Adventures in AI: Data Center Gold Rush, AI Agent Autonomy, and DNA Privacy Risks | TSG Ep. 882

So the AI data center space is a billionaire's club. Let's discuss it here on Techstrong Gang. Hey everyone, happy Thursday.

It's Thursday, man. We're just hopping Monday, Tuesday, Wednesday, Thursday. You know what?

Tomorrow is not Hump Day Friday. But, uh, welcome to Textron Gang here for Thursday. We're glad to have you on here.

We've got some interesting topics to discuss today. As usual, a fair amount of AI thrown in with a little DevOps, a little security, and a whole bunch of money. Crazy money.

We're gonna talk about it with some great people though. Let me introduce you to our gang lineup for today. They're all regulars.

You've seen 'em here before. My friend, Garima bha, Terry Robinson, guy Curer, John Swartz, and the dean, Mike Ard. Hey, Mike, how are you?

I'm doing well, as always, Gang members. Everybody ready? Let's rock and roll.

So, Mike, you know, I thought the NFL was the ultimate Billionaires Club. Apparently not, But apparently not. You need, we're talking big money here, Right?

And I'm gonna ask John to explain this, but at the core of this, in this week alone, Google and Meta and, uh, core and Blackstone, and we're all talking about multi-billion dollar investments in data centers, and there's a lot of other folks building out data centers. And I guess my first question to John is, since you wrote this story over on Text Dry, it is, where the hell is all this money come from? Yeah, Good question.

Good question. I guess, you know, it's gonna, some of it's gonna come from, uh, cost savings using AI eventually, or just getting rid of your employees. How about that?

Why? We just like Microsoft laid off thousands of people and said, Hey, we just saved $500 million. Um, so, yes, uh, that's a very good question, Mike, because they're throwing this, these numbers out like Monopoly money.

And so, again, we all have hard doubts about what's actually gonna happen. You know, this is just kind of, we, we kind of take it at face value, but I'll just throw out some of the things. Evidently, a lot of these announcements were tied into a event at Carnegie Mellon University on Tuesday where Trump was there, the president of Google Roots pour out was there, uh, Blackstone was represented core.

We made an announcement involving Pennsylvania. Almost all these announcements were around either Pennsylvania or Ohio. And so I'll just throw out some of the figures because it gets a little dizzy in confusing at times.

Meta on Monday, mark Zuckerberg talked about this on Facebook. He said they're gonna spend hundreds of billions of dollars on building AI data centers in the us, including this thing first multi gigawatt data center called Prometheus, which is gonna open or come online in Ohio in 2026. Meta is jacking up its budget for AI data center projects to between 60 and $65 billion in 2025, which I found somewhat hard to believe.

But that compares with 35 to 40 billion in 2024 as part of their push for the super intelligence AI systems. Google is inve saying they're investing 25 billion in data centers in Pennsylvania, in neighboring states over the next two years. They also have a side deal with Brookfield Asset Management for 20 year power purchase agreements, totaling $3 billion.

Then we have Blackstone, the private equity firm is gonna inject $25 billion into data centers and power plants in Pennsylvania. And finally, with a mere 6 billion, $6 billion pittance, coral weave is going to build an AI data center also in Pennsylvania. So the numbers are staggering.

They're kind of hard to believe the overly aggressive, uh, timelines. Um, but you're, you're right, Mike, where, where does this money come from? I guess it comes from their capital expenditures, which will be diverted to this area.

Um, I don't believe the numbers will be as high as the companies are telling us, but I think the intent is truly there. I mean, I, this is just rush, essentially to build as fast as you can in order to train your ai. So, um, there we have it.

And, um, I know we, I, we, we might talk about this later, but there are also, at the same time, we have to think about the repercussions of all these data centers going up. One of which from Facebook is gonna be the size of Manhattan, evidently. Um, we have to think about the environmental concerns.

So, um, that we don't think About that anymore. I'll just, with don't worry about it, Joe, baby. Jealous.

Well, Well, there is a, a story, there is a story on the b BBC talking about how, you know, some woman is saying she can't drink the water anymore, logging The BBC Story. Hey, but here's my question. I got 20 bucks.

What did I get with that? Can I get in on this AI thing with $20? This, the, the amount of money we're talking, they call that a prop in the business.

By the way, the amount of money we're talking about here is just ludicrous. It's ludicrous. Come on.

But a couple of things. Number one, you gotta give Zuck credit for using the sci-fi names. You know, there's Prometheus is this thing they're building in Ohio, but the one down in Louisiana, which is gonna be the bigger than Manhattan, is called hyper on one of my favorite books by Dan Simmons, by the way.

But, you know, what's next, dune? But the, the important thing is they're trying to build this stuff near where the energy producing is, right? So in Pennsylvania, in Ohio, basically hydroelectric, uh, uh, liquid gas or natural gas, excuse me, natural gas plants, they're building there.

Um, but, you know, nuclear is certainly an option. We're, we're going to do all of this, but the fact of the matter is, we don't have Stephen Fox for phos fos. We don't have Steven here, FoST here to wave his flag, but it's still wind and solar.

That's the fastest growing energy sources out here for us. You know, we, we, and that's what's gonna be powering. They're talking about, uh, out in west Texas, San Angelo, right.

Becoming the data center capital of, of the US even. So, you know, but you are right, John, this, there's a lot of political points being made. This was done in Pennsylvania.

It wasn't just Trump, but the, the newly elected Republican senator of Pennsylvania was there. And, you know, there's good old fashioned pork, but the good news is they're getting the Yeah, Yeah. They, they, they, they threw out these staggering numbers, which of course, we, we rarely believe, but it's, and again, it's a, a land grab and it's kind of their, uh, placement or placeholder for, oh, manufacturing.

We're building manufacturing, and people live in those areas, can't wait To get jobs. Well, they struck out, right? We're, we're learning that they can't do manufacturing.

And manufacturing doesn't necessarily even bring jobs. But this is the new manufacturing, if we could call, call It. This is, they pivoted to the new talking point as a new diversion, right?

But, uh, you know, me's going to do a huge amount of work in this area. I mean, they're, they're throwing money around, like, like, like I said, monopoly money. They're, they're trying to hire talent at an incredible speed.

They're throwing out these ridiculous salaries. But, but Why, my, my question to you is why I think there's, because there we have a diversion. It there's a fork in the road.

Some of these guys are chasing, you know, the, the chalice, right? Some of them are, are chasing, uh, a GI, right? Or I always get the initials wrong.

Yeah. A GI, uh, a GI, right? Artificial general intelligence, Intelligence, the, the singularity, if you will, Our next misnomer.

Yes. Right? So some of them are, are, are, are off, you know, chasing a GI and this, you know, the unattainable, you know, the sword, um, king Arthur sword.

Others, Can I, can I like, say, I'll say something really quick and I'll get outta the way, you know, in a sense, what they're doing, they're, they're just, they're going for, they're doing the same. They're learning from their friend in dc. They're going from one diversion to another to try to kind of keep us guessing of us what they're going to do until they come up with another new project or new idea.

I'm not saying that, I'm not saying they're gonna, they're not going to consummate some of these, but I kind of see the same pattern, You know? But not everyone is chasing a GI, some of these people, I think, are chasing true AI factory data centers, where the AI applications that we spend so much of our time talking about here will be housed, run, and, and, you know, consumed from, and I, I, quite frankly, I think that is less pie in the sky than chasing the A GI. Um, you know, I, I, I think that is, to me, that's akin to laying dark fiber during the late nineties, early two thousands, right?

We, we built, we laid more fiber than we were going to use for 10 years, but eventually we did use the fiber. So is this the same thing? Are we gonna overprovision data centers?

Oh, yeah. And Then be dark? I think so.

No, don't, no, you don't think so, guy. Why not? Well, I gotta be honest, there's, there's just way too many threads in this particular story.

So, uh, there, there is something of what you say, uh, there's a macroeconomic explanation for all of this. Um, Mike asked John, where does this money come from? Where does it come from?

Well, these companies were sitting on piles of cash for a very long time until AI came along. Um, Zuck, you know, in one sense, you think he just goes and spends whatever he wants to spend on anything, but he lives in a community. He's part of a community, he has a board, he has investors, he has people he wants to please.

So that's part of what he's trying to do. So five years ago, he had all this money, but nowhere to spend it. That's what Larry Summer ton, Larry Summer's called Secular Stagnation.

Uh, meaning there's all this money, but, but none of it looks like a good investment. All of a sudden, AI looks like a good investment. So anybody suck wants to talk to, he can go around and brag about the CAJILLION dollars that they're spending to build that ai.

So he's got permission. So in that sense, I think you have a point, Alan, which is that, um, they're just throwing money. It's something that finally looks like they can throw money at.

Why I don't think it will be like dark fiber or unutilized is because there's tremendous demand, even if there's no real productive result, or I would say no, there's less productive result out of AI than people think. But there's still this huge cultural movement across, you know, all of industry, um, to invest in ai, because it just all looks like we're gonna be able to fire people finally and just tell computers to do everything, and they won't take days off and blah, blah, blah. 53 megabits a second, and someone came by and said, Hey, I could give you a, a t three line at 45.

You had a line around the corner for the T three lines, and then someone said, oh, screw that. I'll bring you fiber. You know, MLPS or MPL or whatever it was.

Fiber. MPLS. Yeah, yeah.

MPLS fiber. Mm-hmm. Wow.

This is Nirvana, which Is now dead, by the way. NPLS is As good as dead. Back then, you know, it was driving, you know, companies like level three and, and the old, uh, who m got bought by m they bought MCI WorldCom, right?

These people were laying fiber because we all said, oh, the demand's there, the demand's coming, the demand's there. And it was right. It was blowing up.

We needed, we needed to get beyond the, the T three line even, but they built so much that it took 10 years for us to, to consume it. I don't know. I think demand is outpacing supply right now.

So today is we, we'll, today, but with this kind Of money guy, So can supply then later because it's all being built out, you know, outstrip demand, uh, yes, but I'm, I just don't think it's dark fiber situation is a different judgment call. Um, but I didn't finish. I didn't finish.

Okay, I'm sorry. Because, because what's a lot of what's motivating Silicon Valley and Zuck and a bunch of other people we could name is a GI, so, and I'm not kidding. So they can upload their personalities into machines and live forever and Be immoral.

Not Kidding. Not kidding. This is a part of the culture and a part of the planning, and a part of the idea.

We're gonna go to Mars, we're gonna do all this stuff. Wasn't There a movie On this? Okay.

And we need AI to do this. Uh, more than one, I suppose, but yeah. Yeah.

So, so I, like I said, there's just so many threads to pull on this I, I, I've only just done, but I don't wanna take, take over here. I think that, that the, the last thing I'll say is there is this, uh, force of gravity, just like there was with the cloud, that all of AI should be in the cloud. All the ai, all of AI should be giant models.

Everybody gets just gonna use cloud-based AI forever and ever I'm in. And that is just plain untrue. It's untrue today.

It's gonna be more untrue tomorrow. So, um, the, the significance of this and the significance of the cajillions of dollars going into this and everything is honestly folks really pretty small. Yep.

Haha. So let me, let me, let me bring in a couple of other points here. So besides the usual tech billionaire cartel, right?

You got, you got Blackstone in here now, Blackstone's a PE and real estate play. So are they looking in AI data centers as a real estate play? Are they gonna invest?

I mean, that, that's where that is. Then you got a relatively small company core weave. They're throwing in a measly 6 billion.

That's why my 20 bucks should count for something, right? They're just putting 6 billion. But this isn't just a US sickness, crazy going on.

We're seeing it around the world. The eu, you know, Macron falls over himself putting more and more French dollars into it. The Germans as usual, very mis early giving it out, but they're in there, right?

The UK doesn't want to be left behind. They can't just count on their special relationship with us to, to get it done. Saudi, Saudi Arabia, they're building, what is it, neon or whatever the city is, it's gonna be a horizontal city, not a vertical city.

And there's gonna be all kinds of ai. I mean, they're putting maybe a trillion dollars in to, to building their infrastructure out with this. And remember, uh, remember our friends at Stargates, would that be interesting to six months ago, Trump was hanging out with open AI and Oracle and SoftBank, and now they're almost an afterthought, given the, given the amount of success They have this money.

Well, they haven't got anything going in this six months either. Yeah, I think that's A cost story tale. That's like something I think About.

That was the prior diversion. Yeah, the Prior, yes. Mm-hmm.

In between the tariffs coming up in, down on Taco Tuesday. I, I do think they're underestimating the NIMBY factor, though. And I'll give you an example.

In Northern Virginia, most of that land around Manassas is a battlefield. And it own, it's owned by an outfit called the Civil War Battle Trust, who pretty much send a message today saying, you're not getting those acres from us. And if you show up trying to put, build a data center on it, you'll be on the wrong end of a musket.

So we're gonna load our muskets up. But, you know, there are plenty of data centers in Northern Virginia, though. Let's not kid ourselves rest in Herndon, Tysons, um, you know, those places are loaded with data centers.

At and t has one that's like the secretive data center. Literally, they have a, it's like built on a mo around a moats around it. Um, yeah, they have A, but even the locals down there have figured this out.

And now they're all kind of saying, you know what? We're not gonna let you expand data center build. 'cause they're like, these things are noisy, and they do impact the environment.

And people are starting to say, Hey, it's not, it doesn't do anything for the local economy other than the fact that we built it. And then, and then it sits there. But it raises the point, though, where if the local electric utility has been pre, their output has been pre-sold to power, the data center, are they gonna have enough to power my home when it's left over because I'm sort of a second class citizen because I can't compete with the billionaires?

And isn't that really what it's about? Right? Are we becoming a country ruled by an oligarchy of billionaires?

Well, Yeah. And that's what we, you know, and it's not just our AI centers. There's a bigger question here, but we'll answer that another time.

We're gonna take a break here on the gang. We'll be back. Let's talk about AI agent autonomy, Discover Textron Group, the epicenter of tech innovation.

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Hey, folks, we're back, and we've been talking about these things called AI agents, but there's a discussion, maybe even a debate now about, well, what does it mean to have an AI agent? What's the level of autonomy that I should give it? And is it an AI agent if it's not autonomous?

And Perforce this week kinda raised this debate as when they launched a AI agent for testing. And one of the things that they were saying is, this AI agent adapts to the mission so that it does more than just execute a task. But garima, what is going on here?

'cause I feel like a lot of folks are tossing around the term AI agent, and there's a, a definition for the word agency, but just how much faith can we put in an AI agent? How autonomous can they get and should they get? So AI agents is not, uh, a solopreneur, right?

So AI agent comes with system, right? So there is a lot of, uh, things behind it. We can talk about that, uh, in a while.

But what this announcement by Perforce software is, is that they're in injecting or inducing AI agents, and they have designed these AI agents, uh, for testing mobile applications. So when we talk about mobile applications, uh, there's a lot of testing going on in terms of, uh, how the UI looks like, the data behind it, the logic, the functional testing and all that, right? So they claim that they have, uh, self-healing tests, which, uh, will automatically change, uh, according to the changes made in the UI or they data behind it, or the business logic behind it.

What are the advantages of it? And I mean, I put, uh, the pros before the cons. So for pros, what we see is you can have, uh, a lot of like, uh, natural language prompts, uh, which can democratize testing.

And if you remember, Alan, we had some discussions with OpenText on this, that this is one of the premium areas where we can start to, uh, investigate the potential of AI agents, right? So this is one of the quick wins. So I do believe that this can provide some kind of, you know, uh, trust in building AI agents for testing specifically.

What it also, uh, is claiming is that they have, uh, cut down the process and the testing, and they're saving 50% of their time, uh, when, you know, this technology is onboarded or it gets matured, right? But there are other factors to be kind of, uh, counted in. Because if you see that, you know, these autonomic enormous agents, how they work, like there is a system behind it.

You will need, um, you know, some injuring, uh, services, which, uh, will enable these agents. You also need data and transitioning from, let's say, script-based tests to script list testing is not, uh, a piece of cake, right? So there's a lot of, uh, parroting shift in how testing practices are maturing.

So there is, like, these scripts and frameworks will not no longer be required in this kind of parroting shift, but then you would need new skillset. You need, uh, integration maturity, right? There's a lot of complexity when you talk about this, uh, seamless integration with CICD pipelines, for example.

And not to shy away from the fact that, um, data behind it, right? I mean, who would provide that data? Who owns that data?

I mean, I mean, mobile testing is for specific set of customer base. And of course, uh, this also raises some questions around, uh, hallucination, for example, which we have talked about in, um, different, uh, segments, right? And validating our proof points that how much this is viable.

Um, last thing, which I would also mention is that skillset is, uh, quite, uh, scars in this area. Like, you know, we'll have to still mature the prompt engineering part of it and see how this whole play, like think plays around a lot of system thinking is required to enable this, uh, efficiency, uh, from a, a testing point of view, right? And this e efficiency can also, uh, go for a toss if you start to build technical depth.

Because if intent towards says, you know, um, the, the alignment of intent is not happening, then it, it also becomes a major issue or major technical depth in the longer run. So we have to watch out from the pros and cons, uh, of this technology. And of course, I do believe that this is one of the quick wins, you know, testing applications and testing software through script less or agent tick framework is I think, uh, a good kind of, you know, segue into, uh, proof pointing this technology.

Uh, germa, um, correct me if I'm wrong, my impression is that a lot of pre-testing is, uh, more observed in the breach, you know, like, uh, regression testing, um, uh, and user, especially user acceptance testing, that sort of thing. Like, it, it's, it's, it's a, a checkbox, but it isn't like particularly well or thoroughly done. Um, it, it is that, right?

Because, you know, in, if you look at it that way, what we have here is what I would call a like, um, maybe a rougher, um, somewhat rougher, somewhat less, less accurate, especially as it gets more autonomous, um, or less effective, let's say, way of testing, but more comprehensive and more reliable. And so that's, that's a, you know, that's quite reasonable trade off, which is, you know, I, I can't, I can't pay these dang developers, um, or product managers or whatever to, to get appropriate testing done and keep having failures or problems or user issues this way. At least I feel like it's more thorough.

Um, and, uh, we can, you know, focus our human capital on other things. Does that sound right? Yes.

I think, uh, quantitative assessment and qualitative assessment are two different things, right? So what we can benefit out of this, uh, kind of technologies quantitative assessment where there is a yes or a no answer to it, you know, a cer certain amount of test cases, and, you know, those, uh, testing scenarios are overlooked. And, you know, you have to have a lot of manual intensive labor to kind of change those test cases in sync with, you know, the UI changes you have done on the data you have kind of, you know, synced in, or even the functional functionality testing from a very, uh, pro bono perspective.

But when it comes to qualitative assessment, it's still like early days for testing, because this is again, uh, how, you know, how valid is this validation, uh, you know, without having a specific framework or a practice behind it. So let me, let me, let me be provocative. Last test throughout the door, shut out the lights.

I, right, this is the beginning. It's not the end of the beginning. It's the beginning of the end, right?

When you could do this and boost test efficiency by 70%, seven 0%, that's not nothing to sneeze at. And it's just the beginning. org.

And, and one of the points we made, we've talking about is AI enterprise ready as a, from a platform point of view. And one of the things that Luca brought up was, what we're seeing with this AI is that things that lend themselves well to ai, like testing, doing these script list testings and doing, you know, guide, why weren't, why aren't those tests? It's not that they're not important, they weren't important enough to get the resources they needed, but in innate, oh, I disagree about the importance, just real quick.

It's that they're bo it's, it's, it's for human beings to work on. It's, it's bo for most of them, yes, it's boring to be methodical and complete and all that other sort of, I just wanna get it outta the way and get back to coding. But it's made for a ai made for there, just, just for the record There, that's Guy Courier saying that testers are boring, not Textron game.

No, not testers. All of his views are his own. But anyway, but it was made, I mean, AI's made for this, right?

And so what we're going to see is a shift to these things where AI is dominant. And it could be very, you know, testing is one aspect of it is coding, another aspect of it is observability, another aspect of it. But these things that seem are, are relatively low hanging fruit for the AI are the things that you're gonna see shift over to the ai, and you're gonna see massive, massive, not layoffs or maybe layoffs, but a lot less people doing that job than, than do it to do them today.

And when We, yeah, and there's a lot of test management and lifecycle the, uh, software development lifecycle firms. So like, it, it increasingly added, um, AI based automation to, to testing and adjusting testing in flight. And like all that sort of stuff.

I'm, you know, there's so much noise about the layoffs here with AI agents, and you can see why there's gonna definitely be tasked that are automated, but I also look at it differently and I go, you know, there are tons of companies out there that could not build any software to save their life. And if it becomes easier for them to do more of those kind companies will build custom software using what will eventually just become a small army of agents. But I, you know, somebody has to direct those agents and, and orchestrate that and manage that and tell that small army what to do.

And I think that's where the role of the DevOps people evolves to. It's less about writing scripts and more about managing the workflow or the outcome. Kareem, am I crazy?

I think, you know, Mike, I want to change the narration from layoffs to less work week, less work hours, right? So technology is an enabler to help, uh, you know, uplift our quality of life. So I would like to change this narration saying that, you know, when you have AI bots and AI agents in your system, you know, do we, uh, ensure that our work hours and work week hours are kind of, you know, consolidating and we have quality time with, you know, family and community, that is the conversation we need to take, right?

I mean, this is again, a narration change, a bold step. Somebody has to speak to these kind of things, right? Agreed.

Agreed. And, and that, you know, if you believe the hype, that's what people will do, right? Right.

That's how we migrate this. This is the, this is the, the path. Um, you know, and eventually you'll wind up on Starship going where no man's or person's gone before, right?

And we don't worry about money and all of that good stuff. My fear, though, Reemer and, and to you all out there is buckle in. It's gonna be a bumpy ride till you get there.

'cause there's gonna be a lot of displacement. There'll be a lot of angst and, and stuff. And, and, and eventually we may wind up in that place.

But I, I would say amongst the, amongst the, the tech community, there's maybe 50%, 50 to 60 or more percent misunderstanding of what AI does and how it works. And in the business community, it's probably 90%, uh, people See, I mean, you know, it's evident what happens when you use it. Um, but, uh, that's the bump.

I, i, that's really the bump. And, and I was also wondering the last segment, uh, you know, some of us, uh, I'll call myself out of, said that there's gonna be some form of AI backlash at some point. Maybe it's building now where people suddenly realize they're not getting what they thought they were getting from it, they temporarily turn against it.

This would be, you know, one example of that, which is, oh, I have all of this stuff and the thing still failed anyway, and I can't figure out what it's dear so many agents, I can't, I can't manage or understand them. But we could very quickly reach that point. Yeah.

So I had a conversation within the community, and this, these communities are for this. So for example, continuous Delivery Foundation ambassadors came together. And we heard this question earlier as well in the community, that who is monitoring your monitoring, uh, server, right?

So who's your, uh, who is actually monitoring your AI agents? It's AI or something else. So if, let's say you creating test cases and validation cases, who is doing call qualitative, qualitative assessment of those validation cases, right?

Is it ai? AI versus ai? So this is a lot of work to be done through community leaders, right?

To define the semantics, to define the assessment criteria, to ensure that we safely onboard these technologies. Uh, also cut down the hype around all this, right? So a lot of work is on the shoulders of the leaders and the practitioners for say, you know, for building this kind of ecosystem.

Agreed. Somebody has that guys all time on the, I'm sorry. Go ahead, Terry.

I was just saying we get the last story. Somebody, somebody has to understand too, why these agents are making the decisions they make as well. That's, I think that's human intervention.

Yeah. I, I think that's a beginning thing. It's a question of trust, right?

Once you trust them to make the decision, then you, he's off. Um, but we're over time on this one. We need to take a break here on the gang.

We're gonna come back and, uh, let's get personal, uh, 23 and me and DNA And how much do we know about you? Scary. com is the leading resource for news analysis and education on challenges facing the cybersecurity industry.

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And as Alan said, we're gonna be talking about DNA. 'cause after all, it is a type of data that needs to be secured. And it's interesting, we've been, you know, taking our DNA shipping it off to some cloud and service to analyze it, that gives us back some sort of results.

And then they send us a bunch of emails telling us about who we might be related to. But nobody seems to really ask any questions about, well, how secure is that data and what's happening with it all? And fortunately, I guess there's been some, uh, merger and acquisition and bankruptcy conversations around some of this that's now getting people to talk about this subject again.

But Terry, how do we secure this data? Are there protocols in place and These What could possibly go wrong? Everything could go wrong.

This is not and did apparently. Yeah. And did, yeah.

And, uh, you know, so as tempting as it is, my, my best advice is don't give up your data unless you know, uh, where it's going. I mean, under very controlled, uh, uh, uh, situations. Don't give up your, your DNA, um, however, that's not the way of the world.

It's already out there. Can't be pulled back. 31 million pounds.

But that's not it. It, it's a drop in the bucket, you know, in, in a way, uh, probably deserved a bit more. Um, they had a two years ago, uh, huge credential stuffing incident, and they didn't even bother to report it.

That shows you how, uh, how secure, uh, your data was with them or your information. Um, and it's all led to, uh, you know, not only this fine, but the fact that they're kind of being given over to a nonprofit as if that's gonna help somehow, if the standards are gonna be greater or the protection's gonna be greater. I think there's a lot of skepticism among security leaders, um, if that would, would be the, the case.

But yes, part of the problem is it's not protected at most of these companies, um, as, as, as well as it should be. But another part of the problem is I think that people who give up their DNA, they don't really have a clear understanding too of, of what they're signing onto or, or signing off on. Um, and that's, uh, that's a real problem.

I don't know, I'm not gonna ask you guys if you've used any of these, um, services. I don't wanna know the answer. Um, I don't wanna think differently of anybody, but I've stayed, um, away from them myself.

I've had a couple of friends who have had some interesting surprises, you know, like a, a sibling that they didn't know Existed, finding didn't know about, yeah, yeah, Yeah. And stuff like that. I mean, it's interesting, you know, to see what, you know, where you come from or where your stock is.

But does it really matter if, you know, in, I don't know, the three hundreds you were related to some big muckety muck, um, and some tribe, I, I doubt it. But, um, so there's that. But then the other thing, and this is probably why for years I sort of railed on these things.

You're also, when you give up your DNA, you are also giving information data on your family and people in your family. And that's something that you really have to think about. That's a, that's a big responsibility.

And sure you can use, um, uh, DNA evidence to crack cold cases and murders. That's fantastic. But how do you feel when an insurance company gets your family members or your family tree data and they make decisions about what they'll cover?

Um, Well, well, that, that's, you know, the genetics of it, right? It's not even your family tree. It's when they have your, your Genetic, yeah.

DNA, they have your genetic footprint. They know what diseases you're susceptible to. Well, you're correct.

You know, you're BRCA positive, you're 70% likely to have breast or ovarian cancer, and I'm going to charge your rates accordingly 'cause you're a ticking time bomb or a heart disease or, or diabetes or what have you. Exactly. And, and not just you, but everybody in your family then that they can trust.

So, so I, I've always, I gotta tell you, so Terry, I've not done it. I'll, I'll be honest, I've not done my DNA or anything. People in my extended family have, and they found half sisters and stuff like that.

Not, not my brothers and sisters cousins and stuff. But here's the thing. I've always felt this was a bit of a scam, that it was a bit of, you know, they're selling sushi out the back door of the bait store.

Okay. Exactly. Right.

Because the real, the real business, the business model here, the business model here was not telling you that you're, you know, 20% Scottish, 25% Irish and 30% picked or whatever, right? Yeah. It, it was, it was about taking that data that they're collecting from you and monetizing it on the back end.

Sure. Monetizing it on. And, and what was beautiful about it is we not only gave him our DNA data, but we went and filled out the family tree.

So now they can match that genetic DNA data to our family trees, right? And, and put it all together. What this is the biggest invasion of privacy of all time.

It's, and, you know, a sucker born every minute. That's right. And again, it can't be called back.

It can't be retracted that data, it can't be changed. You can't, as one of the people I talked to said, you can't, you know, MFA it, I just, there's, there's nothing that works there. I mean, once it's out there, well, So at Terry, and it, what was really horrifying to me about what happened here and the, the reason for the fine and all that sort of thing, um, it was horrifying both because of, of its shocking nature.

And then because it was completely unsurprising was that 23 ME security practices were crap all, and they were easily subject to, to this, to this attack. So, I mean, what the hell man? Like, that's just, it's, it's such a bleak child, But guy that's only half of it.

That's only half. Yes, they had crappy security and who knows what the other guys have too. But that's assuming, okay, so because I had crappy security, someone is going to get access to this data that I didn't think they should have.

The other half of it is what Terry alluded to about why they were forced to put this into a not-for-profit. They went bankrupt and they were looking to sell this information to the highest bidder. That's crazy.

I didn't sign up for that. Yeah. Well, it's a Denmark recently that, uh, that, that passed the law saying that your, your own image is your, is your, uh, uh, property no matter what You, what about your dna?

That's right. No, no, no. That's, that's what I'm saying.

Like just a little Oh, your dna. Okay. Yeah, Yeah.

Well, but I'm gonna say too, there's some gray areas there just in general in biotech about what belongs to you and what doesn't once it leaves your body, you know, once you submit it someplace. I mean, you guys read, was it, uh, uh, what's the book about? Um, Henrietta la Oh, the one lady whose cells have become viral Cancer cells became sort of the basis of modern biotech.

I mean, those cell lines are still used, you know, so the Police have been picking up your DNA from garbage for years to find match criminals or whatever. So, you know, at some point you're no longer on it. But let me put this out there as a notion for a killer security app.

And, you know, just imagine this for a second, but I'm gonna get myself a, a big cha tobacco and I'm gonna chew it up, and then I'm gonna spit in this spittoon next to my laptop, and it's gonna verify that that's actually me accessing an application. And meanwhile, you get oral cancer, but that's okay. Everybody wins.

Yeah, everybody wins. Doctors win tax Accompanies win. How, how different, how different is that than an iris skin or even a fingerprint?

Yeah, facial or facial recognition. It's, Well, it's harder to steal my DNA 'cause I could say that it was fresh DNA, right? Because there's, you can measure the time on it.

So at least, you know, it was me at that, Well, that, that was the thing. A couple years back, if you remember the sports memorabilia and collectible space, supposedly they were gonna have like a thing of the athlete's DNA that would be able to be checked. It's, or the artist DNA that you could verify.

It was in fact them who, who I, Who gave it to you. I see a whole new twist on suspense movies now too, where the bad guys are forcing, you know, somebody, they, they want access to their treasures and they're forcing them to chew a piece of tobacco. So, but you know what, but, but let me, let me tell you who the bad guy is here.

Law enforcement, right? Because under our present law enforcement, you could be forced to give a DNA sample E Exactly. So Combining that, so once that sample, it's in the, in the database.

That's right. So combining that with all going on here, yeah, it's scarier, right? So, so to Terry's point, is there a proper protocol about if I sign up for these DNA things, should I send a note to the family warning them that I'm about to do this in case the FBI is looking for them?

Or how does that kind of work? Well, that's, I guess that's an individual family, uh, decision, but I I, I certainly would, and I'd certainly be asking them if they have any secrets that they don't want. Um, you gimme Deal.

True, but true story, I got a Facebook request from someone and it looked a dead ringer from my cousin. And I asked my brother, I said, who's this person who looks like our cousin trying to be my friend on Facebook? And, and he told me the story.

It was a 23 and me story. Yeah. A a uh, half cousin, or I, well, she'll full cousin.

But, um, yeah, well, you know, we didn't know about her. Listen, It happened to my, a good friend of mine, uh, whose brother's unknown child, uh, connected through my friend's daughter and, and, and he didn't know he had this child out here. It was college girlfriend who never told him.

But my friend was in the position where she had the information and she was like, what do I do with it? Like, how do I break this? Well, that, that's the whole thing.

How do you, I mean, 'cause that would break apart families. Well, exactly. Okay, Hang on just a sec.

This is exactly the Facebook story, which was, there was this amazing utility that rushed everybody into Facebook, which is they found their old acquaintances, they're old friends, their own, you know, uh, uh, uh, schoolmates and all this other sort of stuff I did myself. It was so awesome that I forgot the part that I was putting all of my information and connections and habits and all this other sort of stuff, right into a platform that was now going to monetize and use it in Facebook. And Facebook.

Love the idea that you were doing that. They couldn't Outta the debate shop. Shop.

We never learned. We never learned. No, I think Alan Should take the test so I can discover that he is actually Irish and my third cousin removed.

Yeah. Always to second it. We can talk about it.

All right. Hey, I think we've got, uh, end today's show though. We're outta time.

What a fantastic conversation, what fantastic people. I hope you've enjoyed it as much as we have. Stay tuned.

We've got a full text on TV lineup as usual following today's gang. Also, just a quick reminder, we're breaking individual segments of the gang. So each segment today, all three segments.

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Until tomorrow, gang members, thank you so much. We'll see you soon. Thank you.

Out there. But for now, this is Alan Hummel for Techstrong. We're out.