[Auto-Generated Transcript of the Podcast Audio with Edits]Today we’re going to talk about AI, and this is based upon a presentation I had a chance to give back in 2024. I’m writing this in August of 2026, so I’ve had a couple of years to let this simmer. But the core concepts of this original presentation really stand, and I’ve continued to expand my thinking and deepen my thinking around the implications of AI, and particularly the spiritual implications of AI. Some people know that my original research and my doctoral work was really focused upon the social, spiritual, and ethical implications of technology, and I presented on this topic in the 1990s and the early 2000s, and it eventually turned into a book, some of my early thinking on it, called Digitized: Spiritual Implications of Technology. And while there are parts of that book that are somewhat dated today, the core principles, the premise of the book still stands, and a lot of the fundamental principles, concepts, what I hope are biblical concepts, still stand for today. So you’ll probably see a little bit of that coming through in my reflections here. But let’s talk about it. My original presentation, though, on AI was called “AI and the Soul: Christian Identity and Faith Formation in a Digital Age.” And every presentation, for me, is an opportunity to share. But this one felt especially meaningful because it touched on a topic that’s increasingly prevalent in our schools and our communities, and it touched on a topic that I’d been reflecting on for over two decades and studying in various ways. I’m continuing to grapple with this and make sense of it, and I have a little bit of a civil war going on inside, if I’m completely candid, about some of these matters. They are yet to be resolved. But I remember in this presentation, the energy in the room was really incredible. Educators were clearly intrigued and concerned, and I think some were pretty eager to figure out how to help their students navigate life in a world where artificial intelligence is increasingly prevalent. I had over fifty attendees who stayed after the session just to talk, to discuss, and reflect about the urgency of a number of the questions, and that was already two years ago. Consider what has happened just in the last twenty-four-plus months. Let me just walk you through some of the key ideas, and we’ll start with some basic foundational ideas about what AI is and what it isn’t and where it is right now, and then we’ll get into some principles and questions for us to consider. Now, when I’m talking about artificial intelligence, I’m talking about the simulation of human intelligence in machines and in various computer technologies. So these systems are programmed to perform tasks that typically require human cognition. This could include things like problem-solving or decision-making or learning, understanding a language, recognizing patterns visually or sound patterns, patterns in text. Could be in a variety of things. And there are really three primary types of artificial intelligence. There’s one that some people refer to as narrow AI or weak AI. This is really designed to perform specific tasks, things like voice assistants. Siri or Alexa would be examples of this. Recommendation systems, Spotify, Netflix, chatbots. This is where we are right now with a lot of the AI tools that we’re using, and it’s the only type of AI that, to our knowledge, is really widely prevalent today. Although some people would argue that we’re already at this next type of AI, which would be general AI, or some refer to it as strong AI. This is a system capable of performing any intellectual task that a human can do. Experts predict that this could emerge sooner than we expect. I remember when I was giving the presentation two years ago, experts predicted that this might emerge somewhere between 2060 and 2100. So we have a little bit of time. Yet since then, people have moved that date up significantly to the point where some are expecting it to happen in a matter of months or years, and others argue that maybe it’s already present. What some people would argue is that what we’re really seeing today is just increasingly complex weak AI, that first category, combining multiple human-like tasks into one system such that it begins to look and feel more like how a whole human mind works. But it’s not there in its entirety. Yet also keep in mind that in one sense, most of us humans don’t even meet the standard of general AI, meaning that we vary in our capacity to conduct various types of cognitive tasks. Some of us are better at recognizing visual cues and auditory cues than others, and some of us have higher and lower levels. And that’s why we have different theories like Howard Gardner out of Harvard, the cognitive scientist who liked to describe human cognitive abilities not in terms of a single IQ or a single intelligence, but he talked about multiple intelligences. There’s musical intelligence, interpersonal intelligence, intrapersonal intelligence, mathematical-logical intelligence, and so forth. So he had a number of categories. If we think about AI in a similar way, and we’re comparing AI to human cognition, that it’s really fundamentally built upon the framework of the idea of human cognition, then we could say that really narrow AI and general AI blend together. That in essence, you have narrow AI, you have a number of capabilities that could be merged into one system that are increasingly reaching levels of complexity that are comparable to some humans and maybe not all humans. So then we get the third category, which would be super intelligent AI. Now, this is another stage, and I would argue that this is, at this point, hypothetical, where artificial intelligence completely surpasses human intelligence across all fields. Some predict that it will follow general AI by fifty to a hundred years. Others think that it will come rapidly after general AI is accomplished. Yet what’s already here and likely to be more immediate is increasingly complex weak AI that far exceeds human abilities with regard to very specific tasks that were formerly done by human beings. And this is already happening, and it will continue to expand in the weeks and months and years ahead. So for example, let’s imagine that we have a medical doctor who’s using their training and their cognition, their senses to identify tumors in a human body, and they’ve done it largely in a manual process where they receive the images or whatever kind of data is made available to them, and then they analyze those data, and they can determine where a tumor is present, its size, all of those sorts of things. Well, it’s very possible that a technology could identify tumors with much more sophistication and detail than your typical human being or your typical doctor, or maybe any doctor at some point. So is that super intelligent AI? Well, it is narrow AI that is super intelligent in one specific task. And then you add to that, and you get this system, eventually, this hypothetical system that just has that level of proficiency or skill in these cognitive tasks, such that it’s hard to find any task that a human being can do better than AI. That’s the theory. That’s the framework. I’m not arguing for it. I’m just saying that’s what we’re dealing with when we’re looking at artificial intelligence. But I would argue that generally what we’re dealing with right now, most of the technologies that are available to the public that we know about, they are forms of narrow AI, but they’re being combined together. And over time, a narrow AI cognitive task that can do one thing and a narrow AI cognitive task that is very similar. You begin to lump them together almost like Legos, and it builds something more complex to the point that eventually maybe people are willing to call it general AI. And some of those exceed human capabilities so far that they begin to call it a hint of super intelligent AI. You get… Get full access to Faithful and Flourishing Christian Schools at www.faithfulandflourishingchristianschools.com/subscribe