Headagogy, with Steve Pearlman

About Headagogy, with Steve Pearlman

One of the world's premiere critical thinking experts, you can view Dr. Steve Pearlman's viral Editor’s Pick TEDx talk here: https://youtu.be/Bry8J78Awq0?si=08vBAR1710mgQt0i stevenjpearlman.substack.com (https://stevenjpearlman.substack.com?utm_medium=podcast)

Publisher

Steve Pearlman, Ph.D.

Category

education · society & culture

Language

en

Explicit

No

First episode

11 Oct 2017

Latest episode

9 Dec 2025

Latest episodes

66 episodes in the feed.

1. 

   9 Dec 2025

   ChatGPT "Improves" Critical Thinking in Kids...But Not Really

   📍 📍 📍 think. This study found some evidence for enhancing critical thinking through the use of ChatGBT. The researchers followed 25 students as they wrote essays with the assistance of ChatGPT. Afterwards, students reported gains in critical thinking, system thinking, and strategic competence. That sounds great, right? Well, the devil is in the details. Toward the end of the report, the researchers casually mention something that’s actually crucial. “It should be noted that the students associated AI’s effect on critical thinking with its imperfection-- the perceived need to reformulate their question or to verify the obtained response, lacking the necessary depth. In other words, because ChatGPT’s outputs were so flawed and often incorrect, the students had to think more to make sense of them and about how to use AI at all. So, saying that using chat GPT improved their critical thinking is like saying that driving a car increased their automotive knowledge. Except, it wasn’t driving the car that increased their knowledge. It was that it kept breaking down and they learned automotive knowledge because they had to keep repairing it. So beware of how your kids are using AI, as well as how you are using it yourself. And for more important insights into critical thinking and AI, follow me here at Actual Intelligence and at my Substack “Pearlman Actual Intelligence”. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit pearlmanactualintelligence.substack.com (https://pearlmanactualintelligence.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

2. 

   27 Oct 2025

   Free Your Brain from ChatGPT "Thinking"

   If you you’re someone who values being able think independently, then you should be troubled by the fact that your brain’s operates all too much like ChatGPT. I’m going to explain how that undermines your ability to think for yourself, but I’ll also give you a key way to change it. How ChatGPT “Thinks” Let’s first understand how ChatGPT “thinks.” ChatGPT is one of several Artificial Intelligences that’s called a Large Language Model or LLM. All LLMs use bulk sources of language—like articles and blogs they find on the internet—to find trends in what words are most likely to follow other words. To do so, they identify key words that stand out as most likely to lead to other words. Those key words are called “tokens.” Tokens are the words that cue the LLM to look for other words. So, as a simple example for the sake of argument, let’s say we ask an LLM, “what do politicians care about most?” When the LLM receives that question, it creates two tokens: “politicians” and “care.” The rest of the words are irrelevant. Then, the LLM scours the internet for the its two tokens. Though I did not run this through an LLM, it might find that the words most likely to follow the sequence [politicians]>[care] are: “constituents,” “money,” and “good publicity.” But because LLMs only return what is probabilistically likely to follow what it identifies as its tokens, then an LLM probably would not come up with [politicians]>[care about] moon rocks because the internet does not already have many sentences where the words “moon rocks” follow the token sequence: “politicians” and “care.” Thus, LLMs, though referred to as Artificial Intelligence, really are not intelligent at all, at least not in this particular respect. They really just quickly scour the internet for words that are statistically likely to follow other “token” words, and they really cannot determine the particular value, correctness, or importance of the words that follow those tokens. In other words, they cannot drum up smart, clever, unique, or original ideas. They can only lumber their way toward identifying statistically likely word patterns. If we were to write enough articles that said “politicians care about moon rocks,” the LLMs would return “moon rocks” as the answer even though that’s really nonsensical. So, in a nutshell, LLMs just connect words that are statistically likely to follow one another. There’s more to how LLMs work, of course, but this understanding is enough for our discussion today. How your Brain Operates Like ChatGPT. You’re probably glad that your brain doesn’t function like some LLM dullard that just fills in word gaps with ready-made phrases, but I have bad news: our brains actually function all too much like LLMs. The good news about your brain is that one of the primary ways that it keeps you alive is that it is constantly functioning as a prediction engine. Based on whatever is happening now, it is literally charging up the neurons it thinks it will need to use next. Here’s an example: The other day, my son and I were hiking in the woods. It was a rain day, so as we were hiking up a steep hill, my son tripped over a great white shark. When you read that, it actually took your brain longer to process the words “great white shark” than the other words. That’s because when your brain saw the word “tripped” it charged up neurons for other words like “log” and “rock,” but did not charge up neurons for the words “great white shark.” In fact, your brain is constantly predicting in so many ways that it is impossible to define them all here. But one additional way is in terms of the visual cues words give it. So, if you read the word “math,” your brain actually charges up networks to read words that look similar, such as “mat,” “month,” and “mast,” but it does not charge up networks for words that look very different, like “engineer.” Ultimately, you’ve probably seen the brain’s power as a prediction engine meet utter failure. If you’ve ever been to a surprise party where the guest of honor was momentarily speechless, then you’ve seen what happens to the prediction engine when it was unprepared for what happened next. The guest of honor walked into their house expecting, for the sake of argument, to be greeted by their dog or to go to the bathroom, but not by a house full of people. So, their brain literally had to switch functions, and it took it a couple of seconds to do it. But the greater point about how your brain operates like ChatGPT should be becoming clear: If we return to my hiking example where I said, “my son were hiking and he tripped over a ___,” then we see that your brain also essentially used “tokens” like ChatGPT to predict the words that would come next. It saw “hiking” and “tripped,” it cued up words like “log” and “rock,” but not words like “great white shark,” and it did so for the same reason ChatGPT does so: it prepared for the words likely to follow its tokens. The Danger of “Thinking” Like ChatGPT The good thing about the fact that your brain operates as a prediction engine is that you’re not surprised by every word you hear or read. Imagine if every time a server approached you at a restaurant, you had absolutely no idea what they would say. Imagine if they were just as likely to say “hi, Roman soldiers wore shoes called Caliga” as “Hi, may I take your order?” Every conversation would be chaos. Neither person would have any idea what the other person would say next. So, the fact that your brain charges up neurons for words it expects to use is good in one sense, but have you stopped to ask what makes it charge up certain words instead of others? Where does it get the words it charges up to use next? If I ask you to complete this sentence: “All politicians are ____,” what words immediately spring to mind? Where did those words come from? If you reflect for a moment, you’ll probably realize that most of the words to follow come from things you’ve heard on social media or major media. You might even be able to identify the particular sources from which you heard those words. So, if your brain operates as a prediction engine, and if that prediction engine charges up neurons for words that it expects to follow other word “tokens,” and if the words it charges up come from sources like social media, then how can you think that you’re really thinking for yourself? In many ways, you’re actually not. Your brain, like every brain, adopts ready-made word sequences that it regularly hears. If you engage a lot of conservative sources then you’ll finish “All progressives are ___” differently than if you engage a lot of progressive sources. And vice versa. And doing that means that you’re not thinking independently. How to Think (More) Independently Even though it’s not possible to fully break free of our brain’s reliance on the words it frequently engages, it is possible to think much more independently than most people. And it’s not even all that difficult. To do that, start challenging the pre-prepared language and ideas that your brain generates. Remember, whenever you hear some words, your brain already prepared other words. So, if you want to think better, then do not accept the words that your own brain wants to use. Instead, challenge your brain’s selection of words by consciously considering other words instead. For example, let’s say I ask you to complete this sentence: “All politicians are ____.” And let’s say, to keep it very simple, that your next word is “liars.” “Liars” is the word your brain hands you, and let’s say, as well, that you generally—in broad strokes—think that’s true; you think that politicians generally are liars. But if you want to think for yourself, then you can’t just let your brain fill in the blank with the easiest word. If you do, you’ll be using the phrases given to you by outside sources. Instead, start to challenge that exact word, “liars,” with other words. For instance, you might ask yourself, “is liars really the right word or is it more accurate to say that I think politicians are ‘dishonest.’” After all, they might be dishonest in ways that do not involve lies. Or do I mean that they aren’t as much dishonest or liars, but narcissists, or opportunists who exist in a corrupt system? See, even though we find some general truth in the idea that politicians are “liars,” when we consider other words, we actually think. We think for ourselves. We consider the words that outside sources have given us. So, maybe, even though we do think that politicians sometimes lie, we also realize that, as we consider it more deeply, “liars” isn’t the best word. Instead, we figure out that “narcissists” might be even more accurate, or at least be another word needed to complete the thought. So, don’t let your brain just follow its tokens to ready-made language from social media. Take the words that your prediction engine generates, and consciously challenge those words with other words. Then you’ll think for yourself amidst a world of people who not only use ChatGPT but who also “think” like it. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit pearlmanactualintelligence.substack.com (https://pearlmanactualintelligence.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

3. 

   9 Sept 2025

   Is Higher Ed to Collapse from A.I.?

   Steve Pearlman: Today on actual intelligence, we have a very important and timely discussion with Dr. Robert Neber of a SU, whose recent opinion piece in inside higher education is titled AI and Higher Ed, and an impending collapse. Robert is a teaching professor and honors faculty fellow at the Barrett Honors College at a SU. And the reason that I invited him to speak with us today on actual intelligence is his perspective on artificial intelligence and education. And his contention roughly that higher Ed's rush to embrace artificial intelligence is going to lead us to some rather troubling places. So let's get to it with Dr. Robert Niebuhr. Robert. We talked a little bit about this on our pre-call, and I don't usually start a podcast like this, but what you said to me was so striking, so, uh, nauseating. So infuriating that I think it's a good place to begin and maybe some of [00:01:00] our listeners who value actual intelligence will also find it as appalling as I do, or at least a point of interest that needs to be talked about. You were in a meeting and we're not gonna talk about exactly, necessarily what that meeting was, but you're in a meeting with a number of other. Faculty members and something interesting arose, and I'll allow you to share that experience with us and we'll use that as a springboard for this discussion. Robert Neibuhr: Yeah, sure. Uh, so obviously, as you can imagine, right, I mean, faculty are trying to cope with, um, a perceived notion that students are using AI to create essays. And, and, uh, you know, in, in the, where I'm at, you know, one of the backbones, um, in my unit to. Um, assessed work is looking at argumentative essays. So the, the sort of, the idea that, that this argumentative essay is a backbone of a, of a grade and assessment. Um, and if we're, if we're suspecting that they're, they're using ai, um, you [00:02:00] know, faculty said, well, why should we bother grading essays if they're written by bots? Um, and, and you know, I mean, there's a lot, there's a lot to unpack there and a lot of things that are problematic with that. Um, but yeah, the, the, the idea that, you know, we, we don't have to, to combat a, to combat the perceived threat of, of student misuse of ai, we just will forego critical assessment. Um, that, that was, you know, not a lone voice in the room. That that seemed to be something that was, that was reasonably popular. Steve Pearlman: Was there any recognition of what might be being sacrificed by not ever having students write another essay just to avoid them using ai, which of course we don't want them to just have essays write, uh, so of course we don't want them to just have AI write their essays. That's not getting us anywhere. But was there any conception that there might be some loss in terms of that policy? [00:03:00] Robert Neibuhr: I mean, I, I think, I think so. I mean, I, I imagine, uh, you know, I think. My colleagues come from, from a place where, where they're, they're trying to figure out and, and cope with a change in reality. Right? But, um, there, there is also a subtext, I think across, across faculties in the United States of being overworked. And, and especially with the mantra among, you know, administration of, you know, AI will help us ramp up or scale up our, our class sizes and we can do more and we can. All this sort of extra stuff that it would seem like faculty would be, um, you know, more of their time and, and more of their effort, you know, as an ask here that I think that's, that, that may be, that may have been part of it. Um, I, I, I don't know that the idea of like the logical implication of this, that, you know, if we no longer. Exercise students' brains if we no longer have them go through a process that encourages critical [00:04:00] thinking and art, you know, articulating that through writing, like what that means. I, I don't know that they sort of thought it beyond like, well, you know, this could be, we could try it and see was kind of the mentality that I, I sort of gauged from, from the room. But, uh, it's, I mean, it's a bigger problem, right? I think the, the, the larger aspect of. What do we, what do we do? What can we do as faculty in this sort of broad push for AI all over the place? And then the idea of the mixed messages. Students get right. Students get this idea, well, this is the future. If you don't learn how to, how to use it, if you don't, you know, understand it, you're gonna be left behind. And then at the same time, it's like, well, don't use it from my class. Right? Learn it, but don't use it here. And that's. That's super unclear for students and it's, it's unclear for faculty too, right? So, um, it, it's one of those things that it's not, um, I don't think in the short term it works. And as you, as you, as you implied, right, the long term solution here of getting rid of essay [00:05:00] assignments in, in a discussion based seminar that relies on essays as a critical, I mean, this is not a viable solution, right? We, we got the entire purpose of, of the program in this case. Steve Pearlman (2): And yet a lot of faculty from what you described and a lot of what I've read as well, is also moving towards having AI be able to grade. The students work not just on simple tests, but on essays. And as you point out in your article, that's potentially moving us to a place where kids are using AI to write the essays, and then faculty are using AI to grade the essays. And who, when did the human being get involved in between, in terms of any intellectual growth? Robert Neibuhr: Yeah. No, it, it's, I think it's a, it's, it's really, it's a, it's a really big, it's a really big problem because, um. Again, those long-term implications, uh, are, are clear as, as, as you laid out. But, um, it's also, I mean, like, again, like this notion that [00:06:00] there's, there's a tool that obviously can help us, you know, multiple avenues where AI can be, can be something that's, that's helps us be more efficient and all this, those sort of stuff that, that's, that's, that's true. Um, so it's, it's there. So we should gauge and understand it. Um, but it doesn't mean you just use it everywhere. You know, you, you can buy, I don't know, you can buy alcohol at the grocery store. It doesn't mean you have it with your Cheerios, right? I mean, there's a, there's a time and place polite society says, you know, you can consume this at these times with these meals or in this company, right? It's not all, all of this. So things, so, you know, the message that I think it's a level of respect, right? If we, we don't respect the students, if we don't lay out clear guidelines and. We don't show them respect, we don't ask for respect back if, if we use bots to grade and the whole thing just becomes a charade. And, and I, I think the, again, the system [00:07:00] begins to, to break down and I think people wind up losing the point of what the exercise is all about anyway. And I, I may not just the assignment or the class, but like higher education. Right. I mean, the, the, the point is to. Teach us how to be better thinkers to, to gauge, evaluate information, uh, you know, use evidence, uh, apply it in our lives as, as we see fit. And, and if it's, and if we're not prepped for that, then, then what did they prep us for? If, if, you know, the student's perspective, it's like, well, what did I just do? What did I pay for? That's, that's a, that's a huge long term problem Steve Pearlman (2): it seems like. Uh. That, what did I pay for? Question is gonna come to bear heavily on higher education in the near future because if students are able to use AI to accomplish some of their work, and if faculty are using AI to grade some of their [00:08:00] work and so on, and then the, you know, the, these degrees are costing hundreds of thousands of dollars. And it's an effectual piece of paper that maybe that loses value in essence also because the students didn't really get anything from that process or get as much as they used to because they're using ai. You know, is this moving towards some kind of gross reassessment of the value of higher education or its role in our society entirely? Robert Neibuhr: I mean, it it, I think it certainly. It certainly has the potential, right? I mean, I would, I would even look back and, and think of a, a steady decline, right? That this is, this is one of, of many pieces that have gone, gone down. And I, you know, I mean mentioning in, in your, in your question just now, right? That the sense of, you know, students as client or customer, uh, how that has changed the sort of the, the interface and, and [00:09:00] how, you know. Uh, we, we think of this, uh, this whole, this whole endeavor, right? I mean, um, and, you know, and this leads to things like, oh, retention numbers and, and all these sort of things that the mental gymnastics that happens to, um, you know, do all these things and, and the truth be told, right? Different paths for different people, right? There's not, you know, there's not a single, like, you don't have to get the degree in physics to be as successful, but the, the student as, as, as customer, I think also has, um. Solidified this, this notion, um, that we can le list the student feedback, right? And, and student feedback is important. So I'll qualify that that standards were, were low. I, I know for my own example, you know, even 20 years ago, right, that that undergraduates would have to produce a capstone thesis as part of their bachelor's degree. And I know firsthand that at from the time that, you know, [00:10:00] the history department had looked at, um, exit surveys of people who didn't finish their history degree. And they said, well, why didn't you finish your history degree? I said, oh, well, you know, I, whatever the program was, psychology, sociology, doesn't matter, whatever the other degree was. That degree program didn't require a thesis. So that was. That was easier, right? That was the student saying, you know what, I'm gonna opt out of the hard work and I'm gonna take, take this other one. And so the history department's answer kind of like the we'll stop grading essays was, we won't, we won't require a thesis anymore that'll stem the tide of our losses. Of course it didn't. Right? 'cause they're larger things going on and, and you know, some of it's internal, some of it's external and out of, out of, you know, history departments, you know, control. Um. But I, I think part of, part of this also then sort of, you know, cuts this, this notion of the rhetoric in the last, at least two decades of [00:11:00] college is your ticket to a successful career. Like, and it's just quantifiable, right? I mean, there's no doubt that, you know, if you have a college degree, your lifetime earnings will be such and such amount higher than, right? So there's, there's clear evidence there. There's, there's, there's tangible things, but that's become degraded, I think. To, to a, a simple binary like, oh, my piece of paper gets me this. And, and I think that mentality has been sort of seeping in. And I think this is kind of where, um, some of these things are, are coming from. Like it is just a piece of paper. I don't have to worry about, you know, what skillset I get in higher ed because I'm gonna learn on the job anyway. Uh, or I don't, like, students will say, I don't see this as valuable to what I'm gonna do. So it's, it's as kind of said the reckoning long term, like upending, the higher ed. I mean, I, I think as some of these questions linger and, and, and simmer and, and costs get higher and, you know, [00:12:00] parents get more, you know, upset and, and, and students with their loans. I mean, I, I, I can't see going in, in perpetuity in the direction that it's, it's going with or without ai, but I think AI maybe speeds this up. Steve Pearlman (2): In a sense, I see this as an extension of Goodheart's Law, which is that if we just focus on the measurement, then the thing that we're measuring becomes inval or valueless to us, uh, because the measurement becomes the value. And I see that happening with ai, right? The goal is to create a paper that gets an a, it doesn't matter if I use AI to do it, because I've achieved the goal, right? The, the, the outcome that I want. I've satisfied Good Heart's law. I have produced the outcome and the measurement has been achieved. I haven't learned to write a paper or think for myself or put a sentence together, but I've nevertheless achieved the outcome, and that seems true from both perspectives. There's the student perspective, which is that I've produced the paper, I've gone through a series of [00:13:00] steps that have made the paper happen. I didn't write it, but I used AI to do it in a worst case scenario and presented it, and then it happens from the teacher's perspective, which is that whether or not AI grades it. They have, in fact, nevertheless produced the artifact that I need to assess and achieve the assessment and everybody's happy. Uh, except you know that this is utterly undermining the fundamental premise of education itself, which is the development of the individual. Yeah. Do you think down the road. I know this is purely speculative and maybe it's overly hopeful in fact, but does the reckoning in higher education, and maybe even in secondary education and primary education come down to saying, look, um, you know, AI is something that students are gonna be able to use and be proficient in regardless of whether or not we exist. The only way that we're gonna carve out a meaningful existence for ourself is an essentially, almost a reversion to [00:14:00] what higher education was. Years ago, maybe it is not as much for everybody. Maybe it is more for those people who really want to become intellectuals, use their minds, develop the mindsets and the skills of the intellectual in the positive sense of that, and in whatever way they're contributing to society. Maybe there are fewer institutions, but they are holding the line further on the cultivation of the individual and those individuals. Maybe because there are fewer of them and because they are more specialized in certain critical thinking skills become, again, more valuable to society. Is that possible, do you think? Or is, am I pipe dreaming here? Because I just hope education doesn't implode entirely though. I think a reckoning is gonna be healthy. Robert Neibuhr: Yeah. Steve Pearlman (2): What do you think? Robert Neibuhr: Yeah, no, I mean, um, the, the, the first bit that crossed my mind as as you were talking was this sort of the, the saying. Something about, you know, some of [00:15:00] us can pretend all the time and get away with it. All of us can pretend some of the time, but we all can't pretend all the time. Right? Like this sort of sense of, of, you know, like there, there has to be, someone has to tell the truth, right? Like the emperor with no clothes, it's like, well, clearly there's something wrong here. Um, but I to to the, to the future and where this, where this sort of looks and where you, where you went towards the, the end of the question. Um. I mean, I, I don't, I don't know, but if, if the rhetoric about AI reshaping the workforce, if, if part of that comes true and, and if it's, if it's about, you know, um, one skilled, let's call 'em a critical thinker, because ideally that's what's, what's going on. But one skilled, critical thinker at a desk can, can, you know, enter in the, the correct. Keystrokes to enable a machine to do the work of what 10 people would've done. I, I don't know. Right. Let's assume the, sort of, the productivity is there across [00:16:00] white collar, um, professions. I, I don't think, I think if you give everyone a college degree and the, the act, the, the possibility for a meaningful job is so slim. You create a society that that is. Seething with despair and resentment. Right? And, and you know, I'm scholar of primarily the Cold War. And you look at, you know, across Eastern Europe, the, the, the correlation between high unemployment, yet high levels of degrees of, of bachelor's degrees and sort of resentment and the political, the search, right? Like there, you see, especially in the 1970s and eighties, there's this sort of lost. Um, there's a sense of hopelessness, like, I can't survive here in Poland or Yugoslavia or Bulgaria, or whatever it was. Um, and, and if I don't fit, then, then that's like the society has failed me. And if, if we have this scenario where everyone just gets pushed through and gets a degree, [00:17:00] but you know, they're, they're, they're doing something that they don't, they haven't been trained in or they don't enjoy, or it doesn't fit with anything, it doesn't realize their personal goals. It has to, the system has to collapse. We have to reshape it into something that's trade school, uh, or, or what, you know, various levels. Right. And, and I get the idea of maybe a liberal arts, uh, uh, you know, system that, you know, people who want to enter in and, and, you know, be the sort of intellectual, the philosopher kings, I suppose, right. But, um, but that there, there probably should be some sort of system that would, that would recognize that because it, it, it doesn't, it doesn't seem like society, we'd be playing too many games and, and fi you know, playing with fire if, if society is just sort of running on the status quo. Steve Pearlman (2): I wanna bounce your article in inside Higher Ed against another one that was fairly [00:18:00] contemporaneous and I'll put it in the show notes. And the title was, effectively, AI is changing. Higher education, and it was very neutral in its assessment. But within that was a survey, uh, that was conducted of thousands of college students, two thirds of whom reported that the use of AI was probably degrading their critical thinking skills. And the, the author build this as neutrally changing higher education and I. I think there's a prevailing attitude in among many faculty members, at least the literature that's coming out is so much rah rah about artificial intelligence that if anything, that neutrality of the author was conservative relative to I think a lot of how educators are viewing it, but I was very disturbed by that characterization. If two thirds of students report that [00:19:00] using AI is probably degrading their critical thinking skills. How, how the hell are we describing that as neutrally changing or having positive and negative effects? It seems to me that that has, uh, at least for the time being, should raise enough alarms for us to say, wait a second. That's not having a neutral effect at all. That's a terrible degradation of higher education, especially given that it wasn't really cultivating critical thinking skills to begin with, and now that students themselves. Are reporting that it's harming it, especially when students tend to overestimate their critical thinking skills in most research surveys about it. This seems like it, it's a pretty clear indictment of artificial intelligence's role so far in education. Robert Neibuhr: Yeah, no, I, I think, and, and this sort of, um, I'm not surprised that I, as you said, like this, I, I think seeing that as neutral or, or. Um, continuing [00:20:00] to just cheerlead the, a notion among administration faculty that, you know, this is the new direction no matter what. Right? Those people who think they're critical thinking, those students must be misguided somehow they don't understand, right? I mean, we get this sort of disconnected, um, mentality. Um, but that's, that's, um, that, that does it, it creates a, a, a serious issue for, for the whole system because then again, it's, um. How willing are, are those, how willing are those two thirds, uh, who responded that way? How willing are they to follow the rules? How willing are they to, to not say, well, you know, this is all kind of a sham, so I, you know, I'll bend a little bit. I'll, I'll sort of have more ai, do more of my work. Like who's gonna catch me mentality? And that's, I mean, that's. Not to say they're bad people for student for doing that. That's kind of a natural reaction. We've encouraged people to take this sort of approach, [00:21:00] um, and, and 'cause students increasingly, I've witnessed, anecdotally, I've witnessed the, the decline in punishing students for academic offenses, right? I mean, I remember 20 years ago, uh, as a, as a grad ta. Um, I, I caught two students that I, I was pretty sure that they, they copied each other and they, they had essays that were, they changed some words, but I was convinced, and it, and the, the dean's office concur, concurred. It does seem that way, but you understand that one student has a serious problem right now and his mother's very ill, and, you know, we can give him a break. And I'm not out to, you know, obviously if someone's. Circumstances or circumstances, those are real, right? I mean, I'm not some sort of, you know, like we have to always, but you have a heart, but you, you know, what does that, what message does that send? Uh, that it's, oh, but if I have a sad story or something's going on in my life, [00:22:00] it's okay. And, and I think this AI use and, and the, in the lack of clarity. Um, and this sort of, all this sort of push is, is simply en encouraging the kind of behavior that we o overall don't want. Um, so maybe it's neutral now, let's say give the guy the benefit of the doubt. Um, maybe it's neutral today. I don't think it's neutral in a year from now, or six months, right? I don't, I don't think that can be, it's a sustainable thing. Steve Pearlman (2): Let me touch on that. Uh, because I was around, I'm old enough to have been around when the internet hit higher education. And I remember at that time two things that fascinated me that I thought were very odd, uh, for, and the faculty were as they are now with ai, think racing to embrace the internet, uh, Google searches, uh, HTML, and you know, so forth. And one of the things that struck me as very odd was the push they felt [00:23:00] to incorporate the internet into their classes and teach students how to use it and so forth. Which I didn't understand because it was very clear that the students were far more adept at it than any of the faculty were, and they were becoming the digital natives that they are now. And so I don't know why anyone felt as though we were needing to teach them how to use the internet when they were far ahead of us, obviously, in all of that. And the second thing was that emerged at the same time, was. An argument that, that it was a lateral shift, that reading short little webpages and clicking on different links, and as things got shorter and shorter, uh, and webpages got more desperate and so forth, we would, it was just a neutral shift in how people thought, and it was not a degradation of the ability to focus long term to go deeper. And so on, and I said, well, how can it not be? If we look at the two formats, you have a book on one hand that is a contiguous [00:24:00] set of ideas developed more deeply, and then you have a number of different web pages that are skirting across many different HTML links to different short paragraphs about things. And I sort of tried to scream at the wind a little bit about it back then, but it was, it was obvious that it was blowing in the wrong direction. And it seems to me AI is that only times about a thousand in terms of what's happening. Once again, we see a clamor to teach students how to use AI and incorporate it into their lives when they're already far ahead of us in terms of what AI is doing and how to use it. And the second thing is this notion that, again, it's lateral if not beneficial when the evidence suggests otherwise. Can you, in your insight where, given your position, I'm wondering if you can help me appreciate. Why are what is behind the faculty rush in education to embrace this? Is it, I get a sense and I'll, and then I'll be quiet because I'm trying to ask you a question. I've only asked four [00:25:00] so far. But, uh, I get a sense that, in a sense I think the faculty kind of feel helpless. That, that there's a, there's a sense that if we can't beat this and we have no idea how we could possibly beat this, then we might as well just go with it. Uh, do you feel like that's accurate? Robert Neibuhr: I think, I think, um, yes. I, I, you know, maybe a little more, some nuance to the, yes. Um, I, I suppose on the one side, um, again, faculty coming, generally coming from, from a good place, right? I wanna, I wanna help my students and I think that's, you know, um, you know, rather, rather ubiquitous, uh, among, among faculty, I wanna help, I wanna help the students, uh, do better and, and succeed. I, I think if, if there's this, this huge push to say that AI is the future, AI is if we don't, if we don't talk about it, if we don't introduce it to students, if we [00:26:00] don't sort of teach them things about it, that we're doing the students a disservice. So I, I think there's this reflective, like, we don't have much time. We have to teach them something. Let's chisel together, you know, some sort of idea and, and you know, then I can feel good about, um, having passed on some sort of, you know, knowledge to my students and help me better prepare them. I think that's perhaps, um, part of it. Um. Yeah, I think a helplessness in terms too of, you know, I, I feedback or things I hear from faculty in my unit and, and, and elsewhere is, is this sort of helplessness that administration is, has a tremendous amount of power and is sort of pushing an agenda that faculty don't have the ability to push back against as well. Right? So like. Again, a [00:27:00] perfect world. Let's think about this. Let's figure out what's actually necessary, how we can, how we can prepare students. Let's, let's think about this and, and be, be reasonable about it versus the sort of top down push. And I think faculties across the country have, have lost an ability to, to be self-governing as they would've been, you know, 20 years ago or something like this. Uh, and, and you know, the sort of administrative superstructure that has has dominated. You know, universities, uh, in, in the recent years, um, just simply says, this is what we do. And, and part of this is I think like, like before, right? So my university is, I think, the biggest in the country. Um, uh, or certainly one of the top three or something like this. Um, and, and the notion of scaling up is kind of always on sort of the, the talking points of the, this, right? We, let's scale up, let's do something else to have a even bigger, or let's grow by this much. Or [00:28:00] that, that pressure then doesn't come with let's hire X number of faculty to take care of that, right? Let's hire this many more people to, to get. So it's asking more, but without giving more support. Um. And I think too, what you, what you mentioned with in the beginning, uh, of your question with sort of the way the internet was, I haven't thought this through. This is just sort of, you know, just on the spot here. Um, maybe this is, maybe this is not necessarily the, the best analysis, but my own sort of thought there is, you know, we don't, we don't, we no longer have a robust research librarian. Network at universities anymore, in my opinion. So in other words, like folks who would've been in charge of, um, perusing, you know, the, the publications and, and journals and being in touch with faculty, doing research to say, Hey, I know you're [00:29:00] a specialist in this. Here are the newest titles. Do you want me to buy this database? Or whatever the, the thing might be, right? Like those, the intermediaries between the material and then the faculty. Those, those folks have been largely eliminated and they're not rep being replaced as they retire. There's only a few, a handful of programs that could do library science as a, as a master graduate degree anymore in this country. So with the idea that, that the internet just equalizes us, I'm just as equipped as you would be or the research librarian would be to just go online and find whatever I need. And that's, that's also not. Necessarily true, right? I mean, I, I may be in touch with the things going on in my field, but there's so much going on that I don't have time to, to, you know, and in a sense of research, I am overburdened in a way, and, and letting me fend for myself. Um, you know, maybe it works, maybe it doesn't. [00:30:00] But we've hollowed out the level of specialists who would be that point of reference to go in and, and look at all of those things. Sort of filter a bit and help in the process. And I think that's, you know, that's something I think the internet may have, may have helped, uh, do. And the way that so much became online in the last 20 years in terms of, of, you know, research materials, primary sources, all this sort of stuff. And, and the down, the downfall I would say of, of that profess. Steve Pearlman (2): That seems to me indicative that issue with librarians seems indicative to me of a larger issue. And it's one that you mentioned as well earlier of, um, this, the value of AI to the administration in terms of economizing further economizing further, further economizing instruction. Uh, so what risk do you see or do you hear on the ground? The tremblings of AI [00:31:00] replacing faculty members for certain tasks. I mean, we went from faculty members to adjuncts to teaching assistants doing most of the work. And I, I, I have to think, and there's already publication about it, of administration seeing AI as the next great cost saving measure. Robert Neibuhr: A hundred percent. Yeah. No, I, I think I, I think that's exactly right. I mean, the, the notion that you'd have sort of like. Sort of like at the grocery store, you have two or three checkouts that are open that has a person there checking you out versus the one person loading over 15 self checkouts. I, I, I think that's certainly, and it, especially thinking about economizing and scale and, and saving money. I mean, this has to be, I see it now with, with the, the way that, um, you know, students that used to be. A hundred students, 150, 200 maybe in a class was really big and you had a faculty member with three or four or five TAs or whatever the [00:32:00] breakdown would be. I, I have, I know people at, at my university have six, 700 students in the class. That's, I, I, I don't, how do you, you lose, I mean, that's, I mean, that's just incomprehensible to me in terms of the point of higher ed. Right? I mean, like, you don't, you're not fostering any. Any connectivity, you're not, I mean, it may as well be a bot because you, the student will never interact, you know? Right. Maybe the faculties of noble laureate, you'll never interact with that person. There's, there's very little, um, so that's, that's, that's I think, uh, you know, a, a huge piece of, of where this will go. And I, yeah, I think faculty are vulnerable, that they've been made more vulnerable over the last decades and, and, and Yeah. I don't see it voting well, my advice to the. Faculty. I began the podcast, right? This notion of let's stop grading, you know? I said, well, you know, I mean, we should think of ways that we remain [00:33:00] relevant, right? I mean, if, if we, if we propose that, well, we just won't grade essays. We won't assign essays, then for sure they can get someone, the administration can hire someone at lower pay to do what we're doing in the classroom. That's not. That's not a far stretch of anyone's imagination. Um, so I, I mean, I don't want to be a part of the, you know, the, the group that nullifies myself by taking away the prime thing that I can give. Right. Um, but not to ramble, but I, you know, part of the, this fear too is, is a student yesterday had sent me, um, uh, something that was really interesting. So, uh, we're a Cold War class. Cold War seminar. He read a book by, uh, John Lewis Gatis, and, and he, he read it. He, he had some notes. He understood a lot and really, really bright guy. And, and then he, he said, you know, I put into ai, I forget which, which program, but he put into AI created a [00:34:00] podcast that talks about this book. Holy cow. It was, I listened to 10 or 15 minutes of it. It was two people talking. They, they, it mimicked. It mimicked. I mean, it was, it could have been real had I been in the car listening, I would've thought this was a, a, you know, a book talk about Candice's last book on the call. It was, it was insane how good it sounded. And, uh, you know, uh, that's, that would be easy for, uh, you know, recreate, you know, Dr. Nebo in a, in a discussion seminar. So, you know, my, they can get my image and they can get my voice, and who knows? I mean, that, that can't be that thing. Steve Pearlman (2): No, and you know, it, you raised the point about chatting with bots and it, I'll piggyback on what you're saying right now. I can understand if we're gonna have an interaction with bots as an, as a tutor, and potentially valuably. So I'm not against all usages of ai, where if we're learning, say, the layers [00:35:00] of the earth's crust. Uh, as a very simplistic example, but nevertheless, we can rely on the AI to be relatively accurate in coaching us about the layers of the earth crust. But now there are also ais who will interact with you as Hamlet. Well, you could pull out any 50 Shakespeare scholars and have them respond to prompts and that you'll get different responses. All of them thoughtful. But this bot who is deciding, uh, but based on what algorithms are we deciding its responses as Hamlet to prompts that are not within Hamlet, that now we're crossing quite the Rubicon in terms of where we're putting trust in bots to educate our students or coach our students. In ways that I don't think are reliable, and it's not, even if the, even if the bot gives what might be very thoughtful hamlet responses and very reasonable ones, they are a selection of, of an [00:36:00] interpretation of Hamlet based on certain people. I guess that it's searching across the internet as opposed to others, and now that's equally dangerous to me as far as I can conceive. Robert Neibuhr: Yeah, I think, you know, that I've, I've. The same, the same sort of idea of the sort of book, book summary. And, and, and I mean, I, I, I think it's so even a fact, even just fact as you said, like just scientific facts that we know that can be provable. If, if we wind up having queries to the AI and say, okay, what is this? And it gives us the right answer and we check it, we know it, but at at a point, right? I mean, we have to say, okay, you know, it's been right 52 times. I trust it now, and who's to, and if I stop and check like, you know what, I verified, this is good, and now down the road it lies to me. Or, or again, this other, you know, avatar, other sort of per ai sort of driven personality or, or, or, [00:37:00] you know, this comes in and, and now I don't realize that I'm taking an information at face value. And again, I lose that critical thinking. I, I lose that ability. That's also reasonable, right? If I checked it so many times, what, what else can I do? I'm a busy person, right? We're all busy people. How can I keep referring back and verifying? Um, and that's gonna, I think that's gonna be a huge problem. If, if we wind up at some point saying, yep, that's good. And then, and then Steve Pearlman (2): we're, we're duped down the road. It reminds me of an old Steve Martin joke. He would say that, um, he thought it would be a great practical joke to play on kids. Uh, if you raise them to speak wrong when they get to school, so all their words are incorrect and they have no idea. Yeah, it sort of seems like the same problem, right? A certain point. The AI might be telling us everything that's wrong. We have no idea that it's wrong, and we're living in that world where everything is distorted and we don't know what we don't even know. That's a terrifying prospect. Thanks for [00:38:00] bringing that up. I try to bring up the hide behind. So as, as we wrap this up, where, what didn't I ask you about? Where, what's the thing that you think we also need to talk about here that I didn't shed enough light on for this conversation? Robert Neibuhr: Oh, I don't, I mean, I, I guess I, I, my, my own sense is that, that the conversation. Any conversation about higher ed um, needs to be grounded in the basic principle of, of the point, like the, the value that, that we get from it, the, the goals that it, it it brings us. Um, and, and, um, you know, that if, if that's at the center, if, if the idea of, you know, instilling, uh, you know, students with the tools to. Actually survive in a dynamic world. You know, [00:39:00] my degree today might totally change into the reality. It might totally change in 10 years, whatever, if I'm still equipped to respond to that change. That's been a successful education. Right. And, and, and the, the point of the, the critical thought, the reflection, um, the, you know, preparing for, um. Really the, for our context in the United States, I mean, I think it's, it's also part of the, the whole experience with, or experiment with, with democracy, right? Inform citizenship. I mean, this is all part of it. If, if it's just, um, if the narrative about higher ed is simply the paper mill or green mill for a job to get some sort of, you know, a higher number of, of a wage, or if it's about, you know. Finishing just tick boxes and hitting goals without being ever checked or questioned. I mean, that's, that's, um. That's not the right, that's not the point. I, I don't think. Right. I mean, the, the, you know, what are, what are, how are we growing, how are we building ourselves? [00:40:00] How are we preparing for uncertain futures? And if the conversation they should always be, be, be centered on, on that, uh, whether it's AI or whether it's, you know, any other stuff. But that, that would be the only thing I would sort of stress. But I, we've talked about that already, but I think that's, I try to think of that in, in terms of any of these, Steve Pearlman (2): um, sort of conversations. I wanna ask you one last question that just came to mind. What if, I'm sure we have a lot, we have a lot of parents listening. I'm curious as to what message you would send to them if they have either students, children in college or children headed to college in the somewhat near future. What's the message for them at this point with respect to all of that? Because I don't exactly know what it is. Robert Neibuhr: Yeah, I mean, I, it's, I, it, it seems, what, what I think is, is, is is not gonna be a popular [00:41:00] or not gonna be, you know, what folks, you know, necessarily can, can even, you know, want to hear or, or, you know, could even act on it. But I, I, I guess part of it is, is to, can. Ensure you're involved and, and understand, you know, ask, what's the syllabus? I mean, I'll digress for a second, right? I mean, I, I, this is one of those things that I've had a critique about for, for a while. Um, sort of my grumpy old man coming out. But I mean like the, the sort of sense of like universities. Let's build a really luxurious dorm facility. Let's build up the sports center. Let's have, when, when the TV crew comes for the game day, we'll have brand new flowers. The, the sort of superficial wowing that happens. And parents, the, the, the tours are a big part of this, right? I mean, the tours show all the goodies. And not to say that that's a bad thing, right? I mean, you know, dorms were substandard 30 years ago in large, right? I mean, there's, there's an argument for why these things [00:42:00] are good. Um, but, but I think a lot of the, the, there's been a, a, a cleavage between what parents are told the experience is gonna be and what they're actually sort of shown and informed. And then of course, students want independence. Students want, you know, they're, they're on their own now, their decision makers and in large part, and there's a sort of disconnection there. And I, I think it's, it's hard, it's a big ask, but if parents can, can remain. Ask the tough questions. Like how many books in a library, how many, you know, how many, uh, you know, full-time faculty, how many, you know, go down the list of academic credentials. Um, and then look at the syllabi. Look at the assignments from from your students, right? Or, or think about, uh, if they're already in there or if they're going right. Think about that as something you would, you would do. Um. And, and, you know, keep people's feet to the fire, right? I mean, to use of a tired metaphor, but I [00:43:00] mean, keep, keep that as much as you can and, and, you know, try to push back because if, if students are customers, um, parents are the, are the ones paying for it ultimately. So they're detached their, the true customer. I, I suppose. And if they start calling up the deans and saying things like, what is, what's going on here? Um, maybe things will, will change. Maybe there'll be a, a response. Um, but stay informed, I guess, as, as much as I possibly can, I think would Steve Pearlman (2): be the, well, that seems Sage elite to me. Robert, thanks so much for being on actual intelligence. I appreciate it and, and, uh, as you're thinking evolves on this, maybe we can have you back in the future sometime and continue the discussion. Robert Neibuhr: Sounds great. Thank you. Steve Pearlman (2): Thank you. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit pearlmanactualintelligence.substack.com (https://pearlmanactualintelligence.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

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