WEBVTT
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Hello, I am Debra J.
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Farber.
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Welcome to The Shifting Privacy Left Podcast, where we talk about embedding privacy by design and default into the engineering function to prevent privacy harms to humans and to prevent dystopia.
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Each week, we'll bring you unique discussions with global privacy technologists and innovators working at the bleeding edge of privacy research and emerging technologies, standards, business models and ecosystems.
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Today I'm delighted to welcome my next guest, Jeff Jockisch, Partner at Avantis Privacy, Data Privacy Researcher at Privacy Plan, and co-host of the weekly LinkedIn event - or, yeah, I guess we call it a podcast as well - called "Your Bites, your Rights, which focuses on town hall style discussions around ownership, digital rights and privacy.
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Welcome, jeff.
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Thanks, Debra.
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Great to be here.
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Wonderful to chat.
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Absolutely.
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It's been too long since we've caught up, so why not do it publicly on this radio show right, this podcast?
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I know you did not start out working in privacy.
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And, at Privacy Plan, where you've been for a while, you've been focusing on data sets - like, specifically, 'privacy data sets,' privacy consulting and privacy training.
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And, your website states that you "research and create data sets about data privacy to gain insight into the privacy landscape.
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Can you give us some context as to what you mean by 'privacy data sets,' maybe your approach to creating them, and what you mean by gaining insight into the privacy landscape?
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Yeah, absolutely.
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I guess that's actually a few questions.
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It kind of is.
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I'm sorry.
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Well, I guess it sort of gets to the core of who I am.
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You know, I sort of grew up in technology and marketing technology, sort of the other side of the equation from privacy.
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I actually worked in a search engine for a long time before I got into privacy, and that was my introduction to it, doing some work in CAN-SPAM and COPPA as part of an SMS-based search engine.
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I won't really go into that because it's a little bit deeper, but I really built a lot of data sets when I was doing that, essentially building out a knowledge graph on the back end of a search engine.
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That's really where I cut my teeth on data science and building data sets.
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I really loved doing that.
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So, when I got into privacy, I really loved the privacy world, but I didn't really want to do what everybody else in privacy did.
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I didn't really want to work on compliance.
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I realized as I was studying for my CIPP/ US that the way I was studying for it was building data sets of privacy laws to study them and building data sets of privacy podcasts that I was listening to, to learn.
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It occurred to me that I like to build structured datasets and then I could do that in the privacy world.
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I just really fixated on that, and I started building massive datasets around different things.
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I've got a huge dataset of privacy laws, like all the privacy laws in the United States, and not just a list of them, all the different attributes and things like that.
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Probably there are law firms and organizations that do that.
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But I built a lot of other things like datasets of privacy podcasts, datasets of all the different aspects of privacy regulators across the world.
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I think I've got maybe one of the largest ones of that and datasets of privacy brokers and all aspects of data breach laws in the United States and all the different things that happen there.
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When we start analyzing those datasets and looking at all the different attributes, you really learn a lot and that's where you get those insights.
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That makes a lot of sense and it definitely explains - you're a "data guy.
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" That's how you got into doing privacy datasets and it shows that people get into privacy from all different angles, whether it's being a developer and coming in and starting to be a privacy engineer writing code, or privacy architects coming over from other spaces to work on privacy, or compliance folks, GRC folks, lawyers.
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You are absolutely the first person that I have ever met that has worked on datasets, which really drew me to you a few years back when I saw the work that you were making public.
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Now I know you recently started working for a company called Avantis Privacy to work on location privacy and deletion; and, I think we're going to center some of our conversation today mostly around 'location privacy.
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' I'd love to hear you elaborate on the work that you're doing there.
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Sure, that was actually a little bit of an outgrowth of what I was doing at Privacy Plan, so sort of still doing it at Privacy Plan.
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As part of my research at Privacy Plan, I built a dataset of data brokers.
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I found that nobody in the world, that appears to me, was really tracking them.
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There are actually a few organizations and, frankly, there are a couple of state laws that require data brokers to register - one in California, one in Vermont, and a couple other states are trying to pass some of those laws now; but, only about a little less than 1,000, probably close to around 800 data brokers, have actually registered.
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But we know, way back in 2014, the FTC estimated there were about 4,000 data brokers probably a lot more now.
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We've actually got a database of 3,000, actually 3,200 data brokers right now.
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Wow.
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Well, painstakingly, I built that dataset over three years now and from a variety of different sources, starting there with that 800 and building it out in a variety of different ways.
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Part of that's proprietary methodology, but a lot of it is just scouring the internet for datasets where somebody says this is a data broker, that's a data broker, and combining every dataset of data brokers I can find and growing it from there.
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Then a lot of people saw the lists and say, "ey, I'm a data broker and these are my data sources.
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If you just keep adding all of that up painstakingly over time, you end up with a lot.
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Sometimes I go into individual markets and say, "okay, well, who are the healthcare data brokers?
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Who are the political data brokers?
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Who are the location data brokers?
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and have to individually, in different market segments, try to find who are the brokers.
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It's just a lot of work.
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Absolutely sounds like a lot of work.
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That's an astounding number.
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I'm not surprised that there's that many data brokers, but I am in awe of the fact that you've been able to identify and kind of tag that many.
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So, with Advantis Privacy, you've been working on helping to delete geolocation data.
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What is your approach there?
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Yeah, so what happened was, as I was building this data broker dataset, one of the guys from Avantis - one of the original two founders there - approached me and wanted to chat.
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I actually did some consulting for them.
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I ended up coming on board with that organization.
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Now I've sort of became a full partner there.
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Avantus' approach originally was to actually be a data deletion service sort of like Incogni, Optery, PrivacyBee, DeleteM e.
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One of the things we realized early on is that nobody was deleting location data.
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Part of that is because the location data brokers, until the FTC sued Kachava last year, really were not letting people delete their location data.
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It was not really an option.
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They all claimed that that data was anonymous and therefore not personal data and not necessarily deleteable.
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They very quickly started putting changes into their privacy policy and throwing up delete pages where you could enter your MAID, maybe email address, and delete that information once the FTC sued Kachava.
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Now it's possible to delete your location data, but people don't know who those brokers are.
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They don't know how to find their MAID, their mobile ID number.
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They didn't even know it's a thing.
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Before this conversation - I've been in privacy; I talk about location data - I didn't even know, but I'm not an expert in brokers, I didn't even know that location brokers were kind of a separate category from a data broker.
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They are.
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Break down the difference there, because that is definitely something I think people would be interested in learning more about.
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Yeah, we've had 150 location data brokers defined that are storing your mobile advertising ID, as well as series of lat-longs - places where you've been: your home, your office, your shopping locations, your church, your gym, every place you've been and all the routes you used to get there.
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They've got all this information and they're selling it frankly to just about anybody with a credit card.
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It's not necessarily quite that easy to buy it, but it's not hard either.
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Yeah, let's explore that.
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What are some of the current risks to our location privacy?
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I know there's a lot to expound on here.
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I'll let you answer first and maybe we'll go deeper.
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Well, there are a lot of risks to your location and a lot of ways that your location leaks.
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We're actually trying to put together a little bit of a categorization system of what those different location risks are and where your location ends up.
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Frankly, your MAID is really only one of those vectors, but it's a very large one and one that people don't really understand.
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That's one of the reasons we're focusing on it, because you can delete your profile information from data brokers and that'll get rid of things like how easily your address is exposed to people search websites.
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That's something that the other deletion services can do reasonably well (maybe not perfectly), but decently well.
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But, they're not getting at this other MAID information.
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Then there are other things where you're exposing your location information in a variety of other ways too, like social media posts.
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your car, when you drive it around, exposes your information, sometimes through your mobile ID information, also through automated license-plate readers and through some other things, like other ways through your car.
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Plus, your phone can also leak some data through cell tower information in a variety of other ways, though they're a little bit harder for non-law enforcement organizations to get at.
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What are the restrictions there?
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Actually, before I get to the restrictions of why it's hard for law enforcement to get at some of this data, I did want to expound upon the risks to our location privacy.
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What are some of the privacy harms that could occur?
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Obviously, there's tracking.
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Sure, actually, I was talking about the types of data rather than the risks.
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Yeah, that's fine, you could switch gears.
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Yeah.
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Well, the risks are, it depends upon who you are.
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If people have your location, if you're an at-risk target, they can do a lot.
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First of all, it's a physical safety risk.
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If people know where they are, they can come and get you.
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If you have enemies, if you have somebody who's pissed off at you because you said something on social media, they can find you.
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They can come after you.
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They can SWAT you.
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We know this is a growing problem.
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They can send people after you, which is bad.
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If you've got a stalker, they can come to your house.
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They can find out where you work and go there.
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They can intercept you on your way places.
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That's a really huge problem for people that are celebrities or athletes or CEOs or people that have got stalkers, domestic abuse victims, things like that certain types of people.
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Even if you just are a regular person, you really don't want your location to be out there, because identity thieves can then use that information to commit crimes in your name.
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If they know where you live and they know lots of things about you, it's much easier to impersonate you.
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Those are a couple of the really biggest risks.
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I guess that's where I'm sort of leave it there.
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There are other ones as well.
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So this might be one you're thinking and holding back, but I do want to bring up the risk of, in a post-Roe v.
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Wade world now where in a state like Texas, with Roe being overturned and with anybody being able to pretty much accuse someone of having an abortion or seeking an abortion which is now against the law in Texas governments can use law enforcement or governments can obtain this data to find someone and prosecute them, or to check and see, maybe through a health app or health data set that they get their hands on can tell that you've been near, or to, an abortion clinic or that you went across state lines to an abortion clinic or something along those lines.
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Right?
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Yep.
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So, law enforcement can even be a threat actor here to one's privacy, which is kind of scary.
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Yeah, law enforcement, or just your neighbor who doesn't like you, right?
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It's pretty scary And, to be clear, it's not just about women that have abortion in those circumstances, right, if you get pregnant, there are just as many circumstances where you don't actually carry the baby to birth, where it's not an abortion, where it's potentially miscarriage or some other circumstance, where it's not an actual abortion, but somebody else who's looking at that from the outside might think it was an abortion when it wasn't.
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Right?
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And, they can accuse you of having an abortion.
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Right?
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And put you through all kinds of circumstance and stress based upon some of these new laws that are put in place.
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Right?
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And, that's pretty horrendous.
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I agree.
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I think there's definitely some fundamental harms that can happen as a result of getting access to that geolocation data.
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So, I guess to that point, I wanted to understand from you whether or not these location data brokers are always getting direct, precise information, or are they also inferring someone's location based on behavior or some other elements?
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So most of the data that we're looking at is actual location data that is based upon your GPS.
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Some of it is.
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It can be Bluetooth, some of it can be Wi-Fi, some of it can be cellular, but generally it's translated and then connected to your mobile advertising ID number.
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They can do inferences and stuff like that as well, and a lot of them do, but oftentimes those inferences, I think, are more like trying to impute whether or not, based upon your path and stops, that you were at a particular place or at another particular place, right?
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I don't know if you've ever been in Google, but sometimes you drive by and you park in a parking lot and it doesn't know if you went to the grocery store or you went to the Dunkin Donuts right next to it.
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That kind of inferences are things that these folks might make.
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Right, did you go there?
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or did you go to the mosque that was in the corner of the shopping mall, right?
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So if you go to a mall that has a mosque in the corner, they might all of a sudden think that you're going there instead of going to the Dunkin Donuts next to it.
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Yeah, that makes a lot of sense.
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And I could see how that can be misused as well.
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You previously said that the geolocation brokers in the past didn't really consider themselves data brokers, and I think you hinted that that's because they had anonymized data.
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Yes.
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And so can you speak to that.
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W hy is anonymization not enough?
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Why does that not take them out of being covered by data protection laws or privacy laws or by the ruling, the Kachava ruling?
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Just speak to us about geolocation and anonymization and some of the challenges.
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Sure, sure, Anonymization has always been a way to essentially avoid privacy laws, And the problem is that for a while now we have known that anonymized data can often be deanonymized, And location data is particularly vulnerable to this kind of re-identification.
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If you take three precise geolocations - especially if it's got a time element attached to it, which all of this stuff does - take three of those data points, or even four, you can identify Americans with 95% to 97% accuracy.
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So, if I have four data points on you, just randomly from some set of location data, Debra, I can identify you 90%, let's say 95% of the time that it's exactly you.
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Yeah, that's crazy.
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Because probably one of those data points is your house, one's your office, and one's you're on the way to work from the highway And I can tell just from looking at those three or four points of data that it's you because it can't be anybody else.
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Right, because it's almost like a behavioral pattern that's being recognized.
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Yeah, that's what it is.
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Right?
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And this is proven, statistically proven.
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There's a couple of articles There's one from two years ago from Nature Magazine that proves this right, and so it's impossible for these people to say that it can't be re-identified.
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Got it.
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But this is actually, we've known this for a long time.
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I think it was back in 2011, 2012,.
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Lantana Sweeney from - I forget where she's from, maybe MIT - has done this research, so we've known about it for a decade.
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Right and yet, because there weren't any regulations saying otherwise, so many ad brokers' responses was just to anonymize.
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And I know you wrote about privacy theater.
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So on LinkedIn I recently saw your post that reads quote location leakage coupled with 'consent theater' is an existential threat to our privacy.
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For many it's a threat to their physical safety and well-being.
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" Can you elaborate on this existential threat and what you mean by consent theater?
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I mean, I have my ideas, but I obviously want to hear from you.
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Yeah, well, the way this information gets collected is primarily from your smartphone, from apps.
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Right.
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You are going to go and load up your smartphone and you're going to turn on a weather app, right?
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Because you want weather.
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You need to know if it's going to rain tomorrow or if it's going to rain in the next 15 minutes.
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I've got a weather app that I use that tells me, when I look at it, if I need to bring out the umbrella in the next 15 minutes, and it's highly accurate.
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It's got great know-it-date on it.
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Right?
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But, it also sends my location to a data broker, and that location is connected to a mobile advertising ID, and it's going to get sold to Venntel and Kachava and Gravy Analytics and a whole bunch of other folks like that.
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Right?
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And what people don't realize, though, is that that's happening.
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That is because they put this weather application on their phone and said, "Yeah, i want this application, that they're essentially agreeing to give their location information to that application; and that application is going to monetize it by selling it to these location data brokers.
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They don't even know that they're there, that this ecosystem exists or that information is going to get sold, and then that information is going to go to anybody that wants to buy it, including law enforcement, Homeland Security, the FBI.
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Anybody can essentially get that data.
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Right?
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And when the government's getting it, they're essentially circumventing the Fourth Amendment because they can get it without a warrant.
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Identity thieves can find easy ways to essentially buy that information.
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If I've got a stalker, that stalker can buy - they can't necessarily buy just my data.
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They can't walk in to a data broker and say give me Jeff Jokisch's location.
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But, if they happen to know what state I'm in, for instance, they could probably buy a swath of data in my state or my city, something like that, and then, based upon that blob of data they got, they could probably figure out who I am.
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If they know a little bit about me and be able to figure out more about me, you know what I'm saying.
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So if they knew, for instance, where I worked and my name, they could probably figure out who I am.
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That makes sense, right?
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Yeah, no, that definitely does make sense.
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And then getting all the consents, the check- the- box that everyone gives to the privacy policy, and just to move forward with installing an app on their phone or on a website, gaining access to or creating an account.
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I'm assuming that that's the consent theater part where we can't possibly manage all of these relationships and understand and remember everyone we've consented to using our data for what purposes.
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Right.
00:23:57.401 --> 00:24:12.452
For me, the consent theater is this: they don't mind giving my location to the weather app right; but, what they're not telling me when I say "OK to that, is what happens to my location information downstream.
00:24:12.452 --> 00:24:27.913
It's completely non-obvious to me or to anybody else that that location information is going to be sold and is going to end up with Homeland Security, with potentially a threat actor, with potentially an identity thief.
00:24:27.913 --> 00:24:29.646
How is that possible?
00:24:29.900 --> 00:24:31.644
Yeah, i mean it shouldn't be.
00:24:31.644 --> 00:24:34.289
I hate data brokers, personally.
00:24:34.289 --> 00:24:42.060
I know that's something that Heidi Sass, who's a member of the Avantis team as well, she's always saying, "I hate data brokers.
00:24:42.060 --> 00:24:44.808
I'm not afraid to say it here.
00:24:44.808 --> 00:24:58.551
For the most part, they're trading on unsuspecting people who may have technically given consent but not really knowing what they're consenting to and using their data, sometimes selling it to their detriment of those people.
00:24:58.551 --> 00:25:04.745
How can people protect themselves from having their data collected and sold by data brokers and location brokers?
00:25:04.885 --> 00:25:07.479
Sure, Well, I mean, there's really two phases to this.
00:25:07.479 --> 00:25:07.660
Right?
00:25:07.660 --> 00:25:10.747
I mean we can help delete the stuff that you've already leaked.
00:25:10.747 --> 00:25:18.099
Avantis can help you delete that historical information, but you've also got to stop leaking the information.
00:25:18.099 --> 00:25:24.537
You've got to stop giving consent to these apps, and that can be a harder thing.
00:25:24.537 --> 00:25:30.072
We're also working on something that may be able to help with that, but that's for a later time in a later show.
00:25:30.601 --> 00:25:55.131
Oh, excellent, because I was going to ask whether you think it's incumbent upon the phone manufacturers who have the, whether it's firmware or software, whatever the pop-ups that are enabled to tell you what a particular app is going to use your data for, I find that those topics 'use it for marketing,' 'use it for customization.
00:25:55.131 --> 00:26:13.125
' I find that the reasons that developers can select are very broad so as not to really tell you the real purpose behind the data use downstream, but more of a category that can be selected just so that they can move forward and start the data collection.
00:26:13.125 --> 00:26:26.255
I feel like it needs to be more granular and or allow apps to be able to notify individuals about a more granular use of personal data.
00:26:26.700 --> 00:26:28.687
Yeah, I definitely agree.
00:26:28.687 --> 00:26:30.673
I mean it needs to be more granular.
00:26:30.673 --> 00:26:35.778
It would be great if there was something that said "ey, we're going to use your data, but we're never going to sell it.
00:26:35.778 --> 00:26:36.140
Right?
00:26:36.140 --> 00:26:37.143
Too.
00:26:37.143 --> 00:26:42.266
So, like I'm going to use it for my marketing, but I'm not going to sell it to anybody who can sell it onward right.
00:26:42.266 --> 00:26:50.288
That would be awesome if I could give my location to my weather app without having to give it to the whole world like that checkbox.
00:26:51.210 --> 00:26:52.774
Yeah, wouldn't we all?
00:26:52.774 --> 00:26:56.769
It seems like that should be the way things are.
00:26:56.769 --> 00:26:57.090
Right?
00:26:57.090 --> 00:27:09.105
Optimizing for the benefit of humans and not necessarily for corporations to exploit them for the purposes of just making money off their data that they didn't consent to.
00:27:09.105 --> 00:27:10.610
So I'm with you on that.
00:27:11.292 --> 00:27:15.343
Yeah, I actually think, Debra, that some of this is changing.
00:27:15.343 --> 00:27:20.445
I think some of this consent theater what I've referred to it as is going to change a bit.
00:27:20.445 --> 00:27:29.861
I think the consent boxes are probably going to change a bit in the next couple of years, and there are companies like Apple that are taking somewhat of a leadership role there.
00:27:29.861 --> 00:27:38.125
In terms of MAIDs, because of the ATT framework that Apple rolled out, there are a lot of people that have opted out of that.
00:27:38.125 --> 00:27:49.102
So there are less people on the Apple operating systems - iOS - that have their mobile advertising IDs turned on now than on Android, for instance.
00:27:49.102 --> 00:27:50.004
That's good.
00:27:50.004 --> 00:27:50.305
Right?
00:27:50.485 --> 00:27:55.086
However, a lot of those people still have a lot of historical location data out there.
00:27:55.086 --> 00:28:01.812
So, even if you're running an iPhone and you're like, "h yeah, well, I turned off my mobile advertising ID Well, that's awesome right.
00:28:01.812 --> 00:28:10.521
Except, even if you turned it off, you know, like six months ago, all the data that you let those companies collect for years is still sitting out there.
00:28:10.521 --> 00:28:21.723
Now, some of it might be older and maybe less valuable, but if you still live in the same house, go to the same office, go to the same routes, all that data is still sitting out there for somebody to use against you.
00:28:21.923 --> 00:28:23.727
So, that's a really great point.
00:28:23.727 --> 00:28:28.284
All it does is stop the data collection, but not necessarily purge it.
00:28:28.284 --> 00:28:48.571
So, how could individuals gain more control over their own data, especially if we don't have a unified at least in the United States, we don't have a equivalent of a GDPR And we just have some states, like California's DCPA and a few other states that have kind of followed suit with the privacy law.
00:28:48.812 --> 00:29:03.682
Well, like this, Avantis can help you try to purge that data with our location purge, because with Apple, you can actually go back in, turn your MAID on, grab that MAID number, send it to us, and we can purge that information for you.
00:29:03.682 --> 00:29:07.092
It's actually harder on Android.
00:29:07.092 --> 00:29:15.856
So, on the Android devices, only 3% of people roughly have turned off their mobile advertising ID, which is sad.
00:29:15.856 --> 00:29:25.486
However, there's a problem on Android, and that's this: if you have turned off your advertising ID, there's no way to know what it used to be.
00:29:25.486 --> 00:29:31.605
So, all of that historical information is now no longer reachable.
00:29:32.105 --> 00:29:45.669
So, you can't turn your Android ID back on, figure out what it was and then send that MAID to us so that we can delete that past history unless you can figure out some other way to figure out what your ID was.
00:29:45.669 --> 00:29:48.440
It's like unreachable historical data.
00:29:48.440 --> 00:29:49.241
You know what I'm saying?
00:30:02.749 --> 00:30:07.930
Yeah, well, that's definitely, security-wise, that's a data availability problem now, potentially.
00:30:07.930 --> 00:30:16.733
I mean, arguably, could that be a good thing, like it's no longer identifiable potentially, or is it still going to get bought and sold?
00:30:17.060 --> 00:30:24.667
Still going to get bought and sold, and somebody, anybody who grabs more than three or four points of data can re-identify it and figure out it's you.
00:30:24.967 --> 00:30:25.208
Right.
00:30:25.208 --> 00:30:37.750
So if somebody deletes their ID off of Android, are you basically saying that Google will still track that ID even though that person is no longer - it's not considered "Let's purge that data.
00:30:37.750 --> 00:30:38.733
It's not good anymore.
00:30:39.720 --> 00:30:40.142
It's nothing.
00:30:40.142 --> 00:30:41.766
Google's tracking you, right?
00:30:41.766 --> 00:30:49.009
Because at that point, Google's no longer sending new information based upon any mobile advertising ID.
00:30:49.009 --> 00:30:55.961
But, they've already sent it out, right, and those brokers have collected it and it's sitting in their data sets, got it?
00:30:55.961 --> 00:30:57.544
That makes sense.
00:30:57.544 --> 00:31:07.372
So if you re-enable your mobile advertising ID, it generates a new one, so then they can start tracking you again, but it's based upon a new mobile advertising ID.
00:31:07.641 --> 00:31:08.666
I see, I see.
00:31:08.666 --> 00:31:19.127
So, I think we've been talking about how Avantis can help people protect themselves from having their data bought and sold and how to request purges be made.
00:31:19.127 --> 00:31:21.234
But what about organizations?
00:31:21.234 --> 00:31:25.893
What can they do better to protect people's privacy when collecting and using geolocation data?
00:31:26.215 --> 00:31:31.275
So if you're talking about like a commercial interest, I think that's pretty interesting.
00:31:31.275 --> 00:31:40.882
We're actually talking with some organizations now about how they need to start thinking about this from a threat mitigation situation.
00:31:40.882 --> 00:32:02.027
And, especially if you're talking about people that maybe targets in your organization for attack you know whether it's the C-suite or your IT personnel or other vulnerable individuals where you know attackers might come after them, they're going to come after them based upon information that they can find that's publicly available, right?
00:32:02.027 --> 00:32:11.532
So some of them are actually, you know, going to these data deletion companies and trying to delete all their information on their C-suite employees, their IT employees.
00:32:11.532 --> 00:32:17.195
Frankly, they should probably be doing it for all their employees, but at least those ones that are most vulnerable.
00:32:17.195 --> 00:32:26.241
But, right now, they're ignoring all the location data, right, which is a big vulnerability, so they should be thinking about deleting that location information as well.
00:32:26.241 --> 00:32:27.426
It's a big hole.
00:32:27.686 --> 00:32:28.348
Yeah, definitely.
00:32:28.348 --> 00:32:31.746
That sounds like a real security challenge for corporate security.
00:32:31.746 --> 00:32:33.432
And I do appreciate the answer.
00:32:33.432 --> 00:32:41.781
But, what I was trying to get at is should companies, for instance, not collect geolocation data in the first place?
00:32:41.781 --> 00:32:44.125
Oh, I see what you're saying.
00:32:44.125 --> 00:32:47.313
Or is there a way to do this in a more manageable way?
00:32:47.313 --> 00:32:55.771
If they do collect it, is there like a privacy enhancing technology or architecture that can be used to better protect the privacy of people?
00:32:55.871 --> 00:32:59.249
You know, I'm not sure if I've got a great answer to that.
00:32:59.249 --> 00:33:15.466
I think maybe the best way to be careful with that data is to not collect the precise geolocation, but collect more vague geolocation information, because generally you don't actually need that data to be precise.
00:33:15.846 --> 00:33:21.045
Is it more like people would want to know what state you're in and that's the level?
00:33:21.045 --> 00:33:24.692
Or, could it go deeper than that and be county and be okay?
00:33:25.400 --> 00:33:27.686
Yeah, I mean that's not bad, right?
00:33:27.686 --> 00:33:40.842
I mean, if you can pinpoint it down to a house level, I'm not even sure what the actual fine- grained level is that's problematic, right?
00:33:40.842 --> 00:33:52.106
But, if you were to blur that data out so that was within miles instead of feet, you probably would not have an issue with it, right?
00:33:52.106 --> 00:33:58.671
If it was within like a mile radius and probably if you're in urban or rural areas.
00:33:58.671 --> 00:34:04.731
But it's not going to really change my weather report, and it's probably not going to change a lot of other things.
00:34:04.731 --> 00:34:12.704
Maybe it changes it for the people that are trying to figure out what store you're going to, which could be problematic for certain applications.
00:34:12.704 --> 00:34:18.322
But for a lot of use cases you don't need precise geolocation, but they're storing it anyway.
00:34:18.643 --> 00:34:19.365
Yeah, that makes sense.
00:34:19.365 --> 00:34:20.007
That's helpful.
00:34:20.007 --> 00:34:27.510
I do wonder, and if people here are listening, maybe there's an opportunity to specifically focus on location data.
00:34:27.510 --> 00:34:50.782
I know Privado, the sponsor of this podcast, actually does quite a bit of making sure that - you could scan your code to make sure that location data is behaving as intended and you're not actually collecting sensitive data when you didn't want to be as an organization or it can put you into risk or harm privacy.
00:34:51.364 --> 00:35:02.041
But it seems to me that there is definitely an opportunity out there to educate companies on how to protect people and not harm them, especially when it comes to geolocation and precise data.
00:35:02.041 --> 00:35:33.153
Perhaps it's as you say, that you get not precise geolocation data but work with a statistician or somebody who can take a look at making sure that data is not identified or re-identifiable, making sure that the granularity is not going to harm individuals, and kind of do that threat identification and threat model for the product beforehand, before you ever ship.
00:35:33.153 --> 00:35:34.463
That will do wonders.
00:35:34.463 --> 00:35:48.325
And you could refer to people listening, you could refer to the previous episode on threat modeling with Kim Wuyts and learn a little more about the threat modeling approaches and when you should do that.
00:35:48.325 --> 00:36:02.251
But, I do think that having the right experts on board to help with whether or not this meets privacy bars and not just compliance, but can actually protect the people behind the data is pretty essential.
00:36:02.371 --> 00:36:03.635
Yeah, I definitely agree.
00:36:03.635 --> 00:36:11.592
I think if you change the granularity, you could vastly decrease the reidentifiability of the location data.
00:36:12.860 --> 00:36:13.242
Excellent.
00:36:13.443 --> 00:36:15.311
And it might not be that hard to do, actually.
00:36:15.311 --> 00:36:23.726
I mean, if you have lat- longs, you could just lob off the last few decimal points potentially, and you'd be there.
00:36:23.930 --> 00:36:23.930
Fascinating.
00:36:23.930 --> 00:36:27.988
Well, it's good to know You don't think it's too complex.
00:36:27.988 --> 00:36:32.903
Hopefully this is some food for thought for the privacy technologists in the audience.
00:36:32.903 --> 00:36:51.775
Jeff, is there anything else, any other resources that you would point people to if they're concerned about data brokers or location privacy; or you could also plug your website for learning more about privacy data sets.
00:36:52.657 --> 00:36:57.226
Yeah, well, I think there's a lot of stuff on Privacy Plan about data sets.
00:36:57.226 --> 00:37:02.923
I'd also say follow me on LinkedIn; I do a lot of posts there.
00:37:04.027 --> 00:37:07.255
I also promote a lot of other people there.
00:37:07.255 --> 00:37:09.702
And check out "rivacy podcasts.
00:37:09.702 --> 00:37:21.791
I've been a little bit negligent, but I maintain a huge data set of privacy podcasts And, frankly, Shifting Left is finally in the data set, so that'll be awesome.
00:37:22.253 --> 00:37:27.911
And yeah, I'm going to be doing a Top 10 list here in the next couple of weeks.
00:37:27.911 --> 00:37:41.173
Debbie Reynolds has been on me to redo that because I haven't released one for a while, and I think there's something like 200 privacy- focused podcasts in my data set.
00:37:41.554 --> 00:37:42.757
That's just so wonderful.
00:37:42.757 --> 00:37:45.407
I really look forward to that when that comes out.
00:37:45.407 --> 00:37:45.929
I've seen the list.
00:37:45.929 --> 00:37:52.268
And I have looked at the database and I'm really glad that you finally added S hifting Privacy Left.
00:37:52.268 --> 00:37:53.351
We're relevant!
00:37:55.916 --> 00:37:56.760
You're actually not relevant.
00:37:56.760 --> 00:37:58.686
You're actually high up there now too.
00:37:58.686 --> 00:38:03.863
So, I haven't actually pushed the top lists, but you're in there, so that's awesome.
00:38:04.124 --> 00:38:05.027
Oh, that's excellent.
00:38:05.027 --> 00:38:06.413
It's really great to hear.
00:38:06.413 --> 00:38:09.643
Like I said, I'm really looking forward to seeing that.
00:38:09.643 --> 00:38:11.146
And what else?
00:38:11.146 --> 00:38:17.965
Before we go, let me have you discuss a little bit of your podcast, "our bites, your rights.
00:38:17.965 --> 00:38:28.193
Do you mind just giving us a little overview about the types of things you discuss when it takes place, and how people can participate?
00:38:28.360 --> 00:38:35.664
Yeah, we've actually been on hiatus for a bit, but Christian Kameir and I are going to be ramping that back up.
00:38:35.664 --> 00:38:41.922
We actually had an episode a couple weeks ago and hopefully we're going to get back on a weekly rhythm.
00:38:41.922 --> 00:38:57.724
But, Your Bytes, Your Rights is sort of a weekly interdisciplinary discussion on data rights And we focus a lot on privacy and data ownership and sort of all the stuff that goes around with that.
00:38:57.724 --> 00:39:11.860
We try to bring in people from not only privacy, but just all kinds of different related disciplines to talk about how we can better own and demand our rights to our data.
00:39:12.242 --> 00:39:22.313
Yeah, and I've participated in several of those discussions and I've been really enlightening and engaging with other experts in the field, and so I encourage others to attend them.
00:39:22.313 --> 00:39:26.389
Once you get them going again, no worries taking a hiatus.
00:39:26.389 --> 00:39:28.432
I took a few off this summer myself.
00:39:28.432 --> 00:39:41.842
There's just so much going on in the field that we just have to remember that we're human and we can only - we need to rest at times, and you can only get done when you get done, but I look forward to participating again.
00:39:42.125 --> 00:39:44.854
Yeah, absolutely, you were great when you were on.
00:39:44.854 --> 00:40:02.047
We just finished up an episode with Tom Kemp about the DELETE Act in California, which may finally have a regulation with some teeth in it on data brokers.
00:40:02.721 --> 00:40:03.646
Yes, that's wonderful.
00:40:03.646 --> 00:40:09.409
He's going to be on the show in a week and a half, maybe two weeks actually in the recording times, yeah.
00:40:09.650 --> 00:40:09.971
Awesome.
00:40:09.971 --> 00:40:10.612
Well, that'll be great.
00:40:10.612 --> 00:40:13.817
Well, then you'll have all the details on the DELETE Act.
00:40:14.200 --> 00:40:16.965
On the DELETE Act, as well as his new book.
00:40:16.965 --> 00:40:22.213
"Privacy and Big Tech, which is definitely an interesting book.
00:40:22.213 --> 00:40:24.626
We'll talk a little bit more about that when he's on the show.
00:40:24.626 --> 00:40:30.470
Then he's also a seed investor for a whole bunch of privacy tech companies.
00:40:30.470 --> 00:40:34.927
He's a very interesting individual, and I really look forward to having that conversation.
00:40:34.927 --> 00:40:40.921
Yeah, I love it that we're talking about similar things, you and I, but taking different tacks.
00:40:40.921 --> 00:40:53.157
You have this town hall style engaging show where anyone could join the LinkedIn Live event and then ask questions or join within that format.
00:40:53.157 --> 00:40:53.960
I love it.
00:40:53.960 --> 00:41:02.686
It's all complimentary and really enjoy the value that you bring to the field, especially your enormous focus on data sets.
00:41:02.686 --> 00:41:11.880
Until you came on the scene, I hadn't seen anybody else doing that hard work of pulling it all together and then making it pretty accessible publicly.
00:41:11.880 --> 00:41:13.204
Well, thanks for your work.
00:41:13.264 --> 00:41:13.927
I appreciate that.
00:41:13.927 --> 00:41:17.327
Hopefully we'll put out some new ones and some big ones soon.
00:41:17.729 --> 00:41:18.271
Great, Jeff.
00:41:18.271 --> 00:41:24.172
Do you have any other words of advice or anything you want to leave our listeners with before we close?
00:41:24.619 --> 00:41:25.300
I think.
00:41:25.300 --> 00:41:30.731
Just some kudos to you for Shifting Left, loving the new podcast.
00:41:30.731 --> 00:41:31.713
Thanks for all you do.
00:41:32.221 --> 00:41:34.648
I really appreciate that very much.
00:41:34.648 --> 00:41:35.905
It's a lot of work.
00:41:35.905 --> 00:41:41.771
I got a lot of personal value and pleasure out of having these conversations.
00:41:41.771 --> 00:41:43.284
Thank you for being on the show.
00:41:43.284 --> 00:41:45.846
I'm sure I'll have you back on in the future.
00:41:45.846 --> 00:41:48.224
There's just so much going on in this space.
00:41:48.224 --> 00:41:54.570
Good luck to you on Avantis and the new consumer location privacy and deletion tool.
00:41:54.570 --> 00:41:56.985
I'll be paying attention.
00:41:56.985 --> 00:42:05.606
If people wanted to reach out to you and collaborate or ask questions, is LinkedIn the best place or is there somewhere else that they can go?
00:42:06.740 --> 00:42:08.726
LinkedIn is probably the easiest way to reach me.
00:42:09.048 --> 00:42:09.389
Excellent.
00:42:09.389 --> 00:42:13.106
Well, I'll put a link to that in the show notes and you can have a great day.
00:42:13.106 --> 00:42:14.050
All right, take care.
00:42:14.050 --> 00:42:21.485
Thank you for joining us today on Shifting Privacy Left to discuss privacy, data sets, location privacy and data brokers.
00:42:21.485 --> 00:42:25.947
Thanks for joining us this week on Shifting Privacy Left.
00:42:25.947 --> 00:42:28.284
Make sure to visit our website, shiftingprivacyleft.
00:42:28.284 --> 00:42:34.981
com, where you can subscribe to updates so you'll never miss a show While you're at it.
00:42:34.981 --> 00:42:46.847
If you found this episode valuable, go ahead and share it with a friend, and if you're an engineer who cares passionately about privacy, check out Privado: the developer-friendly privacy platform and sponsor of this show.
00:42:46.847 --> 00:42:49.164
To learn more, go to privadoai.
00:42:49.164 --> 00:42:53.387
Be sure to tune in next Tuesday for a new episode.
00:42:53.387 --> 00:42:54.161
Bye for now.
00:00:49.121 --> 00:00:50.927
Hello, I am Debra J.
00:00:50.927 --> 00:00:51.388
Farber.
00:00:51.388 --> 00:01:03.531
Welcome to The Shifting Privacy Left Podcast, where we talk about embedding privacy by design and default into the engineering function to prevent privacy harms to humans and to prevent dystopia.
00:01:03.531 --> 00:01:15.611
Each week, we'll bring you unique discussions with global privacy technologists and innovators working at the bleeding edge of privacy research and emerging technologies, standards, business models and ecosystems.
00:01:15.611 --> 00:01:40.105
Today I'm delighted to welcome my next guest, Jeff Jockisch, Partner at Avantis Privacy, Data Privacy Researcher at Privacy Plan, and co-host of the weekly LinkedIn event - or, yeah, I guess we call it a podcast as well - called "Your Bites, your Rights, which focuses on town hall style discussions around ownership, digital rights and privacy.
00:01:40.105 --> 00:01:43.066
Welcome, jeff.
00:01:43.340 --> 00:01:44.001
Thanks, Debra.
00:01:44.001 --> 00:01:44.985
Great to be here.
00:01:44.985 --> 00:01:46.068
Wonderful to chat.
00:01:46.381 --> 00:01:47.022
Absolutely.
00:01:47.022 --> 00:01:53.223
It's been too long since we've caught up, so why not do it publicly on this radio show right, this podcast?
00:01:53.223 --> 00:01:56.248
I know you did not start out working in privacy.
00:01:56.248 --> 00:02:07.068
And, at Privacy Plan, where you've been for a while, you've been focusing on data sets - like, specifically, 'privacy data sets,' privacy consulting and privacy training.
00:02:07.068 --> 00:02:17.066
And, your website states that you "research and create data sets about data privacy to gain insight into the privacy landscape.
00:02:17.066 --> 00:02:28.889
Can you give us some context as to what you mean by 'privacy data sets,' maybe your approach to creating them, and what you mean by gaining insight into the privacy landscape?
00:02:29.070 --> 00:02:29.812
Yeah, absolutely.
00:02:29.812 --> 00:02:31.627
I guess that's actually a few questions.
00:02:32.281 --> 00:02:32.903
It kind of is.
00:02:32.903 --> 00:02:33.766
I'm sorry.
00:02:34.923 --> 00:02:37.790
Well, I guess it sort of gets to the core of who I am.
00:02:37.790 --> 00:02:46.028
You know, I sort of grew up in technology and marketing technology, sort of the other side of the equation from privacy.
00:02:46.028 --> 00:03:00.032
I actually worked in a search engine for a long time before I got into privacy, and that was my introduction to it, doing some work in CAN-SPAM and COPPA as part of an SMS-based search engine.
00:03:00.032 --> 00:03:12.210
I won't really go into that because it's a little bit deeper, but I really built a lot of data sets when I was doing that, essentially building out a knowledge graph on the back end of a search engine.
00:03:12.210 --> 00:03:18.612
That's really where I cut my teeth on data science and building data sets.
00:03:18.612 --> 00:03:20.245
I really loved doing that.
00:03:21.021 --> 00:03:28.850
So, when I got into privacy, I really loved the privacy world, but I didn't really want to do what everybody else in privacy did.
00:03:28.939 --> 00:03:32.250
I didn't really want to work on compliance.
00:03:33.441 --> 00:03:50.673
I realized as I was studying for my CIPP/ US that the way I was studying for it was building data sets of privacy laws to study them and building data sets of privacy podcasts that I was listening to, to learn.
00:03:52.181 --> 00:03:58.367
It occurred to me that I like to build structured datasets and then I could do that in the privacy world.
00:03:58.367 --> 00:04:06.711
I just really fixated on that, and I started building massive datasets around different things.
00:04:06.711 --> 00:04:15.687
I've got a huge dataset of privacy laws, like all the privacy laws in the United States, and not just a list of them, all the different attributes and things like that.
00:04:15.687 --> 00:04:20.992
Probably there are law firms and organizations that do that.
00:04:20.992 --> 00:04:32.954
But I built a lot of other things like datasets of privacy podcasts, datasets of all the different aspects of privacy regulators across the world.
00:04:32.954 --> 00:04:44.727
I think I've got maybe one of the largest ones of that and datasets of privacy brokers and all aspects of data breach laws in the United States and all the different things that happen there.
00:04:44.727 --> 00:04:54.786
When we start analyzing those datasets and looking at all the different attributes, you really learn a lot and that's where you get those insights.
00:04:54.939 --> 00:04:59.429
That makes a lot of sense and it definitely explains - you're a "data guy.
00:04:59.429 --> 00:05:24.249
" That's how you got into doing privacy datasets and it shows that people get into privacy from all different angles, whether it's being a developer and coming in and starting to be a privacy engineer writing code, or privacy architects coming over from other spaces to work on privacy, or compliance folks, GRC folks, lawyers.
00:05:24.249 --> 00:05:35.533
You are absolutely the first person that I have ever met that has worked on datasets, which really drew me to you a few years back when I saw the work that you were making public.
00:05:35.533 --> 00:05:49.051
Now I know you recently started working for a company called Avantis Privacy to work on location privacy and deletion; and, I think we're going to center some of our conversation today mostly around 'location privacy.
00:05:49.051 --> 00:05:54.052
' I'd love to hear you elaborate on the work that you're doing there.
00:05:54.480 --> 00:06:03.307
Sure, that was actually a little bit of an outgrowth of what I was doing at Privacy Plan, so sort of still doing it at Privacy Plan.
00:06:03.307 --> 00:06:09.930
As part of my research at Privacy Plan, I built a dataset of data brokers.
00:06:09.930 --> 00:06:15.533
I found that nobody in the world, that appears to me, was really tracking them.
00:06:15.533 --> 00:06:33.930
There are actually a few organizations and, frankly, there are a couple of state laws that require data brokers to register - one in California, one in Vermont, and a couple other states are trying to pass some of those laws now; but, only about a little less than 1,000, probably close to around 800 data brokers, have actually registered.
00:06:33.930 --> 00:06:42.713
But we know, way back in 2014, the FTC estimated there were about 4,000 data brokers probably a lot more now.
00:06:42.713 --> 00:06:48.343
We've actually got a database of 3,000, actually 3,200 data brokers right now.
00:06:48.689 --> 00:06:49.192
Wow.
00:06:50.410 --> 00:07:06.264
Well, painstakingly, I built that dataset over three years now and from a variety of different sources, starting there with that 800 and building it out in a variety of different ways.
00:07:06.264 --> 00:07:21.259
Part of that's proprietary methodology, but a lot of it is just scouring the internet for datasets where somebody says this is a data broker, that's a data broker, and combining every dataset of data brokers I can find and growing it from there.
00:07:21.259 --> 00:07:28.066
Then a lot of people saw the lists and say, "ey, I'm a data broker and these are my data sources.
00:07:28.066 --> 00:07:33.843
If you just keep adding all of that up painstakingly over time, you end up with a lot.
00:07:33.843 --> 00:07:39.384
Sometimes I go into individual markets and say, "okay, well, who are the healthcare data brokers?
00:07:39.384 --> 00:07:40.610
Who are the political data brokers?
00:07:40.610 --> 00:07:41.995
Who are the location data brokers?
00:07:41.995 --> 00:07:48.615
and have to individually, in different market segments, try to find who are the brokers.
00:07:48.615 --> 00:07:49.817
It's just a lot of work.
00:07:50.218 --> 00:07:51.882
Absolutely sounds like a lot of work.
00:07:51.882 --> 00:07:53.334
That's an astounding number.
00:07:53.334 --> 00:08:02.050
I'm not surprised that there's that many data brokers, but I am in awe of the fact that you've been able to identify and kind of tag that many.
00:08:02.050 --> 00:08:09.744
So, with Advantis Privacy, you've been working on helping to delete geolocation data.
00:08:09.744 --> 00:08:13.434
What is your approach there?
00:08:14.456 --> 00:08:24.652
Yeah, so what happened was, as I was building this data broker dataset, one of the guys from Avantis - one of the original two founders there - approached me and wanted to chat.
00:08:24.652 --> 00:08:26.318
I actually did some consulting for them.
00:08:26.318 --> 00:08:29.569
I ended up coming on board with that organization.
00:08:29.569 --> 00:08:32.961
Now I've sort of became a full partner there.
00:08:35.451 --> 00:08:46.760
Avantus' approach originally was to actually be a data deletion service sort of like Incogni, Optery, PrivacyBee, DeleteM e.
00:08:46.760 --> 00:08:51.852
One of the things we realized early on is that nobody was deleting location data.
00:08:51.852 --> 00:09:03.730
Part of that is because the location data brokers, until the FTC sued Kachava last year, really were not letting people delete their location data.
00:09:03.730 --> 00:09:05.474
It was not really an option.
00:09:05.474 --> 00:09:12.278
They all claimed that that data was anonymous and therefore not personal data and not necessarily deleteable.
00:09:12.278 --> 00:09:27.519
They very quickly started putting changes into their privacy policy and throwing up delete pages where you could enter your MAID, maybe email address, and delete that information once the FTC sued Kachava.
00:09:27.519 --> 00:09:33.436
Now it's possible to delete your location data, but people don't know who those brokers are.
00:09:33.436 --> 00:09:37.936
They don't know how to find their MAID, their mobile ID number.
00:09:37.936 --> 00:09:39.961
They didn't even know it's a thing.
00:09:41.310 --> 00:09:54.196
Before this conversation - I've been in privacy; I talk about location data - I didn't even know, but I'm not an expert in brokers, I didn't even know that location brokers were kind of a separate category from a data broker.
00:09:54.196 --> 00:09:55.200
They are.
00:09:55.200 --> 00:10:01.461
Break down the difference there, because that is definitely something I think people would be interested in learning more about.
00:10:01.562 --> 00:10:24.004
Yeah, we've had 150 location data brokers defined that are storing your mobile advertising ID, as well as series of lat-longs - places where you've been: your home, your office, your shopping locations, your church, your gym, every place you've been and all the routes you used to get there.
00:10:24.004 --> 00:10:28.745
They've got all this information and they're selling it frankly to just about anybody with a credit card.
00:10:28.745 --> 00:10:32.721
It's not necessarily quite that easy to buy it, but it's not hard either.
00:10:33.042 --> 00:10:34.466
Yeah, let's explore that.
00:10:34.466 --> 00:10:37.896
What are some of the current risks to our location privacy?
00:10:37.896 --> 00:10:40.140
I know there's a lot to expound on here.
00:10:40.140 --> 00:10:43.394
I'll let you answer first and maybe we'll go deeper.
00:10:43.916 --> 00:10:51.504
Well, there are a lot of risks to your location and a lot of ways that your location leaks.
00:10:51.744 --> 00:11:00.211
We're actually trying to put together a little bit of a categorization system of what those different location risks are and where your location ends up.
00:11:00.211 --> 00:11:07.515
Frankly, your MAID is really only one of those vectors, but it's a very large one and one that people don't really understand.
00:11:07.515 --> 00:11:23.045
That's one of the reasons we're focusing on it, because you can delete your profile information from data brokers and that'll get rid of things like how easily your address is exposed to people search websites.
00:11:23.045 --> 00:11:29.824
That's something that the other deletion services can do reasonably well (maybe not perfectly), but decently well.
00:11:29.824 --> 00:11:33.396
But, they're not getting at this other MAID information.
00:11:33.396 --> 00:11:44.475
Then there are other things where you're exposing your location information in a variety of other ways too, like social media posts.
00:11:44.475 --> 00:11:59.509
your car, when you drive it around, exposes your information, sometimes through your mobile ID information, also through automated license-plate readers and through some other things, like other ways through your car.
00:11:59.509 --> 00:12:13.383
Plus, your phone can also leak some data through cell tower information in a variety of other ways, though they're a little bit harder for non-law enforcement organizations to get at.
00:12:13.630 --> 00:12:14.956
What are the restrictions there?
00:12:14.956 --> 00:12:25.253
Actually, before I get to the restrictions of why it's hard for law enforcement to get at some of this data, I did want to expound upon the risks to our location privacy.
00:12:25.253 --> 00:12:27.837
What are some of the privacy harms that could occur?
00:12:27.837 --> 00:12:29.581
Obviously, there's tracking.
00:12:30.611 --> 00:12:34.690
Sure, actually, I was talking about the types of data rather than the risks.
00:12:35.152 --> 00:12:37.879
Yeah, that's fine, you could switch gears.
00:12:38.430 --> 00:12:38.750
Yeah.
00:12:38.750 --> 00:12:42.158
Well, the risks are, it depends upon who you are.
00:12:42.158 --> 00:12:47.960
If people have your location, if you're an at-risk target, they can do a lot.
00:12:47.960 --> 00:12:50.550
First of all, it's a physical safety risk.
00:12:50.550 --> 00:12:52.436
If people know where they are, they can come and get you.
00:12:52.436 --> 00:13:00.077
If you have enemies, if you have somebody who's pissed off at you because you said something on social media, they can find you.
00:13:00.077 --> 00:13:02.731
They can come after you.
00:13:02.731 --> 00:13:04.196
They can SWAT you.
00:13:04.396 --> 00:13:06.081
We know this is a growing problem.
00:13:06.081 --> 00:13:10.994
They can send people after you, which is bad.
00:13:10.994 --> 00:13:13.420
If you've got a stalker, they can come to your house.
00:13:13.420 --> 00:13:16.013
They can find out where you work and go there.
00:13:16.013 --> 00:13:18.902
They can intercept you on your way places.
00:13:18.902 --> 00:13:31.454
That's a really huge problem for people that are celebrities or athletes or CEOs or people that have got stalkers, domestic abuse victims, things like that certain types of people.
00:13:31.454 --> 00:13:45.956
Even if you just are a regular person, you really don't want your location to be out there, because identity thieves can then use that information to commit crimes in your name.
00:13:45.956 --> 00:13:52.875
If they know where you live and they know lots of things about you, it's much easier to impersonate you.
00:13:52.875 --> 00:13:57.163
Those are a couple of the really biggest risks.
00:13:57.163 --> 00:13:59.396
I guess that's where I'm sort of leave it there.
00:13:59.396 --> 00:14:00.620
There are other ones as well.
00:14:01.911 --> 00:14:07.974
So this might be one you're thinking and holding back, but I do want to bring up the risk of, in a post-Roe v.
00:14:07.974 --> 00:14:51.228
Wade world now where in a state like Texas, with Roe being overturned and with anybody being able to pretty much accuse someone of having an abortion or seeking an abortion which is now against the law in Texas governments can use law enforcement or governments can obtain this data to find someone and prosecute them, or to check and see, maybe through a health app or health data set that they get their hands on can tell that you've been near, or to, an abortion clinic or that you went across state lines to an abortion clinic or something along those lines.
00:14:51.228 --> 00:14:51.589
Right?
00:14:51.589 --> 00:14:51.990
Yep.
00:14:51.990 --> 00:14:57.728
So, law enforcement can even be a threat actor here to one's privacy, which is kind of scary.
00:14:58.120 --> 00:15:01.286
Yeah, law enforcement, or just your neighbor who doesn't like you, right?
00:15:01.286 --> 00:15:32.168
It's pretty scary And, to be clear, it's not just about women that have abortion in those circumstances, right, if you get pregnant, there are just as many circumstances where you don't actually carry the baby to birth, where it's not an abortion, where it's potentially miscarriage or some other circumstance, where it's not an actual abortion, but somebody else who's looking at that from the outside might think it was an abortion when it wasn't.
00:15:32.168 --> 00:15:32.509
Right?
00:15:32.509 --> 00:15:35.108
And, they can accuse you of having an abortion.
00:15:35.108 --> 00:15:35.570
Right?
00:15:35.570 --> 00:15:42.884
And put you through all kinds of circumstance and stress based upon some of these new laws that are put in place.
00:15:42.884 --> 00:15:43.125
Right?
00:15:43.125 --> 00:15:44.946
And, that's pretty horrendous.
00:15:45.600 --> 00:15:45.961
I agree.
00:15:45.961 --> 00:15:53.521
I think there's definitely some fundamental harms that can happen as a result of getting access to that geolocation data.
00:15:53.521 --> 00:16:14.510
So, I guess to that point, I wanted to understand from you whether or not these location data brokers are always getting direct, precise information, or are they also inferring someone's location based on behavior or some other elements?
00:16:15.060 --> 00:16:23.452
So most of the data that we're looking at is actual location data that is based upon your GPS.
00:16:23.920 --> 00:16:24.462
Some of it is.
00:16:24.462 --> 00:16:33.909
It can be Bluetooth, some of it can be Wi-Fi, some of it can be cellular, but generally it's translated and then connected to your mobile advertising ID number.
00:16:33.909 --> 00:16:54.768
They can do inferences and stuff like that as well, and a lot of them do, but oftentimes those inferences, I think, are more like trying to impute whether or not, based upon your path and stops, that you were at a particular place or at another particular place, right?
00:16:54.768 --> 00:17:06.488
I don't know if you've ever been in Google, but sometimes you drive by and you park in a parking lot and it doesn't know if you went to the grocery store or you went to the Dunkin Donuts right next to it.
00:17:06.488 --> 00:17:10.664
That kind of inferences are things that these folks might make.
00:17:10.664 --> 00:17:11.821
Right, did you go there?
00:17:11.821 --> 00:17:15.586
or did you go to the mosque that was in the corner of the shopping mall, right?
00:17:15.586 --> 00:17:25.008
So if you go to a mall that has a mosque in the corner, they might all of a sudden think that you're going there instead of going to the Dunkin Donuts next to it.
00:17:25.799 --> 00:17:27.165
Yeah, that makes a lot of sense.
00:17:27.165 --> 00:17:29.787
And I could see how that can be misused as well.
00:17:29.787 --> 00:17:42.705
You previously said that the geolocation brokers in the past didn't really consider themselves data brokers, and I think you hinted that that's because they had anonymized data.
00:17:42.866 --> 00:17:43.067
Yes.
00:17:43.700 --> 00:17:44.704
And so can you speak to that.
00:17:44.704 --> 00:17:47.648
W hy is anonymization not enough?
00:17:47.648 --> 00:17:57.528
Why does that not take them out of being covered by data protection laws or privacy laws or by the ruling, the Kachava ruling?
00:17:57.528 --> 00:18:02.364
Just speak to us about geolocation and anonymization and some of the challenges.
00:18:02.559 --> 00:18:28.069
Sure, sure, Anonymization has always been a way to essentially avoid privacy laws, And the problem is that for a while now we have known that anonymized data can often be deanonymized, And location data is particularly vulnerable to this kind of re-identification.
00:18:28.069 --> 00:18:47.953
If you take three precise geolocations - especially if it's got a time element attached to it, which all of this stuff does - take three of those data points, or even four, you can identify Americans with 95% to 97% accuracy.
00:18:47.953 --> 00:19:43.085
So, if I have four data points on you, just randomly from some set of location data, Debra, I can identify you 90%, let's say 95% of the time that it's exactly you.
00:19:43.400 --> 00:19:44.104
Yeah, that's crazy.
00:19:44.620 --> 00:19:57.630
Because probably one of those data points is your house, one's your office, and one's you're on the way to work from the highway And I can tell just from looking at those three or four points of data that it's you because it can't be anybody else.
00:19:58.060 --> 00:20:02.144
Right, because it's almost like a behavioral pattern that's being recognized.
00:20:02.440 --> 00:20:03.264
Yeah, that's what it is.
00:20:03.264 --> 00:20:03.545
Right?
00:20:03.545 --> 00:20:06.448
And this is proven, statistically proven.
00:20:06.448 --> 00:20:16.826
There's a couple of articles There's one from two years ago from Nature Magazine that proves this right, and so it's impossible for these people to say that it can't be re-identified.
00:20:16.826 --> 00:20:17.189
Got it.
00:20:17.189 --> 00:20:19.728
But this is actually, we've known this for a long time.
00:20:19.728 --> 00:20:22.469
I think it was back in 2011, 2012,.
00:20:22.469 --> 00:20:30.826
Lantana Sweeney from - I forget where she's from, maybe MIT - has done this research, so we've known about it for a decade.
00:20:31.360 --> 00:20:38.666
Right and yet, because there weren't any regulations saying otherwise, so many ad brokers' responses was just to anonymize.
00:20:38.666 --> 00:20:41.950
And I know you wrote about privacy theater.
00:20:41.950 --> 00:20:52.647
So on LinkedIn I recently saw your post that reads quote location leakage coupled with 'consent theater' is an existential threat to our privacy.
00:20:52.647 --> 00:20:55.663
For many it's a threat to their physical safety and well-being.
00:20:55.663 --> 00:21:00.826
" Can you elaborate on this existential threat and what you mean by consent theater?
00:21:00.826 --> 00:21:04.730
I mean, I have my ideas, but I obviously want to hear from you.
00:21:05.580 --> 00:21:13.589
Yeah, well, the way this information gets collected is primarily from your smartphone, from apps.
00:21:13.589 --> 00:21:13.950
Right.
00:21:13.950 --> 00:21:20.448
You are going to go and load up your smartphone and you're going to turn on a weather app, right?
00:21:20.448 --> 00:21:21.384
Because you want weather.
00:21:21.384 --> 00:21:26.007
You need to know if it's going to rain tomorrow or if it's going to rain in the next 15 minutes.
00:21:26.007 --> 00:21:35.345
I've got a weather app that I use that tells me, when I look at it, if I need to bring out the umbrella in the next 15 minutes, and it's highly accurate.
00:21:35.345 --> 00:21:36.664
It's got great know-it-date on it.
00:21:36.664 --> 00:21:36.966
Right?
00:21:36.966 --> 00:21:52.423
But, it also sends my location to a data broker, and that location is connected to a mobile advertising ID, and it's going to get sold to Venntel and Kachava and Gravy Analytics and a whole bunch of other folks like that.
00:21:52.423 --> 00:21:53.201
Right?
00:21:52.423 --> 00:21:56.044
And what people don't realize, though, is that that's happening.
00:21:56.044 --> 00:22:12.748
That is because they put this weather application on their phone and said, "Yeah, i want this application, that they're essentially agreeing to give their location information to that application; and that application is going to monetize it by selling it to these location data brokers.
00:22:12.748 --> 00:22:29.168
They don't even know that they're there, that this ecosystem exists or that information is going to get sold, and then that information is going to go to anybody that wants to buy it, including law enforcement, Homeland Security, the FBI.
00:22:29.168 --> 00:22:31.846
Anybody can essentially get that data.
00:22:31.846 --> 00:22:32.248
Right?
00:22:32.248 --> 00:22:38.487
And when the government's getting it, they're essentially circumventing the Fourth Amendment because they can get it without a warrant.
00:22:39.480 --> 00:22:43.586
Identity thieves can find easy ways to essentially buy that information.
00:22:43.586 --> 00:22:50.110
If I've got a stalker, that stalker can buy - they can't necessarily buy just my data.
00:22:50.110 --> 00:22:54.467
They can't walk in to a data broker and say give me Jeff Jokisch's location.
00:22:54.688 --> 00:23:09.814
But, if they happen to know what state I'm in, for instance, they could probably buy a swath of data in my state or my city, something like that, and then, based upon that blob of data they got, they could probably figure out who I am.
00:23:09.814 --> 00:23:14.931
If they know a little bit about me and be able to figure out more about me, you know what I'm saying.
00:23:14.931 --> 00:23:22.125
So if they knew, for instance, where I worked and my name, they could probably figure out who I am.
00:23:22.125 --> 00:23:23.450
That makes sense, right?
00:23:23.779 --> 00:23:25.427
Yeah, no, that definitely does make sense.
00:23:25.427 --> 00:23:40.544
And then getting all the consents, the check- the- box that everyone gives to the privacy policy, and just to move forward with installing an app on their phone or on a website, gaining access to or creating an account.
00:23:40.544 --> 00:23:54.410
I'm assuming that that's the consent theater part where we can't possibly manage all of these relationships and understand and remember everyone we've consented to using our data for what purposes.
00:23:57.220 --> 00:23:57.401
Right.
00:23:57.401 --> 00:24:12.452
For me, the consent theater is this: they don't mind giving my location to the weather app right; but, what they're not telling me when I say "OK to that, is what happens to my location information downstream.
00:24:12.452 --> 00:24:27.913
It's completely non-obvious to me or to anybody else that that location information is going to be sold and is going to end up with Homeland Security, with potentially a threat actor, with potentially an identity thief.
00:24:27.913 --> 00:24:29.646
How is that possible?
00:24:29.900 --> 00:24:31.644
Yeah, i mean it shouldn't be.
00:24:31.644 --> 00:24:34.289
I hate data brokers, personally.
00:24:34.289 --> 00:24:42.060
I know that's something that Heidi Sass, who's a member of the Avantis team as well, she's always saying, "I hate data brokers.
00:24:42.060 --> 00:24:44.808
I'm not afraid to say it here.
00:24:44.808 --> 00:24:58.551
For the most part, they're trading on unsuspecting people who may have technically given consent but not really knowing what they're consenting to and using their data, sometimes selling it to their detriment of those people.
00:24:58.551 --> 00:25:04.745
How can people protect themselves from having their data collected and sold by data brokers and location brokers?
00:25:04.885 --> 00:25:07.479
Sure, Well, I mean, there's really two phases to this.
00:25:07.479 --> 00:25:07.660
Right?
00:25:07.660 --> 00:25:10.747
I mean we can help delete the stuff that you've already leaked.
00:25:10.747 --> 00:25:18.099
Avantis can help you delete that historical information, but you've also got to stop leaking the information.
00:25:18.099 --> 00:25:24.537
You've got to stop giving consent to these apps, and that can be a harder thing.
00:25:24.537 --> 00:25:30.072
We're also working on something that may be able to help with that, but that's for a later time in a later show.
00:25:30.601 --> 00:25:55.131
Oh, excellent, because I was going to ask whether you think it's incumbent upon the phone manufacturers who have the, whether it's firmware or software, whatever the pop-ups that are enabled to tell you what a particular app is going to use your data for, I find that those topics 'use it for marketing,' 'use it for customization.
00:25:55.131 --> 00:26:13.125
' I find that the reasons that developers can select are very broad so as not to really tell you the real purpose behind the data use downstream, but more of a category that can be selected just so that they can move forward and start the data collection.
00:26:13.125 --> 00:26:26.255
I feel like it needs to be more granular and or allow apps to be able to notify individuals about a more granular use of personal data.
00:26:26.700 --> 00:26:28.687
Yeah, I definitely agree.
00:26:28.687 --> 00:26:30.673
I mean it needs to be more granular.
00:26:30.673 --> 00:26:35.778
It would be great if there was something that said "ey, we're going to use your data, but we're never going to sell it.
00:26:35.778 --> 00:26:36.140
Right?
00:26:36.140 --> 00:26:37.143
Too.
00:26:37.143 --> 00:26:42.266
So, like I'm going to use it for my marketing, but I'm not going to sell it to anybody who can sell it onward right.
00:26:42.266 --> 00:26:50.288
That would be awesome if I could give my location to my weather app without having to give it to the whole world like that checkbox.
00:26:51.210 --> 00:26:52.774
Yeah, wouldn't we all?
00:26:52.774 --> 00:26:56.769
It seems like that should be the way things are.
00:26:56.769 --> 00:26:57.090
Right?
00:26:57.090 --> 00:27:09.105
Optimizing for the benefit of humans and not necessarily for corporations to exploit them for the purposes of just making money off their data that they didn't consent to.
00:27:09.105 --> 00:27:10.610
So I'm with you on that.
00:27:11.292 --> 00:27:15.343
Yeah, I actually think, Debra, that some of this is changing.
00:27:15.343 --> 00:27:20.445
I think some of this consent theater what I've referred to it as is going to change a bit.
00:27:20.445 --> 00:27:29.861
I think the consent boxes are probably going to change a bit in the next couple of years, and there are companies like Apple that are taking somewhat of a leadership role there.
00:27:29.861 --> 00:27:38.125
In terms of MAIDs, because of the ATT framework that Apple rolled out, there are a lot of people that have opted out of that.
00:27:38.125 --> 00:27:49.102
So there are less people on the Apple operating systems - iOS - that have their mobile advertising IDs turned on now than on Android, for instance.
00:27:49.102 --> 00:27:50.004
That's good.
00:27:50.004 --> 00:27:50.305
Right?
00:27:50.485 --> 00:27:55.086
However, a lot of those people still have a lot of historical location data out there.
00:27:55.086 --> 00:28:01.812
So, even if you're running an iPhone and you're like, "h yeah, well, I turned off my mobile advertising ID Well, that's awesome right.
00:28:01.812 --> 00:28:10.521
Except, even if you turned it off, you know, like six months ago, all the data that you let those companies collect for years is still sitting out there.
00:28:10.521 --> 00:28:21.723
Now, some of it might be older and maybe less valuable, but if you still live in the same house, go to the same office, go to the same routes, all that data is still sitting out there for somebody to use against you.
00:28:21.923 --> 00:28:23.727
So, that's a really great point.
00:28:23.727 --> 00:28:28.284
All it does is stop the data collection, but not necessarily purge it.
00:28:28.284 --> 00:28:48.571
So, how could individuals gain more control over their own data, especially if we don't have a unified at least in the United States, we don't have a equivalent of a GDPR And we just have some states, like California's DCPA and a few other states that have kind of followed suit with the privacy law.
00:28:48.812 --> 00:29:03.682
Well, like this, Avantis can help you try to purge that data with our location purge, because with Apple, you can actually go back in, turn your MAID on, grab that MAID number, send it to us, and we can purge that information for you.
00:29:03.682 --> 00:29:07.092
It's actually harder on Android.
00:29:07.092 --> 00:29:15.856
So, on the Android devices, only 3% of people roughly have turned off their mobile advertising ID, which is sad.
00:29:15.856 --> 00:29:25.486
However, there's a problem on Android, and that's this: if you have turned off your advertising ID, there's no way to know what it used to be.
00:29:25.486 --> 00:29:31.605
So, all of that historical information is now no longer reachable.
00:29:32.105 --> 00:29:45.669
So, you can't turn your Android ID back on, figure out what it was and then send that MAID to us so that we can delete that past history unless you can figure out some other way to figure out what your ID was.
00:29:45.669 --> 00:29:48.440
It's like unreachable historical data.
00:29:48.440 --> 00:29:49.241
You know what I'm saying?
00:30:02.749 --> 00:30:07.930
Yeah, well, that's definitely, security-wise, that's a data availability problem now, potentially.
00:30:07.930 --> 00:30:16.733
I mean, arguably, could that be a good thing, like it's no longer identifiable potentially, or is it still going to get bought and sold?
00:30:17.060 --> 00:30:24.667
Still going to get bought and sold, and somebody, anybody who grabs more than three or four points of data can re-identify it and figure out it's you.
00:30:24.967 --> 00:30:25.208
Right.
00:30:25.208 --> 00:30:37.750
So if somebody deletes their ID off of Android, are you basically saying that Google will still track that ID even though that person is no longer - it's not considered "Let's purge that data.
00:30:37.750 --> 00:30:38.733
It's not good anymore.
00:30:39.720 --> 00:30:40.142
It's nothing.
00:30:40.142 --> 00:30:41.766
Google's tracking you, right?
00:30:41.766 --> 00:30:49.009
Because at that point, Google's no longer sending new information based upon any mobile advertising ID.
00:30:49.009 --> 00:30:55.961
But, they've already sent it out, right, and those brokers have collected it and it's sitting in their data sets, got it?
00:30:55.961 --> 00:30:57.544
That makes sense.
00:30:57.544 --> 00:31:07.372
So if you re-enable your mobile advertising ID, it generates a new one, so then they can start tracking you again, but it's based upon a new mobile advertising ID.
00:31:07.641 --> 00:31:08.666
I see, I see.
00:31:08.666 --> 00:31:19.127
So, I think we've been talking about how Avantis can help people protect themselves from having their data bought and sold and how to request purges be made.
00:31:19.127 --> 00:31:21.234
But what about organizations?
00:31:21.234 --> 00:31:25.893
What can they do better to protect people's privacy when collecting and using geolocation data?
00:31:26.215 --> 00:31:31.275
So if you're talking about like a commercial interest, I think that's pretty interesting.
00:31:31.275 --> 00:31:40.882
We're actually talking with some organizations now about how they need to start thinking about this from a threat mitigation situation.
00:31:40.882 --> 00:32:02.027
And, especially if you're talking about people that maybe targets in your organization for attack you know whether it's the C-suite or your IT personnel or other vulnerable individuals where you know attackers might come after them, they're going to come after them based upon information that they can find that's publicly available, right?
00:32:02.027 --> 00:32:11.532
So some of them are actually, you know, going to these data deletion companies and trying to delete all their information on their C-suite employees, their IT employees.
00:32:11.532 --> 00:32:17.195
Frankly, they should probably be doing it for all their employees, but at least those ones that are most vulnerable.
00:32:17.195 --> 00:32:26.241
But, right now, they're ignoring all the location data, right, which is a big vulnerability, so they should be thinking about deleting that location information as well.
00:32:26.241 --> 00:32:27.426
It's a big hole.
00:32:27.686 --> 00:32:28.348
Yeah, definitely.
00:32:28.348 --> 00:32:31.746
That sounds like a real security challenge for corporate security.
00:32:31.746 --> 00:32:33.432
And I do appreciate the answer.
00:32:33.432 --> 00:32:41.781
But, what I was trying to get at is should companies, for instance, not collect geolocation data in the first place?
00:32:41.781 --> 00:32:44.125
Oh, I see what you're saying.
00:32:44.125 --> 00:32:47.313
Or is there a way to do this in a more manageable way?
00:32:47.313 --> 00:32:55.771
If they do collect it, is there like a privacy enhancing technology or architecture that can be used to better protect the privacy of people?
00:32:55.871 --> 00:32:59.249
You know, I'm not sure if I've got a great answer to that.
00:32:59.249 --> 00:33:15.466
I think maybe the best way to be careful with that data is to not collect the precise geolocation, but collect more vague geolocation information, because generally you don't actually need that data to be precise.
00:33:15.846 --> 00:33:21.045
Is it more like people would want to know what state you're in and that's the level?
00:33:21.045 --> 00:33:24.692
Or, could it go deeper than that and be county and be okay?
00:33:25.400 --> 00:33:27.686
Yeah, I mean that's not bad, right?
00:33:27.686 --> 00:33:40.842
I mean, if you can pinpoint it down to a house level, I'm not even sure what the actual fine- grained level is that's problematic, right?
00:33:40.842 --> 00:33:52.106
But, if you were to blur that data out so that was within miles instead of feet, you probably would not have an issue with it, right?
00:33:52.106 --> 00:33:58.671
If it was within like a mile radius and probably if you're in urban or rural areas.
00:33:58.671 --> 00:34:04.731
But it's not going to really change my weather report, and it's probably not going to change a lot of other things.
00:34:04.731 --> 00:34:12.704
Maybe it changes it for the people that are trying to figure out what store you're going to, which could be problematic for certain applications.
00:34:12.704 --> 00:34:18.322
But for a lot of use cases you don't need precise geolocation, but they're storing it anyway.
00:34:18.643 --> 00:34:19.365
Yeah, that makes sense.
00:34:19.365 --> 00:34:20.007
That's helpful.
00:34:20.007 --> 00:34:27.510
I do wonder, and if people here are listening, maybe there's an opportunity to specifically focus on location data.
00:34:27.510 --> 00:34:50.782
I know Privado, the sponsor of this podcast, actually does quite a bit of making sure that - you could scan your code to make sure that location data is behaving as intended and you're not actually collecting sensitive data when you didn't want to be as an organization or it can put you into risk or harm privacy.
00:34:51.364 --> 00:35:02.041
But it seems to me that there is definitely an opportunity out there to educate companies on how to protect people and not harm them, especially when it comes to geolocation and precise data.
00:35:02.041 --> 00:35:33.153
Perhaps it's as you say, that you get not precise geolocation data but work with a statistician or somebody who can take a look at making sure that data is not identified or re-identifiable, making sure that the granularity is not going to harm individuals, and kind of do that threat identification and threat model for the product beforehand, before you ever ship.
00:35:33.153 --> 00:35:34.463
That will do wonders.
00:35:34.463 --> 00:35:48.325
And you could refer to people listening, you could refer to the previous episode on threat modeling with Kim Wuyts and learn a little more about the threat modeling approaches and when you should do that.
00:35:48.325 --> 00:36:02.251
But, I do think that having the right experts on board to help with whether or not this meets privacy bars and not just compliance, but can actually protect the people behind the data is pretty essential.
00:36:02.371 --> 00:36:03.635
Yeah, I definitely agree.
00:36:03.635 --> 00:36:11.592
I think if you change the granularity, you could vastly decrease the reidentifiability of the location data.
00:36:12.860 --> 00:36:13.242
Excellent.
00:36:13.443 --> 00:36:15.311
And it might not be that hard to do, actually.
00:36:15.311 --> 00:36:23.726
I mean, if you have lat- longs, you could just lob off the last few decimal points potentially, and you'd be there.
00:36:23.930 --> 00:36:23.930
Fascinating.
00:36:23.930 --> 00:36:27.988
Well, it's good to know You don't think it's too complex.
00:36:27.988 --> 00:36:32.903
Hopefully this is some food for thought for the privacy technologists in the audience.
00:36:32.903 --> 00:36:51.775
Jeff, is there anything else, any other resources that you would point people to if they're concerned about data brokers or location privacy; or you could also plug your website for learning more about privacy data sets.
00:36:52.657 --> 00:36:57.226
Yeah, well, I think there's a lot of stuff on Privacy Plan about data sets.
00:36:57.226 --> 00:37:02.923
I'd also say follow me on LinkedIn; I do a lot of posts there.
00:37:04.027 --> 00:37:07.255
I also promote a lot of other people there.
00:37:07.255 --> 00:37:09.702
And check out "rivacy podcasts.
00:37:09.702 --> 00:37:21.791
I've been a little bit negligent, but I maintain a huge data set of privacy podcasts And, frankly, Shifting Left is finally in the data set, so that'll be awesome.
00:37:22.253 --> 00:37:27.911
And yeah, I'm going to be doing a Top 10 list here in the next couple of weeks.
00:37:27.911 --> 00:37:41.173
Debbie Reynolds has been on me to redo that because I haven't released one for a while, and I think there's something like 200 privacy- focused podcasts in my data set.
00:37:41.554 --> 00:37:42.757
That's just so wonderful.
00:37:42.757 --> 00:37:45.407
I really look forward to that when that comes out.
00:37:45.407 --> 00:37:45.929
I've seen the list.
00:37:45.929 --> 00:37:52.268
And I have looked at the database and I'm really glad that you finally added S hifting Privacy Left.
00:37:52.268 --> 00:37:53.351
We're relevant!
00:37:55.916 --> 00:37:56.760
You're actually not relevant.
00:37:56.760 --> 00:37:58.686
You're actually high up there now too.
00:37:58.686 --> 00:38:03.863
So, I haven't actually pushed the top lists, but you're in there, so that's awesome.
00:38:04.124 --> 00:38:05.027
Oh, that's excellent.
00:38:05.027 --> 00:38:06.413
It's really great to hear.
00:38:06.413 --> 00:38:09.643
Like I said, I'm really looking forward to seeing that.
00:38:09.643 --> 00:38:11.146
And what else?
00:38:11.146 --> 00:38:17.965
Before we go, let me have you discuss a little bit of your podcast, "our bites, your rights.
00:38:17.965 --> 00:38:28.193
Do you mind just giving us a little overview about the types of things you discuss when it takes place, and how people can participate?
00:38:28.360 --> 00:38:35.664
Yeah, we've actually been on hiatus for a bit, but Christian Kameir and I are going to be ramping that back up.
00:38:35.664 --> 00:38:41.922
We actually had an episode a couple weeks ago and hopefully we're going to get back on a weekly rhythm.
00:38:41.922 --> 00:38:57.724
But, Your Bytes, Your Rights is sort of a weekly interdisciplinary discussion on data rights And we focus a lot on privacy and data ownership and sort of all the stuff that goes around with that.
00:38:57.724 --> 00:39:11.860
We try to bring in people from not only privacy, but just all kinds of different related disciplines to talk about how we can better own and demand our rights to our data.
00:39:12.242 --> 00:39:22.313
Yeah, and I've participated in several of those discussions and I've been really enlightening and engaging with other experts in the field, and so I encourage others to attend them.
00:39:22.313 --> 00:39:26.389
Once you get them going again, no worries taking a hiatus.
00:39:26.389 --> 00:39:28.432
I took a few off this summer myself.
00:39:28.432 --> 00:39:41.842
There's just so much going on in the field that we just have to remember that we're human and we can only - we need to rest at times, and you can only get done when you get done, but I look forward to participating again.
00:39:42.125 --> 00:39:44.854
Yeah, absolutely, you were great when you were on.
00:39:44.854 --> 00:40:02.047
We just finished up an episode with Tom Kemp about the DELETE Act in California, which may finally have a regulation with some teeth in it on data brokers.
00:40:02.721 --> 00:40:03.646
Yes, that's wonderful.
00:40:03.646 --> 00:40:09.409
He's going to be on the show in a week and a half, maybe two weeks actually in the recording times, yeah.
00:40:09.650 --> 00:40:09.971
Awesome.
00:40:09.971 --> 00:40:10.612
Well, that'll be great.
00:40:10.612 --> 00:40:13.817
Well, then you'll have all the details on the DELETE Act.
00:40:14.200 --> 00:40:16.965
On the DELETE Act, as well as his new book.
00:40:16.965 --> 00:40:22.213
"Privacy and Big Tech, which is definitely an interesting book.
00:40:22.213 --> 00:40:24.626
We'll talk a little bit more about that when he's on the show.
00:40:24.626 --> 00:40:30.470
Then he's also a seed investor for a whole bunch of privacy tech companies.
00:40:30.470 --> 00:40:34.927
He's a very interesting individual, and I really look forward to having that conversation.
00:40:34.927 --> 00:40:40.921
Yeah, I love it that we're talking about similar things, you and I, but taking different tacks.
00:40:40.921 --> 00:40:53.157
You have this town hall style engaging show where anyone could join the LinkedIn Live event and then ask questions or join within that format.
00:40:53.157 --> 00:40:53.960
I love it.
00:40:53.960 --> 00:41:02.686
It's all complimentary and really enjoy the value that you bring to the field, especially your enormous focus on data sets.
00:41:02.686 --> 00:41:11.880
Until you came on the scene, I hadn't seen anybody else doing that hard work of pulling it all together and then making it pretty accessible publicly.
00:41:11.880 --> 00:41:13.204
Well, thanks for your work.
00:41:13.264 --> 00:41:13.927
I appreciate that.
00:41:13.927 --> 00:41:17.327
Hopefully we'll put out some new ones and some big ones soon.
00:41:17.729 --> 00:41:18.271
Great, Jeff.
00:41:18.271 --> 00:41:24.172
Do you have any other words of advice or anything you want to leave our listeners with before we close?
00:41:24.619 --> 00:41:25.300
I think.
00:41:25.300 --> 00:41:30.731
Just some kudos to you for Shifting Left, loving the new podcast.
00:41:30.731 --> 00:41:31.713
Thanks for all you do.
00:41:32.221 --> 00:41:34.648
I really appreciate that very much.
00:41:34.648 --> 00:41:35.905
It's a lot of work.
00:41:35.905 --> 00:41:41.771
I got a lot of personal value and pleasure out of having these conversations.
00:41:41.771 --> 00:41:43.284
Thank you for being on the show.
00:41:43.284 --> 00:41:45.846
I'm sure I'll have you back on in the future.
00:41:45.846 --> 00:41:48.224
There's just so much going on in this space.
00:41:48.224 --> 00:41:54.570
Good luck to you on Avantis and the new consumer location privacy and deletion tool.
00:41:54.570 --> 00:41:56.985
I'll be paying attention.
00:41:56.985 --> 00:42:05.606
If people wanted to reach out to you and collaborate or ask questions, is LinkedIn the best place or is there somewhere else that they can go?
00:42:06.740 --> 00:42:08.726
LinkedIn is probably the easiest way to reach me.
00:42:09.048 --> 00:42:09.389
Excellent.
00:42:09.389 --> 00:42:13.106
Well, I'll put a link to that in the show notes and you can have a great day.
00:42:13.106 --> 00:42:14.050
All right, take care.
00:42:14.050 --> 00:42:21.485
Thank you for joining us today on Shifting Privacy Left to discuss privacy, data sets, location privacy and data brokers.
00:42:21.485 --> 00:42:25.947
Thanks for joining us this week on Shifting Privacy Left.
00:42:25.947 --> 00:42:28.284
Make sure to visit our website, shiftingprivacyleft.
00:42:28.284 --> 00:42:34.981
com, where you can subscribe to updates so you'll never miss a show While you're at it.
00:42:34.981 --> 00:42:46.847
If you found this episode valuable, go ahead and share it with a friend, and if you're an engineer who cares passionately about privacy, check out Privado: the developer-friendly privacy platform and sponsor of this show.
00:42:46.847 --> 00:42:49.164
To learn more, go to privadoai.
00:42:49.164 --> 00:42:53.387
Be sure to tune in next Tuesday for a new episode.
00:42:53.387 --> 00:42:54.161
Bye for now.
