choice point which then was purchased by LexisNexis and shared with Thomson Reuters and it set them up to be a duopoly.


Shoshana Wodinsky  21:37  

That's how do all police work. That was a fun little lesson. I do like I do like that this guy went from being kind of like a professional drug smuggler to being in charge of government records, data services. Yeah,


Sarah Lamdan  21:48  

it's quite quite the transformation. You got really enterprising. Like I think that's probably what I that's why I wanted to get


Shoshana Wodinsky  21:56  

entrepreneur much like drug smugglers. Yes, yeah. To business. But, but enough about drugs. I do want to talk to you kind of about, you know, when we talk about records, when we talk about data, your book makes a very clear distinction. And the subtitle is the these companies like the companies that control and monopolize our information, not data. So what's the difference?


Sarah Lamdan  22:22  

Yeah, so it was that was the first kind of needle I had to thread because information is different than data. raw data is unstructured. So raw data is like Shoshana, Serra de Augustino. Hall, right? Just little bits, kind of I think of them as like a femoral like pieces of dust just floating in the air. And information is structured, right information. If you take that data, and you say, hey, Shoshana and Sarah are going to have a conversation to D'Agostino Hall at NYU, right? That that is information that conveys a message and it takes all the pieces of data puts them in order, right? So these companies, they they are cross market monopolist, they have tons of informational troves, right, they have the biggest academic journals in the world, they have all the Elsevier journals, they have the entire corpus of US law, right? They have nexus Lexus Nexus is one of the largest news archives in the world. And it's updated regularly. So they have all the news. And that's all information, right? Somebody had to put all that stuff together, they also have kind of I wrote a chapter about financial information, because that's semi structured, they have all of the they have, like all the things that Edgar filings have. And they can strip that information down to points of data about corporations and what corporations are doing. And they can use that to make market predictions, etc. So they also have kind of Bloomberg like services that deal with financial information. So I we call, we've started calling it double dipping, they can first make money by selling data, right, by being data cartels and selling


Shoshana Wodinsky  24:01  

alternative data in the field. I want sold to banks. Yeah. And now


Sarah Lamdan  24:05  

that what did they call data, lakes, data lakes, a bill of alternative data? We're gonna be here all night anyway, just, yeah. So these data lakes, but then they also have these huge troves of information assets. Right. So they have Kate They have Westlaw and Lexus. They have Elsevier and they have all this financial information. And they have all this news information. So they can sell the raw data, they can sell the structured data, they can tell platforms that kind of organize the information or structure data. And then they can also break these informational resources to the science journals, the the legal, you know, the legal documents, and the financial information in the news, they can break that down to data too, right? They can break it up into pieces who authored this paper. What is the topic of this paper? What is this new news article about whose names are in this news? Right? And they can break that down and kind of strip it back down today. EDA, you know, strip, strip the information for parts and make new informational products like academic metrics that tell you who's whose academic research is going to be the most important and most lucrative, right? They are making now predictive legal products that predict if you go before certain judge, what are they going to think of this argument, right, and they will even model language for your filings. Now you have to be wealthy enough to be able to afford these litigation analytics products, but now you can kind of game the law with their data products.


Shoshana Wodinsky  25:30  

That just reminds me of like, the last story I did for Gizmodo was right after the kind of dogs stuff happened. And it was about live ramp, which is this commercial data broker that doesn't work doesn't typically work with banks or with libraries, it typically works with like brands and advertisers. And I found that through its own massive platform, you had about two dozen companies selling data that they said was from pregnant people. And when we include like, the number of like, hey, this company is selling this many pregnant people, this can be something that and when we tallied it up, I think my editor was just like, this stopper was like, literally, like two thirds of the people on earth. That can't be right. Exactly, because, and eventually, like later on, I have I talked to some guy that was working in this industry later. And he's like, oh, you know what they probably did, they probably just took like, women that we're seeing here. And people that bought like, this specific type of Vitamin here, and they just mash that together and put a new name on it. Because in the kind of retail industry, they don't, it doesn't really matter. A certain amount of like advertising spend always kind of like vanishes into thin air anyway. But I also feel like you know, we're also seeing that with cops, which is kind of terrible.


Sarah Lamdan  26:45  

Definitely. So I do I make this distinction. And I actually thought of you when I made the distinction because I know, well, you're like, so good. I've


Shoshana Wodinsky  26:52  

never heard it expressed like this before. You're like


Sarah Lamdan  26:54  

my ad tech expert, you make it. But ads. So ad tech, is that we don't want to be creeped on when we're shopping. We don't want to be weird.


Shoshana Wodinsky  27:02  

Don't you want to see targeted ads?


Sarah Lamdan  27:04  

I want to see my butt clap pajamas. If I'm in the right category. Don't you


Shoshana Wodinsky  27:08  

want those nights in your Instagram feed?


Sarah Lamdan  27:10  

Don't you want that creepy sensation where after you like read something about Hawaii, all of a sudden your computer is trying to sell you trips to Hawaii. I mean, sometimes it's helpful like more like this everybody not I don't want to be universal or generalized. But a lot of people like the more like this option, right? Oh, I liked this book a lot. I might also like this book, right there, I get it. I get I get why it's caught on


Shoshana Wodinsky  27:31  

it. And ad supported services. Do you keep the intranet? Well, they keep most of the intranet free. They are the reason that I got my job, my old job where I got to write that privacy story. And then people were in the comments saying, like you're writing about how targeted advertising is bad. But your story is littered with targeted ads. Are you a hypocrite? And I was just like abusive systems. People at the end of the pipeline don't really have power over them yada, yada. And that is an argument that I've been having for basically since I started my career anyway.


Sarah Lamdan  28:01  

Yeah. This whole world. This is a whole other and you should listen. Sean has done a bunch of interviews and like podcasts and other things where she really you dig into the ad tech world. But so the thing about relat remember, relics and Thomson Reuters. They're not ad tech. They're like Risk Services.


Shoshana Wodinsky  28:20  

Yeah, so that's like that. Yeah, that's like banks, libraries, law schools,


Sarah Lamdan  28:25  

insurance companies, care systems. Basically, they're not


Shoshana Wodinsky  28:29  

like Experian, which is like a credit.


Sarah Lamdan  28:33  

What? Yeah. And so they get to say, even though they do the same work that our credit,


Shoshana Wodinsky  28:38  

a credit broke, like a credit credit broker credit it. I don't know, I always just call Experian that company. Yeah.


Sarah Lamdan  28:45  

So they're not they've separated themselves. They've distinguished themselves from those companies, because those companies are subject to certain disclosure laws and limitations. And LexisNexis and Thomson Reuters have magically managed to create the illusion that they're very different than those companies. So they can they don't even have like the it's so well. Yeah, like they're not even subject to the Fair Credit Reporting Act. I think that's the I know, it's FCRA I think that's it. I'm very bad at FERC students know that. She right. Am I around? Look at me getting that that acronym right. On the spot prepared. I can do it. But yeah, so they're not even subject to those laws, because they've they've managed to skirt them by avoiding like being labeled as the kind of company that makes a credit. Credit Bureau. Yeah, that's, yeah, they've managed to avoid being labeled a credit bureau, even though they do the exact same work that credit bureaus do. And they've also managed to skirt Fourth Amendment laws by our fourth amendment obligations by being third parties that can just slide into third party exception for warrant requirements. And they really they're the slippery companies that by magically Bing Bing publishers when it's convenient being information companies when it's convenient, they can also be data brokers that skirt the rules that some data brokers are required to follow.


Shoshana Wodinsky  30:10  

If you want to explain to your kids sitting in the audience right now, what the phrase information company means is Do you think you could?


Sarah Lamdan  30:17  

That's really, I don't know. And I and sometimes I even called like, sometimes I call information content, because I know that what people understand that it's content, you know, the


Shoshana Wodinsky  30:28  

kids understand that


Sarah Lamdan  30:28  

more. Exactly. Right. It is like, because there are people who make content and there Yeah, right.


Shoshana Wodinsky  30:34  

Exactly. And then you can be like, Okay, well, there's content analytics, and then you go into it, then you watch the light kind of fade from their


Sarah Lamdan  30:40  

eyes. Well, that's why your reporting is important that


Shoshana Wodinsky  30:45  

everything is content, you sitting there, your content, I'm sorry, it's it's kind of by virtue of being alive.


Sarah Lamdan  30:53  

But there's no content creator, by virtue of being live, whether you do it on purpose or not. Yeah,


Shoshana Wodinsky  30:57  

exactly. But your your book is not about that these companies are very, very much not in the business of content, or influencing or advertising or anything like that. They're in the business of offering data or offering, you know, they're in the data. They're, you're in the business of predicting, what they do is predicting.


Sarah Lamdan  31:15  

That's exactly they're in the business of predictive analytics. And also I call it risk ranking. They sell their product they call their products. So all of these products give themselves like vague Gazi phrase names that really hide what they do. So they call themselves business solutions. They call themselves Risk Services. What's a business solution? Exactly? What is it? What is a business solution? They're solving your business for you?


Shoshana Wodinsky  31:37  

Is that like, HR, like, your HR department?


Sarah Lamdan  31:41  

Exactly. Right? The the, you don't really know what they do. And I think when somebody says, business, oh, Relex is a business solutions company. It does exactly what you want it to do your eyes glaze over, and you're like, oh, cool, and then you just move on, right? But if they told you what they were really doing, that would be such awful PR, that they would never say, Oh, well, what we do is we scrape and collect tons and tons of your data, run it through these, these analytic systems that we build these algorithms that we build. And then we sell, we sell information about how risky you are to insurance companies. So we rank you by how likely you are to commit fraud, or to commit a crime or to default on a loan or to use opioids. That's one. So we have made all these magic predictive systems that predict all of these different things. And then we sell that information about you to your insurer, your doctor, your landlord, your employer, anyone who wants to buy it, which is so comforting. That's a lot.


Shoshana Wodinsky  32:44  

Oh, much. That's a lot. That's a lot. I I honestly got a sight. But like you mentioned like, I think I think you mentioned in the books that like these companies, sometimes cops or landlords or employers know what the data that they're buying is compiled from a ton of disparate sources. That might not be actually correct. I think he mentioned like a cop that had some sort of access to Lexus for a little while. And then they found out that they were like, marking people as like, they should be sent to prison, even though they'd already served jail time, or like they were acquitted or something like that. And the cop was just like, I can't wait to get access


Sarah Lamdan  33:26  

to like, get my Lexus lumen back the story. I told them yeah, like, it's like, what? What is wrong? Yeah. Oh, yeah, I don't I that. Yeah. A lot of questions. Yeah,


Shoshana Wodinsky  33:42  

exactly. But like, what what do you think? What do you think it is? Do you think they're just do you think? Do you think that not only just institutions of power, so police, major brands, people with the capital to kind of afford these sorts of things? Do you think they've gotten used to having access to them? And they've just kind of accepted the same way advertisers have that like, Okay, sure. This product, like might mark a few people as like, at risk for opioids, even though like they aren't, but I'll just like, take that risk.


Sarah Lamdan  34:09  

Yeah. And well, I think so one thing we talked about a lot in administrative law for any new I have, who are in my class, is we talk about kind of the focus and the government's willing, um, and every institution's willingness to strive for efficiency, right? Bureaucratic administrative efficiency. We want systems that are fast, that are affordable, more affordable than hiring actual humans to do this work and dig through these piles of information and that are efficient and effective. And even when this information is, is erroneous or bias or totally messed up. It sure is fast. It sure is easy. So the product that you're talking about with the police, it was yeah, it was called LexisNexis lumen and it's still it's still it's called LexisNexis lumen. I don't want you to think this product went away. But I think what it did so what my understanding what it did is it has has like a huge database of jail booking photos. So when people are arrested and you take their photo, and then what it does is if you're on the street, if you're a law enforcement officer, you're on the street, you can take your phone, you can literally click a picture of someone, and then it will run that picture through the entire system just on your phone immediately, like when you're out in the field, and you can immediately be like, Oh, that person look has, you know, a bench warrant or has a criminal record? And a lot of so a lot of times when people are arrested, they actually didn't commit any crime. Right. So these jailbreaking photos are incorrect, erroneous, a lot of the time, right. So my book, one of the things that I realized in my book and researching for it is the world of data analytics is just littered of examples of how erroneous data and biased algorithms just like ruin people's lives. There. There's a story in my book, a guy from Texas couldn't get housing, because LexisNexis database listed him as an eviction risk, because there had been like, a bad like he he once had gone to housing court or something. And he had been marked as somebody who had been like, evicted, and he could not get housing because the landlord screening system that use Lexis data, Mark, Mark is a problem. There are people who have been locked out of their own banking accounts, because people with the same name as them have had their own banking problems, their names get mashed together in one file, and all of a sudden, a person who's completely separate from the other person can't get insurance access can't get into their own bank accounts. Yeah, it's


Shoshana Wodinsky  36:35  

well, sure, surely, the solution is just to collect more data and make the product more precise. Well, every fix for


Sarah Lamdan  36:41  

a technological problem is more attack. And we all know, this, which


Shoshana Wodinsky  36:45  

reminds me I was talking to somebody earlier this week about like, I used to live really close to a car dealership, and I would always like walk by it, like on my way to work. And I would always I don't have a driver's license, but I would always get car ads, because I was labeled as in market for a car because advertisers thought, Oh, you're walking by a dealership, obviously, you're in market for a Volvo. And now years later, I still get a lot of car ads. It will it will haunt me for the rest of my life just the same way. These products will haunt these people. But like, in my case, it's oh no a Volvo ad with them. It's they can't get a house.


Sarah Lamdan  37:19  

Yeah, exactly. That's so one thing I say about like, what that's my main differentiation between ad tech and what LexisNexis and read Elsevier or what Reed Elsevier, LexisNexis. And Thomson Reuters do what they do, can like, totally ruin your life in a way that advertisement probably won't.


Shoshana Wodinsky  37:36  

Although cops do buy advertising data, I just want to make that clear. Yeah, I also use it to bypass the form that maybe


Sarah Lamdan  37:41  

you have to think that with the 10,000 sources, that would be 1000. It's all the date all the data, there's no data set that's like left out of the 10,000 Plus sources that these companies get,


Shoshana Wodinsky  37:53  

I will just say this my first job, I was covering Palantir, you know, that company that we all know and love, because I had heard a rumor that they were kind of trying to work with advertisers, instead of cops. And I reached out to one major brand, and they were just like, they charged way too much money when we could just like go to like the data brokers we've been using since like, 1995. Like, what you should have seen some of these numbers, it's what they essentially is what they essentially said. And that just kind of gave me a picture because like, advertisers are used to spending like, hundreds of 1000s of dollars on like a single data product. And I I guess Palantir was asking for a government contract


Sarah Lamdan  38:31  

exactly that government contract money is where the where the like that that's where the money that and I think that's why you know, read Elsevier, LexisNexis and Thomson Reuters, like that's a savvy move to start to stop thinking so much about libraries and thinking much more about government surveillance contracts, and contracts with major hospital systems and major insurance insurance providers and, you know, these big institutions that are used to just shelling out a lot more money than marketing. Right, exactly.


Shoshana Wodinsky  39:01  

But when we talk about, you know, the court system or hospitals are like Social Security Systems. I was kind of joking with you earlier that like I I kind of I have, I have a lot of friends that are in like, kind of like the techno anarchists scene, but I've never aligned myself with them because I always believe you should pull the kids out of out of the out of the school before you like launch a missile at it. Like, it's literally this case, because you have these deeply ingrained infrastructures that if you pull if you just say like, oh, this is illegal, like you snap your fingers and you pull it out, your hospital will collapse. So we're in kind of


Sarah Lamdan  39:43  

a pickle. We become so great and actually because of engelberg center, and because there were there were experts who were so kind as to read my book before winning the world and give me feedback. Somebody kind of turn my attention to this this like old kind of steel Baron oil baron era analogy comparing these big monopolists to octopuses,


Shoshana Wodinsky  40:13  

I, I meant to call it my core. So the big


Sarah Lamdan  40:16  

corporate octopus is right. And they they are octopi. They dig octaves, right? The first they dig there, they put their tentacles around, you know, multiple information markets, but they also dig their tentacles so deeply into government. And they become so intertwined with government, that it's almost impossible to disentangle them, right? They just become embedded. And in fact, we were talking yesterday in class, somebody was talking about election databases and how creepy they are. And I said, and that's one of the reasons you likely will have a really hard time getting data broker legislation. Our legislators depend so much to get elected personal data to get to win election.


Shoshana Wodinsky  40:57  

I remember what is that company GP fan, like the the, I always forget what it's called, but the company that works with election campaigns to like, basically get them voter data. I tried covering them. That was the first story that did that I was trying to do for Gizmodo. When in 2020, when I was first hired, I never finished it, because I'm just like, there's too much here. It is too complicated. Like, like you said, the the tentacles were wrapped around too tightly. And I'm just like, if I write this, it'll just be depressing. Because it's just like, This is how our country has always operated. Well, not always. Because you mentioned my favorite guy, Bill Clinton. Well, well, no, no, no. Because like, whenever I see like, kind of like, anti trust or like privacy issues, I always like mentally, I'm just like, I bet I can trace this back to the Clinton administration. And usually I can. So I'm glad that you also,


Sarah Lamdan  41:49  

I also traced this whole thing back to the Clinton administration.


Shoshana Wodinsky  41:53  

So so so can you kind of explain like how the 90s because the mess we're in today.


Sarah Lamdan  42:00  

So I will, I will bring this by saying there's there's a scholar who I don't know, personally, but I depended a lot on on this one concept that they discussed. Meg Letta, Jones discuss this idea of technological exceptionalism. So this idea that we somehow we can't we tend to categorize new technologies as so exceptional that we can't regulate them, we can't regulate them, because we don't want to slow them down, because they're doing so many amazing things in the world. And we also can't regulate them because they're too complicated. Right? So I think that rather than and also, I mean, because we're in the US, and we are capitalism loves to capital, right, we're doing our thing, that where your market is going to market. So in 1996, when it became clear that there was going to be like, satellite radio and satellite television, and that the internet was going to become kind of part of our lives. The Clinton ministration saw it suitable and appropriate to kind of break down all the walls, that we're separating all the types of media. So there have been all these protective rules in place, that kind of limited the scope and size of different types of information sources, digital information sources, and I mean, I guess, digital it like limited the size of television radio, like


Shoshana Wodinsky  43:15  

crazy, right? Exactly like what like what kind of like I was born in 92. What kind of like digital information was there out there, you had your radio, you had your TVs? You had brand new computers ran a computer and a computers and then like you had whatever the government was using? And then you think that's it?


Sarah Lamdan  43:32  

Yeah. And remember, I mean, I, I was a teenager, in in the early 90s. And remember, at that point, like, different. So the hurt I was, I'm aware that the first time I saw someone talking on a cell phone, I thought they were talking to themselves, like I was like, what is that? What is it that that person's walking down the street and talking like I didn't, but the internet for us was, you know, hooked up to the I would literally I would go to my neighbor's house, use the internet. And we would sit there and we will listen to those, you know, beeps the little bing, bing, bing, and we'd be so excited. And then like, 20 minutes later, a picture of a cat will have would have downloaded onto my screen, or onto her screen. Oh, great. Yeah, we weren't that interconnected. But I think by like the late 90s, we kind of realized that maybe we could mean. And so instead of thinking about the best way to kind of determine who would control that and to make sure that there were like a plurality of people controlling this brand new communication source and these brand new things. We just decided no, let the market do its thing. And then everything like consolidated, enrolled into these big gigantic information barons.


Shoshana Wodinsky  44:44  

Yeah, it really became like a game of like first capture because whoever got whoever got to a certain kind of circle first like Lexus just.


Sarah Lamdan  44:52  

Yeah, yeah. And that's something I discuss in my book lot. So one of the reasons that relics read off your LexisNexis and Thomson Reuters. have been able to get such a stronghold is remember? Well, I guess this is explained in my book, I didn't say it out loud to get all these all of these companies. So the read read was a major news company and magazine company Elsevier, the biggest journal company and academic information company in the world, Lexus own the entire corpus of American law Nexus, own all the news archives and also had like a lot of other research structure. And they had this stuff in the 70s, right, I think read was around before the 70s. And the Elsevier has been around since like the 1800s. It was named after this, I think Dutch scholar named elsewhere, and he was known for publishing Galileo's work. Like that's how old that's how much of a stronghold these companies have. So they predated the internet by so much that when it was time to move things into the digital world, they already had all these archives of information that they could just LexisNexis was the first legal information company to digitize the law. And an Thomson like Westlaw, which was later, you know, consumed by Thomson Reuters had more American law than any other company. So they started from a place of monopoly or duopoly, you know,


Shoshana Wodinsky  46:11  

what's funny, so I'm thinking about it now, because you know, the modern kind of like digital publishing world, like online newspapers, they kind of worked the same way, where like, over time, they've had to more, they've had to mutate from just being a place where like, you go to read the latest news to a place that's actively profiting off of you, or trying to, and it because it doesn't really have a choice. That's the way digital economies work. And I feel like there's just like this, like, polish. Like, there's, there's, there's like, cosmic horror, again, there's something, there's something about the world technology, technology that just pushes people to kind of the most profitable solution, even if it isn't really the one people necessarily want. And then it's just the machine just kind of moves on as


Sarah Lamdan  46:59  

well. And, I mean, remember, I was this is true of all tech platforms. But if you are a publicly traded company, and you have shareholders, you have to increase your profits all the time, you always have to be looking at new venues for profit,


Shoshana Wodinsky  47:11  

venture capital is has a lot to do.


Sarah Lamdan  47:14  

You keep you keep expand, you know, the only way you can grow is by expanding by getting into the health data sector getting, you know, into a new type of government contract, learning how to data fie and make predictions about child welfare services. And other you know, you're always trying to branch into new markets, because you're always trying to increase your profit. Right? Like,


Shoshana Wodinsky  47:33  

at that point, and like, you know, because you mentioned at the, at the beginning of the book, the information that these platforms had, that's what you thought was valuable. But to them, it's not really about information as much as it is the people that use it. Yeah, same Yep. Same thing, the same thing with digital publishing, they sell audiences based on who's going to read this article, what type of person visits something like I don't know, the Washington Post or the Chicago times. And if the right person doesn't visit, then they just don't get paid that day. It's more complicated than that. But we're talking about this book. There were a few other questions that I did want to ask you, if that's okay. We have a little bit more time. At the end of the book, this is the chapter that I didn't read. You say that you mentioned potential fixes here. Because thanks to sort of the loosening of the rains that happened in the 90s, the government really hasn't been able to grab hold of these companies, since they've been kind of slipping through all of these laws and all of these regulations. And when they when they try to regulate them better, it's state by state, so they can just slip through it a different way. It's read the book, but what can we do about this? Scared?


Sarah Lamdan  49:00  

So? Yeah, there's i So one of the problems like one of the I, I was lucky to be reading to be writing like the problematizing book, and not as much the solution finding book because the solution finding book is I've tried it, and it's hard. It's so hard. The one thing I have learned, because I think when I talk about this problem, a lot of people are like, Well, what we need is a law. Like there's this bill out there, like the Fourth Amendment is not for sale Act, or we need to do copyright reform. We need


Shoshana Wodinsky  49:27  

HIPAA to actually apply to websites and apps and not just like health insurance brokers.


Sarah Lamdan  49:33  

Exactly. We need to we need to close close loopholes in our existing privacy laws. Polls, right theory. And the thing is, is like because those aren't competing ideas. It's like they don't yeah, you're right. Yeah, HIPAA, yeah, copyright. Yeah, antitrust. Like we need to not have we not need to not have our main academic information platform also being run by our main governor. My Data Broker, like, that's not good. So we need to do all of those things. It's it has to be a multifaceted approach like there. Yeah, we need to make sure that you have to get a warrant before you use these in a, you know, before state actor uses these are not uses these but for a state actor, you know, ceases and look through your data stores, you need to fix loopholes and copyright law that allow


Shoshana Wodinsky  50:28  

you to apply though it's so much more profitable not to fix.


Sarah Lamdan  50:32  

And these and like these companies poor,


Shoshana Wodinsky  50:35  

the real piece companies are really profitable.


Sarah Lamdan  50:37  

And they pour a ton of money into lobbying, right. They're just I the reason, I mean, the main reason I wrote this book is I wanted you to know that Relex, and Thomson Reuters should be considered along with Google, Amazon, Facebook, Apple and Microsoft. Like they're gigantic, multibillion dollar, data analytics, tech companies, and they are lobbying hard against any sort of any sort of governance or regulation.


Shoshana Wodinsky  51:04  

I will say this, you know, for a long time, I was kind of because in my side of the world, I was really kind of like, bummed. I'm just like, oh, regulators, we're never going to like, get a hold of this. I'm going. I always kind of like half jokingly said that, like, I didn't expect privacy regulation to meaningfully change within my lifetime. Well, right now, and there's a lawsuit going on against Google led by the 40. State agency, you know about this. It's an antitrust case, based on Google's role in the online ads market, where the company is very anti competitive, and has been for a long time, but nobody's been able to prove it under current laws. So the lawsuit kind of like flips it a little bit. And they use kind of a stock market analogy. And they're basically like, oh, Google rigged the stock market. And then lawmakers were like, Oh, we get it. Now. We can sue that. So the fact that like, when I saw that was filed, I'm not gonna lie, I teared up a little bit, because I was like, Oh, they finally get it. Like, kind of gives me hope. You know,


Sarah Lamdan  52:06  

I will say like, this summer, I actually testified in Congress, because there was the one issue that both sides of the aisle were concerned about and could agree on was the issue of data privacy. And and like they were they ever everybody for completely different reasons that were utterly fascinating to listen to. Everybody cares about data being used in government surveillance on both sides of the aisle, everybody for totally opposing reasons that are just fascinating. Everybody cares about it. And they think that that is actually a type of legislation I even heard last week, like, when we were kind of doing the run up to the elections this week, people were talking about how data privacy might be a bipartisan issue. Well, I, I don't know. I don't know what that will say at all about anyone. But it's interesting to think about. Okay, well, it's


Shoshana Wodinsky  52:56  

about time. That doesn't for me, is there anything you want me to ask me?


Sarah Lamdan  52:59  

I think yeah, I


Shoshana Wodinsky  53:00  

think I want you to for next week, anybody


Unknown Speaker  53:02  

have Yeah? Yeah. You can yell. Thank you. So I'm an LLM student, actually here at NYU at antitrust and what you were saying about how Lexus and Thomson Reuters have evolved from traditional publishers, to data brokers to risk analysis. This fascinates me from the relevant market definition from from the entrepreneurs perspective. So I'm wondering how much are we the FTC, but also potentially, class plaintiffs going to rely on how the company's self identify? And how will the court consider this self identification and self labeling, I would personally be more inclined to take a broad market definition, no matter how controversial it may be in quotes at this point in time, because these companies Well, on the one hand, they can compete with publishers. But on the other hand, maybe we can prove even with a broader market definition that they are extremely monopolists. So I think I think in this case, it doesn't matter how narrow or broad you are on the market definition, because it's just them. But I was wondering, how would you solve the dilemma in the designation and market definition, given these companies evolution over time?


Sarah Lamdan  54:39  

That's such a good question. It's actually one that I got to work on this year with Spark, if any, especially library people, Spark is doing awesome work around privacy, and around antitrust work. And so one thing that we did all we would write reports, so these companies are always consolidating, right? And every time there's a consolidation, we will it and it took us funny how long it sometimes took us, we would rephrase what the market was, we would so like the companies call their companies call their academic analytics data analytics of academic academics data, they call it impact factor. Right? So we're like, no, no, that's data analytics in the academic, you know, information and academic data market. And so we would write entire reports, the FTC again and again and again, trying to try and Wait, what did they say in mean girls trying to make that make it happen? Yeah, we make it fair, we kept trying to make it happen. Because we really you it is, so much of it as a matter of reframing what these companies call themselves and what they claim to do versus what they really do. Did we ever figure


Shoshana Wodinsky  55:47  

out a Facebook as a platform or a publisher?


Sarah Lamdan  55:49  

Exactly, right. Exactly. Right. Or, you know, kind of gets even to net neutrality. What's a common carrier? Yeah, it's these these phrases matter from a legal standpoint. So yeah.


Unknown Speaker  56:02  

Hi, so nice to see you both. Eileen Clancy, so I haven't met any of you in person. Twitter, Twitter. Hi, yeah. We're just big fans. And I just love to promote both of those work boys their work. So just have one little question that had read the bucket. One real question, Sarah, you mentioned that third party exception for warrant requirements, just to kind of go right into the law enforcement stuff. So can you say a little bit more about that? You said that think Thomson Reuters, somehow manages to get around that and anything to talk about that?


Sarah Lamdan  56:38  

Yeah. So it's an open secret. And I'll admit, I'm not a common law person. I'm like, I'm an admin, law person and a librarian. But I am familiar with this area, because when you get into Reed Elsevier, and Thomson Reuters, where he you can't not be. But yeah, it's this open secret that one of the reasons that entities like ice and entities, like law enforcement agencies, you know, local, state and federal, like to use data brokers is not just because it's efficient and easy, but because since it is a third party, this information. So instead of taking our information, these law enforcement agencies are simply buying subscriptions to streaming services or to, you know, to information platforms, and that allows them to skirt warrant obligations.


Unknown Speaker  57:25  

wanted to find out stuff about me. And I have committed no crimes. I'm not associated with anyone at all was quite independent. I don't see anybody know. As well, I didn't know I wanted to. So I mean, they could just by bleep information. Oh, no, they wouldn't have to that somebody out there is paying somebody a Twitter or to look into people's DMS, not me, but some, you know what I mean, and that's happening as we had with Saudi and so forth. So so all this, just the fact that all this is out there, and what they do instead of going to a judge, even though they also use administrative warrants in New York City to do this, and and they also just are pals with Verizon, they really can just ask them for stuff. Yeah, right. Anyway, so yeah, so they do that. So just the fact of collecting all this stuff via ad tech is just deleterious? I think to all of us. Yeah. And


Sarah Lamdan  58:34  

to the point that they are that their friends, there is a clear revolving door between law enforcement and these entities. If you look, if you look at who runs the risk services for both of these companies, they've all worked in, in major law enforcement capacity and ice capacity. And at one point, the head of LexisNexis Risk Services was also on the ice Foundation, which is a not it's a it's like a charity and support organisers of ice foundation. Yeah. For the people.


Shoshana Wodinsky  59:09  

I want a t shirt.


Sarah Lamdan  59:11  

Exactly. They buy the cakes. I don't know. They bring the napkins. Yeah.


Unknown Speaker  59:18  

Hi, Sarah. I Shana. Hi, nice shirt. Thank you. Um, is there if you hadn't said that you testified in front of Congress? I would have started my question with well, did you know that's your number? No, Congress? I was. But I might. But my question is, the book focuses a lot on how bad this data is. There's a sort of example after example of how bad the state is. And you know, there have been a lot actually a lot of books about how bad the state is. And as many of us feel that we live in a in a world of eroding declining trust in government and news and financial institutions, while actually living in a world of sort of Greater Good It feels like it's being advertised to us as like greater security of this data, right, particularly for financial institutions. While still seeing, you know, recently Thomson Reuters just was involved in a 300 million data record data leak. And everybody knows about Experian that company. So this is this is a question of trust, as well. And I'm wondering, you know, one of the things that we've talked about is the difference in trust in government, because these are government data brokers versus you know, everybody thinks that Facebook is creepy, and it's a private company. And so, you know, you might not trust Facebook, but in that's okay, but you kind of should trust your government, right, you should trust your news. And so I'm wondering how you feel that these companies contribute to the erosion of trust in the public and to to the erosion of public trust more generally?


Sarah Lamdan  1:00:48  

That's a really good question. I


Shoshana Wodinsky  1:00:50  

was like, Can I do a quick can I do quick rant about KYC know, you know, your customer software that banks use? All right. So banks are very, very afraid of fraud. They're terrified of it. And as a way to kind of get around that you have companies like Experian or Equifax that roll out these very fancy proprietary solutions meant to supposedly detect fraudulent, like fraudulent logins, fraudulent calls, fraudulent everything. So when you make a call to a bank, and you if you hear kind of like a little like this call might be recorded, that call is being recorded. And because they're because they're doing vocal biometrics to figure out whether you are really you based on your phone number, which is why whenever I get asked a lot, you know, is our companies like Facebook and Google like yada yada, like listening in on my phone? I'm like, No, that would be really kind of complicated. But banks and hospitals and these large kind of federal entities love doing that. And obviously, they have very good reason to, but it doesn't really help.


Sarah Lamdan  1:02:04  

And it creeps you out. Like I think that that's, I think that the more we talk and publicize like stuff like that, and then it's Yeah,


Shoshana Wodinsky  1:02:11  

exactly. Like, here's something like I bet nobody in the audience probably knew what KYC was, because it sounds like a brand of like sex jelly. Like, like, like, the, you know, I always say and you mentioned this also in your book, I think you quote me, you know, the stuff the stuff is so like, information platforms, like risk analysis can block it just it sounds. That doesn't sound scary. That sounds like something that like your dad uses. But the fact that we're just like, No, that also means that they're like recording your voice. When you call the bank. Suddenly, you're just like, wait, what? And then you kind of right now, I think the issue, these companies are still too boring. We have to like figure out how to like, break through that initial layer, which is why I try to be as funny as possible.


Sarah Lamdan  1:03:00  

Yeah, the quote that I took from you is purposefully dull. They are their way to make this sound as boring as possible because they want your eyes to glaze over and you do not notice what they're doing.


Shoshana Wodinsky  1:03:12  

I used to work for my first job was actually at a magazine that was aimed at ad tech professionals. I was writing about the Deathstar mechanics for people working on the Deathstar. And you would think that I would just be like, horrified every day. But initially I wasn't. I'm like, this stuff is weird and kind of like dope. But like, there were like a lot of like big words, it's kind of concepts I didn't understand. And then about two weeks in, it finally hit me. And I just sat at my desk and I was like, Oh my God. All these weird kind of amorphous privacy concepts actually have words and like terminology attached to them. And I felt like I was like seeing I felt like I was like seeing through the internet.


It was a weird, weird experience. Highly recommend reading trade journals if you want to get into this.


Sarah Lamdan  1:04:05  

That sounds thrilling. It's really


Shoshana Wodinsky  1:04:07  

boring until it doesn't


Sarah Lamdan  1:04:16  

No, you're gonna do it's gonna be great. Yeah, that's a that's a really good final question that keeps me up at night. I mean, I think the first thing that you have to do is like graduate law school and get out there right and like go convince them because I think that that makes a huge difference right? You all make a huge difference like librarians pushing boys pushing law students pushing it all makes a difference. Like I'll say, what Lexus for my very personal like, you know, my little corner of the world. LexisNexis couldn't care less that me librarian was not happy with their product. They knew they had me they knew I would use their product forever. Anyway, they knew I would teach their product due for eternity, right until, until I retire. But they got really, really upset when students started complaining and stopped using their product. They that was the first I ever heard from them. And then suddenly, they wanted to talk to my boss and have meetings with me, like, suddenly they cared. And it was because their student metrics started sliding and their students started, you know, saying, Hey, we don't like what you're doing. So you have your own set of power, like librarians have their own power to, you know, deal with them through the contracts and deal with kind of deciding what types of information sources to even provide and how to provide them. And then students, you're their future consumers on you know, no matter no matter whether you're a law student, or a student, using, you know, academic, other academic sources, you're there, you're their customer base. I'm just a go between like, nobody, nobody cared about what I was doing. But they certainly care about what you're doing. And I also think, really, we have to stop being technological exceptionalist when it comes to when it comes to so we've done it we did in the past with you know, the printing press the automobile, I have these exams, that bicycle, the bicycle, right, like, the nobody wanted to regulate it. We talked about this yesterday in class, because we were reading the StateFarm case, right? They when we went to try to make cars safer, when Congress said, Hey, you make cars safer, safer. And we we well, the guy wasn't me. I wasn't I wasn't there. But I think was with the N and the National Highway Safety. Yeah, that NSA n h s. T a national highway, National Safety Highway Transportation Administration. So anyway, that agency, they they they tried to, you know, push, their solution was like, Oh, we've heard that the seatbelts and airbags are super, super helpful for making cars safer. And the automobile industry was like, No, we could never, we won't be able to build cars, that's going to be so expensive, we couldn't do. And so for years, we went back and forth over whether the car or the auto industry would be able to function if we had seatbelts in cars like or whether it would be just too hard. It's too hard to put seat belts in cars, right? And now we see that when we pushed when we push the auto industry to do and we said no, you have to do this. They all did it. And now we all have seatbelts and airbags in cars like a Walkman you did it. Yay. And we can do the same thing for the Texas Tech industry. We can say, hey, you have to do this. But you have to follow these privacy protocols. You have to encrypt, you have to you know, you have to minimize and you have to you have to


Shoshana Wodinsky  1:07:36  

ask, gosh, dang consent. Yeah, pretty sure your data,


Sarah Lamdan  1:07:39  

the smartest and it can't just be I agree right as a qualification for getting onto a platform like, there there can be meaningful safeguards put in place, that that balance both the you know, the industry's continued growth, but also our needs, right? And that is possible. And you got you. You are saying you are going to push for it, right? Because yeah, you all are going to push for it.


Shoshana Wodinsky  1:08:07  

I do want to say this, though, because it can be really tough to talk about privacy. I have a lot of experience during this. So I've failed a lot. And I've kind of come up with my own way. When I talk about privacy with folks that maybe are new to the field or kind of want to get into it or don't know why the app spying on them makes them feel crummy, but it does. I like to talk about choice because every privacy violation is a violation of choice. And if you kind of frame it like that, I wasn't this company did not give me the chance to say no. Every time it becomes it becomes a lot easier to talk about, at least in my experience. So yeah, you can go like that to your local librarian or professor or grandma's friends neighbors cousin.


Announcer  1:08:58  

The Engelberg Center Live! podcast is a production of the Engelberg Center on Innovation Law and Policy at NYU Law is released under a Creative Commons Attribution 4.0 International license. Our theme music is by Jessica Batke and is licensed under a Creative Commons Attribution 4.0 International license