Jason opens by describing Cambium and his role protecting students, their data, and the teachers who administer it, and credits his team, especially the people answering phone calls from users and customers and the IT and security operations staff with eyes on glass, now assisted by AI, as the unsung heroes. He then traces his leadership story from 21 years in the military, where everyone has had a bad leader, to the realization that he was one of those leaders early on. He says his neurodivergent son has taught him more about leadership, and crossing from the veteran world into the corporate one meant learning that you cannot tell people to drop and give you 20 push ups. Those lessons became his book, which argues you may be sitting on talent you did not even realize was there. He is blunt that not a culture fit is a cop out, recalling meetings where names on a spreadsheet are judged like a high school popularity contest, and urges leaders to ask whether the person is simply in the wrong seat on the bus.
The center of the conversation is curiosity and diversity of thinking. Jason explains that leaders are often given about 40 percent of the information and asked to decide fast, relying on experience that may be decades old, and that his own quick judgments caused pain, so he now advises taking an extra minute to ask what you are missing. Early in his career he surrounded himself with people who looked and talked like him, until he realized he was looking in a mirror, and he now says a team should look like a window. A neurodivergent analyst in a hoodie crushing Mountain Dews may be the best person for log files and forensics, he says, and some of the people with the best results have ignored corporate politics and gotten things done their own way. He shares a story about splitting a last slice of pizza with his son, who wanted the meat and cheese, as proof that some people attack problems from a completely different angle, and wonders whether AI is missing that because of the bias built into it. He closes the thread with his own fit story: cutting grass as a kid, 17 years in a bank, and a love of AI that finds a time for meetings.
In the back half, Jason turns to AI, security, and people. He sees AI augmenting what we dislike but warns that models can drift from fundamentals, and he uses Copilot every morning to summarize his day. He notes that CISOs think like bad guys, always looking for the next vector of attack, and while defenders are often one or two steps behind, they catch up quickly, so never doubt human ingenuity. He built a Monsters, Inc. style assistant that berates him as it searches SharePoint, yet still values the person who tells you where the coffee is. He argues the bad guys have an edge because many organizations are scared to put AI in their environment to combat AI, and that most CISOs will tell you the problem is users clicking, so he hopes AI takes on more and humans can focus on relationships.
Resources mentioned in this episode
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VP and CISO
Matthew Connor: Matthew Connor here, host of the Cyber Business Podcast. Today we're joined by Jason Stockinger, VP and CISO of Cambium Learning Group. Jason, welcome to the show.
Jason Stockinger: Hey, Matthew, it's great to be here. I'm glad we were able to connect and do this.
Matthew Connor: Me too. And again, thanks for coming on. Before we get too far in, a quick word from our sponsors.
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Matthew Connor: And now, back to our show. Jason, for those who aren't familiar, can you tell us about Cambium Learning Group and your role there as VP and CISO?
Jason Stockinger: I'm super excited to tell you a little bit about Cambium Learning Group. We are four power brands. We've got a homeschooling product, we've got an assessments product, and then classroom aids that really make our students and our teachers across the United States feel valued and supported. I joined Cambium about two years ago, and my role is really to protect the student, protect that student data, and protect our teachers who are administering that data. We take that super seriously, and I'm super excited about all of the work I get to do in this great organization.
Matthew Connor: That's fantastic. I think it's really important for people to have that level of excitement and enjoyment in the work, and you don't see it often enough. And I think it gets even more challenging today with the speed of change. Technology is changing so rapidly now. I'm sure people have been saying this since the dawn of time, probably not, but in modern times, technology has been increasing very rapidly for the last thirty to forty years, and now it is increasing at an exponential rate. I think that's really hard for people to keep up with on top of their normal day job. So seeing you with this level of excitement and enjoyment on top of all that, how do you manage that?
Jason Stockinger: Well, honestly, it's having a great team. I tell everybody that I haven't had my hands on the keyboard since 2008, and it's really true. I go to all of the meetings and I'm advocating for cybersecurity in every one of those meetings, trying to get the funding that we desperately need to combat the bad actors out there trying to get at this valuable information. And really, the unsung heroes are those folks taking the phone calls every day from our user community and from our customers. This is a problem, and we take every single one of those phone calls seriously. And then there are our IT operations folks and our cybersecurity operations folks who have eyes on glass, assisted by AI these days, of course. Those guys are really the unsung heroes of cybersecurity. They're the ones making it happen every single day.
Matthew Connor: And it's very clear that what you're talking about there is leadership. I think there is a bit of a leadership void, which I'm sure is a hot take and insulting to a lot of people, although I think a lot of people feel the same way. We see that in a lot of organizations, governments, commercial, you name it, large and small. Leadership's a tough one for people to get right. And I think this is a great segue into your book. You wrote a book on it, and it is an excellent book. I'd love to dive into it, if you would. Can you tell people about your book and what inspired it? Because I think it's a great story and a great read.
Jason Stockinger: Sure. You know, Matthew, I've been in the corporate environment, and I was in the military for twenty-one years, and we've all had bad leaders. Every single one of us can think about that person who may be in our lives currently, that person who is just a horrible leader. They don't listen, and they are very difficult to work with and work for. We all have those horrible leaders in our minds. And I think I was one of those horrible leaders too. When I became a leader, I said, I'm never going to become one of those horrible leaders. But I think when I first started out on my leadership journey, I wasn't that great to work for and to work with, and that's part of what's in the book. Additionally, I've got a neurodivergent son, my son's autistic, and being a parent to him and seeing him grow up and thrive in his own way has really taught me more about leadership. And then being a part of the veteran community and crossing over into the corporate world was a tough transition, as it would be for anybody. As you can imagine, in the corporate world you cannot tell people to drop and give you twenty push-ups. That is just not a leadership thing that happens. I don't know if it happens in the military anymore, but I'm sure it does, we used that as a leadership tactic. So that's what this book is about, some tips and tricks I've learned over the years about how not to be that bad leader, and how bringing together the neurodivergent, the veteran, and the corporate worlds, they all have some similarities and some differences. And you may be sitting on talent that you didn't even realize was there.
Matthew Connor: Yeah. You hit on some really cool points that I think are fundamental to good leadership and often get overlooked. I'd like to dig in on the compassion, the understanding, the empathy portion of it, because all too often people mistake that for lowering your standards, or being a pushover, or just being a weak leader. I think it's the exact opposite, and I think you make a really good case for it in your book. But let's dive in a little bit on that topic, because I think it's wildly misunderstood and underutilized in modern society, for sure.
Jason Stockinger: And Matthew, we've all been in that. If you're a leader and you're hiring folks, or your company is reducing staff or going through a reduction in force or something like that, you've always been in those rooms where it's like, okay, let's look at our folks, and you're looking at a sheet of paper or an Excel spreadsheet with people's names on the list. And there's invariably some leader in the room who says, hey, that person is not a culture fit. That is one of those phrases that I think is a cop-out as a leader. What does that mean? What does it mean that they're not a culture fit? To me, it takes me back a little bit to high school, in that this is a popularity contest from a leadership perspective. So that's a little bit of what my book is about, taking that "not a culture fit" and really digging into what that means for you as a leader. Are you misreading the person? Potentially they might be in the wrong seat on the bus. They may just need to switch over to another area, or maybe they're in the wrong role. Maybe they don't like their role either. So the empathy you talk about, the real counter to that, is just being curious as a leader.
Matthew Connor: Yeah, I think that's a really great point. As you wrote in the book about compassion and that understanding, I wonder, is it just that people struggle with that because it's easier to make the quick decision, like, that's not like me, they're different, and I don't like it? I tend to be more the type who tries to understand where the other person is coming from, versus it's my way or the highway. So I'm curious what your take is. How do you get people to be more compassionate and understanding, especially in a day and age where things seem to be so polarized in general?
Jason Stockinger: There are a number of tactics I've taken as a leader. I remember I was an individual contributor who wanted to know everything. I wanted to be the smartest person in the room, and that is what propelled me to the leadership ranks, because I was a pretty decent engineer. I could figure problems out, I was pretty quick, and I felt like I read people really, really fast. As leaders, we are often presented with forty percent of the information at any given time and asked to make a quick decision. We have to respond quickly, our leaders are expecting results right away, and so we get into this fast-thinking mode that is based on experience that may be decades old. When you're dealing with people, sometimes it takes a little bit of time for the full person to come out, or for the capabilities to be realized. I have found in my leadership journey that when I was making decisions with forty percent of the information, a lot of the time I would make the wrong choices, and that fast thinking caused me a little bit of pain on the back end. So when I'm talking to leaders about this, that curiosity, taking the extra minute to understand where this person is coming from, or asking what am I missing, something is rotten in Denmark and I just don't know what it is, those things can create the clarity and then allow you to take action as appropriate.
Matthew Connor: You talk in the book about cultural fit, and I think this is really interesting, because I'm generally a big proponent of corporate culture. I think it's so important to have the right values and the right level of trust, and I think part of that corporate culture needs to be compassion, creating a place where people feel safe to focus on the mission, knowing the people who are working there are all focused on the mission, because that's what we do. We're surrounded by good people who are trying to do the right thing, and I think that should be the premise, the base for the right corporate culture. But I think it gets conflated. You talk about how we often use "not a good cultural fit" as a reason not to hire somebody who isn't the exact same as everybody else. That feels very comfortable for natural, normal reasons, people like people who are like them, so we naturally gravitate toward that, but you've got to combat that. Can you walk us through your thinking on that?
Jason Stockinger: Yeah, for sure. I've reported to a lot of leaders, and early in my career I really gravitated toward people who had some of the same fundamentals. I gravitated toward people who were laser-focused on the mission, and perhaps even veterans. I hung out with all the guys who looked like me and talked like me, and it was, oh, you served in the military too. It almost became cliquish. When I looked at the people I was surrounding myself with, it was like a mirror. I saw a reflection of myself in all of the people I surrounded myself with, so when I was asking for feedback, I was getting exactly what I wanted, that exact same thing. What I've learned over my career, and what's been taught to me by really great leaders, and I've had some really bad ones and some really awesome ones, is that your team should look like a window and not a mirror. Perhaps that neurodivergent person in the hoodie, crushing Mountain Dews, may be your best ally when it comes to running through log files and doing cybersecurity investigations and forensics work. Maybe that person is totally awesome, but they don't look like me, they don't act like me, they don't have the same values as I do, and their home life may look totally different than mine, but they may be the best person for that particular task. Or perhaps it's the person who just doesn't think like you at all, who comes from a different country or culture, and maybe their English isn't that great. I've built large teams that don't look like me, and I've really learned that I get a lot of value out of those different perspectives, because they come at a problem from a totally different angle.
Matthew Connor: I think it's really interesting, because a lot of this is tied to implicit bias, which I think is genetically programmed. If you go back in time, it makes sense that you're going to feel safer around people who are like you, because you know what they're going to be like. They come from the same tribe, so okay, I can work with these people, and when there are differences, it's like, I don't know, these people from this other tribe, this might be dangerous. But in this modern day, fifty-one percent of the population is female, and even so, the overwhelming majority of leadership roles are held by men. I think this bias still plays in, and it's the exact same thing you're talking about here, I like people who are like me. And if you don't have the self-awareness that you had to say, hey, look, I'm looking in a mirror when I look at my team versus a window, you're not getting the benefit of diversity. It feels good to be surrounded by a bunch of mini-mes, maybe they're yes men, maybe they're not, but regardless, it becomes homogeneous, and you can't possibly get the same results you can get from a diverse team. People like to use the word "diversity" and say, oh, I've got a very diverse team. Yeah, you might have tall guys and short guys and different colored guys, but at the end of the day they're all basically you, because you've made this comfortable team that you feel comfortable with because they're just like you. I think you do a really great job of pointing that out in the book, and you focus on veterans, which I think is great. Being a vet myself, I certainly understand that transition, and the neurodivergence. And I think this applies just as much to women, because it's also a very large, overlooked population. I think we should be past that as a culture. We should be past racism and sexism, and yet we're not. If I'm being really nice about it, I don't think it's some insidious, necessarily evil thing so much as that, culturally, it's built, we grow up in this system, and it permeates everybody in it, men and women, people of all kinds, these biases. And so we get what we've got.
Jason Stockinger: I totally agree with you, Matthew. I think back to a conversation my son and I were having a few years ago. We had gone out for a pizza, and I said, son, I'll split that last slice of pizza with you. And he said, sure, Dad, I want the meat and the cheese and the top layer. And I said, son, we're just going to split that down the middle, that way we can have all of the good stuff and the bread as well. And he said, oh, that makes more sense. What that made me realize in that moment is that he totally thinks differently than ninety-nine percent of the population. When you think of splitting a piece of pizza, most of us would say, all right, we'll just cut it down the center. But he wanted all the good stuff. He's like, you can have the bread, I want the cheese and the meat. That one interaction made me realize there's a whole population of folks who attack a problem a hundred and eighty degrees differently than I would. I never even thought about splitting it that way.
Matthew Connor: I've never thought about splitting a piece of pizza that way either, but it's technically a possibility, and I've seen people do that as well. I've seen them gather all of the cheese and the meat, and say, I don't want any of the bread or the filling or any of that stuff, I just want the good stuff.
Jason Stockinger: As I dug in a little deeper, I thought, how many people in our corporate world are that same way? How many people are looking at a problem and are going to slice and dice it in a way nobody else has ever come at that problem? And perhaps that is the miracle thing we need to move faster, better, cheaper, et cetera. And maybe AI isn't even thinking about that, because of the bias we've built into this technology. Maybe it's not thinking about things that way either. I really feel like there's this community of folks out there who think differently than the traditional corporate worker. Well, don't send that email to that person at this time. Well, you can't go talk to Jane about that right now, because that's not the way corporate politics work, we have to do it this way. Some of the best people I've seen, with the best results, have ignored all of the corporate politics and just gotten stuff done in their own way, in their own time. As a leader, that's what we're looking for. We're looking for those people who think a little bit differently, who can attack a problem a little bit differently, and perhaps are faster and cheaper.
Matthew Connor: Yeah, well, I'll tell you, I loved the approach you took in your book, because unlike so many leadership books that come off very textbooky or theoretical, here are the principles, go apply them, this was a great read. As you go through it, it's like having this conversation, but nicely organized. It's conversational, easy to consume, and practical. You give very clear examples, and I think it really helps people see things from a slightly different perspective. Hopefully people read it and start applying it, because in today's day and age we need more understanding, more diversity, and more appreciation for differences.
Jason Stockinger: I think that is supposed to be the benefit of a consultant, right? Somebody who's not inside the organization, who can come at it and see it from a new angle.
Matthew Connor: I think you raise a good point, you may have that in your organization already, if you can tap into that and appreciate it. And there are just so many good points in the book, I could go on and on. I really like what you say about a neurodivergent person, or veteran, or corporate worker, taking a person and making sure they're in the right role, which you hear all the time. But the way you put it in the book makes it so easily applicable, you're like, yeah, this is a round peg, square hole kind of issue. It's not that they're a bad person or not a capable person, it's just that they're not in the right role. As I'm reading it, I think, you know what, I could be successful at just about any job other than artist or veterinarian. Only because I'm so bad at art, it's a weakness, and eventually I would get okay with it, but I really don't like hands-on work with a lot of animals. It's a weird thing, I'm fine with pets, don't get me wrong, I'm not a weirdo, but that would be a really bad job for me. You didn't even mention anything about it, but as I'm reading that, it's so well done that you have your own thoughts in these practical ways. It really helped me see that if I were in a job at some organization like a vet, I'd be great in so many other places in the organization. Obviously not a vet, but it just really helps you see things. You do such a great job walking people through it that it puts the reader in the right shoes and the right perspective. So kudos. I hope a lot of people pick it up, but you did a great job of that.
Jason Stockinger: Thank you, Matthew. And when you talk about the right fit and the right seat on the bus, I think about all of those jobs that I've worked. Some of them I absolutely loved, and there were other jobs, as I was growing up and coming through the ranks, that I absolutely did not love. I cut grass as a young kid, and I always looked at these guys in suits who were coming home from work, or going into a business and working in air conditioning. And I told myself, when I was cutting grass, one of these days I'm going to wear a suit to work. I worked in a bank for seventeen years, and that is a great place for suits, because there are tons of them. So I really attained my dream. But what I learned through that process is that I was pretty good at cutting grass too. Even though I disliked being out there in the heat and getting dirty, some of the biggest joys later in my life have been cutting the grass, coming home from the bank job or from the corporate world and being able to free my mind of all the distractions and get a little bit dirty. So I think people can change over time. Sometimes those jobs you really feel you aren't suited to can become really enjoyed and loved jobs. There are some people who will just never gravitate toward a piece of the role. I'm one of those people who cannot stand scheduling meetings. In this age of AI, I can tell Copilot or Gemini or one of these AIs, hey, find a spot for me and these three other people. It is the greatest thing to come to my desktop in a number of years. That is a role I really love using AI for. I really wish everybody's calendars were standardized in that regard. As you can imagine, we probably all have six or eight different calendars. We've got the family calendar, and the cousin calendar that we go on vacation with, and all of those things. But I truly believe there's a job and a focus for everybody out there, neurodivergent, veteran, corporate, whoever you are, wherever you come from, there's something out there for you.
Matthew Connor: Well said. And I'm curious, is this where AI really starts to shine? In the book you talk about how it's so much easier to build on a strength than it is to build on a weakness. Is this where AI really shines, in the places where people are weak, where it can fill in so easily? For instance, your calendar example. A lot of people say, that's not a problem for me, I don't mind it at all, in fact I kind of like finding those things. For some people it's great, for others it's not. Is this where AI is going to fill in and make your job so much more enjoyable, because the areas where you don't enjoy it, where it's challenging, taxing, whatever, it now takes care of, so you can focus on your strengths and enjoy more of that?
Jason Stockinger: I think there's an aspect of that, where AI is going to come in and augment the areas we dislike doing. On the other side of the coin, I also think AI may come in and cause more problems than not, especially as we dig into this technical world. I remember the days when I had to program the computer for interrupt requests for the keyboard, you had to be on the right interrupt request so the keyboard would operate appropriately. How many technology professionals would know what an interrupt request is? Is that still happening today? For sure, the hardware still has to communicate with the software, and I think AI is pretty good at that. However, I think there's probably an area where AI may start to drift a little bit. We've seen the models drift away from the information that is really fundamental and core, and I think there's some danger in that. I also think it's going to take over some of the menial tasks we just don't want to do. I love coming into work every day and having Copilot summarize my day, what I've got to do today. As a matter of fact, when I wake up every morning, I get on my phone and ask Copilot, what are you doing today, as opposed to looking at my calendar. That's probably because I can't see as well as I used to in my younger days, but I definitely think there are some advantages here. There are also some areas where I wish AI would take over, and one of those is cleaning my house. If some robot could come in and take care of that for me, I can promise you the members of my family, as well as myself, would be overjoyed, as long as they didn't bug us and do it when we didn't want it done. But I think there's absolutely an advantage here.
Matthew Connor: Well, I think we're on the cusp. I'm excited to see the Tesla Optimus robot when it comes out doing exactly that. But I think the benefits will be so much greater than just that. The cleaning is going to be fantastic, you're not going to have to worry about where's my stuff after the cleaning. But I think it goes even further, in that I think we will see a great reduction in domestic violence, because any house with an Optimus, which eventually I think will be every house, will have some sort of Optimus-like robot there, so you're not going to be able to commit these acts of domestic violence. It's going to stop the guy from smacking somebody around and hurting them, it's going to stop intruders, so home invasions will be down. These are huge shifts, great shifts. So you've got a domestic helper, you've got security, that's pretty spectacular. Will that happen next year? No, but in the coming years we're not that far from it, especially at the rate things are going. I look forward to that. I think it's going to be far more exciting to see what happens on the domestic violence front and the home invasion front. There's just no two ways about it, I think it's going to greatly reduce crime and make life more peaceful and safer for people throughout the world. I think that is going to be the great advantage of AI robots, not these slave armies, you hear these things about how if it just starts making paper clips, it could destroy the world because it's only focused on paper clips, and blah, blah. I don't think that's going to be the problem. I think the outcome is going to be a massive reduction in crime and a huge improvement in safety and quality of life. I think that's what's going to happen.
Jason Stockinger: It's an interesting thought, Matthew, and I hadn't thought about the domestic violence aspect of it. The military in me went straight to the armies you're talking about, if I've got two bots or three bots, maybe I can take out your one. And I really think that CISOs think like bad guys. I think maybe it's because we've got a little bad guy in us ourselves, but we're always looking for where the vector of attack is going to come from, where's my next incident, and we're trying to prevent those things for the companies. I think there are enough of us white hat guys out there who are going to help protect and put guardrails up. Are we there yet? No, it seems like we're always one or two steps behind, but we catch up quick, and never doubt human ingenuity. That's where, getting back to talent, I really think the talent in our organizations is going to help protect us and defend against the bad parts of this. They're also going to help us innovate and think about new ways. Every time I talk to somebody, it's, oh yeah, I'm using AI for this, I never thought about it that way, maybe I can use that in that way as well. I would also encourage those folks who are anti-AI, most of us like vacation, just download ChatGPT and have it plan a vacation for you. Believe it or not, it's really, really good at it. So I want to encourage folks out there that there's talent in your organizations that you're probably misreading, that is probably one step away from stepping out the door, and you're going to lose that talent. As we all know as leaders, it's very expensive to replace talent. You're probably going to pay more for an individual coming in. Sometimes you can pay less if it's a very senior level, but for the most part you're going to pay more. And there's the time you have to look for the person and find another person to replace that talent in the organization, and it may be sitting right next to you every day.
Matthew Connor: I wonder if that isn't also another good use for AI, thinking about the onboarding and offboarding of personnel. And I don't mean necessarily from the company's perspective, but from the perspective of the new employee being onboarded. How great would it be to come in on your first day of work, and you've got your corporate AI agent, you talk to it, and it gets you completely up to speed on everything? When you have questions like, hey, how do we handle this, what is this? I mean, how long does it normally take? Normally about six months to a year for somebody to get up to speed on their job and the company and know where everything is, and then start rolling. How much does that shorten when you have everything at your fingertips, and people are comfortable using it, and they don't have to bother their boss or their peers? Not that it's a bother, but they don't have to go to them for all these answers. They've got ninety-some percent of the answers at their fingertips, in the right way, and they can just hit the ground running being productive at the job they like doing, they just don't know exactly how it's done at this organization. Shouldn't that be the future of the AI-human corporate solution we're looking for? Isn't that how we should be thinking, this is how AI is going to help you get up to speed and do your job better, not AI is going to take your job?
Jason Stockinger: Perhaps. I hadn't thought about that until you said something about it. One of the first things I did with AI at my current organization, and it was actually in a leadership forum where we had made some jokes about it, if you've ever seen Monsters, Inc., there's that receptionist lady who's a chain-smoker with a real raspy voice, and you didn't turn in your paperwork, and she's just really negative. I built one of those, really for myself, and I pointed it at our corporate SharePoint. I just ask it questions, and it also berates me a little for not knowing the answer, which makes me chuckle personally. This persona I've built in agentic AI is berating me, but it has been super helpful, believe it or not. When I ask it who a person is and who they report to, I get this litany: here's where they've interacted, this is probably the project they're working on. It is just amazing how much information is sitting out there waiting to be consumed. Is it right all of the time? Absolutely not. But it has given me a little bit of insight into who's doing what and what the organization is up to, and has helped me get up to speed in a new organization. So I identify with using AI to onboard a little bit. I also firmly believe, as a leader, that there is nothing better than having another person hold your hand and say, hey, here's where the coffee's at, and when you go by Judy's office, she's always got mints on the table, and I like to take a mint. There's nothing like that human connection.
Matthew Connor: I think it's a little bit of both. And I've got a hot take here, but I think what we're going to see is an increase in people valuing human connection, and it's because the technology is going to be so helpful and so good at the technology stuff that humans will do what they do best, which is the human portion of it. I think it frees us up. If you look at the history of technology, and let's just go modern, with the computers, we see what happened with the advent of the internet, and then iPhones and iPads. It was not nefarious, it wasn't something malicious, but look at the effect it had. We have an entire generation that grew up on screens from the time they were born. They didn't know a world outside of screens and internet, and it had a negative effect on their development socially, because prior to that everybody was going out and playing in the yard, playing in the streets until the lights came on. We had an entire childhood where we grew up completely unattached, completely free to go out and play, and we were out in nature. Now we have the other end of that spectrum. We had an entire generation grow up inside, in bubbles, on screens, and they struggled with people skills. And now we're seeing the youngest generations going the other way. They're telling their parents to put the phone down, let's connect, and they're naturally going away from that, like, why are you so addicted to your screen? It's really interesting to see. So if you look at how we're reacting to technology, we had to be in it to be productive, we were the ones making it happen. Now AI is doing that for us. The goal and the job is not to click and clack on the keyboard, the goal is to get an outcome. If AI can produce that outcome for us and help us think and process, great, I think that takes us to a world where we are freed from the computer and screen interface much more and doing much more of the human stuff. But that's my hot take. What do you think?
Jason Stockinger: I like the perspective, and I think back to the early days of the TomToms and the Garmins and navigation and things like that. I was just on a trip with my cousins, and we were exploring our ancestry, trying to go back as far as we could. We actually visited one of my great-great-great-grandparents' houses. We ended up talking to the person currently living in the house, and of course that person didn't know anything about the owners or the people who built the house in the 1800s, but they knew they were living in a historical house. We had a great conversation, and what that led us to was a restaurant we weren't even thinking about, and that restaurant led us to an area, and we ended up meeting a lady who knew some of my grandparents and knew some of the history of that town, a small town in Minnesota, still a small town. We had the best time in that small space, learning about some of our history and about the people who grew up there, people I don't even know, who passed a long time before I was born, or even before my parents were born. We're digging into all of these things, and I think you're exactly right about the human connection you get. But it was the technology that took us to that place, and the AI that curated all of this stuff together and put this information together. It was amazing how quickly and how easily we got there. The trip was set up for us, AI helped book all of the things, and everything kind of lined up into place. It allowed us to have a really deeply human experience with people we had never met before, and that was really cool.
Matthew Connor: Yeah. You said something earlier about always feeling a step or two behind. In the cyber race, it is an arms race, a game of cat and mouse between the bad guys and the good guys. As we've talked about the effects, benefits, and potential future of AI, I can't help but think about these parallels. Look at where AI has taken us when it comes to self-driving cars. Five years ago it was like a drunk toddler, dangerous, it should not be driving, it's drunk and it's a toddler, it should not be behind the wheel. And to watch and experience the progression from drunk toddler to teenager, to teenager getting their license, and now we are at a place where Tesla released the statistics a few weeks ago, and they found that over something like a billion hours of road driving, it is eight times safer than the average human driver, with fewer accidents. I completely believe that, because the other day, maybe a month or so ago, we were driving back from New York in the fast lane, in full self-driving, and the car beside us swerved very quickly into our lane. I guess they didn't see us, maybe they were dodging something, I don't know. But it happened so quickly that before I could possibly react, it was like the cars were in sync, and ours moved over, slowed down, didn't overreact, and it was all over before I could even react. I was like, okay, I'm done. And it's funny, because I saw a video where it was point-one-two seconds, basically four frames, between the time the Tesla sees something happening, like a person walking toward the road, and it responds, and actually, I'm sorry, it takes us way longer to even recognize what's going on. So seeing that trajectory of AI and its real-world benefit, that's such a concrete example, great safety, love it, fantastic. Plus it frees us up to talk and chill and do whatever in the car instead of actively driving. Now, if you apply that to where we are today with AI and cybersecurity, we're in the drunk toddler stage, right? It is so new. We were drunk toddler last year, now we're in the teenage years, because AI in general has gone a long way in the last six months, let alone almost four years ago, when ChatGPT first came out. I'm getting to a question, I promise. Going back to the good guys versus the bad guys, they are leveraging AI and finding zero-day exploits. Historically, there's one elite hacker in the world finding a zero-day, maybe a handful, but they're not coming after you, they're coming after a nation state, they're coming after a big bank like Chase. They're not coming after the average business. And now somebody with a prompt in Lithuania has a zero-day exploit, and they can come after everybody. It's a game changer. And then you see products like Darktrace and Abnormal Security, and even SentinelOne and CrowdStrike, and the way they're using AI. Let's focus on Darktrace, for instance. They're using machine learning to see abnormal behavior on the network and on the endpoints, which is phenomenal because it's so fast, and you don't have to worry about prompt injection, which we can't see. So as the bad guys start to come at us, I think we're now at the stage where we have the technology. It's new, and there's so much going on, but I think the technology is now there, and I think the tide is shifting. I think we now have enough of an advantage on the good-guy side that when applied, we're winning. I know I'm an optimist, but I think those are real examples. You can go with the patching, and now you've got to do all the basic hygiene stuff, but when there's a zero-day exploit and you can get past all of your patches, what do you do? We now have these stopgaps, these RoboCops that can see it happening without being susceptible to prompt injection, without taking your data and putting it somewhere. I think that gives us insight into where we'll be going, back to that car analogy, it's going to be safer and better than humans. Right now humans are in the loop, but soon I think we'll get there. That's my very long, big hot take. What do you think?
Jason Stockinger: I like the perspective, Matthew. I really think there are a lot of organizations out there that have not invested. I see it every day with AI-blocking technology. The reason I feel like the bad guys have a little bit of an edge is that there are so many organizations still scared of putting AI in their environment to combat these AI threats. I agree with you for more mature cybersecurity organizations, for sure. I've come from some of the most mature companies out there, where we had great cyber ratings and we were looking at everything, and we had every single domain covered, with a good degree of efficacy around our blocking. And really, we were playing offensive security and helping the authorities out with catching some of these bad actors. I've also been on the other end of the spectrum, where it's like, well, I run my updates every month, and sometimes we don't get to them, and I've got a password on my Facebook account. You talked about the driving cars a little bit, so I have to go back to that. I would love a world where I can get into any self-driving vehicle and feel safe. I grew up in the Top Gun era, where we wanted to go Mach 2 with our hair on fire, and I got my share of speeding tickets when I was young. I love driving, it's the greatest thing since sliced bread. But as I've grown older, I've had the experience of the moms in their minivans trying to manage the kids in the back, and the truck driver who's been on the road for eighteen hours and is falling asleep, and I've seen some of the worst accidents out there. I really think this era of self-driving is something I'm ready for, like, sign me up. But at the same time, we still have that human in the loop today, and I think we've got to get the human out of the loop to really up the safety efficacy, because the humans are where the problems lie. Even in very large organizations, I think most CISOs will tell you the problem they have is not with their back-end technology, where they've got AI configured and it's looking at things. It's really that their users are clicking on stuff and going places they shouldn't go, and they are causing the incidents in my organization. I don't know if there's a patch for the human at this point, but if we could give over to AI some of the things we hold near and dear, and perhaps focus more on our human relationships and those human elements, I think we're going to be way better off.
Matthew Connor: I couldn't agree more, Jason. It has been an absolute pleasure talking with you today. But before we go, can you tell everybody where they can find out more about you, more about Cambium, and more about your work, your book for sure?
Jason Stockinger: cambiumlearning.com is the place to go to find out about our education technology products. There's lots of legislation out there about screen time, and I promise this is really, really good screen time. For those folks who say, I don't want my kids on the screens, I get it, I didn't want my kids on the screens either. We've got some print products that are just as great, and you can order them. We primarily cater to school districts, but we've also got great homeschooling products, so go check us out at cambiumlearning.com. You can always check me out at jstockinger.com, and my book is available on Amazon.com. It's called Stop Misreading Talent.
Matthew Connor: Awesome, Jason. Thanks again, and until next time.
Jason Stockinger: All right, thank you.