Sen. Hickenlooper (00:00):
... striving to achieve the best for themselves and the best for their communities. Every technological development has provided tools for these workers, these strivers, to achieve even more from the telegraph to the assembly line. We are currently witnessing what some are calling a fourth industrial revolution.
(00:19)
Technological advances in artificial intelligence and automation are changing how we create, how we communicate, how we work and how we live. These new tools, like the ones that came before, come with great power, but also great responsibility. Small, medium, and large organizations alike are feeling the transformative effects of AI. There's an ever-growing crop of AI assistance claiming they are ready to help you revolutionize your house or your business. But today's businesses wonder, how do I know which tools are worth our investment and which ones over promise and under deliver?
(00:59)
Our governments all want to make use of these promising new technologies. Pacific Northwest National Lab has built AI tools to streamline and accelerate the permitting review process for critical infrastructure. Health and Human Services used AI to identify polio outbreaks. And the Colorado Department of Labor and Employment is using AI to improve its customer service experience.
(01:22)
But no one feels this revolution more acutely than our workers. Today's worker must navigate a dizzying maze of systems that are increasingly automated, job applications, interviews, human resource systems. Each of these entry level roles are shifting and often driven by AI.
(01:47)
New AI driven tools are being implemented across sectors with oftentimes little to no training on how to use them. We need to ensure that workers are getting the training they need at every level, whether they're searching for their first job or transitioning to a new role in the same field or looking to switch industries altogether. Today's workers have got to ask themselves, how am I going to keep up, or even better, strive and thrive in this AI ecosystem?
(02:18)
That's what's driving this hearing today. As we see AI impacting the workforce in all these different ways, we need to work together on making sure we get the right path forward. How do we help employers, educators, and workers prepare for what's next? We envision a fully connected ecosystem where all these entities are communicating with each other among each other, sharing proven practices, forecasting needs, and developing strategies for overcoming these obstacles together.
(02:53)
We're working on a bill to encourage just that. Our bill brings together regional partnerships of educators, industry and intermediaries to provide credentials, apprenticeships, other jobs and training that use AI. Because who knows better than workers and the businesses and educators in a region that in any given region than the workers, businesses and educators in that region.
(03:24)
We've also been working on a bill with Chairman Banks, as he mentioned, Senators Hassan and Husted, called the AI Workforce Prepare Act, which would direct the Department of Labor to gather and analyze data to better inform us exactly how AI is impacting the labor market. And foreign policy starts with good data. You can't say that often enough. Too often we don't see it in this building. And this work is going to provide essential insights into job transitions, layoffs, and future worker needs.
(03:57)
This is a monumental task ahead of us in this fourth industrial revolution. The capabilities of current technology are well beyond previous generations' wildest dreams. We are confident that with the guidance provided by people like all of our witnesses here today, we can forge a path in the right direction.
(04:17)
We need to look at what the research is telling us about how the workforce is shifting and how we can accommodate that and give them a leg up. We need to partner with folks on the ground in our states who are innovating with AI and with workers and employers. We need to shape worker forward policies to set striving Americans up for success. This is a moment in history when everyone's effort matters. The decisions that we make now are going to ensure that any child born today continues to have the highest probability of a healthy and happy life of any person born in the history of mankind.
(04:59)
Thank you all for your testimony and for taking part in our hearing today. And I yield back to the chair.
Sen. Banks (05:06):
Thank you, Ranking Member Hickenlooper. I would now like to welcome our first and only panel. First, we have Mr. Ken Clark, the president and CEO of EmployIndy, the workforce board for Indianapolis and Marion County, Indiana. Mr. Clark brings an impressive combination of expertise in workforce development, technology, and public administration. Mr. Clark, you are now recognized for five minutes to deliver opening remarks.
Ken Clark (05:36):
Thank you, Chairman Banks, Senator Hickenlooper and members of the subcommittee. Thank you so much for the opportunity to testify today. My name is Ken Clark. I serve as president and CEO of EmployIndy, the Workforce Development Board serving Indianapolis and Marion County in Indiana.
(05:52)
Every day we work with employers trying to fill jobs, educators preparing students for careers and job seekers navigating a changing labor market. That gives us a practical view of how artificial intelligence is changing work today. I've had the opportunity to see artificial intelligence from two very different perspectives in my career.
(06:12)
Before leading EmployIndy, I served as chief information officer for the city of Indianapolis, one of the nation's largest cities, helping all three branches of government implement new technology and managing a 7,000 employee workforce. Today, I lead our region's workforce development board, helping employers find talent and workers prepare for the future of work.
(06:35)
In my current role, I have the opportunity to see how new technologies affect employers trying to fill jobs and workers trying to build careers. Those two perspectives have shaped one fundamental belief. Artificial intelligence is not primarily a technology story. It is a workforce story first.
(06:53)
Because technology has never been America's competitive advantage by itself, our workforce has. And that belief has led me to three conclusions. And I'll briefly outline those for you. First, AI is reshaping far more jobs than it's replacing. Much of the public conversation has focused on mass unemployment. That's not what our employers are telling us.
(07:17)
Artificial intelligence is becoming another workplace tool, much like the internet and email. It is changing how work is performed, not eliminating the need for people to perform it. When the new IU Health Hospital being built now in Indianapolis opens, AI will help summarize patient information for clinical review for a nurse.
(07:37)
The goal isn't to replace nurses. We need more nurses very clearly. It's to give them more time with patients and less time in front of a computer. This is AI augmenting workers, not replacing them.
(07:49)
Second, I believe the greatest long-term workforce risk is not widespread unemployment. It's the disruption of career pathways that workers rely on to gain experience and continually develop new skills throughout their careers. Every experienced professional was once an entry level employee.
(08:06)
Today's junior software developer becomes tomorrow's senior engineer. Today's apprentice becomes tomorrow's master trades person. Not to steal from you, Chairman.
(08:17)
If artificial intelligence significantly reduces opportunities for workers to gain those early career experiences, we don't simply lose entry level jobs. We weaken the talent pipeline employers depend upon to develop tomorrow's workforce. Preparing workers for an AI economy means preserving career connected learning, internships, apprenticeships, other pathways to develop judgment, communication, human skills that AI cannot replace. Increasingly, employers are looking for workers who can work alongside AI, evaluate AI generated information and exercise judgment that only people can provide. That means preparing for AI isn't just about a pathway into the workforce. It's about helping today's workforce continuously learn and adapt as occupations will evolve.
(09:01)
And my third conclusion, local workforce boards will play a critical role in helping communities adapt. Every regional economy is different. We're made up of different industries and different talent. And so that is our own DNA within each region.
(09:18)
The AI challenge is facing advanced manufacturing looks different from healthcare. Healthcare is different from logistics. Logistics is different from hospitality. That means workforce solutions must also be very local. Workforce boards sit at the intersection of employers, educators, economic development, and training. We translate employer demand into training strategies, national trends into local action and emerging technologies into practical workforce solutions. Local workforce boards are only as effective as the information they have, and that is why we support the AI Workforce Prepare Act.
(09:52)
Winning the AI race isn't just about building better technology. It's about building a workforce that's ready to use it. Preparing for AI begins with understanding how it is changing work. Better labor market intelligence, forecasting and workforce data will help communities prepare workers before disruption becomes displacement.
(10:12)
And I'll close with this. America has never succeeded by fearing technological change. We've succeeded by harnessing it. Artificial intelligence will not determine the future of work. People will. If we equip employers, educators, workforce organizations, and workers with better information and tools, AI can strengthen America's workforce rather than weaken it. I thank you and look forward to your questions.
Sen. Banks (10:37):
Thank you for that. Next, we have Ms. Carol Rogers, the director of the Indiana Business Research Center at the greatest university in America and the returning national champions, Indiana University's Kelly School of Business. Ms. Rogers is an expert at making complex data useful for real world decisions. She serves on boards of several national organizations focused on economic research and labor market information. Ms. Rogers, you are now recognized for five minutes to deliver your opening statement.
Carol Rogers (11:13):
Thank you so much, Chairman Banks, Ranking Member Hickenlooper and members of the subcommittee. And it's a beautiful day out there. So thank you for being here to listen to us.
(11:25)
I was actually thrilled to have this opportunity to testify today on the impact of AI on the workforce. It is a real issue. There are some knowns, many more unknowns, some unknown knowns. And we could go on, but I'd have to remember the movie that came from.
(11:52)
I do come here as a subject matter from that great university in Indiana, but my views don't necessarily reflect those of my employer, the university. So I want to just make that clear. As director of the center, and thank you so much for giving those remarks about my experience, Chairman Banks, because I can cut out a little bit on describing why I'm here.
(12:25)
But certainly the thing we have been doing since 1925 when the university trustees of Indiana University created our center was to help people in Indiana understand our population, our economies, our workforces. And I say plural because we have many, to provide them with evidence-based data and research.
(12:53)
So getting onto the impact on the workforce, generative and agentic AI, I like to kind of differentiate a little bit. AI generically is many things, but certainly those two have evolved very quickly in the four years since ChatGPT's public release to the world. Nearly 20% of US firms today, and actually not today, it was February 19th in a survey by the US Census Bureau, nearly 20% report using AI in some business function. Harvard's Project on Workforce has surveys looking at the uptake of AI, particularly generative AI.
(13:45)
And they're finding that 62% of adults between the ages of 18 to 64, which is our prime training and education workforce, are using generative AI. And workers in that population are reporting spending about 6.5% of their work hours a week using it. That's kind of hard information. It's useful information. We'd like to see more like that.
(14:22)
My center recently published findings comparing high and low AI exposed occupations in our state, meaning that they have tasks in those jobs that some proportion of them could be done by agenetic AI. So when we say exposed, in some ways you could say they're exposed to the risk of AI.
(14:50)
In another way, you could look at it as exposed to an opportunity with AI. Like many academicians, I talk with one hand and then say on the other hand. So you'll have to forgive me, but we see both.
(15:07)
Notably, we found that job postings in those exposed occupations actually shrank. Postings for AI exposed jobs, and many of those were in technology, shrank since 2022, versus 35% decline in those less exposed, the jobs that require human touch as opposed to artificial touch. Wages in those exposed occupations though grew faster. But at the same time, those jobs lost their employment advantage.
(15:48)
And think about some of the things that we've seen over the last several months about college graduates not finding employment as quickly as they used to. Think about jobs or occupations that people have where they don't have that two or 3% below unemployment that we used to have, people with bachelor's degrees, master's degrees. However, taking this together, what I've described, and it's not enough, taking it together, it looks less like mass job elimination, more like market-based pricing and reallocation.
(16:37)
This bill matters. I'm running out of time. So I want to say very clearly that I support the bill and its goal to collect data, to have better data. And my plea is that we create standards for the definition so that we compare apples to apples. Oh, I actually have 45 more seconds here.
Sen. Banks (17:01):
No, you've gone over 45.
Carol Rogers (17:02):
Oh, I'm done? Okay. Thank you very much.
Sen. Banks (17:06):
Thank you very much. Next, we have Dr. Liya Palagashvili. I practice that all week, and I probably still messed it up, senior research fellow and director of the Labor Policy Project at the Mercatus Center at George Mason University. She is a labor economist whose research focuses on independent workers and how labor markets evolve. Thank you for being with us, Doctor. You have five minutes for your opening remarks.
Liya Palagashvili (17:36):
Good afternoon, Chairman Banks, Ranking Member Hickenlooper and members of the subcommittee. It is an honor to testify before you. My name is Liya Palagashvili. I'm a labor economist and director of the Labor Policy Project at the Mercatus Center at George Mason University, where my research examines the changing nature of work and how policy can help build a resilient labor market.
(17:57)
Let me start with the most fundamental point. The early evidence does not yet show broad AI driven employment loss. Much of the public debate asks whether AI will take jobs, but economists think of jobs as a bundle of tasks. So automating one task doesn't mean the whole job disappears. AI can automate some tasks, augment others, raise productivity, and change how firms organize production.
(18:24)
Recent studies find little noticeable change in employment, unemployment, earnings or hours at AI adopting workplaces. According to a Census Bureau survey, about 95% of AI using firms report no change in total employment. That does not mean nothing is happening. It means the adjustment is more complicated than a simple story of mass displacement.
(18:47)
The clearest evidence of potential concern is concentrated among young workers entering highly exposed occupations. Recent research finds employment declining for young workers in the most AI exposed field without a matching rise in unemployment, a pattern more consistent with slower hiring than with layoffs. This can be a serious concern. However, the evidence is still mixed.
(19:11)
According to research from the Economic Innovation Group, hiring and many highly exposed occupations actually began declining in the spring of 2022. So six to eight months before ChatGPT even existed. Employment outcomes have also weakened among young workers with little AI exposure at all, including teenagers working mostly in food service and retail. The broader pattern points towards macroeconomic factors as much as AI.
(19:40)
So the right conclusion is not that AI is irrelevant. It is that the picture is still mixed. And to the extent employment effects exist so far, they look like a slower hiring pipeline for younger workers, not layoffs.
(19:56)
This brings me to my second main point about measurement. Federal labor market statistics are valuable, but they were built for an earlier economy. Household surveys can tell us whether someone is employed and what occupation they hold, but not how AI is changing tasks within the job. Business surveys can tell us whether a firm reports using AI, and in some cases, whether it says AI affected employment.
(20:20)
But those responses are still too course and are not routinely linked to hiring, separations, earnings, or occupational composition. Even the basic adoption rate depends heavily on how the question is worded. For example, when the Census Bureau broadened one survey's AI question last November, reported use jumped from 10 to 17% overnight. That was a change in measurement, not a month of sudden economic transformation.
(20:48)
The AI Workforce Prepare Act is a constructive response to that problem. It adds AI questions to several major federal surveys and creates a voluntary channel for AI developers to share adoption data with statistical agencies. As Congress considers further reforms, I would emphasize three things in particular on measurement. One, linking business surveys answers to actual hiring and wage outcomes so we can compare AI using and non-AI using firms directly. Two, adding occupational detail to the wage records that nearly every employer already reports so we can see which specific jobs are growing or shrinking. And third, building a timely measure of new solo independent business activity.
(21:33)
The last point matters because of what my own research has found. Since early 2024, new business applications with no signs of near-term hiring have risen 27% in AI exposed sectors while essentially staying flat in less exposed sectors. Solo self-employment shows the same pattern, up 20% in the most AI exposed occupations, unchanged in the least exposed. These results are descriptive, not causal, but they suggest that in some knowledge intense-
Liya Palagashvili (22:00):
... they're descriptive, not causal, but they suggest that in some knowledge-intensive fields, AI may be lowering the cost of working independently rather than reducing employment overall. And this makes sense. If AI helps you do what once required a team, you may decide to go out on your own rather than needing an employer to provide that team for you.
(22:21)
And to summarize, the evidence doesn't yet show broad job loss. Our data systems can't fully see what's happening, and independent work is growing in ways that matter for labor policy. Let me conclude by saying the central challenge is not to predict a single labor market future. It is to build institutions and measurement systems that are resilient across several possible futures.
(22:42)
Thank you for the opportunity to testify and I look forward to your questions.
Senator Banks (22:45):
Thank you. I would like to yield to Ranking Member Hickenlooper to introduce our next two guests.
Sen. Hickenlooper (22:53):
Thank you, Mr. Chair.
(22:55)
First, let me introduce Mr. Jonathan Liebert. He's joining us today from Colorado Springs, where he serves as the CEO of the Better Business Bureau of Southern Colorado, and I think also working as at least the acting CEO of the whole statewide Better Business Bureau as well. Mr. Liebert created the BBB AI Hub to increase AI literacy and capability as well as governance and responsible use.
(23:25)
Dr. Justin Heck is the Senior Director of Research and Data Production at Opportunity@Work, a national nonprofit building a skills-first labor market. Dr. Heck has spent over a decade conducting quantitative research at the intersection of labor market analysis and public policy.
(23:42)
Thank you both for being here and participating.
Senator Banks (23:46):
Mr. Liebert, you're recognized for five minutes.
Mr. Liebert (23:49):
Thank you. Thank you, Chairman Banks and Ranking Member Hickenlooper and members of the subcommittee. Appreciate the opportunity to testify today on the impact of artificial intelligence on America's workforce.
(23:59)
Again, my name is Jonathan Liebert and I'm the CEO of the Better Business Bureau of Southern Colorado. I'm also the past chair of the Colorado Workforce Development Board, and I'm part of my local workforce board as well. And my perspective on artificial intelligence is neither pro-AI nor anti-AI. I'm cautiously optimistic. I've seen in ways that it can absolutely magnify productivity, strengthen small businesses, and expand access to expertise. I've seen it help workers become more capable. I've also seen how people can enter in sensitive information into these public systems, accept fabricated information as fact, and purchase products that are marked as AI-powered without understanding truly what that technology does.
(24:40)
Since 2025, I've trained over 5,500 business owners, employers, educators, and nonprofit leaders in Colorado and now in other parts of the country, and talking to them about how AI needs to be used ethically, responsibly, and practically. This experience has given me really a front row seat to what's going on inside of the workforce. I'm there to see the excitement, the fear, and a lot of misinformation that's surrounding this technology.
(25:08)
Business owners really want to know which tools are a credible source of information for them to be able to use safely, and they want to make sure that they are doing things wisely and not putting their customers at risk. Nonprofit leaders want to know how they can expand their impact and their limited staff resources and level up their organizations. Educators want to know what to prepare students for and knowing that jobs are changing fast and employers are looking for different things and what they should put into their curriculum. Workers want to know whether AI will replace them and they want to know what will help them become more valuable workers to the workforce system.
(25:39)
And so what I've learned is that fear often decreases when people receive practical education. The greatest problem I see is not that people are refusing to use AI at the moment. It is often that they trust it too quickly. And so I tell the folks that I teach that AI is not an oracle. AI is an ideation engine. It gives you the ability to create these templates and information, but you have to keep the human in the loop and double-check everything. An oracle is an answer to be believed. An ideation engine helps generate these options, and you should challenge these assumptions. It'll help you organize information and produce that first draft. The human must remain responsible for verifying the output, adding additional context, and then absolutely making the final decision of how it's implemented.
(26:20)
At the Better Business Bureau, we created the BBB AI Hub to help close the gap between the speed of technological change and the ability of people and organizations to respond quickly. BBB is interested in making sure that trust and ethics are applied when using this technology. And again, as our mission and vision state, we're interested in marketplace trust. If buyers and sellers don't trust one another because of the way the technology is being used, then that has economic implications for all of us.
(26:47)
In collaboration with our local workforce center, the National Alliance for Workforce Boards, Chamber of Commerce, City of Colorado Springs, and partners across business, education, and government, we created this AI hub to really focus on a couple of different priorities. One is AI literacy. The second is workforce preparation, AI governance, and absolutely marketplace trust.
(27:07)
AI literacy means more than learning how to use a simple chatbot. It means understanding what AI can and cannot do, how to verify its output, how to protect sensitive information, and how to recognize misinformation and bias. And more specifically, when that human oversight is required.
(27:23)
AI governance means establishing clear rules before problems occur. Organizations should have robust AI policies and determine which tool should be used by their teams and develop robust AI literacy plans to help them keep up with these very, very quickly changing systems. One of the largest issues that AI has is that most people cannot conceptualize how to use it, since it is moving so quickly. Additionally, we all need to get used to the fact that how we work is changing and we need to learn how to review AI-generated work in a productive way. We must still think critically as we engage with AI and remain accountable for when AI affects an important decision.
(27:59)
Marketplace trust is also extremely essential. Small business owners and nonprofits are being approached by a growing number of companies and consultants that are saying they have these AI-powered claims or AI can fix these things. Most smaller organizations do not have legal teams, cybersecurity experts, nor technology procurement departments, and so they need practical guidance on how to evaluate vendors, how to update their data practices, how to look into these performance claims, and look at security contract terms and human accountability.
(28:28)
The workforce is changing. And in many cases, AI is going to help individuals automate these tasks and do jobs that they never could before. But again, we have to be careful that we're not fully automating people out of the first rung of this career ladder and then wonder why workers can't reach the second. So again, I think Congress can help by doing a lot of practical AI literacy. Obviously, enacting different types of acts will help to create more data and information for all of us to use.
(28:54)
And again, I would say this, that America does not need to choose between innovation and responsibility. We can pursue both at the same time. And in the future, the work will not be predetermined by an algorithm. It will be shaped by all of us and the choices that we make as we lead our workers into an educated system where we protect, make sure people have access to the tools, and make sure that we hold businesses and consumers accountable.
(29:14)
So again, thank you for the opportunity to testify. I look forward to your questions.
Senator Banks (29:19):
Thank you. Dr. Heck?
Dr. Heck (29:22):
Chairman Banks, Ranking Member Hickenlooper, members of the subcommittee, thank you for the opportunity to testify. My name is Justin Heck and I lead research in data production at Opportunity@Work, a nonprofit focused on building a skills-based labor market.
(29:39)
Public debate about AI and work has focused almost entirely on whether jobs will be augmented or automated. Far less attention has gone to how AI will reshape economic mobility. That's what I want to talk about today.
(29:53)
Workers build skills in one job and use them in the next. In aggregate, these moves form pathways. We analyzed 130 million job transitions over 10 years and found three kinds of jobs. Entry-level origin jobs, higher-wage destination jobs, and in between, the stepping stones we call gateway jobs. 60 million Americans work in gateway jobs and 62% of them are STARs, workers skilled through alternative routes who built their skills through work, military service, apprenticeships, training programs, or community college rather than a bachelor's degree.
(30:32)
Consider a customer service representative. Workers reach that job from roles like receptionist or cashier. And on the job, handling frustrated customers, finding solutions under pressure, they build critical thinking, speaking, and persuasion that prepare them for the better-paying HR or sales job that comes next. AI can break that stepping stone function in two key ways. The first is straightforward. There may be fewer of these jobs. Among the 10 largest occupations with high AI task exposure, half are gateway roles. And the Bureau of Labor Statistics projects declining demand for all five. That cuts both ways. A cashier or receptionist loses the next rung up and employers may find fewer experienced workers ready to move up into management or senior roles.
(31:21)
The second is less obvious and it may matter more. AI can hollow out a gateway job from the inside by eliminating what a worker learns from doing it. If that customer service rep spends their time overseeing a chatbot rather than handling the hard calls directly, they lose the opportunity to develop the skills that would have carried them to the next rung. The learning that happens on the job often happens through the hard parts. AI is exceptionally good at removing the hard parts. This can happen without anyone deciding to do it.
(31:55)
Learning has historically been the byproduct of getting work done, not the objective. A company that automates the demanding parts of jobs may see short-term efficiency gains while inadvertently dismantling the pipeline that produces its own future supervisors and managers. Displacement debates miss this. A worker whose job is eliminated knows it immediately. A worker whose learning has been quietly removed from the job may not find out for years until they apply for the next job and discover they no longer qualify. None of this is inevitable. AI can augment work rather than hollow it out. But whether AI narrows pathways or strengthen them depends on how the technology is deployed and on the choices before the subcommittee.
(32:40)
Congress can act in three ways. First, build a skills-based labor market. When pathways get disrupted, workers need their capabilities recognized wherever those capabilities were built. The Federal Jobs for STARS Act would embed skills-based hiring and federal employment while the Skills-Based Federal Contracting Act would do the same for federal contractors. Second, treat investment in workers the way we treat investment in machines. Employers can more easily write off an AI system, robot, or server than they can the cost of training workers to use the same technology. If we want employers to choose augmentation, the tax code should not be telling them the machine is the cheaper bet.
(33:21)
Third, fund what works and measure what's actually happening. The Better Jobs through Evidence and Innovation Act would fund proven programs. Reauthorizing WIOA with adequate funding would give the system we already have the resources we need to meet this moment. And the AI Workforce Prepare Act is a meaningful step toward the data we need, including data to see how AI is reshaping jobs and the pathways that run through them.
(33:44)
I'll close with this. AI presents enormous opportunities, but as it reshapes jobs, it will reshape the skills that workers build and the pathways available to them. If we do this without intention, we lose more than jobs. We lose the routes people use to move up and the talent employers need at the other end. That's a choice, not a forecast.
(34:05)
Thank you. I look forward to your questions.
Senator Banks (34:07):
Thank you to each of you. Good opening statements. We will now move on to questioning. I retain my time for later and I will yield five minutes for questions to Senator Marshall.
Senator Marshall (34:16):
All right. Thank you, Chairman.
(34:18)
I'll let you all answer the same question here, and I'm looking for a 30- to 45-second answer, so all of you can do it. I'm a big fan of community colleges, technical colleges. So let's just assume that there's a significant number of people, probably data entry type of people that are going to lose their jobs to AI and they're going to need to go back and get some more training. They've already got a bachelor's degree. I don't think they need to get necessarily another, but what advice would you have for community colleges, technical colleges to help quickly retrain these people and pivot back in?
(34:48)
And Mr. Clark, we'll just start with you. Two or three things that you think would be helpful. Maybe there's something you assess what we shouldn't do is okay with me as well.
Ken Clark (34:58):
Yeah. Thank you, Senator. Happy to answer. For community college, the key here is Workforce Pell is going to be a huge part of the answer.
Senator Marshall (35:06):
What a good idea.
Ken Clark (35:06):
The investments are going to be made in Workforce Pell. In Indiana, we've now worked out Workforce Pell and have the opportunity for our community college, both Ivy Tech and Vincent's University in Indiana, to be able to skill up. That's going to be a big part. The university has to respond, that community college has to respond with the right training. And so they're still working on that, but that would be my number one.
Senator Marshall (35:27):
Great. Great answer too, by the way.
(35:29)
Ms. Rogers?
Carol Rogers (35:32):
Thank you, Senator. And good question. How do we retrain them when they're displaced?
(35:38)
Over the past 50 to 75 years, Congress has enacted significant legislation to help displaced workers find jobs. I am glad that we're going to be looking at that again. I would argue that each state already has employment projections. Part of the bill is to enhance those projections. I'm one of the people that argues we can enhance it with more information around wage records.
(36:14)
But I would encourage people in my state, for example, to look to the State of Indiana's already existing top jobs platform that helps show people within regions close to where they live which jobs are in highest demand and have a high wage. But we've set it up, and there's a group of people who have worked on this, so that you can ratchet it based on the capabilities of the person. So they may only have a high school degree. Look for the jobs that are high wage, high demand for those skills, and then work with them to increase it.
Senator Marshall (36:56):
Thank you. Doctor, go ahead. I'm not even going to try your last name.
Liya Palagashvili (37:00):
Don't worry.
(37:00)
I will mention what my co-panelist over here mentioned, which was in my written testimony. I think there is a very interesting overlooked low-hanging fruit solution reform, which is that Congress could restore tax neutrality between investing in machines and investing in people. Since the tax code currently makes it easier to deduct the cost of automation equipment or any other capital investment, that's easier to deduct than the cost of training workers to use that equipment or that capital. And I think that is one way to help incentivize firms and a market-based solution way to help incentivize firms to also train in workers as well.
Senator Marshall (37:44):
Thank you. Mr. Liebert?
Mr. Liebert (37:46):
Thank you, Senator. So I agree with much that's been set up here, so I'll add a couple of things that haven't been mentioned yet.
(37:51)
One, I think you're bringing up a very good question because we need to utilize the existing infrastructure that's already in place. And so I think that that's absolutely critical. So utilizing the community college system, whether it's a chamber of commerce or BBB or any of those organizations that are already there. I do think that in order to talk about this whole thing that's already in place of the re-skilling, up-skilling, certification, credentialing, it's these career pathways. And so getting more data to help us understand which pathway they're going into and which type of task they need to be taught I think is key.
(38:18)
But the other thing I'd add to the community college system is just making sure that we're doing the train the trainer. So this AI literacy component is absolutely necessary to make sure that we're getting in the hands of the teachers, the educators, the skills that they'll need to have these conversations with the students, and then also making sure that there's some good correlation and connection between colleges and universities as well as the business community to make sure that we're accessing the skills they need. This stuff changes so, so fast.
(38:42)
One of the partnerships that we're working on right now with the Better Business Bureau and the Colorado Community College System of Colorado is making sure that we're in line with some of the classes and training and formal education that they have. And then coming to the BBB AI Hub for these quick-hit lessons that are just... We're able to be a little bit more quick and fluid, but we're partnering together to make sure we're providing good, necessary, ever-changing skills and curriculum to the folks in Colorado.
Senator Marshall (39:04):
Great. Dr. Heck, give us a brief answer, please. Sorry.
Dr. Heck (39:07):
No worries. I think we need to focus on the skills that folks already have rather than assuming they need to start from square one. Most workers aren't going to go become an AI engineer. We should take seriously the domain expertise that they already have. And we should make sure we bring employers to the table so we know that we're training workers for jobs that exist.
Senator Marshall (39:24):
Thanks. A quick question for the chairman and ranking member to contemplate is they tell me we're going to lose a lot of entry-level positions, accounting. How do you get experienced accountants in if we fire all the entry-level accountants and attorneys? And It'd be interested that we keep pursuing that answer too.
Senator Banks (39:46):
Thank you. Ranking Member Hickenlooper.
Sen. Hickenlooper (39:50):
And I'll maintain my place and yield to Senator Baldwin for questions.
Senator Baldwin (39:54):
Thank you. If I get to it, I have a very similar question to the one that you just posed for some of the panelists, but I have a couple first.
(40:03)
So Wisconsin is all too familiar with the disruption that comes when Washington makes the wrong decision or fails to plan ahead. So as we consider policy and regulation on AI, we have a responsibility to working men and women to get this right. Something we have heard today is that we must have access to the best data to understand how AI is changing the workplace and impacting workers.
(40:32)
So Dr. Heck, and I think I want to ask Ms. Rogers the same question. Thank you both for being here today. One of the policy recommendations that you alluded to in your testimony is improving data collection. What gaps exist in our current data? And what should we be doing differently to better measure and more precisely measure AI's impact on workers?
(40:57)
Start with Dr. Heck.
Dr. Heck (40:59):
Thank you so much for the question.
(41:01)
I think the panel has already brought up a lot of good examples of how we can improve our data systems. I'll highlight two in particular. The first is thinking about how workers are actually moving between jobs. Much of that data we only see two to three years after it occurs. We need really current indicators to see how workers are making these moves and we need to be able to see how their jobs are changing, what they're spending their time on, how AI is coming into the picture.
(41:26)
I would also add that linking to existing systems is a really great solution. So when we think about the great data that exists at the states, how can we take that data, connect it in ways where it's more useful for everyone?
(41:37)
Thank you.
Senator Baldwin (41:37):
Great. Thank you. Ms. Rogers?
Carol Rogers (41:40):
Thank you very much, Senator.
(41:43)
Three gaps really have stood out to me in working toward understanding the bill. First, our occupational classification. Our definitional structure really don't accommodate understanding what the job is. You can't just say it's an AI job or it has AI use in it. We need to work on that and come up with definitions that are already out there among many institutions, certainly academic institutions, but also companies themselves like Meta and Facebook and Amazon. How are they defining the use of AI in their jobs?
(42:29)
Second, and to echo your point about this, states already hold valuable data about workers as well as students. And we have those data linked through the State Longitudinal Data System, or SLEDs, as some of us call it.
(42:49)
And third, we need to figure out what the firms themselves are doing in adopting AI, governing AI, implementing it into different portions of the firm. It's not a one-size-fits-all situation. And I think it's really important for us to know how they're allocating work based on how they're implementing AI.
Senator Baldwin (43:19):
I'm going to jump here. Mr. Liebert, in your testimony, you touched on how people can use AI as a crutch to replace critical thinking. And while AI can be used as a tool to enhance our productivity, we have to ensure that workers are still given the opportunities to learn and gain the relevant skills needed to advance in their careers. For instance, if AI replaces all entry-level programmer jobs, how will those displaced human beings be ready for mid-level positions? And several of you have touched upon that.
(43:59)
Let me start with you, Mr. Liebert. As employers adopt AI tools, what-
Senator Baldwin (44:00):
... Liebert, as employers adopt AI tools, what steps should they take to ensure that this technology compliments their workforce rather than displaces workers, and that employees have opportunities to develop new skills on the job?
Mr. Liebert (44:18):
Thank you, Senator, for this question. I think this is really important. This is something I hear a lot, and you probably do as well, is that will AI take away critical thinking? Will AI kind of dumb these things down for folks? And really what I see is that this is a choice. I think there are people out there that will use AI as this cognitive crutch that will do what I call hollow intelligence. They'll use AI, but they don't know what the answer means or they'll just put it out there into the world and when asked or challenged, they don't really know what it means. That's a problem.
(44:44)
I think conversely, what will happen with a lot of folks that are using it, I think, the right way is that it's forcing to prompt it well. You have to think very deeply, think very critically, kind of reverse engineer the answer that you're looking for, and then come up with information. That's a process that you can teach. That is absolutely a thing you can coach folks on. And really, even with my team who uses AI in the office, I'll give them a hard time when the answer's not good. It's like, "You took the first answer the ChatGPT, your clot gave you, didn't you?" "Yes, I did." "Okay. Well, don't do that. That's the initiating offer. You got to negotiate with it and ask more information."
(45:18)
So it's really kind of telling them a little bit how it works and how to push it further is really, really key. Again, all things that we can teach to really make sure that people are getting it, but at the same time, I think for the people that are more intellectually curious anyways, they're going to push it further. And those are the things we need to teach, not only in the workplace, but making sure that we're teaching our kids as well, our students in academia is really making sure that they're pushing this to the limit.
(45:39)
But again, this is the ability to accelerate your thinking. It should not take the place of making decisions.
Senator Baldwin (45:47):
Thank you.
Sen. Banks (45:47):
Senator Husted.
Senator Jon Husted (45:47):
Thank you, Mr. Chairman. I'm glad we're holding this hearing today.
(45:51)
I've spent most of my adult life working on economic development and workforce development issues in Ohio. And AI is about four years old. And since that time, we are now at a point, at least in my state, where the unemployment rate is almost as low it's ever been in history. We have more jobs at any time in history. Last month, we had the lowest number of job claims nationally since 1969. Doesn't seem to be having an impact on the number of jobs in the country right now, but it's certainly changing the nature of jobs in our country. And if you are one of the people that the nature of that job changed, then it's a problem for you. And so it is a very important issue. And I remember just five years ago, if you would have been to a local workforce development board meeting, how many conversations did you have about coding would be a great place for people to be five years ago, right? We said coding. And now not so much. And electricians, would we have been encouraging that? Well, I just read the Wall Street Journal article today about $200,000 a year electricians and OpenAI is trying to gobble up every one of them that they can to take to build data centers. So it changes fast.
(47:10)
And I know in working through this my whole life that it's very hard for government or an agency or anybody to keep up with the pace of change in the economy and the nature of work. And I've found from my experience that we have to help people navigate this on their own. And good data is one of the ways that we can do that. I went through this little experiment with my nephew a couple of weeks ago. He was trying to get into the Air Force and he couldn't for a variety of reasons, but he still wanted to do something in the aviation aerospace area. And so I walked him through how to use his AI to find the companies in the region that did these things, what skills they needed, where you could go get those skills and do all this. So it's a powerful tool in helping people navigate the job market in itself.
(48:03)
And I think it's important for us, you've mentioned Workforce Pell as an example of how we give people the ability to not have to go away for four years or even for two years, but to go get a workforce credential like that in a matter of weeks that would help qualify them to climb the ladder to these opportunities. And one of the things we did in Ohio is something called tech cred. What is tech cred? It gives people the ability, any adult in Ohio, to go get an in-demand credential. All they have to do is have an employer sponsor them and boom, you go get your credential. We have to be faster in how we help people adjust to the changes in the workforce.
(48:42)
And so I'll start with you, Mr. Clark. How? Well, let me finish with this. And the best way to do that is helping the educators and the employers talk to one another so that everybody. And that's one of the roles that the workforce. Tell me your thoughts on how you think both of this legislation and the data can help create those ability to, one, help people make their own decisions, help them navigate the world and get the educators and employers on the same page.
Ken Clark (49:17):
Thank you, Senator, for the question and for your thoughts there. I will say I very regularly joke about educators not really speaking business and business not speaking education. Those are the constant issue that we're working on within our community and within our region. What we find more often than not, and we are incredibly lucky in Indiana to have a secretary of education who has pushed work-based learning all the way into the diploma requirements. So what we all imagined for so long was you need a college degree. You made a mention of this. College degree is the answer. And then it was not only a college degree, you also need to have internships. You need to have experience in your resume coming out that has pushed down to high school now. We have a requirement now to get one of our SEALs in our high school diploma now that you have to have 75 to 650 hours of work-based learning coming out of high school to be able to make sure they can be employed early. It's really learning as early as possible.
(50:10)
And so we've been able to bridge some of the gap. And it's really been about education listening very closely to what's happening. Our legislature has been involved locally in Indiana or at the state level in Indiana to make sure that that's an understanding and to be business focused and business first because there is less and less. It's the idea of skills-based hiring that they need to gain these skills as early as possible.
Senator Jon Husted (50:32):
It's got to be faster.
Ken Clark (50:33):
Yes. Yes. Younger too.
Senator Jon Husted (50:36):
Because think about it. If you went in to get your college degree in four years, the entire labor market changed from the time you enrolled as a freshman to when you graduated as a senior. So we have to change the way we think about education and it has to be more of an incremental lifelong education work combination. I know I'm running out of time. I see some heads nodding. Others want to add to that.
Mr. Liebert (51:02):
I just want to add that it's like you were in my home when I was talking to my son about go do coding. And then now I'm trying to convince him to be an electrician or a plumber. So that is a real thing.
Senator Jon Husted (51:11):
Real thing. Yeah. Thank you. Thank you, Mr. Chairman.
Sen. Banks (51:15):
Senator Hassan.
Senator Maggie Hassan (51:16):
Well, thank you, Mr. Chair and Ranked Member Hickenlooper for holding this hearing. And thank you to the witnesses for a really informative discussion. I'm really grateful to all of you.
(51:26)
And Mr. Liebert, I'm going to start with a question to you because I think it's really important that the benefits of AI flow to workers and not just the wealthiest among us. And as Senator Banks and others have mentioned, he and I co-lead a bipartisan bill called the AI Workforce PREPARE Act. Among other things, it would help hold large corporations accountable by requiring companies to publicly disclose when they fire employees in mass layoffs in order to replace those employees with AI. So why is transparency in layoff decisions critical to our understanding of the AI's impact on the workforce? And how can this transparency help in developing effective protections for workers?
Mr. Liebert (52:10):
Thank you for that question, Senator. This extremely important. Right now, there's a lot of misinformation out there and a lot of fear. The media and the headlines kind of tell us about all these mass layoffs that are primarily coming from a couple different companies in very specific sets. And so I think with the PREPAREs Act, so support everything you're trying to do with that. Thank you for putting that together. It's very beneficial because it will kind of create one, the transparency that we need, but also the data. So if we learn what jobs are actually going away, what dislocated workers are doing, that'll kind of help us be able to figure out what are the skills we need to train on and be more specific and precise with this. And again, this is going to move very quickly. It already is as we know that.
(52:47)
But again, I think having more specific information in these specific areas to be able to know and give that back to employers, but also specifically the school system so they can obviously help with that retraining and the upskilling that's going to happen from a lot of this displacement.
Senator Maggie Hassan (53:02):
Well, I appreciate that. And that also kind of leads me to my next question, which is for Mr. Clark and then you, Mr. Liebert. Senators Young, Collins, Kaine and I have a bipartisan bill called the Gateways to Career Act that would fund local workforce partnerships to create and scale career pathway programs for training workers. By design, community center programs like this are nimble and responsive to local industry needs. They meet workers where they're at in their careers. We've talked about the importance of career pathways and how they may change with AI. But what I'd love for both of you to do is just talk about what role you see for career pathway programs in helping workers, both new and established in their careers, get the AI skills that they need to succeed.
(53:46)
You've touched on it a bit. I'd love to hear a little bit more. Mr. Clark?
Ken Clark (53:50):
Thank you, Senator. Yes. There's no doubt that those types of programs, those community-based programs that are really looking at the DNA of a local region and thinking through with employers at the table, giving you what those skills need to be and how we build out that with our education partners, K-12, community college. There are great examples where we have little bits of this all over the country, but something that's larger that would allow us to do this with all of our growing industries that we know are resilient would be critical for us to be able to be more effective as a workforce board and intermediary. And there are many partners at that table, right? This is also my state chamber of commerce, my local chamber of commerce, our local economic development. We could all be at the table with businesses listening and I think we could gain a lot by doing something like that.
Senator Maggie Hassan (54:32):
Great. Mr. Liebert, in about 40 seconds, please.
Mr. Liebert (54:36):
So I think we understand now that when used properly, AI can kind of level individuals up. It's the same thing for a company, for a city, for a state, and for a country. And so I think this is absolutely critical, but again, it also is dependent upon the different type of ecosystems, infrastructure and industries that are in these communities. So going back to the communities where this is at is absolutely vital. Again, we don't need to rebuild the entire system for this. A lot of it's there. So again, focusing on those career pathways because it's going to be all over the place, I think is wise versus kind of this one size fits all that doesn't make sense for AI. We've got to be very careful and very strategic as we deploy these types of education.
Senator Maggie Hassan (55:13):
I appreciate that. Thank you. And Dr. Palagashvili, I want to just drill down on something. A couple of the other witnesses were asked about data gaps, which I thought was really important. And each of you today has highlighted how timely data on job losses, occupational changes and industry needs can help us understand AI's impact on the workforce and help inform efforts to protect workers. And we've had testimony about what some of those data gaps are. My question is, what specific data gaps at the federal level are the most time sensitive for us to address?
Liya Palagashvili (55:48):
Thank you for the question, Senator. I think one of the most important things that we can do is linking some of the business surveys asking about AI to actual hiring and wage outcomes so that we can compare AI using and non-AI using firms directly. And I have 10 seconds, but I-
Senator Maggie Hassan (56:06):
You're fine.
Liya Palagashvili (56:07):
We've seen that administrative records are the best on this, but they're not as timely as we need them to be. And also they're not directly linked to some of the surveys asking about AI usage. So if we can link those, that would help a lot of, and all of the co-panelists here are probably in agreement on that. That would be one of the best things that we could do.
Senator Maggie Hassan (56:26):
I really appreciate that. Thank you. And thank you, Mr. Chair.
Sen. Banks (56:29):
Thank you. I yield five minutes to myself.
(56:32)
Mr. Clark, Indiana is the crossroads of America, Middle America, and you work in central Indiana. What trends do we see that are specific maybe to where we come from? And do those trends lag the rest of the country or are they a pulse that the rest of the country should be paying attention to?
Ken Clark (56:51):
Thank you, Chairman. I appreciate the question. Yes. Hyperlocal, my job is hyperlocal. I'm involved in Central Indiana and I look at the Central Indiana market from an employment perspective. And then from a resident service, I'm obviously focused in Marion County and Indianapolis specifically. What we're seeing that I think compares to the rest of the country is that every region has their own unique set of industries. Some are more resilient than others. Some are more likely to be automated or to have AI displaced jobs. We've all talked about that today. Within Indiana, our largest sector is healthcare. Healthcare, without a doubt, will continue to be incredibly resilient. We need nurses badly. And AI automation's going to help support that work by allowing a nurse to spend more time in using their clinical judgment than filling out paperwork that is changing drastically. And as we see technology roll out with that kind of capability to automate some of their work, that's going to be incredible. Healthcare is the largest industry in most major metropolitan areas across the country because of our aging population. So that's going to ripple across the country without question. That's not just Indiana.
(57:56)
Unique to us in Indiana, and a number of other cities too, are things like hospitality, transportation and logistics. A number of us have a large market where we're trying to fill those jobs. We struggle to fill transportation and logistics jobs even though we have plenty of those jobs. A lot of it's about getting employers to agree on what it is specifically they're looking for, what the skills are in those jobs. And Amazon treats those completely differently than FedEx does. Moving between these different organizations is difficult sometimes. And so understanding how AI is going to disrupt that is important for all of us. But I would say some of this is specific to central Indiana too, that we are focused on those specific industries that we know are going to be disrupted most.
Sen. Banks (58:36):
Ms. Rogers, would you say those trends lag the rest of the country in a Middle America, Rust Belt state? Are those trends that are following the rest of the country or should the rest of the country be looking at the trends that they see coming out of Indiana?
Carol Rogers (58:51):
I would argue that what I have seen in the Midwest is that we're really kind of right in the middle, of course, crossroads of where the nation is as a whole. We see the coastal states, Virginia, South Carolina, Florida having much higher rates of uptake in the use of AI in business firm functions than we do in the plain states in the Midwest. But many of them are starting to catch up, even advancing past California, which was an interesting finding with those Census Bureau data.
(59:35)
I think part of the challenge that I see for businesses, and I'll talk about Indiana specifically, is they really don't know what each other is doing. And they don't have data about what they're doing. How quickly are you adopting it? How much are you using generative versus agentic? I will tell you that Indiana University, we have been up in the AI Kool-Aid a lot in a very structured way to get students, faculty, staff using it knowledgeably, governing their use, protecting the data. How many companies know how to implement? And I think that as much as we need to have retraining of workers, we need to retrain business leaders as well in terms of what it can actually do for them.
Sen. Banks (01:00:32):
Mr. Clark, can you talk a little bit more about what your members, businesses are asking for from you? What do they need?
Ken Clark (01:00:41):
Yeah. More often than not, we're hearing that they need entry level employees having some type of experience to start, being job ready. Truly with some of those job ready skills you'd expect. A lot of us learned them in our first job. You learn how to be on time. You learned how to use good judgment. You learn to listen to a supervisor and to work as a team. All of those types of things are the things I hear the most that they feel like is missing as people are coming out of school and going into work. And so now with AI, I think that they're expecting even more of an entry level role than they used to. And so this idea of work-based learning and learning early in high school and in college enough is critical for people to be successful now.
Sen. Banks (01:01:20):
Got it. Senator Kaine.
Senator Tim Kaine (01:01:26):
Thank you, Mr. Chair and Senator Hickenlooper, and what a great panel. So just a couple of things. So Dr. Palagashvili, I'm really glad that you mentioned the disequity in the tax code where we reward companies for investments in capital, but not in human capital training. Senator Warner has long had a bill to try to equalize the depreciation schedules for those kinds of investments so that we don't advantage capital investments over human capital training investments. And I'm glad that you mentioned that. One of the things that I have been really grappling with as I've been listening to you is kind of Mr. Clark's statement at the beginning of the worry of knocking out the first jobs on the ladder so that people can't learn what they need to climb the ladder. And it does match up a little bit with some recent employment data suggesting that the unemployment rate among young adults is ticking up while others are ticking down. Both the 18 to 24 year olds, but also the 24 to 30 year olds who are finishing college. And the New York Fed just did a study that was interesting. They did not yet find that AI was a big generator of that. Although this issue of knocking out the first rung on the ladder would make us want to watch that trend. But what they found actually was remote work was a significant reason for it because companies that want to go into remote work would prefer to hire folks that they don't need to mentor because they've already gained the skills through mentoring. So if you're going to do a remote work thing, well, I need to really mentor that first time worker, but others who've done it already, I don't need to mentor. And it turns out that that is for young workers.
(01:03:06)
So I'm very worried about this youth effect. Nothing would be worse to have a society where young people, especially starting off their careers are unemployed or underemployed. And so we have to kind of think that through. And so I hope we'll grapple with that as a committee.
(01:03:24)
I was thinking, what is an area of work where the young people will never be pushed aside by AI? And I thought the military. We're never just going to say, we only need sergeants. We don't need privates anymore. We will continue to bring in newcomers. And so I'm on the Armed Services Committee and it might be a really interesting thing for academics, think tanks, employers to study because the military is extremely intentional about personnel and training. Everybody gets an MOS, their military occupation specialty, and everybody gets trained in that MOS. And I know the different branches of the military are trying to incorporate AI into that training.
(01:04:05)
And so a system-wide study of the way the military is using AI for that very entry level, that 18 year old to advance in their skillset and probably works really well in some MOSs and maybe others not quite so well, but it would be a fertile field of study for like a million plus people to see the way AI is being used to augment military training. And it's also, I think, going to end up being a real advantage that folks who've been in the military may have when they get ready to transition into the civilian workforce. I have been in a workforce where what I have been doing has involved pretty significant interaction with AI tools at every step along the way. I think that'll be a positive for military members as they transition.
(01:04:51)
But I don't know, I've got a minute and a half left. Does anybody want to just offer a though about how we should try to focus on the needs of young people so that this squeeze of whether it's remote work or the first rung of the ladder disappearing, we're not losing a generator... Depressing the hopes of young people that they're going to have meaningful careers. Ms. Rogers, you were wanting to jump right in.
Carol Rogers (01:05:14):
Thank you, Senator Kaine. I think one of the things that we need to consider is one of the things happening is in terms of demographic trends. We are having fewer proportionally young people moving up. In some ways, AI could wind up helping us mitigate the slowing population gains that we have in the younger population, while we have a larger gain in the elderly population. So I think part of what we can do is think about AI not as a thing, but a set of opportunities with knowledge that we can apply to challenges. We don't talk about-
Carol Rogers (01:06:00):
... two challenges. We don't talk about the arts and creative employment, and yet what we have seen through Bureau of Economic Analysis data over the past few years is a significant, small but significant growth, continuing growth in Indiana among those creative worker positions. And one of the things that we ought to do is start thinking more creatively or more globally about what is in demand in our neighborhood, in our regions, in our state around not high knowledge occupations or skilled trades, but what about some of these in the middle that we're not really paying-
Tim Kaine (01:06:51):
And I'm over time, but I would just say as the kind of surprised father of two working artists who are quite confident that their work will never be replaced by AI, I'm really glad to hear you say that.
Sen. Banks (01:07:04):
Thank you. Senator Blunt-
Carol Rogers (01:07:05):
I could say they will use AI though, but not be replaced.
Sen. Banks (01:07:11):
Senator Blunt Rochester.
Lisa Blunt Rochester (01:07:13):
Thank you, Chairman Banks, as well as Ranking Member Hickenlooper for allowing me to wave onto this committee. The conversation is important and riveting and timely. I must say, I'm a person who is generally a very hopeful person, and the conversations around AI a lot today are very fear-based. A lot of people have a lot of concerns about losing their jobs. Artists have concerns about there's a sole artist out there making more money than people who actually have souls. So it's a challenging time when we talk about AI. And also as a former secretary of labor from Delaware, I was around when the workforce investment boards were first established under WIA before WIOA. And so I have so many questions for you in so little time. One question that I have for Mr. Clark, which I'll come back to, is workforce investment boards, are there changes that we need to make in light of these changes in technology?
(01:08:20)
So that's a question for you. You can write it down. You can answer it later. Dr. Palagashvili, I have a question for you. We've all been talking about the gaps in the data. And I'm just curious, are there places that you right now, sources of data that you use to help predict and plan now or sources that we don't want to stop collecting, that we need to continue to collect? And that's probably for the entire panel. So I'll start with that question. What are we getting right and don't want to stop in terms of getting data?
Liya Palagashvili (01:08:59):
Thank you. Thank you for the question, Senator. The data sources I rely on are almost all federal statistical products. So I'd say we should definitely continue those. They're really helpful for researchers like myself, and I think the co-panelists here would all agree. And one of my own recommendations today is adding occupational details to the federal quarterly workforce indicators. I'd note that the Results Act is also pursuing the identical missing piece occupational codes attached to wage records at the state level. And I think those two efforts would compliment each other well.
Lisa Blunt Rochester (01:09:31):
Thank you.
Liya Palagashvili (01:09:31):
Yeah, that would be really helpful. And if we want to name specific surveys, we use the current population survey. The Census Business Formation Statistics are some of the two that I've used in my own research that I highlighted here, as well as the annual business survey and then the BTOS for adoption context.
Lisa Blunt Rochester (01:09:48):
Thank you for highlighting the Results Act, which I am partnered with my colleague, Roger Marshall. And it's a bipartisan piece of legislation that will support states as they modernize and integrate data systems to answer the important questions, really looking longitudinally at how does AI impact work, school and beyond. And so I hope my colleagues will join me in that. I think I saw heads shaking in terms of the data sources. And if you have more comments, we can do that for the record. But I want to switch gears. Last year, Black women experienced one of the steepest one year employment declines in the past century, past quarter of a century. And last week, we marked Black Women's Equal Payday, which indicates the amount of time that it takes a Black woman to earn equal her white counterparts since last year. Analysis from the National Partnership for Women and Families found that women make up over half of workers that are most AI-vulnerable in the most AI-vulnerable occupations with women of color making up nearly a third of workers in AI-vulnerable jobs.
(01:10:59)
Dr. Heck, in your testimony, you focus on worker mobility. What can you share with us about how the economic mobility of women and people of color in the workforce might be impacted by AI?
Dr. Heck (01:11:14):
Thank you so much for the question. I want to introduce a concept of adaptive capacity. It's this idea of how well any worker can weather an involuntary job loss. And so in the moments where AI exposure does lead to job loss, not all workers can handle that to the same degree. Some workers will find it harder to see their skills transfer and to be able to weather up that financial storm. The workers who are in gateway roles are often women and workers of color. And those are often among the most exposed roles. Women are 93% of secretaries and administrative assistants. 49% of customer service representatives are workers of color. Nearly half, 46% of Black women stars earning median wages or higher are in gateway occupations. We need to think about these pathways and how we can strengthen them and think about the new ones that we'll build alongside them.
Lisa Blunt Rochester (01:12:07):
As a follow-up, I would love it if you could follow up with any strategies that you would recommend or any others on the panel, that would be really helpful. And we're also doing work on updating the Warren Act. And so particularly as it relates to AI and unemployment, folks that are facing layoffs. So would love to follow up with the panelists. And thank you so much again for allowing me to wave onto the committee and I yield back.
Sen. Banks (01:12:35):
Senator Hickenlooper.
Sen. Hickenlooper (01:12:38):
Thank you, Mr. Chair. And again, I'll thank each of you. What a great panel and so diverse and so thoughtful. I do think it's worth pointing out, Senator Banks, you asked a couple times whether Indiana was lagging or ahead. I spent a fair amount of time on workforce and educational issues when I was back in Colorado. And Indiana is right among the top in terms of innovation. And to hear that you're going to require 75 hours of on the job training as part of the high school degree, we worked very hard to get... We got rid of the college degree requirement for over half the workers in the state of Colorado, but it's a battle. These are efforts that go on. And I love that several of you have alluded to this arc of a lifetime of learning skills and that that's got to be explicit, that people have that expectation.
(01:13:37)
That's one way we could do this. Let me ask the first question, Dr. Heck. And I was thinking today, I was talking to a lawyer back in Denver, a guy named Ayers. And he was looking at, he thinks that there's going to be a real issue on what happens with you're not going to have enough, that first rung lawyers, how are they going to get the training to be professional lawyers? Obviously lawyers are always, they provide judgment that I think AI is going to take a long, long time to displace that sense of trust. But those young lawyers, you're not going to get as many. But it's also possible, and I guess not just Dr. Heck, but all of you, doesn't it make sense that we could imagine these young lawyers, we're asking more of them to learn AI and to be able to service more of the senior lawyers. And as we have a smaller number, those young people who we burden with more responsibility will actually grow faster. I think we learned that from history. So anyway, why don't you go down the line? Is that plausible from your perspective?
Ken Clark (01:14:43):
I think it's possible. It definitely depends on industry as we've mentioned before. But I would say in the attorney's space especially, AI's ability to reference case law and learn and provide you productivity gains as a new attorney is really something that usually you would gain later. You still have to learn that. The value of an attorney who understands and can make the judgment based on all the case law they know, that is really one of those differentiators. Lots of different kinds of attorneys, but there's no question that it could play that role too. Yes.
Sen. Hickenlooper (01:15:17):
Ms. Rogers?
Carol Rogers (01:15:20):
I think the possibility exists there as it does in medical and health positions, accounting, where actually the price per hour, and I apologize to any attorneys here, but I'm married to one, so he might have something to say. But bring down that price per hour charge. The cost that is becoming prohibitive for some people to be able to hire a lawyer or go to a doctor or see a therapist. There are a lot of positions who don't have an accountant do their taxes. Let me-
Sen. Hickenlooper (01:16:00):
I want to walk-
Carol Rogers (01:16:00):
Oh, go ahead.
Sen. Hickenlooper (01:16:01):
Make sure I get everybody to have that moment.
Liya Palagashvili (01:16:04):
Thank you, Senator, for the question. I think that's definitely possible. I just want to reiterate that one of the key things is that in law or other fields, AI can automate some of those tasks, augment others, raise productivity. And so it remains a little bit unclear what will happen in the future. And I think it also depends on the sectors, industry and occupation.
Sen. Hickenlooper (01:16:24):
Right. But so many of them, I think we've seen what we see in lawyers, it's going to be in a bunch of different places.
Liya Palagashvili (01:16:29):
Yeah.
Sen. Hickenlooper (01:16:29):
I didn't get to practice. Palagashvili. So ready-
Liya Palagashvili (01:16:33):
It's perfect.
Sen. Hickenlooper (01:16:33):
Mr. Liebert.
Mr. Liebert (01:16:35):
So I also agree. I would just add another piece to this is that context in all these cases is so critical. And so there are individuals that are going to have this context, this experience. That counts for a lot. So just having somebody in who has come in and understands the basics of it, who's highly intelligent is beneficial, but the person who's actually been in that courtroom, been in that doctor's office or whatever, the context is absolutely key to this. And so I tell a lot of folks that I teach that AI is approaching this genius level intellect, but treat it like an intern, smartest intern you've ever had, but you got to give the AI context. And so just putting that in there, that context is key for all this and that counts for a lot.
Liya Palagashvili (01:17:12):
Dr. Heck?
Dr. Heck (01:17:13):
I think it's certainly possible. Learning requires friction and time. AI reduces both. And so I do have concerns about the hollow knowledge that was introduced here. There's also concerns around the mental load. Early research shows that overseeing AI agents is an exhausting process. And so when we think about trying to raise folks up to stay in careers, we don't want to burn them out early.
Sen. Hickenlooper (01:17:36):
Although I've also heard that that's because it's so new and that as they get further into it, it's not as exhausting. You probably have better data than I do.
Dr. Heck (01:17:46):
I think that's certainly part of it. I think folks are balancing more plates and the mental load of the task switching can add up as opposed to deep work on individual issues.
Sen. Hickenlooper (01:17:58):
Absolutely. Last thing I'll leave, I've got other questions that I'll just send in writing, but I do think we don't have data on measuring how well some people are going to adapt to AI and the productivity, what they actually provide to the company. Whatever it is they're doing, they're going to take a giant leap, whereas others having the same tool are just not going to be able to use it as well. And I think we're going to have to measure that to really begin to predict what we need to be ready for.
Sen. Banks (01:18:31):
Thank you to the ranking member. Thank you to all of our panelists and guests and to our staff for arranging this great hearing, a great conversation. I thought it was a very productive committee hearing today, but I am biased because I chaired it. But if there are no further questions, the panel is now excused. I ask unanimous consent for statements from the Society of Human Resource Managers, the Taxpayers Protection Alliance, and the Sutherland Institute to be entered into the hearing record without objection. For any senator wishing to ask additional questions, questions for the record will be due at 5:00 PM on Wednesday, August 12th. Thank you again to all of you for joining us today. The subcommittee is now adjourned.