Privacy in the Age of AI: DeNet x The Hated One

Yeah, thank you. Thank you for joining. And we also have Rita, a developer at Dnet who'll bring the engineering perspective to some of the questions we'll discuss today. Rita, hello. Hi, everyone. Thank you very much for having me. Yeah, I'm a protocol engineer at Dnet. You may already know that Dnet is a decentralized storage network. And we built a protocol behind it plus the apps that make the network work. So I do every day with who can access our data and how to protect it. So that's the perspective I'll share tonight. Thank you. Thank you, Rita. Yeah. And before we dive in, so thank you Rita for the introduction. And I wanted to have some kind of little intro from the hated one as well. So like for anyone who is discovering your work today, could you tell us a little about what got you interested in digital privacy? So I think yeah, that's make the trick. Yeah, I started following the privacy scene ever since this node on leaks as well as with the Chelsea Manning links. They happened quite at the same time period. And it was quite shocked by both the revelations about the US government and all of their allies, how they are surveilling everybody and also using the surveillance powers to then murder people without any judicial oversight. And I wasn't really technical before then, but I really wanted to find solutions. And I realized that as I was learning myself, that the solutions themselves are quite approachable, that even someone like me could understand them and deploy them for myself. I wanted to teach everybody that they can do that as well. And they could be empowered. And I thought that the best way to do this would be through what was at a time, the second largest search engine that was YouTube. And I wanted to give people my ability to provide these in depth essays and combine with tutorials to help them understand the problem. And as well as understand the solutions, that they can also do implement, they can implement all of those solutions themselves. That I need to be worried about, that it need to be on the at-roots-known level of technical understanding. And that's what has motivated my work for the past 10 years. And so I hope that it will continue to do so in the future as well. Thank you, that's impressive. Like 10 years and starting from learning to teaching, that's really great. Thank you for sharing that. Yeah. So yeah, I think let's start with where things stand today. So we are going to discuss a few topics today, but all connected to the privacy in the age of AI. And I think the best one to start will be about how is it changing over days? Like are people becoming more aware of privacy and the value of their personal data? Or is the thing like not changing at all? So the hated one, I would give the word to you. So do you think people are becoming more aware of privacy and the value of their personal data? And yeah, how the things change in the past years, maybe in the past 10 years, as you started it like long time ago. Yeah, what's your take on this? I would say that things have definitely changed because the original scene started with, oh, it's just a conspiracy theory. And they would never do this. And then it was all confirmed that they actually do do this. And they are very happy about this. And they will just break all the laws and constitutional amendments in order to achieve that mass surveillance goal. And it took a while for all of that to kick in. Fortunately, with this note and leaks, we had a lot of coverage of that. But it wasn't really until recently when we've had the mainstream leak had shopped to how vast the surveillance state as well as the sort of the corporate sector, or the corporate part of that surveillance state, how large that is. And now I would say that, yeah, more people are aware that this is a problem. But I think they are not aware to what extent this is a problem to them individually. And I think the problem is that a lot of people basically conceptualize these very complex topics through meme and pop culture. So sort of like the the flock surveillance that became a meme, but it's just the flock, right? When we have dozens of other companies that do exactly the same thing, and flock cameras are just one brand of these cameras. So the problem really is much broader that we have this level of surveillance deployed and it's a whole industry, it's a business model. That's what we need to tackle. And unfortunately, it is just memes, how people are destroying the flock property in the cameras. And that's all amazing, but it's just not getting to the root of the problem. And similar meme is the Palantir Technologies Company, where it's just a reincarnation of evil. And it's just so comically ridiculous, how open they are about their intentions and plans. But Palantir is just another brand, another company that is just part of this massive industry, that is proliferating this data-brokering market. And it is monetizing and profiling everybody. And it's just hundreds or even thousands of companies that are doing this nowadays. And if Palantir did not exist, we would have another company that we're doing the exact same thing as Palantir is doing. So I find it quite positive and fortunate that we have more people, especially the Gen Zs and the younger generations that are aware of them, of the threats that the technologies oppose to them and to all of us. But I still feel like that people are not simply aware that the solutions are available to them. They are easy enough to learn and adopt. And also that this is something that affects everybody, not just people that might be high-value targets or people that might be persecuted by some kind of an authoritarian government. But this affects every single one of us. Yeah, thank you. So I think the first step is understanding the problem. Yeah, and after that, of course, we can start changing the behavior of what we do in everyday life. So do you see actually that this growing awareness has actually translated into changes in people's behavior? Or it's just a awareness at this point of time? I think that people are changing their behaviors and it's also due to their discontent with the current situation. I mean, people are going through multiple crises at the same time. The most immediate one is the cost of living crisis. And they're trying to take matters into their own hands. So people are taking action. There are more sign-ups on signal. More people are organizing over encrypted apps. There is more maybe cloud over the decentralized apps as well. Although it's nowhere near the levels where we need them to be at. And it's not even posing a threat to the mainstream centralized tech. But it is growing. I have to admit that there is a tension there. And in fact, people are looking for some solutions even if they don't know where to find them. But these blogbuster apps like Signal, they are breaking that curtain that prevented people from seeing that. So I hope that I answered that question. Yeah, thank you. Thank you. So yeah, actually it's great. That's because with every piece of news that we have, I think the awareness grows. And when you have these pieces of news like more and more every day, it's like, you can't sit still, let's say you start taking actions. You start looking for solutions. So yeah, and this is where are we standing nowadays. And of course, one of the biggest developments affecting all of these problems that you mentioned already. This is obviously AI, AI development, AI technology. So and we have been generating like enormous amounts of data. And it's like growing every day. But the ability to analyze it and connect that information like is changing really quickly with the development of AI. So what would your take be? Like how is AI changing data collection? And how is it changing the profiling you already mentioned? Yeah, this is a very powerful distinction that's happening right now. We've had the data collection that's been happening for maybe like two decades by now. That's been that's been progressively more and more dystopian and it's just collecting everything. But it was much more difficult to process all of the data and to find patterns on on regular basis and to have the frequency of targeting individuals like they always wanted to but they just didn't have the tools. Well, now they have the tools and it's in the AI. And what the AI enables is that it actually speed runs the process of finding the patterns in behaviors and in individuals. And that has multiple layers of applications. So one of these is you can just look for routes and figure out certain patterns. So what they want to do in certain applications is, for example, if you have people at a train station, they would want to find those that are just lingering in our nervous. So they would want to identify some potential or criminal suspects or maybe some somebody who is fleeing a scene or somebody who's stolen something and they just want to identify that person. But obviously this is something that will also be able to use to identify and then track those targets across across their entire movements. So nobody would be able to hide, to escape authorities and at first glance, like this sounds like it's a great thing because you would be able to always find the missing persons and you would always be able to go after the criminals. But you can also go after the dissidents. You can also use this technology to go after people that criticize the government the wrong way or criticize the corporation the wrong way. I mean, there are so many whistleblowers that have died recently that came from the corporate set-tracking. That's pretty coincidental how many times that have happened. And it's becoming more and more difficult for people to even organize because now you can have these behavioral AI that would be deployed into surveillance cameras in the streets. And you can just disperse any kind of gathering or rally before it even becomes big enough to become a problem for the people in authority or in position of power. And another way that AI helps to boost the data collection is that it incentivizes this sort of collecting because even the corporate sector is benefiting from it greatly. One of my recent deep dives into this application was when McDonald's had this thing where it would be ranking their customers' behaviors and it would try to predict what they would order at what frequency and when and where and all that stuff. And they would have like multiple hundreds of pages per every individual customer, which is way more than it would have in a high profile FBI case. And all of that was using AI to get to these sort of so-called consumer scores. And consumer scores have existed for about a decade now as well. But now with AI, any company can do this. And it's McDonald's which has not been a big tag or big data company whatsoever. It's a retailer. But now it is also a data company. And they seek to generate dozens of billions of dollars a year off of this new profiling scheme. What's going to come next is you will see this application of AI on surveillance in personalized pricing. And if that happens, then we'll no longer see price stacks in grocery stores, but everyone will be basically asked to get an app. And on that app, you will see personalized pricing on individual items based on characteristics and behavioral archetypes and other psychological traits or perhaps even essentialist traits and things like your demographics and zip codes and income to figure out what you should get and how much you should pay for it. And this is also going to be used in the labor market where wages and promotions and who is going to be the candidate for the job is not going to be decided based on the merit, but based on calculations that include your current financial status, your distress, your price-paying tolerance and all these things that have nothing to do with how well you will perform at the job, but how desperate you are in your economic situation. So they'll be using AI to pick those kinds of workers that are more likely to be submissive, that are less likely to ask for a raise, more likely to stay at the job because of those things that have nothing to do with the qualification, education or other factors of merit. And so the last thing that AI is actually boosting that the data collection is that it opens up possibilities that were in there before. So for instance, facial recognition has always been a threat but facial recognition had a problem that it really required good conditions for the cameras to pick up the face properly in order to identify the person. Like even at the airport, like half the time, he doesn't even work. But now with street level surveillance, you have bad lighting, you have cameras from high angles or too low angles or they're just way too far. So you have things like grain or noise introduced into the camera and also atmospheric turbulence is distorting the image. So it's harder and harder to identify a person as they go by through the street and they're exposed to these cameras. But now with AI, there is actually in the United States, there's this government database called Breyer Database that has been...