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Good afternoon and welcome to the City Club of Cleveland, where we are devoted to conversations of consequence that help democracy thrive.

It's Friday, October 16th, and I'm Andrea Lyons, board chair of the Deaconess Foundation.

I'm pleased to introduce today's forum, which is in partnership with the foundation in honor of the 6th annual Deborah Vesy Systems Change Champion Award.

Deborah Vesy, who is with us today, was a longtime president and CEO of the foundation.

She retired in 2020, and in honor of her leadership, this award is given annually to a highly impactful systems change or innovation workforce initiative.

Earlier today, Deaconess announced this year's primary award winner, Youth Opportunities Unlimited.

Where Newbridge and McGregor's Foundation's work were also recognized.

Please again help me congratulate them all.

There's no doubt that all workforce systems, and frankly all workers, will be impacted by one of the innovations which is on top of everyone's mind today.

Artificial intelligence.

But where is it going?

And how do educators, whether in schools, community colleges, or workforce organizations, build curriculum and programs which prepare their scholars?

It's with this in mind that today we welcome Dr.

Cameron Sublett.

Cameron is the Senior Director of Innovation and Incubation at the Foundation for California Community Colleges, where he leads efforts to design, test, and scale initiatives that expand educational access and improve outcomes and increase economic opportunity across California's community colleges.

He wrote a seminal article this year that he'll talk about today, about how career and technical learners should be prepared for an AI-driven workforce, a topic of much interest among all educators and workforce organizations.

Among his many degrees, Cameron has a PhD in education policy, leadership, and research methods from University of California, Santa Barbara.

A quick reminder for our livestream and radio audiences.

If you have a question during the Q&A portion of the forum, you can text it to 330-541-5794, and City Club staff will try to work it into the program.

Members and friends of the City Club of Cleveland, please join me in welcoming Dr.

Cameron Sublett.

That was very gracious of you.

That was very gracious.

Hello everyone, it's good to be here.

Thanks for the invitation.

Greetings from California, where we're sad about the Dodgers but rooting for the Guardians.

I just want to say, wow, I'm absolutely humbled and excited to be here with you all.

What a beautiful city.

This is my first time to Cleveland, and what a beautiful venue this is.

This is certainly my first time here.

Thank you, Kathy, and the Deaconess Foundation for this invitation.

Looking at all the luminaries on the wall outside there, I'm still convinced you have the wrong guy here on the stage.

I'm humbled to have this opportunity, but my work these days focuses on the intersection of AI and learning and opportunity in America.

And I strongly feel that needs to be all of our work moving forward.

So let's get into it.

What is career and technical education?

Career and technical education or CTE, refers to the career-oriented education pathways in the nation.

Many of you may know contemporary CTE as yesterday's vocational education.

Vocational education, or even occupational education, was the historical approach we took as a nation for preparing our young learners for specific occupations, often within agriculture, construction, and manufacturing industries.

I'm talking trades education, the dirty jobs.

Want to become a plumber?

Take the vocational education route.

Want to be a scientist?

That's academic.

Want to be a welder?

That's vocational education work.

Want to be a lawyer?

That's academic.

Importantly though, it didn't really function this way throughout history, with students choosing a career path and then going and finding an educational pathway.

There's actually a dark history of tracking in vocational education where students were steered away from academic college-oriented pathways and steered into menial vocational programs tied to low-opportunity occupations, not because of their aspirations, or their aptitudes, but because of their academic or demographic profile.

If you were poor, if you were Black or brown, or if you came from a certain zip code, the system had already decided what you were worth.

Vocational education, as it functioned in practice back in the day, didn't just reflect class structures in America, it reinforced them.

The good news is that vocational education has undergone a thorough rebrand, driven largely by great advocacy and policy, and the result is today's contemporary, rigorous, and relevant CTE.

Don't get me wrong, today's CTE pipelines can still be stratified.

First, access to high-quality CTE is uneven.

Studies show that CTE offerings vary widely from schools to schools, school, and students in better resource schools tend to get more of it.

Second, CTE pipelines mirror gender segregation in the workforce.

You're more likely to find males in the trades and STEM-based CTE pathways, and you're more likely to find females in the service-based pathways.

But it is also true that contemporary CTE is far more diverse than it used to be, not just in terms of which students are enrolling, but the programs themselves.

Advance CTE, one of the nation's largest CTE advocacy organizations, sets the blueprints that all states use to organize their CTE offerings, and they've identified 14 distinct career clusters for students today.

These clusters range from cybersecurity to health sciences, from advanced manufacturing to arts and communications.

Is there still tracking in CTE?

It's not entirely eliminated, but I don't see a strong empirical case for it either.

Why?

Well, first, again, there are many more CTE pathways today than ever before, and many of these pathways are attractive to a broader swath of learners.

Second, the academic versus vocational binary that I mentioned earlier, is far less prominent than it once was.

The vast majority of high school students today, in fact, take at least one CTE course in high school, even if they're off to a 4-year college program.

Third, studies, including my own, show that CTE programs boost academic and career outcomes.

CTE concentrators, for example, graduate at higher rates and enjoy employment and wage premiums relative to students in traditional academic pathways.

So not only are contemporary CTE programs more diverse, they're straight up more effective.

And that is great because CTE is awesome.

And I mean that.

I come from a long line of proud trades and technical workers.

My dad was a plumber.

My uncle was a plumber.

My great uncle, a mechanic.

My other great uncle, a mechanic.

My stepfather, an Army chemical specialist.

My mother and grandmother both worked in medical billing.

My other grandmother was a nursing assistant.

My grandfather, a Navy information systems technician.

My great-grandmother, a switchboard operator.

And my great-grandfather, a machinist.

Me, I was the deviant one who went off to college.

But being the first in your family to go to college is hard, especially when sitting, reading, and obedience are not in your nature.

Unsurprisingly, I got kicked out.

But a year after landing at a community college put me back on path, and I eventually got through.

But after college, I sprinted to work for my dad, building custom homes and later commercial self-storage units.

It was a great fit.

I loved the work and I was good at it.

The one problem is that I couldn't see eye to eye with my dad, who was my boss.

So I quit, and I left, and I decided to get the ultimate revenge and go to graduate school.

Even crazier is that I somehow ended up a professor, and I did okay at that job, if I'm honest, but it always felt like I was wearing like an ill-fitting suit.

I've always had a preference for job sites over conference rooms.

Taco trucks over faculty lounges, and power tools over computers.

I wasn't sure why academia was such a strange fit for me until one day I was talking to my dad about why he didn't go to college.

He said, I went to college.

I went for one day and dropped out.

But that's all it took for me to realize that my brain was in my hands.

Wow.

For such a big, burly, scary dude, it was pure poetry out of his mouth.

And it was also an eye-opener for me.

Things suddenly clicked into place.

Why I loved futzing with my dad's PVC and copper scraps as a kid, working on an avocado farm throughout college, then the job sites I landed on, residential framing, industrial fabrication.

This was all problem solving in the physical world.

It explained the ill-fitting suit of academia for me.

And it suddenly became obvious, even though I hated to admit it.

I was just like my dad.

My brain is in my hands.

And once I made that realization about myself, I made that realization about CTE.

That's what CTE is.

It's the education experience built for people whose brains are in their hands.

So I've since spent the better part of my career focused on improving this experience for learners just like my dad, my mom, my uncles, and my grandparents.

I love this stuff.

These are my people.

And it's personal, which brings us to artificial intelligence.

AI is certain to transform the future of work, but the nature and direction of that change is unclear no matter what you hear.

I've read the research, I've contributed to it, and I can tell you there's a lot of noise out there.

I turn to history for a bit of comforting signal where I can get it, and what does history teach us?

First, AI is not the first technological disruptor.

It's just the latest.

Second, here's what you need to know about the ways in which technology impacts work.

AI does not act on occupations directly.

It doesn't add jobs.

AI's not gonna take away jobs.

AI and other technologies impact occupations through the tasks that compose those jobs.

Take nurses, for example.

Nurses collect and chart patient data.

Nurses conduct patient assessments and perform medical procedures.

Nurses attend to patient comfort, and they console family members, and they work in teams within very high-stress environments.

The question for nurses is not, will AI take my job?

The question for nurses should be, can AI do the tasks that make up my job?

But it's not even that simple.

The relationship between AI and tasks is actually fascinatingly complicated, and I would encourage you to embrace that complexity.

If AI can perform a task, it can substitute the human skill needed to perform it, displacing the human nurse.

But AI can't perform every task, so some human nursing skills are still gonna be needed and in demand.

Then there's a third scenario where AI complements a task, thereby supercharging the nurse needed to perform it.

This doesn't displace the nurse, it makes the nurse more efficient.

Fourth, AI can introduce entirely new tasks, thereby creating demand for a novel nursing skill, redefining what it means to be a modern nurse.

Given that a typical occupation, think of your own occupation, is composed of myriad tasks that require myriad skills, skill sets, you can quickly see that the will AI take my job equation is in reality complicated calculus.

All right, Cameron, I get it, but don't you have some sort of idea of how AI is going to influence the world of work that learners are preparing for?

Unfortunately, again, I stay out of the betting markets on this one, but what can I tell you based on history?

Well, my read is that technology disruption after technology disruption has tended to favor workers with the ability to leverage those technologies, while at the same time targeting those who work in occupations composed largely of tasks that require routine physical and routine cognitive skill.

Look at bank tellers and ATMs, like those made by U-Bolt.

The routine tasks, deposits, withdrawals, balance checks, got automated.

But the tellers who survived, their task bundle, right, shifted toward relationship banking, financial advising, and problem solving.

The routine middle got hollowed out, and what was left required either higher-order skills or the kind of human judgment no machine could replicate.

That very pattern, repeated across industries and over decades, is what economists refer to as labor market polarization.

On the high end of the spectrum, workers with skills complemented and accelerated by technologies have seen increased employment and wages.

On the other end, workers with skill sets that cannot be substituted by technology have also seen increased employment, but they've also seen their wages stagnate or decline.

Meanwhile, the so-called middle skills segment of the labor market has seen decreased employment and decreased wages, because this segment includes a disproportionate share of jobs involving routine tasks amenable to tech substitution.

The conventional bet would be to hold that AI is simply going to accelerate this trend around polarization.

The only reason it wouldn't is that AI genuinely represents a new kind of technology, one that for the first time in history kind of bursts this technology can't replace what humans do bubble.

LLM chatbots, as you all know, and generative AI tools in general are very human-like.

They speak, they write, they calculate, and they reason like humans.

They even mimic empathy and other human-like emotions.

And they're just getting started.

History might not actually provide any signal at all We've sort of entered into this, quote, era of AI uncertainty, to quote the great David Autor at MIT.

What comes next?

No one knows.

I know for a fact though, that while LLMs and chatbots are the now, they're certainly not the next.

What we're seeing is just the first wave in a coming set of big waves.

AI agents are increasingly a part of our daily workflows and communication channels.

Robotics are just around the corner.

Digital AI will soon be in the rearview mirror for all of us.

Physical AI is just down the road.

And further out, quantum computing, which is gonna amplify the capabilities of AI in ways we're only beginning to understand.

In his recent essay on AI, Bill Gates, argued that we're entering one of the most turbulent times in all of human history.

So what does this all mean for CTE?

Well, I asked that very question in a blog post back in 2023.

In that post, I worried that AI and what we've learned about the propensity of technology to decimate the middle skills workforce and stagnate or suppress wages among low-skilled workers has the potential to revert CTE back into that malign tracking mechanism, a situation where CTE's dark history becomes its dark future.

It's easy to see how that could happen, actually.

It would just take 4 things.

One, it would require AI to accelerate labor market polarization.

Second, it would require CTE and career education programs to overemphasize the development of technical skill at the expense of social and transferable skill.

3, it would take an uneven, inequitable rollout of AI into CTE classrooms.

4th, it would take an uneven and inequitable rollout of AI into school systems, similar to the rollout of online learning technologies, where the more resource schools and districts accelerated adoption faster and earlier and had access to better, more powerful tools quicker than under-resourced schools.

What might this look like in real life?

Picture a student in an under-resourced district enrolled in a business management and administration pathway.

That's one of CTE's most popular.

The middle skill occupations his pathway was designed to feed into are already eroding.

Data entry, records management, routine reporting.

AI handles these tasks well.

Meanwhile, his well-intentioned instructor focuses heavily on the technical acumen of his students.

Perhaps as a way of compensating for the compressing labor market his students are entering.

So he doubles down on the technical skills, thinking those will get his students ahead.

So far, that's condition one and condition two.

Meanwhile, down the hall, his classmates in a cybersecurity program are training on state-of-the-art AI-powered threat detection platforms.

His program?

Well, he's allowed to use ChatGPT.

If he wants, but it's optional.

And chat is the only tool he's ever been exposed to.

That's condition 3.

And condition 4, well, his district was 18 months behind on procurement while his neighboring district was already on their second generation of AI-integrated platforms.

What's the result?

He graduates credentialed in competencies that are being automated without the transferable skills to pivot or the AI mastery to adapt.

The student across town, same state, same CTE system, walks in prepared to work alongside AI, not be replaced by it.

Same ambition, same effort, different zip code.

Yeah, Cameron, I don't know.

They say AI is set to wipe out the white-collar jobs, not the knowledge worker, or yeah, and the knowledge worker, not the plumbers and the trades workers, right?

The CTE kids, they should be fine.

That very well could be, but I'm not entirely convinced.

In fact, you're right.

Research has shown that knowledge workers are more exposed to AI capabilities, right?

But it's also true that that very same exposure puts them in a position to leverage AI to greater impact.

Remember, AI is just not gonna substitute human labor.

It's also gonna complement it.

And it can accelerate the workers in those roles in the same way that calculators and spreadsheets complemented and accelerated the work of CPAs.

And on plumbers and trades workers, sure, plumbers look safe over a 10-year horizon.

But plumbers are safe right now because there's not enough plumbers.

Nobody's entering the trade anymore.

My dad will be the first one to tell you that.

The crisis facing plumbers isn't AI and robotics, it's demographics.

But AI still has the potential to materially shift the work plumbers do and who benefits from it.

Take AI-monitored plumbing and HVAC systems.

These exist.

If leak detection systems convert to a subscription-based service owned by platforms, whose software then dispatches the plumber to execute a ticket.

Plumbers still have a job, but now they're a gig worker for an algorithm.

So are plumbers safe?

Or are they just safe from unemployment while losing everything else in the process?

Autonomy, upward mobility, ownership of their trade.

So where does this leave us?

Importantly, I've just described a scenario that I don't believe in.

I refer to this in my report as the pessimist case for AI.

But I personally believe the future can and will be much brighter.

There's an optimist side to this story, one in which CTE learners are actually better positioned to navigate this era of AI uncertainty.

Why?

One, we've got wind in our sails.

As I mentioned earlier, contemporary CTE didn't get here to this moment by accident.

Relentless advocacy and strong policy solutions— bipartisan, by the way— have made it so.

Federal policy, for example, now requires all CTE programs to engage with local industry and employers, which means the infrastructure for integrating industry-grade AI tools already exists.

Also, CTE is home to work-based learning, internships, apprenticeships.

These are the very mechanisms through which students get their hands-on experience with real tools and real workplaces.

Funding set-asides have also helped to drive the diversification of CTE pipelines to limit the potential downstream impacts of stratification.

And CTE is one of the rare policy unicorns we have in our country that enjoys tremendous bipartisan support.

Parents also support CTE in increasing numbers, and there's a growing wave of young learners hungry to enter the trades.

These are the so-called tool belt generation.

So how can our CTE systems do right by these CTE learners?

Well, my thinking here has been shaped by the work of Ethan Mollick at the University of Pennsylvania.

In his book, Co-Intelligence: Living and Working with AI, which I highly recommend all of us read, Mollick argues that sure, there's a lot to be concerned about, But there's also a lot of upside, especially in the context of education and learning.

Consequently, Mollick argues for 4 things in his book.

One, always invite AI to the table.

Use it, get to know it.

As AI diffuses across work, the ones who know how to work with it are best positioned to unlock it.

2, be the human in the loop.

Incorporate human judgment and oversight I don't know if you've noticed, but LLMs prioritize user happiness over accuracy.

Mollick compares LLMs to eminently qualified interns prone to lying.

3, treat it as a person.

Give it a personality, a perspective, a specific role to play.

Mollick argues that to fully leverage AI, we have to commit the cardinal sin of anthropomorphizing it.

You could even give it a name.

4, assume the version you're working with is the worst one you're ever gonna use.

Again, this is the first wave in a coming set of waves.

The AI of today will not be the AI of tomorrow.

Tomorrow's AI will be much, much better.

But Mollicks model isn't necessarily tailored for CT learners.

That's my argument.

It lacks a grounding in hands-on, safety-critical, occupation-specific work.

For CTE educators inspired by Malek's vision, as I was, but curious how that vision applies to their advanced manufacturing, hospitality, or science classroom, I built the Applied Co-Intelligence model, or the ACI.

Importantly, my intention with the ACI is not to advance dogma.

It's not the only way how to do it, but the model is simple and applicable.

Any CTE instructor from any CTE cluster can run with the ACI.

The goal is not to tell them what to do.

They know what to do, but it's to tell them where to start.

Here's how it works.

The ACI is built around 3 overlapping spheres.

Think of a Venn diagram.

The spheres are technical skill, transferable skill, and AI mastery.

My argument is that students need to have all 3.

Critically important, however, is that these 3 spheres exist within a larger sphere representing a specific occupational context.

So what are the spheres?

First, there's the sphere of technical skills.

It's the bread and butter of CTE programs.

Technical skills remain essential in the age of AI.

You can't AI your way through electrical wiring or patient care.

You can't use AI to install a 4-inch drain line or to sweat your copper.

Not yet anyway.

Technical skills are arguably more important in the age of AI because only those with a firm technical knowledge base are able to audit and improve the AI.

You are in fact a lousy human in the loop if you're not looped in on the technical know-how.

Second is the sphere of transferable skills.

These are the human skills that generative AI can't fully replicate, and we hope never does, or I hope never does.

Mollick, along with Jamie Marisotis at Lumina Foundation and others, believe AI has the potential to amplify the role of the, of the importance of skills like critical thinking, communication, resilience, problem solving, ethical reasoning, leadership, entrepreneurship.

And many believe that's only going to become more true In his recent manifesto, Mark Zuckerberg claimed invention, not automation, will be the greatest contribution of superintelligence.

I don't agree with Mark Zuckerberg on anything.

But I think I actually agree with him on this point.

But invention, it needs to be pointed out, only works when you have creativity, problem-solving, and entrepreneurship at your disposal.

His future only works if we equip students with transferable skills to complement their technical training.

The third sphere is AI mastery.

What's AI mastery?

Well, at a high level, fostering AI mastery isn't about teaching AI on the side.

I'm pretty firm on that position.

CTE students shouldn't be learning about AI in a separate AI class or program.

The right approach is embedding AI skill development inside the real work.

AI tools vary across occupations and industries.

ChatGPT is not this tool that your CTE learners are going to need.

Students may not even need generative AI at all.

In my interviews with industry experts, logistics, agriculture, traditional AI dominates, like machine learning and predictive analytics.

AI mastery means moving from generic off-the-shelf AI chatbots to task-specific AI applications aligned with occupations and industries.

The progression should be from, I know AI exists, to, I can use this inside my field.

CTE students develop applied co-intelligence because their instructors have intentionally designed their courses and assignments around this sphere concept that I've advanced.

Let me show you what it looks like in practice.

Meet Maya, a community college student enrolled in a healthcare program preparing to become a certified nursing assistant like my grandma.

Maya's program is built on the ACI.

Her instructor designed the syllabus not only to align with the ACI framework, but in partnership with the local hospital network and long-term care facilities just down the road who are going to eventually hire Maya.

Her technical skills come first.

Maya learns to measure vital signs, perform safe patient transfers, apply infection protocols, and assist with activities of daily living.

These competencies, importantly, map directly onto the physical care skills domain of the National Nurse Aide Assessment Program.

That's the certification exam that she's going to need to pass to join her state's nurse aide registry and get hired.

But Maya's program doesn't stop at the technical.

In her simulation lab, Maya's instructor purposely programs her LLM-enabled sim patient to present with messy, conflicting symptoms.

Maya has to communicate her assessment clearly to a supervising nurse played by one of her classmates, collaborate with a peer healthcare team under pressure, and make and defend judgment calls when there isn't a clean answer.

That's transferable skill development— critical thinking, communication, teamwork, executive function embedded in a clinical context.

While building her technical and her transferable skills, Maya also develops AI mastery rather than a generic AI literacy.

Maya's instructor worked with the local healthcare employers that helped shape the syllabus to identify the specific AI tools they're actually using on the floor.

And critically, because the department couldn't afford enterprise licenses for these platforms, the employers provided access to every student in the CNA program.

So Maya isn't learning AI on a generic chatbot.

She's assigned to use the same AI-powered tools her future employer uses.

Also, Maya's instructor teaches her how to effectively anthropomorphize her LLMs and her agents.

So just as Mollick recommends, she's giving these agents a persona and a personality.

Her training in prompt engineering and contextualization has taught her to give her agents a role and a perspective.

For example, to serve as a veteran charge nurse reviewing her intake notes.

And asking them to push back.

Notice that in this scenario I just described, Maya didn't take an AI class.

Maya didn't take a transferable skills class.

She enrolled in a CNA program where all 3 spheres were developed together inside the sphere of an occupational context.

That's applied co-intelligence.

And an exciting spillover benefit of the ACI isn't just that it prepares Maya.

For her first job.

It's that it prepares her for whatever comes next, and who knows whatever is coming next.

In a landmark study, Eric Hanushek and his colleagues at Stanford found that while students leaving technical education programs enjoyed immediate employment and wage premiums, those advantages faded over time, potentially because their training was narrowly technical, tightly bound to a specific bundle of tasks that technology steadily eroded.

Leaving them exposed in an increasingly volatile, polarized labor market.

The ACI is designed to solve that problem, among others.

Even if AI were to completely substitute every task in Maya's nursing pathway, every single one, she doesn't languish.

She walks out with technical skills that give her credibility, transferable skills that give her humanity, and AI mastery that gives her resilience.

Her displacement is temporary because she didn't just learn a job, she learned how to learn the next one.

Maya's experience is the ideal, though, and there's a reality in its way.

And what is that reality?

Well, the reality is there's a tremendous amount of work to be done to get from now to Maya.

Let's start with the employers.

The very partners the ACI depends on.

Right now, they're out of sync with CTE providers.

A landmark study from the Harvard Business School found that 80% of educators agreed to the statement, my college is producing work-ready graduates that employers need.

Yet, only 62% of employers agreed with that statement.

At the same time, over half, just half, business leaders surveyed couldn't even assert they knew which skills they were hiring for.

Then there are the CTE providers.

Our systems of education do not move fast.

The more critical voices in the room would say they don't move at all.

I don't think that's fair, but I do think systems prefer stasis over innovation, tradition over turbulence.

But let's be honest, Stasis isn't an option anymore.

Banning AI from classrooms isn't an option either.

It just isn't.

As Ethan Mollick pointed out, even if all future AI development were to stop now, if policymakers around the world stood up and placed a moratorium on all AI development, the AI we already have amongst us is comprehensively transformative.

Most educators I've spoken to know this, and they're not entirely resistant.

Mostly, they're just unsupported.

They need capacity, they need resources, they need space to learn and experiment, and time to develop a comfort with tools that didn't exist when they got into their profession in the first place.

In our survey of all 37 Perkins coordinators across the Tennessee Community and Technical College System, 85% said they believe AI will significantly change their fields, but over 90% said they lacked the support, guidance, and training to prepare.

Most educators and school leaders know they need to do something, and many systems, school, and districts have developed AI policies and frameworks, but they're largely punitive.

Focusing on what not to do versus on what to do and importantly how to do it.

Meanwhile, a Lumina Gallup survey of nearly 4,000 college students found that 57% are already using AI weekly or daily in their coursework, and they're not using it to cheat.

86% said they use AI to better understand complex course material.

65% said that it helps them prepare for their future career.

Students are treating AI the way the ACI says they should, as a learning tool, a productivity tool, a career readiness tool.

But they're doing it on their own without any connection to their careers.

Why?

Because more than half of those same students said their school either discourages AI use or prohibits it altogether.

Meanwhile, 47% have thought seriously about switching their majors because of AI.

16% already had.

And last, what about policymakers?

Policymakers at every level of government have a tremendous job and responsibility here.

Yes, our systems of education do need to move faster and be more nimble.

But it's also true that our society and economy could benefit from much more stability.

Bill Gates argued that the choices we make now are critical and that we need to move fast.

We need to develop plans, policies, and frameworks.

But he argued we don't even have a plan to make a plan.

I fully agree.

Case in point, Brian— Brad Smith at Microsoft recently pointed out that washing machines and milk are more regulated in America than AI.

Policy guidance doesn't have to hinder R&D.

I'm sorry, that's a false binary.

Thoughtful bipartisan policy could actually drive progress.

We've seen it with other spheres of our society.

Good policy gave us the GI Bill.

Good policy gave us good CTE.

So again, we have our work cut out, but I think we do have an opportunity to work smarter rather than harder here.

Let me explain by taking us back in time, and I'm almost done.

Remember the early days of online learning?

I don't know how many of you were in the college classroom at that moment.

But I was, and I don't know if you remember MOOC mania.

What a messy period in higher education that was, right?

People were terrified.

Faculty thought they'd be replaced, and they drew lines in the sand as a result.

Some faculty avoided it, some leaned in.

Meanwhile, accreditors didn't know how to regulate it.

Administrators were largely hands-off, not knowing whether to promote it or suppress it.

Depends on which side the union was on.

Systems, districts, institutions spent differently on infrastructure and resources.

Nothing was standardized, even within the same campus or even the same department.

The distance between a high and low quality online learning course was a country mile.

Sound familiar?

It's not perfect, but today's online learning is much better than yesterday's online learning.

We've come a long way, but it took way too long.

And in the meantime, the uneven rollout of the technologies exacerbated the very inequalities it did have the potential to close.

Well-resourced institutions moved first and faster.

Under-resourced institutions got left behind.

By the time we had quality standards, accreditation frameworks, and real infrastructure, the gap had already widened.

And then COVID hit.

So if we could go back to the beginning of the online learning era, knowing what we know now, what would we do?

First, we would demystify it and avoid fearmongering.

The early years of online learning were plagued by moral panic.

It was gonna destroy education.

It was gonna devalue degrees.

It was going to eliminate the need for teachers.

None of that happened.

What happened is that we wasted years debating whether online learning was legitimate instead of figuring out ways to legitimize it.

We need to focus on the upside of AI as a teaching and learning catalyst, is the upshot.

Second, we would demand and define quality early.

In the early days of online learning, anything with a login screen counted as online education.

It took us years to develop standards, frameworks, and accreditation benchmarks.

With AI, we need to get ahead of that curve.

What does quality AI integration look like in the CTE classroom?

The ACI is one answer, but it's not the best.

We need more.

Third, we would invest in infrastructure and make sure every student can reach it.

Today's online learning is way better than it used to be, largely because the technology also got better and more diffused.

More affordable and also more accessible.

The learning management systems got better, the bandwidth got better, the hardware got better.

AI needs the same investment.

Our classrooms need compute, the platforms and the tools that are transforming the industries students are entering.

And then fourth, we would pick up the phone before we built anything.

One of the great mistakes of the online learning saga is that faculty, institutions, entire states were wrestling with the exact same challenge while building their own solutions from scratch on different timelines without ever talking to one another.

We ended up with 1,000 versions of the same wheel.

With AI, we can't afford that sort of inefficiency.

Those figuring this out right now need to start sharing what's working for you across departments, across institutions, across state lines.

Let's crowdsource solutions to accelerate transformation.

Every one of these lessons I just laid out for online learning applies to AI.

And if you look closely, they map directly onto the barriers I raised earlier.

Importantly, none of it replaces the winds already in our sails.

We need to double down on the policies already in place, like those that have helped build stronger bridges between employers and providers, diversify CTE pipelines, and put more learners in work-based learning and apprenticeship opportunities.

These.

I'll wrap up now, but before I do, in this speech I've compared the current iteration of generative AI as the first wave in a coming set of waves.

I like that analogy.

I think it's apt, not only because it brings perspective but also because it motivates action.

Also, I love surfing, and if you've ever surfed on a big day You know that if a big set is on the horizon, you have very little time to decide on 3 choices.

Paddle in, stay put, or paddle out.

But experience will tell you there's really only one choice.

If out of fear you paddle in towards the shore, you swim against the sucking current and you're gonna get caught by the turbulent whitewater.

If out of paralysis you stay put, you're gonna get decimated in the impact zone.

You're gonna take a big wave to the forehead.

Paddling out may be terrifying, but it's gonna get you over the wave to safety before it breaks.

Critically though, Paddling out doesn't mean wholesale abandonment to the sea.

By paddling out, you actually put yourself in a position to catch the next wave in that set.

So you're not just surviving, you're catching waves and you're having a good time.

We paddled in on online learning.

We swam against the current, got caught in the whitewater, and spent decades getting pummeled in the impact zone before we figured it out.

But think about what might have been different if we had paddled out early.

How might COVID and the online pivot have been different?

How many students might we not have lost?

Whatever you may feel about AI, and I have feelings about AI, it's here.

We have a lot of work to do, but we begin by paddling out, not only to survive, but to put ourselves and our students in a position to catch waves.

The ACI shows what this can look like, a contemporary, rigorous, and relevant CTE for the AI era, built for learners whose brains are in their hands.

Thank you.

We are about to begin the audience Q&A.

For those just tuning in via our livestream or radio audience, I'm Cynthia Connolly, Senior Director of Programming here at the City Club of Cleveland, and we're joined by Dr.

Cameron Sublett, Senior Director of Innovation and Incubation at Foundation for California Community Colleges.

He is discussing how those in CTE, or Career and Technical Education, like schools, community colleges, and workforce orgs can prepare talent in the age of AI.

We welcome questions from everyone in the room, City Club members, guests, and those joining via our livestream at cityclub.org or our live radio broadcast at 89.7 WKSU Ideastream Public Media.

If you'd like to text a question for our speaker, please text it to 330-541-5794, and City Club staff will try to work it into the program.

Can we have our first question, please?

Sure.

Hi, Ethan Karp, CEO of Magnet.

We help small and medium manufacturers, both adopt technologies like this and people get in.

So last week we did a panel with manufacturers talking about how they're using AI inside their plants.

And they also talked about the things they were sort of looking for in the people that would come into them.

But it was very nebulous how they described that.

So how, when you are successful at getting these skills into the hands of students, would you say that employers in particular should be able to measure that as they're hiring and judge it once they're inside their company of how effective that AI education was?

That is a fantastic question.

Can I punt on that one?

Do I have— Kathy, do I have to answer every question?

Okay, so for me, the low-hanging fruit here on this one is, as your question was, how do you assess whether or not they are ready for— is to take stock of what are the specific AI tools and applications within your industry and measure that against whether or not the tools have, the students have that in their tool inventory.

I think that's the argument I keep harping on.

I did a bunch of interviews with folks across all industries for a series of briefs I did, and I came across some AI tools I had never heard of, and I would encourage you to do a little bit of research too.

There's actually a universe of AI tools out there that do things other than help you make your dinner for that night, or whatever you use your chatbot for, I learned about AI tools that increase dairy production among farmers in Canada.

I learned about AI tools that help hospitality companies serve their customers from start to finish.

So I think that's where I would begin is by determining what are the tools in the trade that are AI-enabled and making sure that the tools coming, the students coming in the door are familiar with those tools.

And I would encourage you, to make sure that the community colleges in a proximal area are aware of those tools and that they have every resource at their disposal to make sure that they're used in the classroom.

So I don't think that answered your question at all, but okay.

I could not agree more in the sense that the durable human competencies and critical thinking, collaboration, communication are so important for the next step of our learners.

I know that robotics obviously has a long way to go, but I'm curious on the CTE and more so on the skilled trades side, As the potential for robotics to replace humans through humanoid robots comes into play 20, 10, 30, 50 years down the road, how do you see that impacting the skilled trades piece of this?

Yes, I love that question.

I've been thinking on that one too because I get a lot of pushback.

I mentioned it in the speech, like, hey Cameron, but the CTE kids are fine, right?

Like, no one's going— no AI is going into the crawl space to fix your furnace.

But the more I sit with that, the more I'm less convinced that's the case, actually.

I think in Bill Gates' recent piece, he pegged it at 10 years that we'll start seeing robots able to complement physical work that we might associate or think is immune to AI substitution or complementarity.

I don't know if it's 10 years.

I don't wanna put a time on it.

If you think robots cannot do the sorts of human tasks, you know, do you think that robots are not able to perform human tasks?

I would just go online and see the robots that do exist that are almost kind of quotidian and regular in Asia.

They're quite advanced and quite able to perform a number of really, really complex tasks.

But I would just— when people say, no, Cameron, AI is not gonna take away the job of the plumber, I'm increasingly asking people, you're thinking too small about ways in which homes and buildings are built, right?

Your assumption that plumbers are safe relies on this assumption that we continue building homes in the traditional way that we have built homes, where the lines are within the drywall, right, and they are sweated by copper, but that's changing.

We already now have the ability to 3D print homes.

That's happening.

What's stopping us from the ability to 3D print a home, and then make sure all of the water lines, all of the HVAC systems are exposed on the outside, so that you could actually pull up like an Amazon truck, deploy a robot who then goes and is GPS-enabled to then access those exposed lines, and then solve the issue, right?

That assumption that trades work can't be replaced by robots is false, in my opinion.

If we're thinking too small and we're too attached to the old ways of building homes, I think that's going to change dramatically.

We're going to take a text question that we received.

So this question is, workforce training looks very different region to region.

How do you see AI impacting training here in the Midwest And is this an opportunity for the Rust Belt to spring ahead of the curve in manufacturing and other sectors?

That is a fantastic question.

Let me stall.

You know, I, I will not speak on behalf of the Midwest.

I do know that, you know, certainly workforce development is regionally focused, and what I would tell anybody Midwest or the West where I'm at, is that certainly sort of monolithic statements about the ACI and whatnot are valuable, but do need to be contextualized to a local economy and workforce.

So the answer to that question is taking stock of what is the economic drivers, the economic opportunities for a region.

So I would encourage the Midwest to chart out what are the main economic drivers at the moment, where are those likely to shift, And then the AI strategy follows downstream from that.

Germany in particular has always had very admirable trades education programs, and I think they do.

I mean, I think a lot of people think that they do a better job with apprenticeships and putting people into good roles earlier than maybe we do in this country.

I was just curious if you've seen— is there any sort of comparative perspective you like in terms of looking at other countries who do a particularly good job with integrating AI into how they're thinking about the workplaces of the future?

I have not spent a tremendous amount of time doing comparative research between us and Europe.

I think, like you said, yeah, we all hold Europe in venerable status for being ahead of us.

Like classic Americans, we think that we're the only ones struggling with this problem or this challenge, but of course that's not true.

The solutions to some of these problems are certainly available overseas in Europe, and I think there are some models we can be looking at.

But I don't know if, you know, all the solutions are there either.

I think AI doesn't have any respect for international borders, and I feel like this is in many respects a shared exigency we all have, and I don't think they have the solutions to AI necessarily, but I think they have solutions that can help us with the moment, and I think the really important one is an established work-based learning apprenticeship model, which we're just now really starting to be serious about in this country, but I think, yeah, that was my answer to the question.

Yeah.

All right.

Thank you once again to Dr.

Cameron Sublett for joining us at the City Club today.

Forums like this one are made possible thanks to generous support from individuals like you.

You can learn more about how to become a member of the City Club and how to support student engagement at cityclub.org/passthemike.

Today's forum is in partnership with the Deaconess Foundation as part of its 6th annual Deborah Vesy Systems Change Champion Award, which was presented to Youth Opportunities Unlimited, with Newbridge and McGregor Foundation's work also recognized earlier this morning.

Congratulations to each of these organizations.

Coming up next, Friday, October 23rd, at the City Club, we will be discussing Ohio's current and future energy needs.

We will hear from energy producers and distributors and industries whose growth depends on access to energy.

You can learn more about this forum and others at cityclub.org.

Thank you again to Dr.

Sublett and to our members and friends of the City Club.

I'm Cynthia Connolly.

This forum is now adjourned.

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