Michelle Weise on Long Life Learning

You’re listening to the Getting Smart podcast, where we unpack what is new and innovative in education. I’m your host, Jessica, and this week, Tom sits down with author and advisor, Michelle Wise, to discuss her new book, Long Life Learning, preparing for jobs that don’t even exist yet.

Michelle is currently serving as an entrepreneur in residence and senior advisor at Imagineable Futures, a venture of the Omidyar Group. She was formerly the Chief Innovation Officer of Strata Education Network’s Institution for the Future of Work and Sandbox Collaborative, the Innovative Center of Southern New Hampshire University.

She also co-authored Higher Education, Mastery, Modularization, and the Workforce Revolution with Clayton Christensen. In this conversation, Tom and Michelle discuss a background in the arts and innovation, tech and career pathways. Let’s listen in to learn more.

Hey, Michelle Wise. Welcome to the Getting Smart podcast. Hi, Tom. Thanks for having me. Michelle, congratulations on your new book, Long Life Learning.

I’m looking forward to diving into that. Yeah, you know, it was supposed to come out today, which is election day, but the publisher decided against that, finally. And so it’s coming out in a few more weeks. You never know when books are going to land.

My Power of Place book came out the day that the WHO declared a global pandemic. So you know, you write a book for the world, you know, and you never know when and how it’s going to land. Michelle, I had such a great time preparing for this interview. I did not know that you’d studied English literature, well, literature, English and

other. Did that interest in language start in high school? Yeah, it definitely really started to take off in high school. I had some amazing English teachers. And really the thing that kind of spurred me into poetry in particular was the death

of my 10th grade chemistry teacher during the year. He passed away from AIDS. And so it was just totally traumatizing. But I found refuge in words, in poetry, and that’s really kind of how it all began. Michelle, was it both reading and writing poetry that helped you get through?

Yes. It was first writing and then really starting to get more entrenched and immersed in the literature and in the actual poets and then ended up becoming the crux of my college thesis and then also my dissertation. So did a huge piece on the aesthetics of anorexia and Emily Dickinson’s poetry or the art of

hunger and then moved on to Asian American fiction and poetry in graduate school. And that was, so you did an undergrad at Harvard and then you went to Stanford for a master’s and so that’s really where you dug into Asian poetry? Yeah, I really started out, I did a doctoral program there at Stanford and I started out doing all kinds of poetry from medieval poetry to 18th century to the 21st century poetry.

But then I started to realize that all my colleagues, people in cohorts ahead of me who were doing kind of generalist poetry, they weren’t getting jobs in the job market. So I decided to kind of concentrate on ethnic American literature. Did a lot of stuff in African American fiction and poetry as well as Asian American fiction and poetry.

Were there any African American poets that you fell in love with in grad school? Yeah, one in particular, he was actually from Jamaica, his name was Kamau Brathwaite, really, really kind of was inspired by his poetry. And then in when I was kind of moving more towards the Asian American poets, I started to realize that there was this kind of technique they were using where they were leveraging

and using these sort of more obvious tropes of Asian Americanness. But then sort of undercutting those images with sort of deeper darker images. And so that kind of became the thrust of my dissertation. Really that came out a lot in the fiction of folks like Chang-Rae Lee. Michelle, when I was a school superintendent, I fell in love with the work of Rita Dove.

She wrote occasionally about learning and human development in a really poignant way. So, yeah. Michelle, how and why a Fulbright in Korea, how did that happen and what did you study there? So the year before I got the Fulbright, I had the opportunity to learn another language.

It was kind of a requirement to get a PhD. You had to kind of fulfill these language requirements. And so I decided to actually go to Korea to brush up on my Korean and fell in love, which is kind of living in the country. So I tried to figure out one way to get back and was able to get this amazing fellowship

to go back and write a book of poetry and really wanted that to be a way of doing some research on the Korean War and my great aunt who lost her husband during that war and the kind of tragedies that ensued from that moment. And that’s what I sort of ended up doing for a good six months while I was there. What a beautiful experience.

When you came back, you finished up your PhD at Sanford and then you really began a sort of a traditional tenure track. You were at Skidmore. You’re a few years into your English tenure track. And then you suddenly veer off to the left coast and join an ed tech startup with our

mutual friend Gunnar Kaltemann. What’s the backstory there? Yeah, so I did. I had an amazing sort of preplanned trajectory ahead of me to be a tenured professor, ideally, at Skidmore.

And it was a wonderful, wonderful environment. I think what I realized within the first couple of years and it really crystallized when I had my first child was I was missing the opportunity to get to engage with a much more diverse learner population. I had incredible students at Skidmore, but they were slightly more homogenous in terms

of the population. Like they were affluent. They were mostly white. I had very, very small classes, sometimes only eight students at a time. And so I was sort of aching to touch a more diverse learner population.

But I unfortunately was a professor. I became a sort of full time professor right at the beginning of the recession. And so I was really lucky to have my job. But there was really no way I could ever get a new job anytime soon. It just doesn’t work that way in academia.

And so as I was sort of trying to figure out how to, you know, how to how to reconcile this, this, this sort of misfit that I was kind of sensing in my life, I decided to take a break. And we actually we moved to the West because I didn’t have a job. But I just knew I wanted to sort of see if if there was a way I could maybe have a slightly more a slightly bigger impact on a larger population of learners.

And that’s where I got to meet our friend Gunner. And it was it was the most serendipitous meeting. And it’s where I got to really touch quite a diverse learner population. I mean, these were service members trying to figure out how to transition out of the military into civilian careers. And I got to meet so many incredible, incredible folks.

And really, we just started building things from scratch, even though I was only there for about eight months before the company had to pivot completely. I it felt like four years worth of knowledge building. We we just built all these different kinds of small modularized learning apps to get people moving along their way. And it’s really where I found that first sense of being mission oriented in in my work.

After a short stint at Fidelis, you joined our mutual friend Michael Horne at Christensen Institute and you had the extraordinary opportunity to actually write a book about higher education with with clay. It’s called Higher Education Mastery Modularization and the Workforce Revolution. What was that like working with clay on that manuscript? Yeah, I’m so lucky to have met both Michael Horne and clay through that experience.

I actually met Michael through Fidelis. He was a board member there. But Clayton Christensen just completely I think everyone says it and sounds trite, but he changed my worldview. Like he just completely upended the way I look at data, the way I think about innovations that you would normally kind of just shrug off or or scorn. You know, just he gave me just this really powerful way of thinking about newness and and how to you know, and how to how to evaluate it. He was just a he was a beautiful person.

You know, I think everyone I remember being at a Gallup and people at the table around me were asking me, is he really this nice, you know, because he comes off like so folksy and lovely. And he really is, you know, he’s not faking it. That’s the most incredible thing about that was the most incredible thing about Clay is it was entirely authentic. He made you feel like you were the most special person whenever he was talking with you. And while deeply insightful, Clay was one of the best storytellers that I’ve ever encountered. Yes.

I wonder if you were at Cambridge the day that I interviewed Clay. It was just Clay and I on the stage and I asked him a question and he started talking about paddle boats on the Mississippi. And I thought he had lost his mind. I had it had nothing to do with the question that I asked him. And he slowly swung it around and made this beautiful poignant story that that so thoughtfully illiterate.

The point and helped us as an audience sort of reframe the changes that we were seeing. It was just one of the most artful things that I have been through. But I it scared the heck out of me because I didn’t know where he was going. I suspect you had a few experiences like that with Clay. Yeah, he really was this this master story that he was talking about.

And I think that’s probably been the most important lesson I’ve learned just through every work experience I’ve had since meeting Clay is it doesn’t matter the data you bring to the table. The evidence that you that you share with with folks. If you cannot figure out a way to tell the story to the audience, you can’t tell the story to the audience. You know, the evidence that you that you share with with folks. If you cannot figure out a way to tell the story in a way that captures people’s you know, just just you know, captivates them.

There’s you know, there’s sort of no hope even for the best and most sound data, you know, and he really. You know, anytime if ever someone says, oh, you made it so understandable, you know, if anyone ever sort of says that to you know, something I say it’s all because of what I’ve learned from clay that’s and and also how important it is to use analogical thinking right to take a story to take a related thing from a seemingly unrelated domain and then help you understand how that gives you the same sorts of tools to analyze what you’re looking at now in your own industry. Michelle after Christensen Institute you did another three year extent at Strada education. This is a very interesting nonprofit impact fund in any Indianapolis and they built an amazing portfolio in the post secondary and and navigation space. They’re a leading advocate for helping more Americans move into valuable post secondary experiences. Maybe you could tell us what you did there and how that led to your new book, Long Life Learning. Yeah, so when I first joined strata they were early on in their days of sort of shifting from being USA funds into strata education network.

And at the time we were trying to figure out which sort of void to fill in the post secondary to employment space and I luckily had the opportunity to join pretty early on and sort of make the case for, you know, there are a lot of other impact organizations who are very much geared toward the traditional college going so I feel like we have the opportunity to carve out more of a space in in those lifelong learning opportunities because we keep talking about it but we’re not actually seeing people’s investment theses change and we’re not seeing investments in the architecture and infrastructure needed for lifelong learning and so that’s that’s really also the when we formed the strata Institute for the future of work is how do we get smarter on all these implications about the future and then start building more strategic investments that that get us prepared for that uncertain world of work ahead. And so that Institute that I built was kind of an R&D lab where we’re trying to get smart and then also engage in some strategic learning through investments and grant making.

And it was kind of a second iteration of what I actually tried to build right before then at Southern New Hampshire University which was another kind of innovation lab where we were trying to also kind of, you know, synthesize different kinds of information and research to think about new business models for the future and that was kind of the strata Institute for the future of work was sort of like a version 2.0 of trying to bring in the theories of disruption and think about innovation and creativity differently to get us toward building something new. At strata you had the opportunity to interview hundreds of people was that specific to this book or did you really begin that as part of your R&D center. That really began more from the R&D center. When we really started to say like let’s think about adult learners more specifically, we realized how monolithic this category is right it’s anyone over the age of 18 to death right I mean those are those are your potential adult learners and so how do we how do we

elevate their voices how do we surface nuances in these different learner populations within this adult learner population. That was kind of critical to the series of in depth 100 interviews that we did with folks specifically also in the bottom quartile of the labor market we weren’t necessarily so interested in folks who had access to, you know, great finances and social capital we wanted to focus on the people who were already being left. So you’re really kind of looking at a lot of the new insights that are actually behind. Michelle your your book starts with and it’s title is really built on an insight to insights I think that are artfully combined one is that people are living longer.

that are alive already that will live to 125, maybe even 150 years old. And simultaneously, young people are already experiencing more novelty and complexity, much more change, probably over a longer life,

they’ll experience several times more change than I have. And my career has been in the information age, a really dynamic period in history. So young people are going to live longer and live through far more change.

And so you oscillate that our old notion of thinking of education as five to roughly 20 or 21. And then working for 40 years is it’s already obsolete and that we need to think about long life learning is that a fair summary of the opening postulate?

Yeah, that’s a perfect summary. I think one of the things I’ve always just sort of found interesting is when I go to conferences and this is over just the last 10 years, I would watch people talk about lifelong learning

and immediately you would see the entire audience nodding their heads, yes, lifelong learning. Everyone kind of said, yes, we all need to be lifelong learners. But then that’s like where it just would end.

Nothing actually happened after that. And so I was so curious, where do we go for lifelong learning? Why isn’t this catching fire? Why isn’t this instigating more action?

And so to me, what really did snap it all back into attention is this idea of long life learning. And I think I was just completely taken aback by some of the experts and futurists and folks who study longevity talking about

some of these crazy notions that we could be living much, much longer. And there’s this incredible podcast that Derek Thompson did for The Atlantic where he interviews a Harvard Medical School professor.

And this guy is working on stopping the aging process completely. And he has been working on these specific molecules and his dad, who is 70 years old, has been taking these molecules

that help sort of alter your biomarkers. And he no longer groans when he gets out of bed. And as him, the researcher himself, David Sinclair, he’s 45, he used to have the biomarkers of someone who was 55.

Now he’s more like a 35 year old. So it’s just crazy to think about these kinds of innovations that are affecting our lifespans. And for me, that was just sort of a useful mental model to just completely snap me out of this stupor

of not doing anything. So there’s a lot that we could springboard off that simple but profound observation. I guess first of all, does it mean it’s less critical

making that big decision about where you go to college? If it’s not just four years and done and then 40 years of work, if you really are gonna be learning this earn and learn ladders that you talk about in chapter five,

does that mean it sort of de-risks that big first step into post-secondary? Is it less critical where you go? Is that a fair observation? I mean, it’s hard to say at this current moment

just because their earnings premium, if you go and get a bachelor’s degree are strong. No matter what, right? Like if you actually go get a college degree and complete your college experience,

you will be ultimately better off. That’s just kind of what the data tells us. In terms of thinking about it from the perspective of a risk averse young adult or families who can’t afford the four year experience,

it does give you other kinds of options because we’re seeing so many different kinds of alternative learning providers and on ramps and boot camps emerge that give you some pretty good options

to try out a field. Maybe I think I wanna go work at a place like Facebook or Google, so I should maybe get some coding skills. There are pathways to get you there. And so it does de-risk.

And then it also, you can kind of chunk it up. And I think the thing is, the Stanford Design School came up with this idea of an open loop university where you could kind of go in and out of learning and have some work experience,

come back and get some more learning. The only problem with their model was that they kind of made it like a six year experience. For the 60 year experience. Exactly, yeah.

And the Harvard Extension School is actually now talking about a 60 year curriculum and somehow thinking about these different kinds of subscription models. So there are folks who are starting to think about this, but we’re still fairly early days

in terms of being able to stay with certainty to folks. Oh yeah, you don’t need to go get a college degree. I don’t think we’re quite there yet. Our friend Ryan Craig is in his 2018 book, I Knew You, had a sort of a radical postulate

that unless you can get a free or subsidized education at a selective university, you really ought to think about a hard sprint to a good first job. As an entry point on to an earn and learn ladder. What’s wrong with that advice?

I don’t think there’s anything wrong necessarily. What he’s pointing out is how critical that first job is. I think when people are holding up a college degree and saying, your first job doesn’t matter, what a college degree does is prepare you for a world of work

and being able to pivot endlessly. I think that’s what he’s sort of railing against. And especially when you think about the kinds of rates of underemployment for newly minted college grads, there are really high underemployment rates.

And that means just that people who have got a bachelor’s degree are getting jobs that don’t actually require a bachelor’s degree. So was it worth it? And the challenge is when you start off your career

underemployed, that challenge persists for a long period of time. It’s not just like a one year period that you can be underemployed. It often persists for five or 10 years.

And so when you’re doing that, you’re losing out on all the different kinds of professional networks you could be building, the social capital you could be building, and then the financial, just sort of wealth generation

that you could be engaging in. Like you’re earning on average about $10,000 less per year. So that first job is critical. And what learners need to understand

is how much their majors play a role in that first job. But I think the kinds of last mile providers that Ryan is pointing to are the groups that are saying, we know that for those folks who are deeply risk averse, who need a well-paying job to sustain a family, say,

this is a really good pathway because it’s connected directly to an employer. And they can say that this is a pipeline to a good job. And that’s really valuable for some learners who cannot just sort of put their hopes in a four year degree

and just kind of pray that maybe they will get a good job on the other end. That’s where we’re seeing this kind of tension now. Those are really great insights, Michelle. I appreciate the idea of,

it matters where you grab onto the economic ladder that if you come out of school with a $100,000 job compared to coming out of a school and needing to find a $30,000 job, that disadvantage will stick with you for a long time.

So yes, considering earn and learn ladders, but being really thoughtful about the pathway and those starting salaries and then the advancement opportunities that exists within those pathways.

Michelle, you have spent a decade now in a series of what Reed Hoffman would call a tour of duty, where you go somewhere for three years and you create a center, you create a capability, you do some important work, you write a book,

and then you move on. Do you think more Gen Z learners are gonna have those kinds of careers and do these tours of duty? So I think part of the tours of duty

that I’ve been engaged in, I think are connected to innovation cycles. It tends to take about three years to launch and build something that can gain traction. And then for me, it’s time to build again.

In terms of the longevity of staying in a specific company, I don’t think it necessarily, I think when we used to have all those headlines about millennials changing jobs seven times by the time they were in their mid-20s,

that was kind of a captivating headline for us. I don’t think necessarily that has to be, that’s not an ideal. I think what we’re seeing is that employers are really struggling to build new skills

in their incumbent workforce. Over the last 30 years at least, we have been consistently retreating from training our workforce. And this is really costly to companies and employers

and it’s not sustainable. So I think there’s real loyalty to be built within a workforce where you don’t necessarily have to, as an employer, go in with the mindset that, oh, these people are just gonna leave me in a year or two,

that shouldn’t be our default way of thinking about things. It’s how do we build trust, how do we build loyalty? How do we help them understand the trajectories that exist within our workforce? Because there’s very little transparency

about how you navigate and make your way up the chain. And I think that when you see some of the folks leaving and feeling like, well, I have no more way to climb here, it’s because there hasn’t been that ability to understand, how do I navigate this company?

How do I navigate to something better? Michelle, we’ve seen a big tech move into the learning and training space, they’ve become quite active in training their own workforce. Amazon recently announced the $700 million commitment

to train its workforce. They didn’t mention a university in that press release. We’ve seen Google become more active, Microsoft, the big Indian tech giant Infosys has become quite active in America and has been creating training centers

around America where they’ve started to hire even community college graduates and then put them into their own tech and team finishing schools. Can we count on big tech solving this training problem

or do we need a public response to it? I guess in short, what are the business models for long life learning going to be? So, I mean, it is heartening to see some of these major employers start to figure out,

okay, we do need to figure out a way to upskill our employees. That’s the best recruiting policy, which we shouldn’t always be recruiting externally, but instead looking at who is in, what kind of talent do we actually have access to right now

and how can we mold them into the goals, the people who can fill the goals that we’re seeking to fill in the future. The only problem with some of these upskilling initiatives is that they are not actually figuring out

how to carve out this really important piece of solving for time. They’re talking about building skills, but the implicit piece there is that they expect people to do this on top of everything else going on in their lives,

on top of their work responsibilities, on top of their family responsibilities and whatever kinds of other caregiving things they have going on in their lives. There’s no real delineation of how employers

are gonna carve out time in the workday, in the flow of the workday to build those skills for their workers, right? And that’s really problematic because already all the risk and all the burden of retooling for the future

is on the individual. And so there needs to be much more of that sharing of that onus by both the learning providers in terms of sharing risk, in terms of financing these learning opportunities and for employers

to actually carve out hours in the day to build new skills. I think I’m always kind of struck by this data that Peter Capelli over at the Wharton School shares where basically like in 1979, we used to train our workers at least two and a half weeks

per year with new skills. And now basically, by 1995, that number went down to 11 hours per year. And that wasn’t about building new skills, it was about compliance training,

sexual harassment training or risk mitigation. It wasn’t about training them for the jobs that might come next. And so as exciting as some of these $100 million initiatives are,

what an entrepreneur like David Blake, who’s starting this group called Learn In, is saying is they haven’t actually solved for this first order constraint of just time. It’s this idea of time poverty.

People are time poor. They don’t have, even as much as they would love to advance and pursue more education, there’s no way to fit it in. Michelle, I know you spend time at Strada

thinking about the question of navigation. I wonder how you think we solved this problem. Should people just rely on their HR department to tell them what to learn? Should they look to their alumni association

for advice on what to learn, given how rapidly the world is changing? What advice do people need to make good decisions about what to learn next? Yeah, it’s a really good question.

And one of the things that I like to point to, but it’s not a silver bullet, but it’s interesting. It’s exciting because it’s like these digital breadcrumbs we can latch onto is this access to real time labor market information.

So now with the big data that we have with hundreds of millions of job postings every single day and the way that we all present ourselves through social profiles and resume data, there’s actually amazing ways to marry all of that information

to, for the jobseeker, surface the kinds of skills that maybe we didn’t even know we had, but also for us to be able to tell in our specific region of this state that we live in, here are actually the emerging skills

that we need to think about. And again, these data, especially the job postings data, are not perfect data, but they’re a whole lot better than the stuff coming out of our Bureau of Labor Statistics rear facing sometimes as old as 10 years.

And so when we’re able to kind of refresh that data every couple of weeks, you can actually see, in Indianapolis or in Columbus or in DC, if you’re looking for a cybersecurity specialist, it looks very different in terms of the kinds

of specialized skills you need to bring to the table. If you’re even just trying to figure out what kind of production role I wanna go into in manufacturing in LA versus San Francisco, those skill shapes look very different

in just being able to drive six hours between those two cities, right? Like it actually matters the kinds of skills you bring to the table. So that to me is exciting is to sort of access

these breadcrumbs that are starting to emerge. And they’re also getting better over time. We’re getting a little bit clearer about the kinds of skills that we need to think about. Michelle, if the task is not only about getting a job,

but sometimes making a job with an entrepreneurial mindset, whether you’re helping to launch a new initiative inside an organization like you’ve done several times or standing up a new organization, that suggests that everybody needs to learn

both deeply in their field, but also broadly so that they can spot opportunities. So it feels like a combination of really focused study in your field, paying attention to that labor market data that you described, but also enough breadth

to be able to see opportunity. Yeah. Is that fair? Yeah, it’s that sort of concept from the 90s of the T-shaped learner, right? Where you have to have that kind of broad-based

generalist knowledge, but then you also have to have a little bit of vertical technical expertise. And especially as we think about the future of work, and I know you’re interested in questions of artificial intelligence, right?

As we think about the growing role of artificial intelligence that, you know, in everything that we touch and do, we as citizens, if we wanna be civically engaged, we actually have to be smart enough to understand what it is that we’re dealing with

when we’re talking about artificial intelligence. Right now, everything is kind of really hard to understand, and it’s in a black box, and actually most companies don’t even feel like they can 100% trust the AI that they use, you know, in their work.

We need to actually know enough to be dangerous, right? And when it comes to artificial intelligence, we need to have a little bit of that technical expertise so that we know when to intervene at the right time to question the data, right?

We need to be able to say, it’s like the Amazon execs did as they tried to use AI to be a new sort of human resources tool, suddenly they realized, why are all our applicants white? And why are there so many people named Jared, right? Like it’s because it was being trained on flawed data, right?

And they had the capacity to sort of question and intervene, and we really need to be able to do that with the things, because it’s infiltrating everything that we do, even prison sentencing, right? These really impactful things in our lives,

we need to be able to intervene at the right times. You know, Michelle, I was reading my clips this morning. I, since Google killed their RSS feed, I now have set up a number of search terms and get clips on those every morning.

I imagine that clips like that are kind of a very early precursor to the sort of guidance spot that we soon will have, where we can train a smart application to help us learn what we think is most important for us to learn. Do you see AI helping to solve this guidance challenge

of making it easier for us to learn in the direction that we point to? Yeah, I think there’s real extremes when it comes to the kinds of AI we’re dealing with today. So on one of the most sort of positive sides of the spectrum,

you have AI being able to sort of, we’re able to coordinate with AI and say work with a resume builder, and we’re typing in something like barista. I used to be a barista,

and it’ll surface certain competencies that we didn’t even know we had, but when we see them articulated, we’re saying, oh yes, I actually do know how to do some budgeting, and I do know how to do this kind of customer service.

And so the AI is helping surface who we are so that we can better envision pathways forward for ourselves, which is great because we as humans are not great at imagining the kinds of work we may be able to do. So that’s exciting.

There’s another kind of AI that, as you think about that kind of RSS feed example, that’s really scary when we think about the kinds of human skills we need for the future. I was really struck by Lindsey Graham’s

sort of description of the Amy Coney Barrett confirmation is sort of saying no one is going to be persuaded. Like this isn’t about being persuaded, right? And this idea of being able to be persuaded and inhabit another point of view

is really critical to think about as we think about AI, because we’re really starting to live in our own filter bubbles. It’s something that Eli Perizer talked about in his TED Talk a long time ago. And so we’re only being exposed to ideas

that make us feel comfortable, right? And this is hugely problematic as we think about the kinds of skills in emotional intelligence we need to be able to display in the future to coordinate better with the robots.

We’re not going to be practicing those skills if we’re never exposed to those ideas and those challenges to our thinking in the first place. So that to me is what really worries me as we think about the role of AI there is,

as we look at the stuff coming into our feed, are we really getting that broad-based view of the world that we need in order to build up our human skills for the future? Michelle, are you optimistic about adaptive learning? Learning that adapts not only to level,

but maybe by experience type, so it can pick the right course for me or the right learning experience so that I can learn more faster? Is that an area of growth?

Yeah, I mean, I think like you, you’ve been exposed to every entrepreneur who touts that they have an adaptive learning technology. And as you kind of start to peer more closely into it, it’s really just kind of branching, right?

It’s sort of like, okay, you did this, so we’re going to do this. It’s maybe not as sophisticated as we would love it to be, but I think there are really interesting groups out there, actually close to where you live, out at the University of Washington,

you have folks like Zorin Poffovich working on N-Learn, right? And it’s this idea of taking these infinitely, you know, these challenges that we deal with and scaffolding the learning in kind of in new ways, where he knows that when you’re trying to solve

for this math problem, there’s 600 ways to answer that problem wrong, right? And he’s creating these different kinds of learning technologies to help learners there. That’s exciting, but I feel like we’re still

fairly early days. I do have hope for it, especially just having young kids right now going through a public school system. You see how challenging it is

when the material is not pitched to where they are, right? And they can’t actually, and they lose interest, they lose that sense of curiosity because you have to pitch it at that mid-range level in order to move everyone along at that same pace.

So I do have real hope for that in the future. Are there some more pedestrian ways that AI is gonna help things like scheduling if everybody is in these adaptive systems and learning at their own rates?

And if learners have their own schedule and professors have their own schedule, it feels like you’re gonna need AI just to build a master schedule and a staffing system. Is it gonna help in the sort of back office challenges

like that? Yeah, I mean, I think it already is not necessarily in the scheduling realm, but it is in the transcription realm or validation of people’s learning.

I think people are using machine learning to create different kinds of credential transcripts to say, oh yeah, this person actually can do this kind of work. So there is hope there. I think it would be great for different university systems

that are flooded by these challenges where they can’t admit or get people into the right classes so that they can actually graduate. There is hope there, but the challenge is right now, most, even if we have a really exciting innovation,

the challenge is that most of our traditional systems are connected to a very time-based system, right? And federal financial aid, the way it is given out, is based 100% in that time-based system. So it’s really difficult to kind of pull in that new innovation

and just kind of plug it into a university setting and hope that it works, right? It does often require almost a new model sometimes to prove it out. Will artificial intelligence,

does it have the potential to make hiring more equitable, the move to sort of skill-based hiring and when those systems are AI-supported, can that make hiring more equitable or are you worried about more inequity surfacing

in AI-driven systems? Yeah, I think there are data to support both sides right now. They’re right there. I think it really 100% depends on the kinds of data

that the AI is trained on. If you’re upholding a certain kind of person who looks like the people who have the jobs today, it’s gonna present a challenge for folks who are already excluded from the system.

So I think we would like to think that somehow leveraging AI will put everyone on the same playing field and put us all kind of competing based on skills. But the real nut to crack is actually figuring out

the right kinds of assessments to evaluate whether someone actually has the skills. Like we, as many pre-hire assessments as there are today out there, we actually haven’t had a lot of basic science done

on the kinds of human skills that employers are saying that they want. We always hear them talking about communication, collaboration, teamwork, system thinking, creativity, curiosity.

We don’t actually have great mechanisms to assess those skills. And so that to me is kind of the exciting next wave of work that I hope to see more of. And there are professors like David Deming over at Harvard

doing some of this work where they’re trying to get it. How do you evaluate these human skills? And I think that’s pretty critical to making our pipelines wider, like the funnel wider

and accepting a more diverse range of learners, especially folks who may not have a college degree. This is the way we can begin to do some of that work is actually get better at assessments. All right, two more quick questions.

Michelle, as a long life learner yourself, is there a learning hack that you can share with us? How do you keep getting smart on so many new topics? I write a lot. I probably what you do, right?

You’re reading all the time, but it’s only once I kind of pull these, three or four distinct ideas and pull them together on the page that things start to make sense to me.

So it’s just those blogs, the small blogs, even if they never get published, it’s just my way of making sense. And that’s what this book was. It’s my way of just making sense of the world.

I love it. No, it’s right to learn. I don’t know what I think about a topic until I try to write it down. All right, last question,

since you’re an expert on the topic, was Louise Glick a good choice for the Nobel Prize? I was so happy that Louise Glick, I’m such a poetry nerd. She was my favorite poet in college. Love that she won the Nobel Prize.

But the most hilarious thing is I was so excited about seeing her read when I was in college and I got a ticket and I was telling all my friends that I was gonna go hear her read. And I nearly fell asleep when I listened to her read.

She had just kind of this very monotone soft voice and I was so tired. I just, I wanted to fall asleep. But her poetry is by far still one of my most favorite. I appreciate that.

Everybody should get a copy of Long Life Learning, preparing for work that doesn’t exist yet. Michelle, it’s a great book. And for our listeners, Long Life Learning is great for workers, teachers,

education leaders, whether you’re in K-12 or higher education, if you’re an employer, if you’re a civic leader, there’s a lot in Long Life Learning for everybody. So Michelle, thanks for the book

and thanks for joining us today. Thanks so much, Tom, it means a lot, thank you. Thanks for being with us. A big thanks to Michelle for joining us on this week’s episode.

We greatly appreciate her commitment preparing working age adults for the jobs of today and tomorrow. For a conversation with a colleague of Michelle’s at Imaginable Futures, check out episode 285

with Amy Clement. We’ll put a link in the show notes for you. A key component of preparing for jobs that don’t exist yet is problem finding as well as problem solving. In the new book, Difference Making at the Heart of Learning

by Tom Van Der Arc and Emily Leavtag, the authors explore new learning priorities centered around making a difference and a framework based on the 25 most important issues of our time.

Lots and still are future generations with purpose. We’ve got a link in the show notes so you can learn more about the book and our Difference Making campaign. That’s it for today, listeners, but before you go,

don’t forget to rate and review the podcast. As always, thanks for tuning in. For the Getting Smart podcast, this is Jessica, signing off.