The College Question Podcast

Dan Currell
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The College Question provides answers on all things college: what it costs and why, how financial aid works, where majors lead and more. Hosted by Dan Currell, former U.S. Department of Education official and regular contributor to the New York Times. thecollegequestion.substack.com

  1. 17h ago

    Faith on Campus

    It’s June, so high schoolers are out visiting colleges. Lots of questions come up in this process, and I’ll touch on many across the summer. I’ll start with something where I see a lot of confusion: faith on campus. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

    9 min

  2. 6d ago

    You’re In! But Not Yet.

    Q: My child was accepted to the University of Miami, but not for the fall - they want him to start in January. What’s the reason for that? A: It’s an increasingly common practice among a certain kind of selective school. It’s about manipulating statistics and smoothing out the school’s programming and revenue. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

    8 min

  3. May 23

    Presence and Persistence

    In Part 1 of the Gustavus Keynote, Knowledge and Strength, I considered the college motto, e caelo nobis vires, roughly “from heaven come our strengths.” In Part 2, I talk about the conditions necessary for building strength, and discuss what it feels like to be beckoned by a device at all times. I dip very briefly into Habermas and his ideas about lifeworld and system-world in connection with our device-mediated culture. Then I consider another snippet from Gustavus history, contrasting what the Minnesota Swedes were doing in the 1860s to what the Iowa Norwegians were doing at the same time. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

    15 min

  4. May 16

    Knowledge and Strength

    Last week I delivered the keynote at a staff retreat at Gustavus Adolphus College, where my wife and I met in the 1990s and I am on the board. I’ll split it up into a few pieces. Today, I confess to a crime and consider the college motto. E Caelo Nobis Vires I’m going to talk about the Gustavus motto today – the Latin one, on the seal. Why I think we chose it, and why it’s still perfect for us. And I’m going to talk about strength, and in particular some research that shows how we build it through experiences and relationships in the college years. That’s where we’re headed. The (Attempted) Mattress Heist of 1993 But first, I’d like to confess to a crime. It was the Mattress Heist of 1993, a break-in with a getaway car, like the recent daring caper at The Louvre, except if it had been done by people who were bad at heists. I spent my junior year at Oxford, which is on trimesters, so you’re not done until almost the middle of June. I came back to campus to spend the summer of 1993 teaching math. (To myself. That’s another story.) I found a place to live with one of my closest friends, who is now a highly regarded professor at a respected university, which will seem like a surprising outcome after you hear the rest of this story. My buddy, who I will refer to as Scott to protect the half-innocent, had an apartment in town that had almost everything we needed. That did not include windows – it was someone’s basement. It did include some elements of a kitchen underneath all the unwashed plastic dishes, a couch that generally matched the dishes, and a TV. I remember that we watched a good deal of Beavis & Butt-Head on that TV. The fact that we were immersed in Beavis & Butt-Head sets the scene pretty well for what happened next. Because the apartment had just one mattress, and after I arrived there were two of us. I spent a few nights sleeping on the couch that matched the dishes before one of us observed that there were around 2,000 unused mattresses in St. Peter, and we knew where they were. We planned to borrow one for the summer. We got into Scott’s Ford Probe, a car that was kind of like a Prius but sportier and with less storage space. The plan was for Scott to drive up to the front door of the CoEd dorm, drop me off, and pull around to the back. I would go in, find my quarry, and then drag it a few hundred feet across what is now the softball field to his car. The idea, I think, was to elude the gaze of campus security while we got the mattress into his car. We did elude campus security – they were nowhere to be seen. We did not elude the Saint Peter Police, who it turned out can identify a mattress heist pretty easily when it looks like this: * A guy and a mattress emerge from the back utility door of the CoEd dorm. * Mattress and guy hustle across an open field for 200 feet, or however long a regulation softball field is. It was like Pickett’s Charge, but dumber, and with a mattress. * Mattress and guy arrive at an obviously waiting getaway car, at which point the perpetrators have no idea how to fit a Twin XL plastic mattress into a Ford Probe. As I sat in the back of that Saint Peter Police cruiser, I thought – this is a surprising way for college to end. Campus security was consulted, which resulted in Steve Waldhauser being consulted – he was the head of Res Life in those days. To my great relief, no charges were filed, the mattress was returned, and I had a date to meet with Waldo the next day. I was back on the couch that night, and I did not sleep well. I do not remember the details of the meeting the next day except that it involved tearful groveling and resulted in some assigned community service. I got off easy, you could say, which had to do with the fact that I had no prior record of heists, mattress or otherwise. I was a heist virgin, and Waldo could tell, given how good I was at heisting. For whatever reason, my community service couldn’t happen until school started again in September. I did my penance by spending the Labor Day weekend screwing towel bars onto the backs of dorm room doors in CoEd. As it happened, the first time my wife ever laid eyes on me – I had been gone for the entire preceding year, remember – was that weekend. She was a CF, and I was walking around in overalls with a cordless drill screwing towel bars onto the backs of doors. It was not love at first sight. She understandably assumed I was not a student. There is obviously a lot more to that story, which would not develop until much later. Given that it started with me wearing overalls, that too may not be a surprise. How Strength is Built As I said, I want to talk about strengths today. How we build strengths in ourselves and in students, and what conditions we need in order to build them. So let’s turn to that. Our kids are in college now. We have two, plus a bonus child who was given to us in the form of our son’s “randomly assigned” freshman-year roommate at Luther College. (It wasn’t random. I don’t believe there is a renegade molecule in the universe.) We have been reminded by the ups and downs of these years that strength is shown in the successes – the play that finally turns out right, the year-long research project that eventually does make it onto a poster-board for the big presentation, the grad school application with a happy ending. But that’s not how strength is built. Strength is built in the moments when you’re groveling in front of Waldo because of the dumbest attempted heist in world history, or you finally turn off the light and go to bed, believing that the paper really never will get done, or walk out of a rehearsal knowing in your heart that this play will be nothing but an embarrassment. Nobody has ever stood up at their retirement party and said, “I am the person I am today because of my Hawaiian vacation in 2007.” We are transformed by the hard stuff. Our strengths come from the work and the failures and the suffering. Not just what’s intellectually hard, but when the challenge becomes emotional. We have lifted all we can, and there’s nothing left. We get strong from the weight room, not the jacuzzi. And we don’t get strong alone. Not usually. We are social creatures, so our strengths are built with the support of relationships that help us through the hard stuff. The encouragement of our key relationships gets us through building strength to showing strength. And strength is built when we know there’s a purpose. Pain that is pointless is just pain. It breaks you down. For pain to build strength, we need to know there’s a calling to something more. From Heaven Comes Our — What? I want us to look at the college seal. It’s simple – just “GA” and our Latin motto: e caelo nobis vires. It has been dormant for a few decades. I’ve asked around, and I tend to find that nobody knows what it means. But I think it’s ready for a comeback. Let’s talk about what it means. Caelo means heaven. Think ‘celestial.’ So, e caelo = “from heaven.” Nobis of course is “ours” or “to us.” So we’ve got “From heaven comes our … vires.” What’s vires? I always thought it was truth. Harvard’s motto is just “veritas” – which does mean “truth.” So I figured vires is probably related to veritas, and it makes sense for a college motto to be, “from heaven comes our truth.” So for a few decades I wore a Gustavus class ring with – as far as I was concerned – “from heaven comes our truth” on it. (I have an unusual class ring – it’s just the college seal.) But that’s not what it says. Our daughter would roll her eyes at my ability to be confidently wrong for so long – I think it’s a gift; she has doubts. She’s quite clear that vires means “strengths” – it’s plural. So here’s the Gustavus Latin motto: e caelo nobis vires from heaven come our strengths On the fact that nobody but the Classics department knows what this means - I’ll let us off the hook on that a bit. The University of Chicago’s motto is crescat scientia; vita excolatur. Nobody knows what it means. Well, not quite. There’s an official translation, which was necessary because nobody knows what it means. Here it is: crescat scientia; vita excolatur let knowledge grow from more to more; and so be human life enriched Somehow four Latin words that nobody understood became thirteen English words that are still a little confusing. With a semicolon. Perfect for the University of Chicago. I think Latin mottos have been ignored for a few decades at most colleges, except at Harvard where the founders took the precaution of making it just one word. What has been hiding from us for so long, though, is the fact that the Gustavus motto is different from the rest. Chicago’s is about knowledge. Harvard’s is about truth. That’s what you’d expect for a college, right? That’s what this is about. But the Gustavus motto is about strength. Scrappy From the Start The people who created St. Ansgar’s Academy, later to be renamed Gustavus Adolphus College, had reason to beg heaven for strength. They had gotten themselves into something and they didn’t know how it would end. They were scrappy, and they did what they needed to do. But they weren’t about to do it alone, nor could they. Gustavus was started in 1862, on the frontier, by people who lived in wood structures they built with their own hands. Minnesota had become a state just four years before. 1862 was the year of the Dakota War, a series of civilian massacres followed by the largest mass-execution in American history. That happened just down the river in Mankato, the day after Christmas. The Civil War was raging and some of the Swedish immigrants who founded this place would be swept up in that war. In the summer of 1863, when Gustavus was still St. Ansgar’s Academy, some of them would fight in the Battle of Gettysburg where the 1st Minnesota Infantr

    13 min

  5. May 10

    Mother's Day!

    It takes a lot of work to get kids to the point where college is even possible. Moms have a certain tendency to do that work. This was our Christmas letter in 2009, describing what - if you read between the lines - was a lot of work. Thanks, Sara, for all of it. * About a year ago, Annika declared that our house was Elbertwood School. Then she started conducting classes. And recess. And gym. And lunch. And after-school clubs. We have no idea where the name came from - neither does she - but every day, Annika and Tollef come home from school and they promptly start school again. In real life, Annika is in first grade and Tollef in Kindergarten at Minnehaha Academy, but at Elbertwood they are both in second grade, and Annika is both teacher and student. The daily saga of Elbertwood has been our story in 2009. An Annual Update From Elbertwood School An Arts & Snacks Magnet School Dear Parents & Friends of Elbertwood, I write to provide an update on events in our beloved Elbertwood School in 2009. Miss Annika remains our only teacher, but enrollment has grown considerably. Tollef was the original conscript – well, student – but classmates now include Emma, Tom, Tim, Abigail, Olivia, Julia, Tookie, Manjo, TV and Noodle. Even with so many imaginary friends at Elbertwood, Tollef gets all the attention he could possibly need from Miss Annika, and I think it’s fair to say, more than he ever wanted. Curriculum remains innovative and rigorous. Miss Annika prints worksheets from the internet and grades them meticulously. Subjects include math, language arts, science, lunch, snack time, candy time, gym, and recess. Miss Annika has been enhancing the Bible curriculum lately, but not without some challenges along the way. She was preparing to teach a class on Psalm 100 when she discovered that her Kids’ Bible did not have Psalm 100 in it. A stern conversation was had with the Head Librarian, and real Bibles have replaced the Kids’ versions. 2009 has not been entirely smooth sailing. The cafeteria/kitchen was flooded in August and has not been functional since. Miss Annika and her students were nonplussed by the news that it had been raining in the kitchen, and positively thrilled to hear that Snuffy’s Malt Shop and Pizza Luce would be on the menu until it was replaced. Miss Sara – the Principal of the Lower School – has overseen the kitchen’s reconstruction, and it may be functional by the New Year. Elbertwood was pleased to get a new mascot this year. Porter, our faithful 15 year-old poodle, is still with us – but a local radio station ran a piece on a 14 year-old poodle at a local shelter. The entire school piled into the car and got him. Emmy, Elbertwood’s goldfish, is a different matter. Emmy was acquired in 2008 and she is still with us. Her original aquarium-mate, rest her soul, is not. Nor is her second. Or third. Or fourth through seventh. Emmy now lives alone, as even the snails at the local Petco recoil with fear when we enter the store. Word got around. Elbertwood staff and students enjoyed Summer Camp in Ontario again this year. We did not manage to do the intended Fall Camping Trip, but living without a kitchen has been a lot like camping. For other extra-curriculars, Miss Annika and her student are both in Spirited Feet Dance Class at church, and the recent recital was a great success. It featured about 150 girls – and Tollef. Miss Sara splits her duties between Elbertwood and Bible Study Fellowship International, where she now teaches the three year-old class every Tuesday, and Easter Church, where she teaches and helps to lead the childrens’ programs in various ways. Mr Dan continues on as Custodian and Principal of the Middle School. There are no Middle School students. He is occasionally consulted on matters of curriculum, particularly for Gym Class. His travels continue. Elbertwood has had a fantastic 2009, and looks forward to an even better 2010. Students and staff alike wish you and yours a blessed New Year! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

    15 min

  6. May 6

    Will AI Create Mass Unemployment?

    AI is a formidable automation and labor-saving tool, so the going assumption is that it will wipe out millions of knowledge workers’ jobs. Automation always kills jobs because it changes the nature of work, but it doesn’t always result in fewer jobs when the dust has settled. That’s what we care about when we’re deciding whether to study accounting, or computer science, or become an actuary. Should you go to law school or medical school — or is it better to wait and see what AI does next? Even though AI creates huge efficiencies, I think it is likely to increase employment in many knowledge-intensive industries. Whether this happens in any given field will depend on whether we are capable of consuming more of whatever that industry produces. This is because automations like AI make things a lot cheaper, and we buy more things when they’re cheap. The result is that “job-killing” automations sometimes end up creating more jobs. This is called the Jevons Paradox, named for the economist who first noticed the phenomenon. Why Automation Sometimes Creates Jobs Instead of Killing Them I think the best example of the Jevons Paradox is cars. The earliest cars were hand-made, one by one, so buying a car in 1900 cost about twice what most people made in a year. Because of this, very few cars were sold, and hardly anyone could earn a living by making them. Then in 1913 Henry Ford introduced the assembly line and reduced the labor necessary to make his Model T by almost 90%. By then the Model T had been assembled by hand for five years, so the workers at his factory likely thought their jobs were toast. In a sense they were right: assembly line work was very different than what they had learned to do, and in many ways it was worse. But they couldn’t have imagined what would come next. Here’s how many cars Ford sold from 1905 to 1925: Ford’s plant employed 12,000 people in 1910; by 1920 it employed 40,000. But look at the bars for 1910 and 1920 above: Ford increased employment by 400% … and increased production by 4,500%. Our ability to consume more and more cars — which is to say, our ability to consume more and more transportation — meant that millions of people would earn their livelihoods in the automotive industry, including much of my family throughout the 20th century. Those millions of jobs only existed because “job-killing” technologies made cars affordable. This doesn’t always happen when job-killing innovations come along. Sometimes they just kill jobs. Agriculture is a good example, because we produce food much more efficiently than in the past, but the agricultural labor force didn’t grow - it did this instead: So in the case of cars, labor-saving tech created jobs, but in the case of food, labor-saving tech killed them. Why the difference? In short, there’s only so much we can eat. (I contest that point whenever an Oreo McFlurry comes through the driver’s-side window – but even I have a tiny bit of shame, so it’s embarrassing to order more than two when it’s just you and the dog in the car.) When food gets cheaper, we eat a bit more than before – but consumption doesn’t multiply tenfold, or a hundred-fold. But cars? We can buy as many as we want. Here’s how many cars we owned per person from 1900 to 2000: So whether a new technology will kill or create jobs depends mainly on how much we can increase our consumption of whatever it makes. If some blessed soul invents a $1 McFlurry, I will — with regret — cap my consumption at something like two a day. Three on Sundays and holidays. All that said, it’s usually quite hard to predict whether demand for a product will rise or fall. Ten years ago, Impossible Burgers seemed ready to take the world by storm – then they didn’t. But if you told someone in 1905 that Ford would make 1.9 million cars in 1925, they couldn’t have conceived of it. This is partly because they would have had to imagine a different society, one where people didn’t need to live close to work and could go nearly anywhere for the weekend - not just where the trains ran. Whole cities were built around these changes, and broad social transformations like this are nearly impossible for most of us to envison before they happen. Will AI Make IT Jobs Scarce? Let me take two examples of fields where I think jobs will be steady or even increase: IT and law. Computer science graduates have had a very hard time getting jobs lately, and some tech CEOs have talked openly about AI-driven hiring freezes and even layoffs. The ones who are singing this tune are, of course, selling AI-powered tools to corporate customers, so their hiring freezes and layoffs are part of the sales pitch: Our AI product will reduce your biggest cost – people. Other tech companies are doing business as usual, and some are taking the opportunity to hire top graduates in a soft market. Overall, the market is in a rough transitional period on the back end of an explosion of computer science majors: The computer science wave seems to have crested, which is probably good. Official data isn’t out yet, but programs started reporting steady to lower enrollment in the Fall of 2025. I think studying computer science comes with AI risk, but so does studying a lot of other things right now. If incorporeal robots are the future of work, getting close to them might be a pretty good move. To be clear, coding has been transformed in just the last year. Software engineers commonly don’t write their own code any more; they orchestrate code delivered by AI tools. That orchestration still requires an enormous amount of human expertise, and like the assembly line, it’s at least ten times more productive than the previous method. So it comes to this: can we consume at least ten times more software? When I ask it that way, it seems like the answer could be no. But let me ask it this way: does the software you use at work suck? Or, is there software you only pretend to use … because it sucks? If I say this describes most corporate IT platforms, the only people who will deny it are the ones who sell corporate IT platforms. It also describes the still-terrible checkout experience at every online retailer except Amazon, and much other bad software that we simply take for granted. On the Good Leadership Podcast a few weeks ago, Dan Mallin, a long-time corporate hand and software entrepreneur, said that the typical corporate IT department has about five years of “technical debt.” That’s the amount of work you have to do to make the software you currently have work properly. Forget about the software you should have. And by the way, making your ERP or CRM systems work properly won’t cause people to actually use them. Solving that is yet more work. (If you don’t know what an ERP or CRM system is, you should stop right now, say a prayer of thanksgiving to God, and forget about them forever.) All of this is to say that we have a lot of very productive work left to do in software – making it better, and making better stuff. For the first decades of the computer era, we’ve been typing code with our fingers, something that will seem as absurd to the next generation of software developers as hand-making each Model T seemed by 1920. Will AI Kill Legal Jobs? My second example is law, and I can shorthand it this way: * After decades of legal technology development, most legal work is still hand-crafted. * If you ask the general counsel of a big company how much legal and compliance work doesn’t get done in her organization, she’ll tell you – well - we’re all right. * Then she’ll close her office door and tell you the truth. You have no idea. This is one of my principal fields of work, and I can attest that the “legal debt” in every big company is at least as formidable as the technical debt Dan Mallin described above. Organizations are simply too big and complex, and too fast-moving, for the lawyers to handle every question or review and tailor every contract. Not even close. And the cost of hiring more lawyers - forget it. They’re already some of the most expensive people in most companies. Another example: when a big company like Netflix buys another big company like Warner Brothers, they are really acquiring tens of thousands of contracts. That’s what a corporation is — a nexus of contracts. The research Netflix’s lawyers do before the final purchase – called due diligence – usually involves looking at a just sample of those zillions of contracts, since it’s not humanly possible to look at them all. In other words, they’re buying a black box the contents of which are largely unknown - but they have an idea. This could be done better, and AI will make it so. Most acquisitions destroy shareholder value, and it’s basically because their scale and complexity is far beyond any person’s ability to comprehend. It’s not just the contracts - it’s everything. We’ve been assembling increasingly complex corporate structures with duct tape and pliers. Now that it will be far cheaper to do the work thoroughly and well, I expect lawyers to remain very busy. And like IT engineers, they will increasingly be in the business of orchestration, not hand-crafting. Law will be transformed at the consumer level, too. Over half of Americans have no will. Over fifty percent of people show up in court with no lawyer — they’re too expensive. Entrepreneurs regularly start businesses without incorporating them or papering their contracts. Small business owners rarely consult lawyers, and the same goes for management advisors and even accountants, not because they don’t need the advice, but because they can’t afford it. When did you last consult a lawyer? And I don’t mean your friend who went to law school. AI will make legal services accessible, just as it will make big IT projects affordable and maybe even on time. I expect jobs in these fields to change, a

    15 min

  7. Apr 26

    Does AI Understand What It's Reading?

    Let me tell you about a children’s board book called Robbie the Robot Learns to Read. Robbie the robot wants to read, so he visits a teacher named Ms. Snead, a bespectacled turtle who insists that “rules are what make language tick!” Robbie learns the rules, but when he opens a book, it doesn’t work: “new situations here, conflicting rules there, Robbie could only stare and stare.” Robbie then visits a wise owl named Alex, who gives different advice: “Just keep reading for examples. The words will make sense once you have enough samples.” Robbie dives in. He scans thousands of books at great speed. “He built vast language models including words, patterns, order, position.” By the end we are told: “Robbie learned, after studying heaps, that you can know a word from the company it keeps.” That’s essentially what AI does. It knows a word by the company it keeps — by what other words tend to appear near it, in what order, in what contexts. This is a powerful thing to be able to do. It is also not what reading is. World models Consider this sentence: “You are the light of the world.” What does it mean? For a human, the answer involves an extended frame. There’s a speaker saying something metaphorical about identity and moral visibility. The reader has to understand the metaphor, understand who is plausibly being addressed, understand what the speaker probably wants the listener to do. To understand the sentence, you have to build a mental model of what the speaker thinks the listener will think he means. That is not word prediction. It is world construction. This is a difference between knowledge and understanding. Now more than ever, education is about understanding, since machines can retrieve and render all the world’s knowledge at almost no marginal cost. The competitive advantage of humans is our ability to understand. Here’s an illustration of one thing you can do that AI can’t. You are riding your bike along a highway and an ostrich merges somewhat aggressively into your lane. Like this: Even if you have never traveled with ostriches before, you know the ostrich won’t do certain things. For example, the ostrich will not: * meow * suddenly melt * draw its sword * ask you for a light * blast off vertically * transfer itself to your C: drive * stop on a dime (that’s Road Runner) You know these things because you have a world model. Even if you’ve never seen a live ostrich before, you can tell that it is a large bird, a biological creature, subject to certain laws of physics. But AI lacks a world model, so it is quite capable of believing that an ostrich’s next move will be to melt or meow or draw its sword. No five-year-old human would make these mistakes. What does this mean for knowledge work? For now, machines are useful for tasks where meaning can be derived from word associations and statistical patterns, and where a high degree of accuracy isn’t that important. That’s a lot of tasks. Summarizing a document. Drafting an email. Answering a routine question. Brainstorming titles for a Substack post. Finding the relevant sections of a long report. These capabilities are rapidly enhancing the productivity of knowledge workers, and the world will be better for it. But the underlying limitation remains. A machine does not understand what it is reading in any sense a human would recognize. It is doing something else. This matters especially when being wrong can be catastrophic. A doctor who confidently makes a bizarre diagnosis is a bigger problem than a doctor who is modestly wrong in a sensible direction. A financial analyst who confidently asserts that a bridge is a sailboat is more dangerous than one who is slightly off on a growth estimate. Even if this happens one time in a thousand it will destroy credibility and ruin a career. We rely on working with others who share our world models. The solution for now is to have humans initiate, review and oversee the work of machines. There will be lots of jobs like this — seeing where and why AI is wrong, and imagining how it could be made to do its work even better. These are management skills, but the jobs will be entry-level. There are plenty of young people who can do this well, but most of our educational system is not built to develop these skills. As to our title question, the answer is no, AI can’t really read. It can’t be surprised, or notice that something is off, or wonder what the author really meant. Those are jobs for humans, and they will remain so for a long time. * Links to the original series at Legal Evolution: I: Legal’s AI rocket ship will be manned II: Did Robbie the Robot really learn to read? III: My new Volvo is a Mazda IV: My mind is just a broken machine This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

    7 min

  8. Apr 23

    AI – What Is Judgement?

    As we assess how AI works, we get a better sense of how our own brains work. To be clear, even the people who create AI don’t quite know how it works, and nobody knows how our brains work.* Today, I want to look into what we mean by exercising “judgement”, whether and how AI can do it, why we’re able to do it, and how we can educate for judgement. I sometimes teach a course on presentations at the University of St. Thomas School of Law. It grew out of a class we ran at CEB, the research firm where I grew up professionally. It was live-fire training intended to help young professionals get better at delivering presentations. The speaker was carrying a message developed and refined by an experienced research team, so they knew what to say – they just needed to get good at saying it. That’s what the training was for. When I first taught the class in a law school, the students were similar – people in their 20s and 30s, college-educated of course, varied backgrounds. As with the corporate course, the core activity was speaking: from Day 1, every student gets up and presents material. And on Day 1, I discovered that this course was going to be about judgement, because the students got up and said things that would get them kicked out of the room – or worse – by a real audience. Real audiences have their own problems and their own perspectives, and the first thing to figure out is not what you’re going to say — it’s what their situation is. It’s the management team of a failing tech company, or the assembled partners of a booming law firm, or a disappointed student activist group, or a church governing board (no adjective necessary: there is always strife). So occupied by the task of presenting material, students hadn’t thought this aspect through. In practice, judgment is asking, and envisioning, how will these people interpret and understand me in light of their situation? What is their situation? Do they agree among themselves on the nature of that situation? (Always: no.) Who do they think I am? Do they have an incentive to agree with my framing of their problem – or to disagree? What does the audience want to hear, and what don’t they want to hear? And finally, the job: in light of all that, what do they need to hear? It is empathy fueled by imagination. If this seems sophisticated, it is. But we start doing it before we can talk, and we keep doing it throughout our lives. Children learn to imagine what Mom wants, and what Dad wants, and what their insufferable older brother and insufferable younger sister want. These imaginings are imperfect but serviceable, and we get a lot better at them over time. They help us navigate. They help us get another Christmas cookie or another story before bed. It’s how we get a date to the prom or a first job or a recommendation from a professor. At CEB, everyone had lived a few years in the corporate world before getting up in front of an audience. We had some experience imagining, based on our experience, what supply chain executives cared about, how that varied by industry and capital structure, how it differed from what their colleagues in Legal or Finance or HR or Strategy wanted. We imagined what they thought of consultants, and young consultants, and young consultants in suits or not in suits, depending on the location. This let us anticipate and manage what this Finance or Legal or Supply Chain executive wanted to hear, and needed to hear. This is judgement. It’s imperfect but serviceable. I did around 800 live presentations, and only faced full audience uprisings in three or four (one of which involved a threat to have me removed by corporate security … we got through it). Sometimes you really don’t get to have the extra Christmas cookie. Back to class - law students don’t necessarily have experience with this stuff, and their first presentations reflected that. Figuring out what to say and how to say it doesn’t leave much brain energy for seeing the six different ways their words could be received by different audience members. Can you teach judgement? Absolutely. As anyone can attest who knew young Danny Currell, I (ahem) didn’t always have it. We get it by putting ourselves in others’ shoes, envisioning diverse “what if?” scenarios, considering alternate outcomes, and doing all of that repeatedly. We build judgement by feeling the effect of mistakes, but more than that — and this is perhaps a hallmark of natural intelligence — we build judgement by correctly inferring effects that we never experience. (I call it natural intelligence, by the way, because animals are quite good at this, too. We’ve had self-driving vehicles since horses were tamed.) In class, developing judgement was mainly about the audience: Who are they? What do they care about? Who’s the decider? Who knows the most? Who’s the most powerful? Who’s the influencer? Who can call corporate security on you? In the event of defenestration, what floor are you on? Yesterday, I wrote about the idea that AI doesn’t have a world-model – only a very sophisticated text string. After that post, an old friend and I emailed about whether it matters that machines currently lack the ability to envision things and to rapidly manipulate those resulting images or mental models like we do. His point is that if AI can use text to describe our mental models accurately and instantly, does it matter if they are one step away from having those models themselves? Let me say why I think it might matter. * Confidence and trust. Part of good judgement is imagining when we are likely to be lied to and why. AI struggles to separate truth from lies, lies from inaccuracies, and lies from fiction. (We know there’s a difference between lies, inaccuracies and fiction. It’s a matter of intention, which that requires empathy to imagine.) If we’re working with AI, at least now we try to mitigate the problem with better prompts. In other words, we supply our judgement. * Empathy and anticipation. Judgement also involves empathy and anticipation. Empathy is “what if I were her?” Anticipation is envisioning what I might do next if I were her. It is alleged that, when asked how to carry out a school shooting, ChatGPT provided a helpful (to the shooter) response. Humans would normally recoil at the question, so it’s worth thinking about why. I think it’s because we instantly imagine why someone would ask such a thing, then – involuntarily, instantly – envision what that person may want to do next. Those thoughts, those world models and their alternatives, form in the blink of an eye. By contrast, at least for now, AI has to run complex calculations to identify a risk, or - as here, allegedly - it just answers the question. How do we teach people to be better at using their natural judgement? It’s a question for the ages, but I think a short piece of the answer is a series of simple questions that are hard to answer: * How do I know? * Who am I dealing with? Are we sure? Are they real? * Who else could I be dealing with? * What might they want? Why? * What’s the best outcome from my perspective? From theirs? * What facts do we probably agree on? * What do they want to hear? What do they need to hear? Am I sure? * Will others accept what I know? Why not? * Who’s getting paid? In the short run – and in the long run? How – and why? * How well does the audience, the author, or my opponent understand their own situation? * How well do we understand our own situation? Do we disagree internally? Why? Tomorrow (post #3) I’ll turn to a related question: what AI, critical thinking, and the liberal arts have to do with each other – and why the answer matters more than most people think. * *On the matter of how our brains work, at least in the terrain we’re talking about here, I think some of the most helpful stuff comes from Iain McGilchrist. Here’s a fun and easy starter video on his ideas. After that, Ways of Attending is terrific. After that, the reading gets a lot longer — The Master and His Emissary at least fits into one volume; his most recent two-volume work, The Matter With Things, I will freely concede I haven’t read yet. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thecollegequestion.substack.com/subscribe

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The College Question provides answers on all things college: what it costs and why, how financial aid works, where majors lead and more. Hosted by Dan Currell, former U.S. Department of Education official and regular contributor to the New York Times. thecollegequestion.substack.com

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