Aiming for the Moon
Aiming for the Moon
127. Connective Labor - What Machines Can't Replace in Our Disconnected World: Prof. Allison Pugh (Author of "The Last Human Job" | Prof. of Sociology @ Johns Hopkins University)
As we enter a world of artificial intelligence, the question of what should be automated looms before us. Models need clear, objective metrics to train on. But, can jobs really be distilled to data points? In her book, The Last Human Job: The Work of Connecting in a Disconnected World, Prof. Allison Pugh asserts many jobs have a relational component that can’t be caught in the metrics. In this episode, Prof. Pugh warns that devaluing connective labor leads to automation that overlooks the core issues and leaves us more isolated.
Topics:
- Connective Labor
- Undervaluation of Connective Labor
- Automation of Connective Labor
- Role of Data in Education
- Educational Inequality and Standardized Testing
- Artificial Intelligence and Relationships
- Growing Demand for Connection
- "What books have had an impact on you?"
- "What advice do you have for teenagers?
Bio:
Allison Pugh is a Research Professor of Sociology at Johns Hopkins University, and the author of four books, most recently The Last Human Job: The Work of Connecting in a Disconnected World (Princeton 2024). The 2024-5 Vice President of the American Sociological Association, Pugh was faculty at the University of Virginia for 17 years before moving to Hopkins this summer. She is a former journalist, and her writing has appeared in The New Yorker, The New York Times, The New Republic, and other outlets. She served as a US diplomat in Honduras, cofounded a charter school in Oakland, waited on tables at the US Tennis Open, packed salmon roe in Alaska, and was an intern at Ms. Magazine.
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As we enter a world of artificial intelligence, the question of what should be automated looms before us. Models need clear, objective metrics to train on. But can jobs really be distilled to data points, or is there a more emotional and relational side to effective labor? This is the Aiming for the Moon podcast and I'm your host, Taylor Bledsoe. On this podcast, I interview interesting people from a teenage perspective. In her book, the Last Human Job the Work of Connecting in a Disconnected World, Professor Allison Pugh asserts many jobs have a relational component that can't be caught in the metrics. Allison Pugh asserts many jobs have a relational component that can't be caught in the metrics. Pugh warns that devaluing what she calls connective labor leads to automation that overlooks the core issues and leaves us more isolated. Allison Pugh is a research professor of sociology at Johns Hopkins University and the author of four books, most recently the Last Human Job. She is also the 2024-2025 Vice President of the American Sociology Association. Pugh was faculty at the University of Virginia for 17 years before moving to Hopkins this summer.
Speaker 1:If you enjoyed this episode, please rate the podcast and subscribe. You can follow us at aimingthenumber4moon on all the socials to stay up to date on podcast news and episodes Check out the episode notes for links to our website, aimingforthemooncom us at aiming, the number four moon on all the socials to stay up to date on podcast news and episodes. Check out the episode notes for links to our website, aiming for the mooncom and our podcast. Substack lessons from interesting people and all right with that. Sit back, relax and listen in. Well, welcome, Professor Pugh, to the podcast. Thank you so much for coming on the show.
Speaker 2:Thank you for having me.
Speaker 1:So you wrote a fascinating book named the Last Human Job, the Work of Connecting in a Disconnected World.
Speaker 2:And to kind of dive into our conversation. What is connective labor? That's the name I came up with for a kind of practice that happens all over the economy. We have all experienced it and maybe all of us have done it. What it is is the moment of reflecting back to the other person, the person that you see. It's the act of seeing the other and being seen. It's reciprocal, mutual, interactive and it involves some emotion, emotional sensing of the other. Therapists call this attunement. But it happens not just in therapy, although that's the most iconic example. It happens in teaching, it happens in the law, it happens in management, it happens in high-end sales, it happens in medicine. It's wherever someone has to convince you that you're being seen. For whatever they do to work Teaching is a really powerful example, I think they do to work Teaching is a really powerful example, I think, especially for young people.
Speaker 1:It's really interesting to think about connective labor because, as you highlight throughout your book, it's something that you don't tend to think about when you think about specific jobs. When you think about doctors, for example, you talk about did they prescribe the right medicine, did they diagnose the patient correctly, and you don't always. You talk about bedside manner perhaps, but it's more of this means to an end of kind of getting a patient treated. Why is that? Why do we not value this type of work as much? Is that a problem too?
Speaker 2:I think it's such a problem and you could say that's really underlying the whole book. It's why I wrote this book, because we don't value it and so we're doing things to it to make it harder, and actually it's on its way to being widely automated, and so I wrote this book to point it out and to hopefully reveal some of its value. I think the reason why we don't see it is because it's not what we pay for. You know, we want a child to learn algebra. We think, or many people might think, that a lot of these things are about information download. Like just you know, here are the download. Like just you know, here are the you know 10 things you have to know about algebra.
Speaker 2:But actually we know this across many occupations, people won't hear the thing, the information they need to download, unless they feel seen. This is a human fact, and so doctors have told me, you know I interviewed many primary care physicians and they've told me, you know, I know, you know that someone needs to stop drinking or that they need to lose weight or stop having so much sugar or all the things that everyone does, and they also know that it's the relationship that will kind of nudge the person towards better behavior and that the patient won't hear them, won't hear any of this advice unless it comes from a place of I see you. I understand your situation and I see you is not just you drink too much, it's this is your situation. And I see you as not just you drink too much, it's this is your situation, and I get what's happening here and I get what your goals are. It's a really interactive thing and seeing is at the basis of so much of economic activity that we actually value actually value.
Speaker 1:A big part of having conversations like this and a big part of their disruption seems to be the value of data we put in a lot of these jobs, which one of the other questions that I want to get to later on is. That balance is specifically with science jobs, where you need data to assess whether someone is becoming healthier, for example, but there's also this connection where, when you valued the data and the analytics, you're missing a big part of maybe why you were originally even assessing this and you cite schools as a big factor. Could you discuss that a bit?
Speaker 2:I mean, if your listeners are teenagers, they know this backwards and forwards.
Speaker 2:Many schools, in part, you know to be kind, they are kind of nudged or pushed in this direction by their, you know, by their societies, by the superintendent, by the district, by the legislature, but nonetheless, schools have become places where we count students more than we see them and so we are counting how many people you know are attending and how many people are graduating and how many people are maybe passing. You know English, but we're not really seeing the kids underneath the numbers. And that started or that gained real traction with in the United States, with the no Child Left Behind Act, which put real punitive measures in against schools that you know didn't meet certain metrics, but what it did, what that did, was really that became the engine behind the counting revolution, so that there's actually, you know, people have, you know, an administrator has recently was quoted as saying you know, an administrator was quoted as saying I know kids by data more than I know them by faces, and that's a corruption, that's a serious degradation of teaching and learning, and most teachers will tell you that.
Speaker 1:What would you say to the argument that this? Well, first off, this argument might be not true, so I am curious about that as well. But the argument that says, well, going the data-supported route, the kind of the analytics route, is what produces the most efficient and best students, for example. So in order to make sure that your students know math, know English, at a standard level, for example, you need the ACT, the SAT and tests that kind of create that, I guess, analytical description of the world. And so by that we need to be as efficient as possible and, for the sake of the student, provide them these skills, even if it means we don't have as much of a personal connection.
Speaker 2:So what you're really getting at is isn't data worth something? And you know, standardized metrics can have their use and I agree with both of those. So I'm not like anti all data. I'm a sociologist.
Speaker 2:This book is based on data, you know like it's qualitative data but nonetheless it is. You know, the gathering of a lot of information and then the studying it for particular patterns. So I understand data and I, you know, have I appreciate it. I think it's useful. You know what it is is like, kind of gathering the information before you make a decision, make an analysis, make an argument. So yeah, but what this book is really arguing is that data, for data's sake, has really taken over many spaces where actually relationships are vital and they're kind of moving relationships aside, they're shouldering relationships out of the picture.
Speaker 2:And I actually want us to prioritize relationship and see if we can fit data in, and right now we're prioritizing data and seeing if we can fit relationships in. So I think that you know, yes, standardization, standardized tests, I think, have a place, you know, for schools, for admissions, you know, considering, you know who have 50,000 applicants, say, and have to figure out some way to sift through them, but more importantly, really for the student themselves to be able to say like. More importantly really, for the student themselves to be able to say like huh, it looks like I'm stronger in English than in math or whatever, but beyond that it's not going to tell you much, not going to tell you how you learn, not going to tell you you know, kind of, what tactics to take to master a particular field. So it's pretty modest what it's getting people and it's certainly not worth, in my opinion, all the inordinate attention that it gets in a teenager's life.
Speaker 1:You know I was reading about an example of in the book Weapons of Math Destruction and I believe the preface or the introduction the author discusses I believe it was the DC schools who basically decided, in order to improve the quality of teachers, they were going to assess whether to rehire them based on standardized test scores and we were discussing that and she discussed how the author was saying that's a terrible idea because of all the other factors, as your book connects and discusses in great depth and I was talking to one of my teachers about that. He was like I would quit on the spot, like that is a terrible means and the interesting thing about that is that system lost great teachers because of the almost. Just. It's the data encroaching on the thing you're going after which is really interesting to me.
Speaker 2:And also there's a kind of really important inequality component to that that so much of standardized testing is actually just measuring socioeconomic status and privilege or advantage, you know, built in over time. It's not actually measuring what teacher grabs this set of kids in September and ends up with this set of kids in June, and so it's not really a measure of teaching. It's a measure of what kind of social environment the kids have came into school with. And yeah, so it's a terrible sign, it's a terrible signal for a society to send to teachers that you know, we have this, we have this one hammer and everything is a nail, and instead teachers are about teaching, is about relationship, and I'm not saying that we don't know what's good and bad, and I'm not saying it doesn't matter what's good and bad.
Speaker 2:In fact that was another motivator for this work thinking about this kind of deeply interpersonal, humane service and how do we scale it up so it's not only available for the rich or the lucky, like we all as a society worry or should be concerned about that. How to spread good teaching, doctoring, therapy, counseling, et cetera, you know. And so that was a kind of initial motivator for figuring out how to you know, for my doing this research, and the people that were really also thinking about that were in AI, and so I came into this project. I would say more agnostic about that than when I left it or, you know, after I, you know, wrote the last word, I ended up more cautionary about the AI project than when I started.
Speaker 1:That was actually the area I wanted to dive into next, because a big part of the summer, at least for me and my interviewing schedule has been, like, very specific about AI. What's the effects of AI on society? And also, how do you build AI and AI technologies in a way that doesn't not in the way as some people talk about, as it has the least amount of harm, but actually helps people as well? What do you think the balance is there? Because when we talk about science, for example, artificial intelligence provides incredible connections across research and even in like interpersonal connections with doctors. Scribes perhaps it's scribing so the doctor can look more at the patient. What's the balance between getting data from interactions and also the connection?
Speaker 2:Well, if we can draw a kind of line from the argument that we just were talking about with regard to data and the argument that I want to make about AI, there's some consistency there, because what I really want us to do is prioritize the relationship. So AI has a you know wealth of kind of applications, many that I'm sure we have not, you know, even conceived of yet. So it is a you know kind of a cornucopia of offerings for us. But engineers are kind of, you could say, like throwing a lot of spaghetti at the wall hoping something sticks, and one of the spaghettis strands that they're throwing is about automating relationship, is about automating relationship. So the scribe, for example, who's, you know, for your listeners, someone who's writing down the or usually updating the electronic health records so that the doctor can actually have eyes on the patient and have a, you know, direct, you know emotional, thoughtful, reciprocal, connective labor type experience with a patient thoughtful, reciprocal, connective labor type experience with a patient. That's not, you know, automating relationship. That's actually doing something better. That's actually arguably that's allowing the doctor to have this relationship, and so that's, I would argue, that's, you know, kind of AI or AI plus, you know, kind of in service to relationship.
Speaker 2:But there are many instances where engineers are like, huh well, what if we just automate the discharge nurse? What if we just automate the palliative care consultant? What if we? These are I'm not making these up, these are actual cases where engineers are kind of trying out you know kind of agents, ai agents that stand in the stead of actual humans who would have relationship, or you know kind of connected labor, a lot of uses but engineers who are trying everything they can are also aiming at automating relationship, and that's gone too far, that's AI run amok. So those are cases, for example, where you have automated palliative care consultants, automated discharge nurses, automated therapists and the argument and I explore this in my book because I want to kind of inoculate the reader against these arguments technologists advocate for the use of these because it's better than nothing.
Speaker 2:You know, oh, places that don't have therapy. Or, oh, students that can't get good teachers, you know, et cetera, and I worry that we're kind of turning to technology to solve things, solve problems that we are not willing to solve with just providing better staffing. Or, you know, improving our credentialing system. Or you know improving our credentialing system. Or you know, trying to pay people more so that it attracts them into the business.
Speaker 2:You know like there are other solutions, hard politically perhaps, but technology is not going to solve these problems. Because what happens if we use technology to solve better than nothing problems is we are, you know, running towards a future in which rich people get you know kind of this interactive human experience and low income people or less advantaged people get that, get that work automated, get you know, they get to have the teacher, that is the bot, whereas the wealthy person gets the person that you know in the human who is devoted toward to having a relationship with that student. So it's just that utter inequity where the human contact becomes a luxury. That's what we really need to avoid.
Speaker 1:It's a really interesting dystopia there, because it's almost flipped the model on its head of what you would usually see across like sci-fi things, where rich people have servants who are robots and like Alfred is a robot or something like that. It's flipped, it's on its head and actually the more I guess traditional or non-technotopia society would be at the higher class, for example, which I hadn't ever considered and it was super interesting to me. One of the other things that's concerning is doing more research into so backing up. Some listeners know that some listeners don't. I love computer science and programming, especially like natural language processing, but it's concerning where some of this stuff is being applied.
Speaker 1:So there are great ways to apply natural language processing in the study of algorithms in human language, but also some areas where that's a little creepy, such as Instagram's now, like chatbots that are replacing people and like saying I can talk to you, I can be your friend, I can talk to you about anything, and you're like well, there's multiple things. One, you're replacing a person there. That's that's creepy. That's a computer. Two, aren't you also telling really personal things to big corporations Like that's? That's the other aspect that you discuss in your book that we assume computers are these safe spaces but they're not and it's yeah.
Speaker 2:Could you discuss that a little bit more too? That analyzes why that basically says they. You know the the web is where they have privacy from their parents and their. That is worth more to them than privacy.
Speaker 1:What was the thing that? What was the thing that teenagers had more of it. Just cut out that one word.
Speaker 2:Teenagers want privacy from their parents and are willing to. They find that in the internet, they find that in social media, they find that out there in the world, even though they are kind of giving up privacy vis-a-vis the corporation and so traditionally they care more about getting privacy from their parent than privacy from the corporation. But at the same time I talk to you know, undergrads all the time and they are aware and, you know, kind of aren't thrilled about corporate surveillance. So, yes, what you're describing is really disturbing and actually we're going to see more and more of that, because I've seen, you know there's a toy that's getting a lot of attention and, I think, some significant purchasing called Moxie.
Speaker 2:Have you ever heard of it? It's like an AI companion for kids. Heard of it? It's like an ai companion for kids and I think it you know it's it's being sold again, better than nothing. So it's being sold by people who sold on the premise of like, this will help your child practice friendship and it's supposed to be for kids, maybe, uh, making friends or something like that. But it's the same principle. It's the to be for kids, maybe making friends or something like that, but it's the same principle, it's the same issue. These kind of better than nothing arguments are a way to get the AI into the household, you could say, and it's replacing real human relationship, and that's the kind of AI I want us to really draw the line about.
Speaker 1:Like a hundred years ago you might not have seen the same connection problems. And it's kind of the sad thing. Now we're using our technology to kind of retrograde and go back and say, well, that problem we didn't have a hundred years ago. Well, you can just fix it with technology, and it's really unique, I guess. Look at the world. I'm not entirely sure why, you know.
Speaker 2:I'm not entirely sure why, you know, I'm not sure, I'm not a historian, but I've read histories of the motion et cetera, and I'm not sure that I would agree 100% with what you just said, because I actually think this is kind of an interesting moment.
Speaker 2:I believe that there's evidence to suggest that we actually are searching for greater connection now than ever before, that there's a lot of pressure we're putting on each other to truly see the other. Those kinds of demands of being seen and being seen, those weren't really expectations, say, 150 years ago. So it's almost like these problems that we have are in part because of this kind of greater need for attention, sure, but also for a deep emotional connection. And yes, we're not that good at it and yes, we're looking to technology to solve that problem, but also it's kind of, I think, a relatively new problem. These are very we have essentially very high expectations for our relationships and for our capacity to be seen in this world. I'm all in favor of those pretty much, and so that's what this book is about, is about valuing connection and about how to get more of it, etc. But I also do think that it's pretty modern, I'll say.
Speaker 1:Well, that's great. I hadn't heard that argument before, and that's a much more hopeful and optimistic view of the world versus the terrible downfall of humanity that you usually hear with social connection.
Speaker 2:I think they're always getting worse or whatever Right.
Speaker 1:Exactly.
Speaker 2:So that's great, yeah, I mean I actually behind a lot of you know I come to this from. I started as a family sociologist and that's really what we know about marriage, for example. Like marriage, now you hear like, oh, you know, half of marriage is in end of divorce. But really what it is is you're either going to be married for 50 years and it's. You know there's a bifurcation of marriage. But our expectations of marriage is much, much greater because of this intensification of emotional kind of action. So it is a positive, but it also makes things more fragile and more fraught, so it has some negatives.
Speaker 1:Well, that's great, honestly great, Like I'm definitely going to be thinking about that idea more, because it's usually it's doom and gloom.
Speaker 2:Yeah.
Speaker 1:So, backing up and asking the last two questions, we ask all of our guests what books have had an impact on you.
Speaker 2:So such a fun question. For me, the best books, the books that I discovered I loved, were books that have the craft, because you want to be astounded by the writing, have the plot so that you can go through. It's someone who can tell a good story and also have the heart Like where do they grab you? Do you love the people? I need that actually, and so for me a pinnacle story here would be Bel Canto by Ann Patchett. If you haven't read it, run and get it. It's about um. It's about an opera singer in a Latin American country and um and a takeover by terrorists and by the end you have great sympathy for everybody involved and it's a wonderful story. It's an amazing story.
Speaker 2:I think it's the best thing she's ever written. I actually think it's my favorite novel of all time. But also, I actually read a ton of YA. I have three kids, read a ton of YA. I have three kids and I'm a big YA reader. So something I've read probably 10 times or more has been the entire Tenere series written by Naomi Novik, who's a really fabulous YA writer, and that has taught me a lot about kind of integrity and coming to know ourselves and just trying to be true to the person you now understand yourself to be, and also masculinity and the British-French wars of the early 19th century, and dragons, sorry.
Speaker 1:Hey, that's very eclectic. That first book sounds absolutely fascinating, like the heart and soul of it. Plus, the country gets taken over by terror. So well, that's a thriller in its own right, and but I love those books that combine, as you said, the plot in the heart and also have these kind of like revealed deeper truths about the world and society and people.
Speaker 2:Yeah, exactly, me too.
Speaker 1:Our last question is what advice do you have for teenagers?
Speaker 2:Yeah, I actually so, as I have three kids and walked them, you know, walked alongside them as teenagers, and it wasn't until my last teenager that I figured it out or that we figured it out together. So I believe that the way the US does high school, we do high school really badly, I think, and we do college really well. So high school is a story of you can't really choose anything and everything is really high stakes and so it's. You know, lack of choice and intense stakes makes for a rat race. That is really appalling and deadening to the soul. Maybe I'm being too negative because you look very happy. High school is a rat race, but college is actually a place of great autonomy, great choice and actually not that high stakes. An individual grade is not as consequential except, of course, if you're going to pre-med, but everybody else is just trying to learn and trying to do, trying to figure out what they're interested in. So college is actually a great place.
Speaker 2:But for teenagers, my daughter and I discovered something we call the joy metric and we borrowed it from Marie Kondo. I don't know if you remember Marie Kondo. She was the one who was all about how to make things tidy and it was all like you have to throw things out if they don't give you joy. If things don't spark joy, throw them out. And that is we actually applied that for my daughter applied that was, you know, in some intense calculus and you know, do I stay with field hockey or do I, should I retake this exam? You know, like all these terrible questions that you have to answer as a college, as a pre-college person, in high school, and we just started to be like what gives you joy?
Speaker 2:So she, she dropped, for example I tell this story to people because she dropped band in the one year that the band was going to London and then rejoined it the next year when they went to Gatlinburg and I was just like you missed London, you know. But that's the, you know, that's the parent, the over-involved parent, the rat race speaking, and she was really happy and she dropped field hockey. And then she picked up like I forget cross country and just kind of did and it sounds these sound like minor choices and at the time they were her life, so they were major for her. But I understand they sound like minor choices, but the good news is she still uses it today.
Speaker 2:She's now 23, and she has a sense. She has an inner sense that she has developed of being able to hear what sparks joy, what she, what, what what sparks joy, and if you can hear it, that's that's something. That is that's something. You have to develop that antenna and that's what I recommend for teenagers to do it today Develop your own joy metric. You won't have a choice for everything, because we don't give teenagers a lot of choice, but whenever you have a choice, try and hear it and live the joy metric, because developing your own sense of hearing, your own antenna, will serve you for the rest of your life.
Speaker 1:Well, thank you so much, Professor Pugh, for coming on the podcast. I really enjoyed our discussion. We went from automation to relationships to, of course, books and advice. It was a great discussion. Thank you so much for coming on.
Speaker 2:Thanks. Thanks so much for having me. I really appreciate it. I loved the conversation.
