Sandra Matz: The Personal Data Privacy Crisis

29:27So once your data is out there, it's almost impossible to get it back. And you don't know what's going to happen tomorrow. Even if Zuckerberg is not willing to share the data, there could be a completely new CEO tomorrow who might be a lot more willing to do that. So I think that the notion that we don't have to worry in the here and now about our data being out there is just a very short-sighted notion. And ideally, we can find a system, and I think there are ways now, in which we can get some of these perks and some of the benefits that come from using data without us necessarily having to collect the data in a central server.

30:03Okay, so if I'm listening to this and I'm scared stiff because, you know, yes, you could look at what I do. You could look at I went to the synagogue or I went to the, you know, temple or whatever. So yeah, and you're right. Any of those people could replace and who knows. So then what do I do? I do think that people should be to some extent scared. So I'm really trying to not say that technology, it's all, like we're all doomed because the data is out there and technology can be used to many. But I think there's like many good use cases. But I do think we should be changing the system in a way that protects us from these abuses.

30:41And the one thing that I describe in the book, which I think we're actually seeing a lot more of, but just not that many people know of, are these technologies that allow us to benefit from data. without necessarily running the risk of a company collecting it centrally. So what I mean is, and there's a technology that's called federated learning. And you can imagine the example that I give is take medical data. So if we want to better understand disease and we want to find treatment that work for all of us, not just the majority of people who usually the pharma companies collect data of, but like we want to know, given my medical history, given my genetic data, here's what I should be doing to make sure that I don't get sick in the first place, or I can treat a disease that's either rare or not as easily understood, we would all benefit from pooling data and better understanding disease.

31:31Now, there's a way in which you can say, instead of me sending all of this data to a central server, and now this entity that collects all of the data, they have to safeguard it, same way that Facebook is supposed to safeguard your data against intrusion from the government, instead of having to sit in the central server, what we can do is we can make use of the fact that we all have supercomputers, right? That might be your smartphone. Your smartphone is so much more powerful than the computers that we used to launch rockets to space a few decades ago. So what this entity that's trying to understand disease could do is they could essentially send the intelligence to my phone or ask questions from my data and say, okay, here's like how we're tracking your symptoms.

32:11Here's what we know about your medical history. but that data lives on my phone. And all I'm doing is I'm sending intelligence to the central entity to better understand the disease. Apple Siri, for example, is trained that way. So instead of Apple going in and capturing all of your speech data and centrally collecting it, right now Apple would be one of these companies who has to protect it now and tomorrow. And they just send the model to your phone. So they send Siri's intelligence to your phone. It listens to what you say. It gets better at understanding, gets better at responding. And instead of you sending the data, it essentially just sends back a better model.

32:48It learns, it updates, sends back the model to Siri, and now everybody benefits because we have a better speech. And that's a totally different system, because we don't have to collect the data in a central spot and then protect it. But Sandra, I mean, the point that you just made is that, yeah, Tim Cook may be saying that to us now, we're only sending you the model and all your data is staying on your phone, but tomorrow's Apple CEO could have a very different attitude, right? So how do we know if they're only still sending the model right now? So I think it's a great question. And it's funny that you mentioned Apple in that space, because I think they're thinking about it this way.

33:27So again, I would much rather have Tim say, we're only going to locally process on your phone. And that even if they change it tomorrow, What I'm mostly worried about is that they collect my data today under Tim Cook with the intention of making my experience better. They collect it today and then tomorrow there's a new CEO because now that CEO can just go back into the existing data and make all of these inferences that we talked about that are very intrusive and we don't want to be out there. At least, even if Apple decides tomorrow to shift from that model to a new one, that's going to be publicly out there.

34:00So if that happens, at least people can start from scratch and decide whether they still want to use Apple products or not. My main concern is that all the data that gets collected and now leadership changes. Wow. Okay, speaking of collected data, you mentioned an example of a guy who applied to a store and he took a personality test. And the personality test yielded, let's say, undesirable traits. and so he didn't get that job and that personality test stuck with him and you know kind of hurt his employment in the future too so what's the advice don't take the personality test or lie on the personality test what's the guy supposed to do if he's required to take a personality test to apply for a job yeah and you're really going to all the dark places but i think which i think is important Because for me, this example, and this one is not even using predictive technology, right?

34:59So this one is a guy sitting down and admitting that I think in his case, he was like suffering from bipolar disorder. So it kind of sends the score on neuroticism, which is one of the personality traits that kind of says how you regulate emotions through the roof. And because he admitted to that, he was essentially almost discarded from all of the jobs that had like a customer facing interface because companies were worried that he wouldn't be dealing well with people who come in and complain. Now, the reason for why I think this example is important is it just means who other people think we are kind of closes some doors in our lives, right?

35:36Sometimes it opens doors. If someone thinks that you're the most amazing person and you absolutely deserve a loan, maybe you have opportunities that other people don't have. But oftentimes the danger comes in when someone thinks that we have certain traits that then would lead to behavior that we don't want to see. And now in the context of self-reported personality tests, at least you have like some say over what that image is. If you take it to an automated prediction of an algorithm and coming back to this notion that those algorithms are pretty good at understanding of psychology, but they're certainly not perfect.

36:10So now you suddenly live in a world where someone make a prediction about you based on the data that you generate. You never even touch that prediction because you don't even get to see it. They predict that you're neurotic. and maybe they even get it wrong. Maybe you're one of the people where the algorithm makes a mistake and gets it wrong. And now you're suddenly, you're excluded from all of these opportunities for jobs, loans, and so on. And so I think for me, this notion that there's someone who passively tries to understand who you are and then takes action, that again, sometimes open doors.

36:40Sometimes it's incredibly helpful because maybe we connect you with mental health support. But at other times, it might also close doors in a way that you don't even have insights to. And for me, that's the scary part where I feel like we're losing control over essentially our lives. Wait, but are you saying that you should refuse to take the personality test or you should lie? So in the case of the personality test, first of all, it's not a good practice. So as a personality psychologist, the way that we think of these personality tests is that it shouldn't be an exclusion criteria. So I think that what they're meant to do is to say, here's certain professions that you might just be more suited for.

37:23Because if you're an introvert who kind of hates dealing with other people and you're constantly at the forefront of like a sales pitch, you're probably not going to enjoy it as much. They were never really meant to say, you got a low score on conscientiousness and we're going to exclude you. it's also very short-sighted because technically what makes a company successful and what makes team successful is to have many people who think about the world differently so i have this recent research that's still very preliminary but it's looking at startups and it just looks at how quickly do they manage to hire people with all of these different traits so you can come together and you can say well but i think this way and then you think this way and we all bring a different perspective to the table and they're usually more successful so this notion that companies just say here's a trait that we don't want to see, is very short-sighted.

38:10What we do know, and I promise coming back to your question, is that saying that you don't want to respond to a questionnaire is typically seen as the worst sign. So there was this study where they looked at things that people don't like to admit to. I think it was stuff about health, stuff about people's sexual preferences. And saying, I don't want to answer the question, is worse than hitting the worst option on the menu. So I absolutely agree that in that case, The guy essentially didn't have a shot. But the problem is once it's recorded, he didn't even get to take the test again because the results were just shared from company to company.

38:47So what I hear you saying is lie. In this case, frankly, if it had been me, I probably would have lied. And if I had known that this is if the company is making the mistake of using the test in that way, what I would recommend to people taking the test is, yeah, like think about what the company wants to hear. Okay. Which is harder to do with data, by the way. It's funny because oftentimes when we think of predictions of our psychology based on our digital lives, we think of social media and it's always that I can to some extent manipulate how I portray myself on social media. That's true for some of these explicit identity claims that we think about and have control over.

39:31There's so many other traces. Take your phone again. The fact, like, my thing is that I'm not the most organized person, even though I'm German, so I think I was expelled for a reason. I don't organize my cutlery the way that my husband does. Would I admit to this happily on a personality test in the context of an assessment center? Probably not, right? If someone gives me the question there that says I make a mess of things, would I be inclined to say I strongly agree? Maybe not because I understand that's probably not what they want to hear. Now, if they tap into my data, they see that my phone is constantly running out of battery, which is like one of these strong predictors of you not being super conscientious.

40:11I constantly, I go to the deli on the corner five times a day because I can't even plan ahead for the next meal. And I constantly run to the bus. So if someone was tapping into my data, they would understand 100 % that I'm not the most organized person. And so there's something about this data world and all of these traces that we generate, which are in a way much harder to manipulate than a question on a questionnaire. Well, and now people listening to this podcast are thinking, how many times did I use the pronoun I? Oh, my God. I'm telling people that I have, you know, depression and stuff.

40:49And again, it's not deterministic. So you might be using a lot of I because something happened that you want to share. It's just like on average, it increases your likelihood. Up next on Remarkable People. If I wanted to get a portfolio, a data portfolio on most of the people, I would be able to get it really cheaply. And that's something that, again, I think most of us or all of us should be worried about. And you do see use cases where policymakers are actually waking up to this reality. there was this case of a judge actually across the bridge from me in New Jersey, whose son was murdered by someone that she litigated against in the past.

41:27They found her data online from data brokers, tracked her down, and in this case, killed her son.

41:37Thank you to all our regular podcast listeners. It's our pleasure and honor to make the show for you. If you find our show valuable, please do us a favor and subscribe, rate, and review it. Even better, forward it to a friend. A big mahalo to you for doing this. Welcome back to Remarkable People with Guy Kawasaki. So you had a great section about how by looking at what people have searched Google for, you can tell a lot about a person or at least draw conclusions. So do you think prompts will have the same effect? Like, you know, what I ask chat GPT is a very good window into what I am. I think so.

42:23And I don't necessarily, I think it's prompts. I think it's questions that we have. And if you think about Google, there's questions that I type into the Google search bar that I wouldn't feel comfortable asking my friends or even sharing with my spouse. So it's like this very intimate window into what is top of mind for us that we might not feel comfortable sharing with others. Yeah, so I was actually, which I thought was so interesting because I was part of this. It was like a documentary, but artistic. And what they did is they invited a person. So they found a person online. They looked at all of her Google searches and then they recreated her life.

42:58all the way from here's the job that she took kind of suffered from anxiety and the feeling that she wasn't good enough in the space that she was working in all the way to her becoming pregnant and then having a miscarriage and they kind of recreated her life with an actress and then at some point bring in the real person and the person watches the movie and you can see how just over time she realizes just how intimate those google searches are because what the team had, the documentary team had created, the life that they had recreated was so close to her actual experience. And again, just by looking at their data.

43:33So for me, it was a nice way of showcasing that it's really not just this one data point or a collection of data points, but it's a window into our lives and our psychology. And not to get too dark, but the CEO of Google was on the stage, right? So what happens when generative AI takes over and, you know the ai is drafting my email drafting my responses and to take an even further step what happens when it's my agent answering for me yeah then is it still as predictive or will the agent reflect who i really am or it throws everything off because it's not guy answering anymore so to me that's a super interesting question first of all in a way like generative ai democratize the entire process.

44:23So when I started this research, we had to get a data set that takes your digital traces, let's say what you post on social media, and maybe a self-support of your personality, and then we train a model that gets from social media to your personality. Now I can just ask ChatGPT and say, hey, here are guys' Google searches. Here's what he bought on Amazon. Here's what we talked about on Facebook. What do you think is his big five personality traits? What do you think are his moral values? What do you think is, again, like some of these very intimate traits that we don't want to share? And it does a remarkable job.

44:56It's never been trained to do that. But because it's read the entire internet, it understands so much about psychology. And then obviously taking it to the next level, it's not just understanding, but also replicating your behavior. And the one thing that I'm most concerned about, aside from like manipulator, it's just that it's going to make us so boring. if these language models, they're very good at coming up with an answer that works reasonably well, like 80%. But it's very unlikely that it comes up with something like super unique that we've never thought about that makes us different from other people.

45:30So I think what happens is that we're just going to see more and more of who the AI believes we are, because it's essentially almost like the solidified system of here's who I think Guy is, and now I'm just optimizing. And in the way that humans learn, there's this trade-off between exploitation. So that is doing the stuff that you know is good for you. So if you think about restaurant choices, you can either go to the same restaurant time and again because you know that you like it. So there's not going to be any surprise. It's going to be a good experience. But the second part of human learning and experience is the exploration part.

46:04And it exposes you to risk because maybe you go to a restaurant and it turns out to be not great and you would have been better off going to your typical choice but maybe you actually also stumble on a restaurant that you love and for that you had to take the risk and explore something new and my worry with these ai systems and most types of personalization is that they very much focus on exploitation they take what you've done in the past who they think you are and they try to give you more of that but you don't get like the fun parts of exploring it's like google maps is amazing at getting you from A to B most efficiently, but you also never stumble upon these cute little coffee shops that you didn't know were there before because you got lost.

46:44And for me, that's in a way the danger of having these systems replaces. Is that just going to make us basic and boring? Well, what if I ask the opposite question, which is I want to help companies be more accurate in predicting my choices, right? So I want to tell Google, stop sending me world wrestling news in Google News and stop telling me about the Pittsburgh Steelers and, you know, and stop sending me ads for trucks because I don't want a truck and I don't want a Tesla. And I want to make a case that what if you want companies to understand you better, then what do you do? First of all, I think it should be an option, right?

47:28So there should be two different modes for you, Guy, that says right now I'm trying to explore. Right now, I just want to see something that's different to what I typically want. But also now I'm in this mode where I just want you to know exactly what I'm looking for and I don't want you to send me the camera even though I was not interested in the camera for the last three weeks. So in this case, I think what companies can do, which is what they I think oftentimes don't do enough of. So it's like having a conversation with you that kind of allows you to interact with the profile. Most of the time they just passively say, here's who I think Guy is.

48:01and now we're optimizing for their profile. But if they get it wrong, there's no way for you to say, no, no, no, why don't you just take out this prediction that you've made? Because it's not accurate, which is annoying for me. Because now, as you said, you get like ads for wrestling that you might not be interested in at all. And it's also bad for business because now they're optimizing for something that is not who you are. So I think, first of all, give people the choice whether they want to be in an explorer mode or an exploitation mode. And then second part is even within the exploitation mode, We're just trying to optimize for who we think you are.

48:34Give people the choice and say, no, you're wrong. I want to correct that. It's good for the user and it's good for the company. Well, if anybody out there is listening and embraces this idea, I suggest you not call it exploitation mode. Maybe optimization mode might be a more pleasant marketing. Personalization mode, yeah, that's true. A personalization mode, yeah. Okay, so three short tactical and practical questions. So knowing all that you know, and I think we went dark a few times and show people the risk here. So do you use email, messages, WhatsApp, or Signal? What do you use personally?

49:17I mostly use WhatsApp. First of all, it's encrypted, but then it's also just what everybody in Europe uses. So I wouldn't even give myself any credit for that. And it's funny because I think the fact that I've become a lot more pessimistic over the years has to do with my own behavior. So I know that we can be tracked all the time. And I still mindlessly say yes to all of the permissions and so on and so forth. So I think we just don't have the time and the mental capacity to do it all by ourselves. There's only 24-7 in a day. And I'd much rather spend a meal with my family than going through all the terms and conditions and permissions.

49:49So I think if it's just up to us, it's an unfair battle that we don't stand a chance. And why of all people in the world would you not default to Signal because it's encrypted both the message and the meta information? It's mostly because not that many of my friends are using it. So again, in this case, it would be a tradeoff between I get protected more, but there's also like a downside because I can't reach out to the people that I want to reach out. And I feel like if that's the tradeoff, the brains of most people will gravitate to I'm just going to get all of the convenience that I want. Okay.

50:25Second short question is, when you use social media, do you use it like read only and you don't post, you don't comment and don't like or like, are you all in on social media and dropping breadcrumbs all over the place? I think even if you don't use social media, even if I was completely absent from social media, I would still be generating breadcrumbs all the time because I have a credit card and I have a smartphone and there's facial recognition. I just don't want people to think that social media is the only way to produce traces. Now, I don't actively use it as much, but not because I know that I shouldn't be doing it.

51:02It's just because it's so much work. I feel like I'd much rather have interesting offline conversations than thinking about what I should post on X and some of the other ones. So it's a different reason than worries about privacy. Okay. Now, is the logic that, yes, you know, Google knows something, Apple knows something, Meta knows something, X knows something, you know, everybody knows something, but nobody knows everything. So the fact that it's all sort of siloed keeps me safe or is that a delusion? I think it's probably a delusion. So my argument would be that they have most of these traces.

51:41So if you think of applications, again, like when you download Facebook here, it asks you to tap into your GPS records, into your microphone, into your photo gallery. You use Facebook to log into most of the services that you're using elsewhere. So they have a really holistic picture of what your life looks like across all of these dimensions. And by the way, they also have it for users who don't use Facebook because it's so cheap now to buy these data points from data brokers that if I wanted to get a portfolio, a data portfolio on most of the people, I would be able to get it really cheaply.

52:15And that's something that, again, I think most of us or all of us should be worried about. And you do see use cases where policymakers are actually waking up to this reality. There was this case of a judge actually across the bridge from here in New Jersey whose son was murdered by someone that she litigated against in the past. They found her data online from data brokers, tracked her down, and in this case killed her son. Biden signed something into effect that now protects judges from having their data out there with data brokers, which makes me think if we do this for judges and we're concerned that we can easily buy data about judges, why not protect everybody else?

52:53I think there's a good point to be made that data on us is so cheap and available from different sources that even if you don't use social media, it's easy to get your hands on. You introduced the concept in the last part of your book, which I don't quite understand. So please explain what a data co-op does. Yeah, it's one of my favorite parts of the book, actually, because it thinks of how do you help people make the most of their data, right? So we've talked a lot about the dark sides. And I think regulation is needed if we want to try to prevent the most egregious abuses. But it doesn't really give you a way of, first of all, managing your data in the absence of regulation.

53:34And it also doesn't give you a way to make the most of it in a positive way. So data corps are essentially these member-owned entities that help people who have a shared interest in using data to both protect it and make the most of it. So my favorite example is one in Switzerland. It's called MyData, and they are focused on the medical space. So one of the applications that they have is working with MS patients, so patients who suffer from multiple sclerosis, which is one of these diseases that, again, is so poorly understood because it's determined by genetics. and it's determined by your medical history, by your environment.

54:07And what they do is they have a co-op of people, so patients who suffer from MS and healthy controls that own the data together. So it's a little bit similar to the financial space where you oftentimes have entities that have fiduciary responsibilities. So they're legally obligated to act in your best interest. So data co-ops are entities that are owned by the members. They are legally obligated to act in their best interest And now you can imagine in the case of the MS patients, they can pull the data, they can learn something about the disease, and they can also then, in this case, work with doctors of the patients and say, here's something that we've learned from the data.

54:46This treatment might be particularly promising for a patient at this stage with these symptoms. Why don't you try this? so the people benefit immediately and also because they're now together they can hire experts that help them manage their data think about well here's maybe some of the companies that we want to share the data with but maybe we do it in a secure place that doesn't require us to send all of the data so these data clubs for me is just like a new form of data governance that gives us i think of it as allies so if we have a way that we want to use data we need other people with a similar goal so that we make data, first of all, more valuable.

55:23Because if I have my data, my medical history and my genetic data as an MS patient, it doesn't help me at all. I need these other people. But it's not coming together as a pharma company that's grabbing all of this data and then making profits, but it's coming together as a community and benefiting directly. So that's what data co-ops are. But a data co-op doesn't exactly solve the problem of all my breadcrumbs on social media and Apple and, you know, all the other stuff, right? This is for a very specific set of data. Agreed. So it's not necessarily a specific set of data. You could imagine in the European Union where you're allowed to pull your data, you could have a data quam of people who just pull together their Facebook data and now they go to Facebook and say, hey, look, we're all going to leave if there's no way, if you're not putting in, let's say, technology like federated learning to protect our privacy a bit more.

56:17So I do think that there is also ways in which people can come together and get just a lot more negotiation power at the table. Then like if you go to Facebook and say, hey, I'm Guy, I want to force you to do something different. Not sure if they're going to listen. If you suddenly have 10 million people doing that, you are in a better spot. Okay. I like this idea. Okay. Now I understand it better. Thank you very much. So listen, I like to end my podcast with one question that I ask all the remarkable people. And clearly you've proven you're remarkable with this interview. And that would be stepping aside, stepping back, stepping up, whatever, you know, direction you want to use.

56:58Like, what's the most important piece of advice you can give to people who want to be remarkable? I think it's don't take yourself too seriously. I think some humility and the way that you approach yourself and others goes a long, long way. All righty. This is a great episode. Thank you so much. And I hope I didn't go too dark for you. This is a dark subject. I do think it is. And I think there's a lot of room for improvement. That's why I care about the topic so much. All righty. So Sandra Matz, thank you very much for being a guest. This has been Remarkable People. I'm Guy Kawasaki and I hope we helped you be a little bit more remarkable today.

57:38So my thanks to Madison Nismar, the producer, Tessa Nismar, our researcher, Jeff C and Shannon Hernandez who make it sound so great. So this is the Remarkable People podcast. Until next time, mahalo and aloha.

57:56This is Remarkable People.