Cindy Lopez: There’s a lot of talk right now about AI and the way kids access and use technology. It’s in daily life through entertainment and even in places like school. At Children’s Health Council, we believe technology can be a force for good in the communities that support and educate kids. And families are a child’s first support system, with educators there right alongside with them. So that’s why we created Ellis. Ellis is a chat-based resource for educators that provides evidence-aligned guidance, drawn from trusted expertise. And we use AI to surface that guidance quickly. Over the past year, our team at CHC has worked thoughtfully behind the scenes to build Ellis in a way that supports educators who support your children. So, when teachers encounter challenging moments, whether a student is struggling with focus, anxiety, behavior, or learning differences, they can describe what they’re seeing and receive meaningful guidance in one place. Grounded in over 70 years of CHC experience, Ellis helps educators respond with clarity and consistency, so students receive thoughtful study support from their teachers. You can learn more at askellis.org or find the link in our show notes to share with your favorite teacher.

Welcome. My name is Cindy Lopez, the host of this CHC podcast, Voices of Compassion. We hope you find a little courage, feel connected and experience compassion every time you listen.

Artificial intelligence is everywhere, from homework tools to social media algorithms, but what does that mean for your child? In this episode, we sit down with renowned computer scientist and AI expert, Kerrie Holley, to break down what AI is and isn’t, how it’s shaping our daily lives, and how parents can set healthy guardrails without fear or panic. So listen in as we discuss how generative AI works and the importance of teaching critical thinking and reasoning and how to support your kids in this age of AI. And the takeaway, you don’t to need outsmart AI, you just need engaged parenting, open conversations and clear values. Really excited to talk about this topic that’s AI and what parents can think about and give some advice around the topic of AI and their kids. So, before we launch into the conversation though, I’d love it if you could take a minute to tell our listeners a little bit more about you.

Kerrie Holley: Yeah, absolutely. So, the short story is I am a father, I have four kids, two of which are adults. One is a freshman at college and one is in seventh grade. So, I sort of run the gamut of parenthood. And, of course only very recently have I had a child who has to experience the era of AI. In terms of my professional background, I started writing programs as a high school student, which is not remarkable because six year olds and seven year olds do that today.

Cindy Lopez: But I didn’t, so I find it remarkable.

Kerrie Holley: But, I started in ’68 before the personal computer, before the arrival of Google and Apple and Facebook, and Meta, and Nvidia, et cetera. So, I’ve been writing software for quite a long time. At that time I was doing punch cards and teletypes and old languages called Basic and Fortran. But I went to school as a mathematics major. At that time there weren’t a lot of computer science programs in the late sixties in the United States, and particularly not in the Chicagoland area where I needed to go to school. So, I used computers still at the university, but really to solve math problems, left the university, became a programmer basically at a big retail company where I was writing order processing software. I got bored, decided to quit the profession, and went to law school, finished law school, and instead of going into law, I got attracted by a startup, a vendor named Tandem Computers. Their technology is now part of HP, but it opened my eyes to a new arena of technology working for a vendor is where you actually create the technology that people use. So, that was an eye-opening experience.

From there, I moved to California. I joined IBM, which is where I spent most of my career. So, at IBM I did just a number of things, traveled all over the world, got involved in a lot of innovative technology things. I first got my introduction you might say to AI with the 2011 IBM win in jeopardy, which some of you may remember, but what was fascinating is I was not a part of the IBM development team, but I had a CTO role at IBM at the time. I was also an IBM fellow, and IBM fellows there were very few of us about 40 and 50 in the organization appointed by our CEO. But at that time, I was asked to go on stage the day after the Jeopardy win, along with the chief scientist, David Ferucci and others, one other, a medical doctor to really talk about what people had just seen with Watson beating the world best jeopardy champions.

Post that event, I was asked to help monetize the technology within the IBM company. When I say monetize, I don’t mean from a financial standpoint, but to help from a business and technology standpoint, how we could leverage this technology, broaden it beyond the usage in a game show. So, that’s my first introduction and from there, I’ve been involved in quite a few things. So, a lot of my AI work was done at Cisco, where I spent the year after I retired from IBM. I then spent about four and a half years in healthcare where I spent time with the largest healthcare company in the country, perhaps in the world where I led an AI team, about 150 people: PhDs, researchers, scientists. And my role was to really introduce that organization to an aspect of AI. And I’ll get into that later in this conversation. And, from there, then I joined Google. I was recruited by Google; spent about three years there and then decided to retire from work. And now I spend my time both engaging with universities, engaging with K through 12, mostly middle school, I should say through high school and other endeavors around the area of AI. And I’m proud to say that along the way, I got inducted into the National Academy of Engineering, and I also got inducted into the National Inventors Hall of Fame for some significant interventions that I did with my experience and projects at IBM.

Cindy Lopez: Wow, that is pretty impressive. There’s a lot there. This is not necessarily related to your technology experience, but I also read about your school experience. Is that true that that was kind of a unique experience, your school experience in Chicago?

Kerrie Holley: It was, I went to a school that’s called Kenwood Academy today and that school as I said in 1968, it was a new school. I think I was the second year of its start. But the point is that there’s a technique called timesharing where the Chicago public school system had a big mainframe computing system, and we were able to basically share time on that computing system. Our instructor basically was new to computers himself, it was only like five of us in the class, and he turned the class over to us and said, “Hey, teach yourselves.” And, we had, you know not 24 by seven, but we had a lot of time that we could spend. Uh, so that was a unique experience in Chicago, I think a unique experience in the country where high school students had access to a computing system.

Cindy Lopez: Yeah. Wow, that’s amazing. And with all of your experience and your deep knowledge of AI, I wonder, let’s start by talking a little bit about what is AI? What is generative AI?

Kerrie Holley: Yeah, I think I bring a unique perspective in terms of talking about AI, which I’ll get into. But let’s start with answering the question you just asked. So, I think everyone knows AI isn’t new. The idea has been around since 1950 or the 1950s. The term was coined in a conference in Dartmouth where there was pretty much all the founders of AI sat and met and talked about all the things that we’re talking about today in terms of machine learning and natural language processing and computer vision, and I’ll talk about what those are in a minute. But basically when you talk about what AI is then and now we’ve always imagined computers doing things that only humans could do as being what AI is like: thinking, seeing, or making decisions. So, that’s still the basic idea today that AI means that using computers to do tasks we thought required human intelligence. So, that’s the big picture, but under that big umbrella called AI, there’s something that’s more specific because one of the biggest breakthroughs in AI came in the 1990s, something called machine learning. And machine learning means instead of programming a computer with rules, we let it learn from examples. And people already use machine learning everyday. I mean, they don’t use it directly, but they use apps. They use devices and programs that are using AI, that are using machine learning, which is a subset of AI – your iPhone recognizing your face is machine learning; Netflix recommending shows; Amazon suggesting products; Instagram or TikTok choosing what to show you; self-driving cars. They all have one thing in common, they learn from data. So, a simple example, if we teach a computer what a cat is and imagine how you would do that. You don’t give it a rule book, but you give it a cheat sheet. The cheat sheet is thousands of pictures of cats: fluffy cats, black cats, big cats, tiny cats. And eventually, the computer can accurately predict, because that’s what’s going on, it’s predicting with a high probability that that’s a cat. So, that’s how machine learning works by learning from data. We show a computer thousands of millions of pictures of cats over time. It learns the patterns, pointy ears, whiskers, tails. It’s kind of like giving the computer a big cheat sheet. And then something else happened, which we should understand. So, I’m talking about AI in the big picture. I’m talking about machine learning, which is really the heart of AI. And then there’s another element of machine learning called deep learning. That’s where we sort of take the next step. You know, if machine learning is like learning to spell words, deep learning is like learning to read whole paragraphs.

So, deep learning lets computers recognize far more complex patterns. So, for example, when I was in the healthcare business, we were using machine learning to predict whether someone would get diabetes, and maybe we could predict that with a 95% accuracy. But when we put and apply deep learning, we could increase that accuracy from 95% to 98%. Now, that 3% doesn’t sound like a lot, but when you talk about saving lives in a population in millions, that’s a huge number of people whose lives you’re affecting. So, deep learning lets computers recognize these very complex patterns, faces, voices, handwriting, emotions, patterns, and I know this is a long definition, but I think it’s useful to the reader. But then, we have a local computer scientist, Fei-Fei Lee, who around 2012 had a major breakthrough. She asked a simple question, because in 2012, we didn’t have the facial recognition that we see today. Uh, she said, what if computers aren’t bad at seeing, we just haven’t shown them enough. So, she led a project called ImageNet, which was basically a giant photo library, millions of labeled images. She crowdsourced, got people from all over the world to basically say, that’s a car, that’s a cat, that’s a dog, that’s a house. So, computers got dramatically better at recognizing image. By the way, this field is called computer vision that’s how computers see. So, when you think about what is AI, it’s what I said, but it’s also a field of study. It’s a field of study around computer vision. And then we have another professor and computer scientist, Andrew Ng, who said, you know, kids are playing games with these GPUs and gaming computers. What if we were to use the same computing in a gaming computer and used it to do the algorithms, to do the deep learning and suddenly super computers, you might say, came into being, bigger computers, more data, and suddenly we have what we have today, this idea that drives AI.

Cindy Lopez: One of the reasons we’re able to have conversations like this–grounded in real expertise–is because we collaborate with content partners and educators who are thinking deeply about what students and families actually need. That same spirit is behind Ellis. Ellis is a chat-based AI tool built to help educators quickly access the 70 plus years of evidence-aligned resources from CHC and trusted partners in the mental health and learning differences space. If you’re curious about how Ellis works, or you’d like to share it with your favorite educator, you can explore it at askellis.org.

That was all really interesting and how it all tied together, especially as I think about the chronological timeline too, of how things happened. I am mindful of something that you and I talked about previously is like there’s no physical thing called AI. So, it’s always a human, it’s always a person that’s creating. Do you want to comment more on that?

Kerrie Holley: Yeah, actually a couple of things. That’s a great point. So, before I do, just very quickly to answer your question about what’s generative AI. So, we’ve talked about AI in terms of recognizing cats, identifying faces, recommending movies, but generative AI is different. It doesn’t just recognize things. It creates things. And that’s what’s really different whether we are creating texts like with ChatGPT, images, music videos, code. So, that’s what’s different. One of the more interesting things I find about AI is that the industry at large, the media, journalists, historians, philosophers, if you go to YouTube, you see an abundance of this. They use AI as an umbrella term, as a generic term. So, you’ll hear very influential figures in our society and our world who will talk about the disturbing effects that AI might cause, who will talk about the harm that AI may cause. But as a student, as a parent, it’s important to understand that as you just asked me, AI is not a thing, it’s not a physical thing. So, when I say it’s not a thing, what I’m really saying is that the only things that can do things in our world are people can do things, systems can do things, and machines can do things. There’s nothing else that I know of in our physical world that can take action. I’m not talking about nature, so obviously nature can do things, but the point I’m making in terms of our physical world, there’s just no physical thing called AI. And why is that important? Since you can’t touch it, you can’t trip over it, you can’t point to it sitting in a room. It’s not sitting somewhere in the internet. It’s not sitting somewhere in the cloud. It’s not a robot. It’s not a machine. It’s not a beam. It’s math and software. So, in the physical world, if only people, machines, and systems can do things, when people say that AI decided, AI took action, AI caused this, that’s the wrong question. The better question is, what product or system are you talking about? Who built it? Who turned it on? Who’s responsible for it? Once you ask those things, it becomes much more clearer. Because if you think of AI like electricity, electricity doesn’t decide to turn on lights. It doesn’t choose what songs to play. It doesn’t decide where a train goes. People design systems, so the nefarious things that could go wrong with AI could be because we built a system that did something that is bad or people are doing things that are bad. But it’s important to understand that the dystopian views that people talk about when they talk about AI, the reason those are scientifically flawed thinking is because since AI can’t do it, if you’re going to tell me that AI is going to cause this bad effect, you’ve got to tell me what system is going to do that. Has it been built already? Do we know how to build it? Where has it been built? Those are the questions I think the media has never asked.

Cindy Lopez: Yeah. And you alluded to this, when you were talking previously too, it’s part of our lives. It’s somewhat, I don’t know

if ubiquitous is the right word, but we are using it in our lives already. And you mentioned, a few ways that we are using it. What are some ways that it’s being used, even ways we might not recognize as AI?

Mike: That’s a great question. I think that it’s become so ubiquitous in terms of helping and shaping our lives that I don’t think generally that most people realize that, and I’ve said this, but using YouTube; the filtering out our spam; choosing the fastest route with our mapping applications; phones unlocking when they see our face; deciding what shows up in our feeds. Or you know, your doctor may be calling you and saying, “Hey, I think you should come in for these tests. A lot of these systems are built using very basic AI, the AI that is vogue or rather talked about mostly today because of things like ChatGPT or Perplexity or Claude, they think this is magic because I can give it a document or I can tell it to write a document and it’s remarkable what it does, but this is still statistical. I mean, most people don’t recognize that. And, I’m going to answer this question a little bit differently. So like, if I use ChatGPT everybody knows that they’re using AI, but what they don’t know is what’s happening, right? They don’t know that I can represent good grammar, I can represent bad grammar. I can represent a particular writer style all statistically. And because I can do that statistically in terms of statistical patterns that enables these models, which we know as large language models to be able to seemingly do remarkable things and looks like human understanding. CHC’s Voices of Compassion podcast is made possible by the generosity of people like you. To learn more about supporting CHC, go to chconline.org/donate. Also make sure to follow us on social media for more inspiring and educational content from CHC.

Cindy Lopez: I think part of what people are experiencing is that it’s really hard to get away from AI. It’s so ingrained into what we do every day from our phones to you mentioned GPS to all kinds of things. So, I think one of the things that I’m hearing from parents about AI is because it’s so ubiquitous it seems like it’s out of control and parents are thinking about how they can control the use of AI with their kids. I know you’re a parent, I’m wondering what your take is on that. Do you have any concerns, or what are you hearing from other parents?

Kerrie Holley: Well, I think the concerns that I’ve heard and see are well founded and a lot of those concerns to be clear, I would assert are not solely because of AI, it’s because of the systems that are using AI. So, I’m going to answer this again in two ways. We have you know, systems like, Meta’s Facebook that have been built to keep your attention, show you content that you’ll react to, keep you scrolling, and they’re using AI to do that. But it should be clear that it’s a combination of a system that those companies have built plus AI and those could have some bad effects. And some of those have been well documented lawsuits, have been launched because of some of the bad effects. So, the point is that I don’t think avoiding AI is realistic. And I think we have to ask ourselves, how do we manage it? So, I think what parents want is control and boundaries. They want to control, and that’s what I’m hearing how my child uses AI and what I think they mean at least I know what I mean when I say that. I want my child to think critically. I want them to stay safe. I want them to learn, not cheat. I want technology to support growth but not replace effort. So, that’s what I think most parents want. So, and I don’t think they want to stop the use of AI, but they want to make sure it’s not making their kids lazy. AI doesn’t make them lazy, but how they use it could make them lazy. And so it’s important that parents understand, okay, how do I do this? And we’ve been here before, by the way. It’s just a more profound or more impactful technology because I remember using slide rules before calculators, and I remember people saying, well, if you don’t use a slide rule, you’re not going to be as good at math. And now with some of the math problems we’re solving, we need the speed to be able to use a calculator to solve the problem. So, we’ve been here before. So, tools don’t replace effort, our choices do, and AI is a tool. It can help explain a hard concept. It can give examples. My daughter is in seventh grade and one of her friends in preparation for a test basically asked ChatGPT to prepare a study guide for her, and then it asked ChatGPT to quiz her. I think that’s a great use of AI. And, uh, so I think what parents and teachers can do instead of asking, should kids use AI, a better question I think is how should kids use AI? And some helpful rules – AI can explain, not answer, it can help brainstorm, not submit work. I mean, those are the things you shouldn’t be doing. It can support learning, not replace it. So, I think the bigger picture, as you’ve said, AI isn’t going away. So, the goal as a parent, my goal is to help in thinking, judgment, responsibility, curiosity.

Cindy Lopez: Yeah. And I think your point about all the critical thinking and reasoning and learning and helping kids understand and see, be able to evaluate like what’s biased or inaccurate content or inappropriate content, like for a student, being able to like sift through all of that is an important reasoning and learning task for them. And it seems like it would give students, kids more opportunities to really develop critical thinking and reasoning in a bigger way. There could be also students who are out there thinking, well, why do I even need to go to school or are there going to be jobs for me? Is AI going to take over and will we lose jobs because of it? What do you think about those kinds of questions?

Kerrie Holley: Again, great questions, reasonable concerns, and we have a challenge today, to talk about one particular sector of jobs that a lot of pundits we’re pretty strong in stating, software developers is a skill of the past, software engineers is a skill of the past because now AI can write code and AI can replace this large pool of software engineers that we’ve had. And there’s a YouTube video on this. I’m using this as an example, but we can go across industries and give other examples. For example, there’s something called Vibe Coding and Vibe Coding is, there’s just a ton of companies that have built tools that allow you to literally generate with a push of a button and in seconds or if it’s a little bit more elaborate in minutes, be able to not only create websites, be able to create programs, and so forth.

So, two answers to your question. What’s happening I would assert in our industry at large is that a lot of companies are deciding not to pursue certain projects and instead invest their capital in buying hardware and data centers. A lot of the tech companies are doing that because they need these large data centers and in order to fuel the products that we’re beginning to see in our everyday lives. So, that’s not AI taking the job, that’s a company deciding to make an investment in machines versus people, not machines that are doing AI, machines that are helping build AI.

The second thing is, and I mentioned vibe coding because very recently what has been discovered, and we knew this, many of us, that yes, I can generate code fast and I can replace all these people, quote writing code, but it’s not going to be sustainable code. And what I mean by that is we’ve been here before. And not to get too technical, but as someone who’s been writing software in every era of computer, we used to have some tools called, visual programming where basically I could draw what I want and generate code. That was abandoned, by the way, for the same reason generating code with AI is going to be abandoned to a large extent is because the code is hard to maintain. And when you have code that’s hard to maintain it creates very similar to in the financial markets, we all know about credit card debt and coding there’s something called technical debt. And if you have technical debt, what that means is that whenever you want to change a system that you’ve built, there’s a cost to that if you’ve written sloppy code and there’s a lot of AI slop that’s now being produced that companies are basically having to revisit, to say to themselves, okay, I’ve got to make a huge investment here in something I didn’t intend to. So, that’s something that’s really different. I think the YouTube video’s called, Why Replacing Developers with AI is Going Horribly Wrong, but one of the more famous computer scientists predicted, it’s on video, five years ago that AI would take the jobs from radiologists, and now five years later, we see the demand for radiologists is on the rise.

I was talking to a yoga friend of mine who’s a lawyer, and we were talking about AI and he said, uh, him and two other lawyers were talking and he said, “Hey, how are you using AI at work?” And then I asked the question, “What does AI do for you at work?” And he said, “Everything.” I said, well, John, if that’s true, why are you still working? And the point I’m making is that, you know, as computer scientists and the people who make these predictions about job loss, job loss is for a lot of economic reasons, but AI is not the dominant reason, I would assert, because, you know, as a computer scientist, we don’t know the ins and outs of what a radiologist does.

And, I was looking at another video where this woman was just making a joke about AI and she says, ‘When is AI going to take my work? I’m tired of cooking, I’m tired of cleaning the floors.” You know, she just had a laundry list of things, but my point is every job that we see, yes, AI will have a tremendous value add. AI will be able to create assets. if that’s all your job involves, is creating assets, like code is an asset, a website is an asset, a spreadsheet is an asset. Go down the list, but I would assert that most jobs do a lot more than create assets. And unfortunately or fortunately, AI’s not going to replace that work.

Cindy Lopez: Thinking that most of our listeners are likely parents, what advice do you have for them, parents and caregivers regarding, I’m going to call it guardrails for their kids’ use of AI? I think parents are filled with a little concern about AI and its potential impact on their kids. So, do you have advice for them about guardrails?

Kerrie Holley: Yeah, absolutely. I think start with values, not rules. So, what do we want learning to look like? What does honesty mean in our family? What does healthy curiosity look like? And I think with that several guardrails jump out at me. Number one, AI is allowed, but not invisible. So, the use of AI should not be a secret. That doesn’t mean spying, it means openness, shared understanding, just normal conversations. Kid says, “I use AI to help me understand this.” Great.

Guardrail number two, line of sight matters. Parents don’t need to monitor everything, but they should maintain a line of sight. That means knowing what tools your kids are using, understand what they’re watching or generating, checking in regularly. You don’t need constant control, but you need awareness.

Guardrail number three, phones and access should be age appropriate. There’s no single right age for a phone or AI tools. Every child is different. Parents are going to have to make that call. What matters is maturity, responsibility, context. I remember my college student doing something which we certainly told him it wasn’t a good thing to do, and he learned from that because we didn’t stop him or monitor him or spy on him. We just told him, what our values are, what we believe his values are, and he never did it again. He understood very clearly.

Guardrail number four, teach navigation, not avoidance. I don’t think kids need less technology. I think they need help navigating this digital world. So, questioning information, recognizing bias, understanding manipulation, knowing when to step away. These are life skills, not just tech rules. And, critical thinking we don’t teach that enough, but that’s key. And of course we as parents, we got to model, healthy behavior. And then maybe another guardrail is around education. It’s going to be different at different schools.

I love what I see some schools doing, which is like my daughter, I was talking with her the other day. And she’s been using AI to help her understand math, but the teachers, one of the ways they help the kids is, and my older kids who are adults who went to a school in San Francisco, it did the same thing, which is this concept of retest. So, a student gets 6 out of 10 in a test, and then they have a conversation with the teacher to explain what they missed. And the teacher says, well, let’s do it again. And then boom, they get 10 out of 10. They could have easily, the teacher said, why don’t you have a tutor session with AI right now? And then 10 minutes later, let’s see if you’ve learned anything, but the point is, that’s education. And I think parents got to decide without judgment. We have to not have judgment for what other people are making decisions. But the calm takeaway for me is, we don’t need to outsmart AI, we don’t need to ban it. We don’t need to get it perfect. We just need to have engaged parents, clear expectations, open conversations, and consistent values. I hope that helps.

Cindy Lopez: I’m always reminded in a lot of conversations we have on these podcast episodes with our clinicians a lot, they talk about parents, caregivers, even educators, one, to listen. Listen to your kids, what are the needs that they are hoping to meet with using AI? And also be curious, ask the questions. And those kinds of things help them build their reasoning and thinking skills. So, I really appreciate everything that you’ve said, Kerrie, too, about those guardrails, and I think some really important things for parents to remember. So, I’m wondering, Kerrie, as we think about this conversation today, what do you hope that our listeners really hear from you?

Kerrie Holley: I hope they have a balanced view of AI – it’s neither a miracle nor a menace. It’s not smarter than you. It’s a powerful tool. The real question isn’t whether it’s good or bad, but how do we guide our kids to use it well? You know, there was a time when people were scared of things like magic, but AI is not magic. This is just math, and I’m going to go back to something I said earlier. Whenever you hear something that frightens you about AI, you should be asking the question, okay, what system? A system, by the way, could be an app, it could be a website, those are examples of systems. What system are we talking about that has made you frighten? So, if a speaker, a newscaster, says something, if they haven’t identified the system, they’re just in my opinion spreading nonsense. If we can’t identify the system, the machine or the person, we really can’t go any further. We’re just using AI as an umbrella term. It would be like, and this is my takeaway, my last takeaway is if someone told you that transportation will one day cure the climate challenge problem, you would ask questions. You would say, well, what are you talking about? You talking about cars, more cars? You talking about scooters? Are you talking about bicycles? What are you talking about? But with AI, we don’t ask that question. People just say, AI is going to cause jobs to be lost. AI is going to be a digital being and well, AI’s not going to do any of those things. The question is, let’s be specific: what system, app, website are we talking about? Oh, you’re talking about something that hasn’t been built yet. You follow what I’m getting at? Just stay calm. A lot of these dystopian views are not based in computer science or science at all.

Cindy Lopez: Thanks so much, Kerrie, for spending the time with us today. And for me, one of the things I’m walking away with is that understanding that AI doesn’t exist without some kind of you know, skeleton around it.

Kerrie Holley: Exactly. Yeah. It’s got to have a physical embodiment.

Cindy Lopez: Right. Right. And I think that that’s really important. And what you just said in terms of asking questions. So, what system is this AI actually running in? If you have questions and you’re concerned about your child in terms of their mental health and how technology might be impacting them, please reach out to us. You can reach us at chconline.org. You can reach our care team at [email protected]. Thank you so much for joining us, Kerrie, and our listeners as well.

Kerrie Holley: Likewise. Thank you Cindy. And thanks to all the listeners for listening. 

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