Episode Transcript
[00:00:00] Speaker A: Taylor Stockton, thank you so much for joining me today from the Department of Labor. There's so many things going on in the workforce in AI and then the economy that we need help with out here in private sector land. Tell us a little bit about your role as the, as the Innovation Officer and what is Department of Labor's mandate around the workforce first, and we'll talk about a lot of policy things.
[00:00:22] Speaker B: Well, first of all, Josh, it's great to be with you. I've read your reports for many years and so glad to have this conversation today on the Department of Labor side. It's a really exciting time to be here. In general, in terms of our role, in the simplest terms, DOL exists to help American workers and help American job seekers succeed. And we do that by overseeing the nation's workplace laws. So think about things like wages, health and safety conditions we set and enforce all of those different elements of the workplace. But then we also own a really important portfolio of programs to support job seekers and workers. So think about unemployment insurance, job training, apprenticeships. All of that fits within the Department of Labor. And so now in particular, super exciting time to be here because given the acceleration of AI, given a lot of these different trends, it's really a time where I think the nature of labor itself is changing perhaps more significantly than I think anytime in modern history. And so I think our role at DOL is really to say, how do we not be reactive to some of these changes? How do we really be taking proactive steps to actually harness AI and these other trends to make sure that they positively support workers, positively support job seekers? So to your question, my role as Chief Innovation Officer is really to lead DOL's perspective and an exploration into how is AI reshaping work and what are the different ways that we can modernize and innovate our programs and policies to better help workers and businesses navigate that new reality?
[00:01:54] Speaker A: Well, that's a huge, really important mandate, as you know and you know as well as I do that every organization is struggling with this. And, and there's lots of issues in the workforce in general and fears. So we're going to get into all that. Let me talk to you first about the Presidential AI Action Plan, and then we'll talk about the Talent strategy document that came out. Also, there's some really, I think, significant changes taking place in Washington. So what is your perspective on how organizations should or should not build skills and literacy and capabilities around AI to prepare for the jobs and new roles and new technologies that we're kind of dealing with right this minute.
[00:02:35] Speaker B: Yeah, I think it's critical that organizations are thinking about this not only in the near term, but also in all of the different waves of the acceleration of AI that we expect to come in the coming years. And our view specifically is that in that new reality that the workplace will be, AI literacy skills are the gateway to opportunity, are the table stakes that all workers in an organization have to have. Not just by certain industries, not by certain occupations, not by certain levels within an organization, but truly everyone across the organization needs to have those foundational skills around AI literacy and AI skills, and not just in general, but embedded in terms of the specific role, the specific workflows that they're doing.
And so a lot of what we're seeing is organizations experiment with different models of what the best way to transform their organizations are. And I think a lot of it comes from basic change management principles of how do we have the best ambassadors throughout an organization, how do we have both a bottoms up approach to get really good ideas, but also somewhat of a top down approach to say how do we make sure that people aren't just looking at, at their own roles, but you have those people that are looking at the bigger picture and perhaps the bigger shifts that could happen. And so a lot of what we've started to look at in the documents that you mentioned, the AI Action Plan, America's Talent Strategy, is how might the Department of Labor really play that role to support companies, to share best practices, to play a convening role, to create the right incentives and the right systems where companies can really move as quickly and effectively as possible to prepare their organizations.
[00:04:18] Speaker A: So your job is not so much to come up with the methodologies, but to really incent and motivate organizations to go through this literacy building process. But there's a lot of other details to this.
[00:04:29] Speaker B: That's right. And it's still early days, as you know, Josh. And so I think there are some elements of AI, for example, where we, we could look at policy, we could look at guidance, we could look at regulations and things like that.
But there are others where it's much more of a softer and we might just play that, that convening role and uplifting best practices and drawing attention to success stories of the types of organizations that have really led this transformation in a way that's both been positive for the bottom line, but also positive for the workers in terms of the productivity and opportunities that they see. And so it really varies and it's something that we want to be able to pull a lot of different levers as the AI landscape evolves to make sure we're best supporting the economy and the workers.
[00:05:17] Speaker A: Great. Well, you know, that's been a lot of what we've been doing with our academy, and I talked to a lot of companies who are building literacy programs. But it kind of gets down to my next point, which is this research hub that you guys are starting, which I'm very excited about. Why don't you tell us what that is and what you're trying to accomplish there?
[00:05:35] Speaker B: Yeah, glad you called that out. It's something we're very, very excited about and think is really critical. The AI Workforce Research Hub, as you alluded to, was announced in the President's AI Action Plan as a part of his overall leadership to say, how can America be the leaders in AI on a global basis? And a big piece of that was workers. And so in a specific section around empowering American workers in the age of AI, there was a specific note that DOL would launch this AI Workforce Research Hub. And the purpose of it is, I think, really to build this muscle of agility to say, how do we have an ongoing effort that is looking at data and research on the ground?
And I would say, in contrast to perhaps a lot of the headlines that we see every day that are just predictions to say, this is what I think, or this is what the labor market might do in five years or 10 years.
And I think our push is we need a way to say, let's ground this in data. Let's ground this in what's actually happening. What are we seeing on AI adoption? What are we seeing on some levels of job creation, some levels of job displacement, whatever that is, how are we proactively getting that research early, but I think, crucially, turning that into policy and turning that into programs as quickly as possible. And so, for example, if there are new challenges that we start to see in the data that workers are struggling with, that businesses are struggling with, how do we not wait 18 months until other data sources pick that up? How do we immediately think about, are there certain policy changes? Are there certain innovation pilots? Which was also something in the AI Action Plan that we can get it started earlier rather than later to try to be as agile as possible, to address both the opportunities and the challenges that we're seeing?
[00:07:19] Speaker A: Well, this is, you know, this area of research, of course, is what I've been doing for almost three decades. And I have learned that while academic research is important on the ground, examples, best practices stories are so vital. So Anything you can do to collect that information and promote it and share it would be just so valuable, especially since it's changing so fast. I mean, anything you study about AI today is out of date in three months.
[00:07:46] Speaker B: No, that's right. And to be honest, Josh, part of the reason why we feel so strongly about the value of this hub is because people talk about and ask about the challenges of AI a lot. Our view is that one of the greatest challenges of AI and the workforce is not actually this risk of mass job displacement that's in the headlines sometimes. It is actually the speed of change itself. That's what we view as the challenge. And so that muscle of agility we view as so important because the, the skills in the economy that are needed, the talent that's needed, is only going to change in a faster and faster rate. And so our view is how do we think about DOL internally and how we can move faster, but how do we also encourage and support companies and other stakeholders to build their agility muscles internally as well?
[00:08:32] Speaker A: Well, that gets them. And that leads me to the next question. I want to talk a little just about that issue. You're familiar with our super worker, super manager approach, and you've read Dario amadai's comments that 50% of white collar jobs are going away. You know, I think a lot of people maybe historically thought the Department of Labor was to protect labor against these evil employers who were going to disrupt their lives. And so there is a lot of fear about AI out there, and I think some of it's coming from the tech vendors. What is your perspective on the job destruction issue or where you think the economy is going to go? And how are you going to help us get through this as quickly and easily as possible?
[00:09:12] Speaker B: I think our view is in a lot of these conversations, and I'll get to this placement point, but maybe just let me say one thing first. In a lot of these conversations about how will AI impact the economy? I think a lot of times it does start with, as you said, a focus on risk, a focus on disruption. And our push would be how do we shift the narrative a little bit to say, can we start with the possibilities, can we start with the opportunities of how AI could reshape the economy and in a way that can actually uplift a lot of workers from, from the opportunities that they have now? And so a lot of what we're tracking is what are the different jobs that, that don't exist today that might be created across industries? And one side point that I'll Just say there is particularly exciting for us is that some of these jobs, including AI infrastructure jobs, right. As we build out data centers, some of the occupations that are really critical there, some of these jobs are both high paying but also do not require a four year college degree. And so this is really a movement that can expand jobs and really expand the middle class in a way that is going to be remarkably beneficial. So jobs is one point. But then to your point about superworkers, there's also this whole other benefit around productivity and how can this really give individuals and small teams the ability to accomplish so much more than they could before? And some of the second order effects that we see there are how does that affect entrepreneurship and the opportunities there, how does that affect small business ownership and the different possibilities there? And so point number one, I would just say is we view AI and the economy overall as a new frontier of opportunity. To your point, there is still the question of but won't, won't all of us just be replaced? Right.
Didn't I hear Dario from Anthropic say that the other day? And I think our view there is that there is certainly a risk of some level of change in the labor market, as there is with with all new technologies. But, but our view is that the displacement narrative out there right now is overstated because in the vast majority of cases, we believe it's much more likely for jobs to transform than to be completely replaced. Right. This idea of a human in the loop, and maybe just a couple examples that I'll give, that gives us confidence that that's the case. What is this notion about how productivity or efficiency actually then relates to hiring and employment decisions? I think many people assume that, for example, if AI makes workers more productive, that companies would simply then choose to want fewer workers to produce that same amount of output. But I think in practice what we're seeing is in many cases the opposite, which is that companies are using AI to help the same number of workers produce more output. Right. And so that productivity gain is translating to that existing amount of workers being able to create more content, launch new products faster, serve customers better. And so I think that's a lot of the, the, the data that we're.
[00:12:16] Speaker A: Seeing, which in turn leads the CEO to say, well, now that we're so scalable, let's hire more people and double the size of the company.
[00:12:23] Speaker B: That's right, right, right. I mean, it's funny, even some of these studies about, I think it was PWC had a study about the types of jobs that have the most quote, unquote, AI.
[00:12:34] Speaker A: Right.
[00:12:34] Speaker B: And actually what they found is since the launch of ChatGPT, there's actually been an increase in the volume of jobs that have the largest AI exposure. And obviously in the early days, there's still a lot of hypotheses of why. But one of the leading hypotheses is the productivity benefits has really caused there to be more demand for these types of workers.
[00:12:54] Speaker A: Well, I'm totally in agreement with you there, 100%.
Which leads me to another question in the America's Talent Strategy document, which is really an interesting document for somebody that's studied the education industry and the credentialing industry for so long. I see some really different things here.
One of the areas I wanted to ask you about is career pathways, because, I mean, when I went to college, I was fortunate enough to have a father that had a good career, so I could kind of mimic that. But there was virtually nothing other than the strong vocational aptitude test in the 1960s to help me me figure out what to do with my work life later. And I talk to people now in, say, marketing or publishing that are just not even sure what to do about AI. They know it's going to affect their job, but they don't know. So how can you help this career pathway visibility in the workforce so people have a sense of direction and hope, where they should be going and what they should be learning, and where should they should be putting their attention as AI comes along. Is that a big focus area for you guys? Guys? And how do you think that's going to play out?
[00:14:07] Speaker B: It's a huge focus area that came out of the America's Talent Strategy report, as you alluded to. And part of that was this report was put together by the Department of Labor, the Department of Commerce, but also the Department of Education. And part of what these agencies came to the conclusion of with the support of the White House, is that we really need to not be, you know, outlining different strategies for each agency. We need a very cohesive and unified approach to workforce development and really to more than just workforce development, to human capital development, which starts at a very early age in K through 12. And so as we are seeing these different changes in the labor market of what are the new jobs that are out there, what are the, what are the jobs that have talent shortages that we want to make sure people are aware of, you know, as there is all this talk about the existing and the new opportunities and the skilled trades, if people don't know where they are where are the moments in life where they're actually going to gain more awareness and interest in those roles? And so we really think that all of that feedback and action that's happening in the workforce, there's an opportunity to say, what does that look like? To have the right breadcrumbs to those types of career pathways across the K through 12 system. And so one of the things that we said in the report was even as early as middle school, what are the types of exposure and awareness opportunities that are there? And again, at that level, you're not talking about internships, you're not talking about.
[00:15:33] Speaker A: No, but even giving kids an idea of where they might want to go with their lives at that age I think is really valuable.
[00:15:38] Speaker B: Yeah, I mean, research and studies continue to say, as I'm sure you've seen as well, that a lot of the challenge is just awareness of they may not have seen people in their life, people in their community, where they live, that have been in these roles. And so how do you put more roles on the radar of these kids? And then they can start to explore, hey, which ones of these most align with my skills or with my interests. And so you start with awareness, but then you can build on that through high school and post secondary for those who go to that route of more career immersion, more apprenticeships and work based learning. But it all starts with that awareness. And we think that can start really early on.
[00:16:19] Speaker A: Taylor, let me just tell you something really funny that just occurred to me when I graduated from. I don't know, I'm almost 70. When I took that vocational aptitude test, whenever it was in high school, the number one job for me was astronaut. That was where the world was at that point in time.
[00:16:34] Speaker B: Well, I was going to say, we still don't know. That's not true.
[00:16:37] Speaker A: I suppose I think I'm a little too old for that now. But that leads me to another really big question. And I don't mean to be political at all, but you know, the, as I understand it, the government spends something in the, in the hundreds of billions of dollars on education.
Many, many loans, grants, Pell grants. I don't even know where all this money goes. And the Department of Education has been sort of, I don't know what status it's in, but I got the feeling, reading these documents that you're taking on, you and the Department of Labor are taking on some sort of an advisory or leadership role in deciding where all this money is spent at the federal level to try to align it towards these Workforce needs, which to me would be a miraculous change in the way, you know, we do education in the country. I'm just curious what your perspectives are on that. And if I'm read that correctly, it's.
[00:17:27] Speaker B: A huge part of, of what these different agencies have thought about in terms of what the best way is to have a more unified approach. And so the specific vehicle that we're using for that is what's called an interagency partnership between the Department of Education and the Department of Labor. To say for some of these programs that are most connected to the workforce side, rather than going through completely different processes and being administered by completely different teams, can we have those be administered in the Department of Labor through that interagency partnership? And so that's what you've seen.
[00:18:01] Speaker A: So you would see the investments and you would apply the labor market requirements to whatever the educational funding is going. Is that the idea?
[00:18:09] Speaker B: Well, the idea is it's a lot of the administrative process on the back end that is causing slight fragmentation in experience for grantees and for states, but also slight fragmentation and just decision making.
[00:18:22] Speaker A: Right.
[00:18:22] Speaker B: Programs that should be extremely aligned from, from a strategy standpoint. So there's multiple benefits to all stakeholders that we see of this closer, more cohesive relationship.
[00:18:32] Speaker A: Well, that leads me to another question I want to ask you about. So there's also a big section in there about accountability for educational spending and apprenticeships and other programs. I've been involved in trying to create measurement programs on corporate training, which is hard enough.
What is your thinking or I don't know if you've been involved in this, on how we can get more accountability into the spending on education so that it can go in the right places because it's a moving target all the time. I mean, there's so many ways to invest in education and credentialing. It's almost an infinite possibilities, you know, what are you, what are you thinking there?
[00:19:07] Speaker B: Well, our starting point is that what's happening now is not working for workers, it's not working for businesses, it's not working for taxpayers. Because as you alluded to in the previous question, we are spending billions of doll without in the workforce space much, you know, clear standards for success.
And there are a lot of grants and programs that are happening that have very few consequences when the programs fail to deliver the results that they've promised. And so the first piece is just, I think on our side developing a strategy around outcomes based accountability, whether, you know, whether it's leading to new jobs or whether it's leading to higher wages or how much we're spending in the ROI calculation. But part of what we realized and what we identified amongst the agencies, Josh, is that a lot of the historical challenges around doing this better has been around the data and reporting infrastructure. And so there's a need here to just say, how do we modernize our systems around data, around outcomes, around tracking, how do we make sure we're linking different data sources, in some cases using AI, using automation to bring some of this data together to actually, first of all, just have the transparency, because a lot of times you don't even have all of the data points in front of you of just how ineffective some of these programs have been.
Two other quick things I'll just say is besides that infrastructure and transparency, a lot of what we're thinking about is also where are there opportunities to test out pay for performance models, where it's not just we're cutting a blank check and hoping for the best results. But for example, one of the, the, one of the places that was mentioned in the workforce report was around apprenticeships, which is a huge priority for the President and for the Department of Labor and saying, let's make sure that every dollar we're spending is actually generating the most growth in this proven model of apprenticeships. And so I think those outcomes, aligned incentives, aligned models like paper performance, is something that works. Really excited to experiment and see what further impact we can drive.
[00:21:07] Speaker A: Fantastic. Okay, one more sort of technical question and then a wrap up. So one of the ongoing issues with AI is bias. Hiring bias, bias in pay. Now eventually, very soon we'll have AI doing performance appraisals, deciding how much money to pay somebody to, obviously already deciding who to hire. I know Keith talks about this a lot, but what is your thinking or perspective on what your position or, you know, strategy is to help with those, you know, kind of ongoing technology issues in companies and legal issues.
[00:21:38] Speaker B: It's a really important question. As you said, it's, it's constantly evolving as well, which is one of the reasons that, that there's need for guidance and reflections on this to make sure that companies can navigate this in the right way. I know you know this, but maybe just to clarify for your audience, in terms of the federal government structure, the eeoc, the Equal Employment Opportunity Commission, is the agency that when it comes to employment decisions, whether that's hiring, firing, promotion, etc.
That is the agency that, that sets and enforces those employment discrimination laws, whether or not it includes some layer of AI. So that is an independent agency The Department of Labor is a separate agency from that. But as you said, we have a unique relationship with some of those issues right now because our Deputy Secretary of Labor, Keith Sonderling, was previously the EEOC commissioner and really led on a lot of those issues. And so all to say we want to stay in our lane in terms of, of enforcing those laws and setting those laws. But I can still share some general reflections about how we think about guiding companies in terms of what they might consider around this area.
One is that I think companies have to still remain responsible for employment decisions, right? Even if the algorithms are playing a role, even if the systems are playing a role, they have to continue to take responsibility for what decisions are being made and how those are being made.
The second thing I would say is just making sure as companies are working with these vendors, that they really demand the right amount of transparency of how some of these systems are built, how these algorithms are being used, and asking those questions, both both on front and on an ongoing basis.
And the last thing I would just say on this, and I think this is a really important point as this job search and hiring process, you know, it's a two sided issue where there's both more and more AI bots and AI use cases for the job seekers, but also more AI bots and use cases on the hiring side. And our view is there's a strong role for AI to play, but there's also a strong role for humans to play. And so how do you think about, as you adopt some of these systems, where they can best play versus where you want to have humans still involved in that process?
[00:23:55] Speaker A: Wow, Taylor, they really seem to have a very, to me, from my perspective and tremendous understanding of what the issues are out here in the private sector. So thank you for sharing that with us. Just as a wrap up to the heads of hr, the HR leaders, the business people that listen to this, what general advice or philosophical advice would you like to give them to make sure they're taking advantage of these technologies and really optimizing the workforce for everybody, for the employers as well as for the workers and the rest of the economy?
[00:24:27] Speaker B: I would say three things I would start with around some of this rhetoric around AI. How do we shift the narrative from a fear based narrative to an optimism based narrative? There are so many opportunities for organizations for workers that we can take advantage of, but we have to shift that narrative first because I think there's a lot of fear out there and we have to help demystify this and bring workers and bring organizations along for the ride of what those opportunities are. And so I'd say as a part of that, a couple pieces within that one is back to the piece around AI literacy. We do think that's really the foundational element of investing in AI skills, investing in AI literacy at all parts of an organization that's going to allow you to achieve some of those types of gains. But, but then the second and and final thing I would say is back to apprenticeships. As the the market and the economy continues to move faster and faster, we think that apprenticeships are the talent model of the future. We, we have sent the strongest signals possible that that's where the Trump administration believes a kind of cornerstone of the workforce policy needs to be. We think it's something that we are looking internally of how we can make that model easier for employers, more valuable for employers, more flexible for employers. And so for those HR leaders that haven't already adopted apprenticeships, we'd love to share more about the value of them and how the Department of Labor can support.
[00:25:53] Speaker A: Fantastic. I couldn't agree more. We've been doing apprenticeships here, in fact, and it's just such an incredible way to bring new people in and educate people and make sure this is a good fit for them and in any organization. Taylor, I feel a sense of confidence knowing that you're there watching over us, helping us. We all want to participate, to contribute to the research hub and whatever else you would like. So thank you for sharing this with us us and we'll keep close in touch. Thanks again.
[00:26:19] Speaker B: Thanks, Josh. Great to talk to you.
