Should We Tax Artificial Intelligence?

AI is everywhere, and now it's in the tax policy debate. In this episode of The Deduction, hosts Kyle Hulehan and Erica York sit down with Alex Muresianu, Senior Policy Analyst at the Tax Foundation. Together they examine what current labor market data actually shows, why proposals from Senators Sanders and Kelly risk backfiring, and what smarter reforms like worker retraining deductions and consumption-based taxation would strengthen the tax code no matter how the AI story unfolds.

Connect with the Guests

Kyle Hulehan — Host, Senior Marketing Associate and Creative Producer Tax Foundation: taxfoundation.org/about-us/staff/kyle-hulehan 

Erica York — Co-Host, Vice President of Federal Tax Policy Tax Foundation: taxfoundation.org/about-us/staff/erica-york Twitter/X: @ericadyork LinkedIn: linkedin.com/in/erica-york-a68ab474 Substack: ericadyork.substack.com

Alex Muresianu — Senior Policy Analyst, Federal Tax Policy Tax Foundation: taxfoundation.org/about-us/staff/alex-muresianu Twitter/X: @ahardtospell LinkedIn: linkedin.com/in/alex-muresianu-2b1802181

Related Reading

• "When Taxing AI, Don't Reinvent the Wheel" — Alex Muresianu, Tax Foundation
• The Deduction Podcast
• Questions? Email: podcast@taxfoundation.org | Twitter: @DeductionPod

Transcript

Kyle 0:00

There is at least one super niche AI tax that I would like, which is, I don't know. I'm sure you guys have seen this, is that there are. podcasts and as a podcast host, I find myself vaguely concerned about this. We created an outline for this podcast and I was like, oh man, I wonder what would that podcast would be like if we fed it to them? And I would like, maybe we just need to tax that. Like all AI podcasts get heavily taxed and we maybe just push those down for a little while so I can at least retire. Yes. But that's actually a real.

Erica 0:32

but I, I think we can compete. I, I think people will like us better than an AI SLAP podcast.

Kyle 0:38

I'd like to think so.

Alex 0:40

I believe, Kyle, you have many, many valuable skills that would, would make you, um. Valuable, uh, uh, uh, contributor in other forms if such, if such a, a technology, um, was spread.

Kyle 0:53

Thank you. I appreciate that. hello and welcome to the Deduction of Tax Foundation Podcast. I'm your host, Kyle Houlahan, and we are back today with another episode. And I'm joined by my co-host, Erica York, and we're joined by Alex Muresianu, senior Policy Analyst at the Tax Foundation. all right, so here's the deal. AI is everywhere right now. It's like, I think you guys saw the Super Bowl, right? Like the a, it was all ai, which is kind of crazy. It's in the headlines every day, all the time, 24 7. but now it's part of the tax policy conversation. And so, you know, Alex, I'm wondering, know, do people need to know about this and, and where the debate stands on taxing ai.

Alex 1:36

Yeah, so I think there are a lot of different angles that people, uh, um. Come to the AI policy conversation. Um. And there are a lot of different proposals out there that we can, we can get into. But generally the angle that at least I'm sort of most interested in is a sort of purely economic one. Uh, about how AI will, uh, or will not, uh, change the future of work and how it affects sort of basic, uh, uh. How we produce goods and services, sorts of questions. And also what does that mean for, for, uh, employment in the way, uh, work works. Um, and so I think the, the driving concern, uh, for a lot of these proposals relates to how, um, artificial intelligence will change, uh, or potentially replace, uh, human workers in various jobs. Uh, and, uh. Usually that's the focus of policy proposals, uh, to specifically target ai. The point that I, I think I'll, I'll probably make a, a couple times in various forms, is that like a lot of things that are AI might already be taxed. In other words, if you're thinking about profits from ai. Those are covered by the corporate income tax. you know, the, the particular concern here is, is sort of bespoke, uh, policy making that's sort of targeting, uh, whether it's, uh, investment in, you know, data centers or just, or revenue perhaps from AI products, no, I'll use the word again. Bespoke, bespoke policy specifically related to, um. Yes, it's a good word. It's a good word. Although I felt like saying it again, reminded me that there's a Veep episode where everybody uses the word, um, robust, um, in like three different meetings and then it becomes like a news story.

Kyle 3:39

So what are people in particular most worried about?

Alex 3:43

A lot of science fiction stories, of course, uh, uh, talk about how machines will, will, like replace humans. And in the most extreme case, that has been covered in a few sort of, um, theoretical economics papers, uh, recently, and it is an interesting sort of theoretical exercise, at the very least, um, is that artificial intelligence will replace like all human labor as like an input in the economy. That's a, a sort of pretty extreme example, and I think people have predicted that technology would end, you know, uh, uh, human labor for a very long time like that. That's a, a, a prediction that has kind of failed, um, many, many times before. Um, to be fair, you only have to be right once, uh, for that one, but at a slightly less extreme level. The concern is more that that large portions of, uh, what people might call, like knowledge work or, or white collar employment, um, will be, will be replaced because all this technology, um, makes the work sort of much, much easier to, to, uh, a finish. And that this rapid productivity increase will replace, uh, a lot of human workers and the. The thing is that like, well, at the very high level, we don't know what the future holds. Um, but at a more specific level, we don't know how technology that makes a sector or, uh, a certain type of work, um, more productive. More productive, or. More efficient. We don't actually know what that means for employment, uh, in that particular sector. Um, there are story that there, there are sort of two, uh, terms to think about here, uh, that people sometimes use. One's bowel, mals cost, uh, cost disease, and the other one's Jevons Paradox. Um, those are just, just term good, good terms to know. But like the, the bowel mo cost disease story, is that like as. Some sectors get more productive, they kind of shrink, as a share of employment. fewer people work in them because new technology means you can get like a lot more, uh, uh, done with fewer people. So like a good example here might be like agriculture. Um, like we've gotten a lot more productive in producing, uh, uh, food and. The share of people who work in agriculture has declined dramatically, uh, over the past, you know, 200 years. That's like one end where we're getting better means fewer workers. The other end of the spectrum, I think would be like software or data analysis. I think where the technology for doing data analysis is so much better than it was in say, 1970 We have way more people who like do sort of data analysis or software, uh, now than did back in the 1970s as like a very direct example. Um, Tax Foundation has like software engineers, like I do not think that we had that in the eighties. Uh, for instance, like baseball teams. Baseball teams. Now, every baseball front office has like an analytics department where they have a bunch of, uh, uh, uh, you know, uh, stack geeks pouring over these sort of advan new advanced metrics that didn't even exist, um, you know, 30 or 40 years ago. Uh, and so what it boils down to is like how much more of something people want. Sometimes new technology opens up new markets and new applications. For certain types of work and that that means more employment in that sector and sometimes it replaces work because people don't actually want that much more of whatever this stuff is. So ultimately that's to say that one things are ambiguous, uh, and, and in terms of how productivity growth affects employment in a particular sector. And two, the big picture claim that. All of human labor would be replaced is quite an extreme one, and it would make sense to think about AI in more of the terms as other periods of technological change.

Erica 8:13

so we're at this like early stage where we don't know how this new technology is going to affect the labor market, but there are a lot of fears that it could be extremely disruptive. We've got senators, we've got some economists, we've got even AI company CEOs. Proposing these really targeted taxes that could try to slow adoption. is that kind of getting ahead of where we need to be right now? What's the evidence for like labor market disruption today and does that justify like new tax provisions targeted AI right now? Or what? What should we be thinking of and what, what do we actually know? Like today in 2026?

Alex 8:54

there are a whole host of, um, uh, labor market sort of indicators that one could, could comb through and, and probably put together a, a compelling narrative once you've gone through enough of them to say that something, something, you know, big is happening. But the. Big picture for most of the headline numbers is, not indicating a mass wave of, of automation. Um, the, you know, unemployment rate is lower than it was for the vast majority of the 2000 tens. Uh, labor force participation is at, you know, close to a, a, you know, 20 year high. Um. You, you know, so those are like the most basic high level, um, uh, employment indicators. Um, the one that people sort of most often, um, you know, rattle, the rattle the SARE about is the low rate of like entry level white collar work or, or like low, um, job hirings particularly, and, and software. Um, but the. Sort of confounding factor here is that there was this sort of massive hiring boom in those sectors in, in like 2021 into 2022. Um, and. The sort of low hiring rate is mostly I, I think a reflection of those, um, decisions that, that, you know, you had, um, you pulled a bunch of hiring to 20 21, 20 22, and now you're hiring last because you walked all those people in and it's, um, not confirm morale to just lay everybody, uh, uh, off if you, you were hired. So you just avoid hiring new people. Um, and so I. Like, like I sort of said, about like uncertainty. Like this is not like proof that, that some massive wave of automation could come in the future, but to say like, it's here and we need to like design some crazy new policy because, uh, uh, you know, the, the writing is on the wall for all this stuff. I think that is a, a pretty extreme reaction to existing evidence.

Kyle 11:10

Yeah, and, and obviously. We don't wanna completely invalidate the fear around this. This is obviously, is a very new thing and it's a very real massive change in all of our lives. Um, and so that, that makes sense. I understand some of the fear, but, but what do you see as like the, what are the main tax proposals out there right now and, and who or what is driving those?

Alex 11:31

there's a, a category that I think of as explicitly targeted at the employment issue and or the employment issue, I think is the, the driving focus of a lot of them. The intent, uh, of the policies might vary. So, uh, the two, uh, um. Proposals that I highlighted in the, uh, piece, uh, for tax foundation that I wrote are on the one hand, uh, Senator Bernie Sanders has proposal to, um, both tax like AI profits and also, uh, to. Uh, get rid of deductions for, uh, investment in equipment. So that's covering physical automation as well as sort of digital automation. And, you know, the Sanders perspective is explicitly like, this is a problem. This is going to, you know, replace workers and like, we need to stop. The, uh, uh, replace, you know, you know, we, we just need to, to penalize these investments to, to prevent them from happening and prevent the employment disruption from happening. Then the sort of other perspective is not as, uh, sort of ideologically like motivated. It's more oh. It's good that we have this new technology, but it will come with downsides or, or, or some people will be disrupted. Or, or, or, or, you know, you, you might have some sector level unemployment and the proposed answer is to sort of fund programs, uh. Four people who are, are disrupted through some sort of tax targeted at the industry. Um, this is the, uh, Senator Mark Kelly proposal. Um, and the details of, of that proposal, at least when I, I wrote the piece. Maybe there's something that has come out that's more fleshed out that I, that I missed. Um, but his proposal, basically some sort of tax on, on industry revenue. Um. And so I think Kelly's thought process is a little bit different and a little bit more reasonable. However, I wouldn't be confident that the tax designed to just ameliorate some of the issues wouldn't itself disincentivize a new investment. Um, you know, again, the details aren't out there, but just because your intentions are a little bit different doesn't mean that you wouldn't have the same effect of, of slowing down a technology adoption.

Erica 14:03

Sometimes when we, we hear. Proponents of of AI taxes talk. And this has parallels to the way, like other conversations go on, like the, the trade policy space and what do we do for the manufacturing sector. And there's kind of this like long thread of thinking that the tax code. Favors capital over labor. And so we need to, you know, change policy to write that, to make sure that we're not incentivizing investment here over investing in workers. Can you speak to that and, and what's actually the case there?

Alex 14:37

Yeah, so you know, the biggest picture, uh, illustration of this is, uh, how companies deduct certain kinds of costs, um, and. And you know, just about, just about every case, uh, companies deduct the cost of like worker salaries immediately, our wages and salaries, uh, immediately. Uh, while often they have to spread the. Costs of, of capital investments, uh, out over time. Um, now there are some provisions that are, are currently in effect in, in, in us, uh, tax law, na, many of which are relatively new, that allow for the, uh, full deductions for investment. Um, the, uh, uh, introduction of. A hundred percent bonus depreciation for equipment, um, expensing for research and development. Immediate deductions for r and d investment that has been brought back into law. Um. But those just put those investments on a sort of level playing field with, um, you know, worker compensation. Um, and not all investment is eligible, uh, for those provisions. Uh, and so if anything on the whole, um, that tax system kind of dis favors a, a, a capital investment. Um, but I think the, the point about how. This links to other debates about like displacement, uh, of which, which is usually wrapped up in, in at least historically related to manufacturing jobs or, um, uh, you know, I know our, our, uh, our producer talked about, uh, our produ, our great, great producer Dan, uh, talked, uh, talked to us in our, our prep call about, um, history of the coal industry in West Virginia. You know. There are, uh, uh, precedent for or localized disruptions, uh, uh, to, uh, um, uh, employment and, and, you know, general economic prospects related to economic change and technological changes. Um. But those are, are sort of unprecedented. And the, the answer wouldn't be just to try and like slow down change it would be to figure out how best to, to ameliorate it. We have, you know, some experience with that and, uh, to, to think through. There are lessons to be learned.

Erica 17:13

So rather than slow the adoption of new technology, find ways to directly help the workers who may be impacted. Rather than saying, no, we're gonna freeze technology in place. It, it reminds me of a line from a paper, um, that was looking at, you know, the. The decline in manufacturing jobs and looking at whether technology or trade was a bigger contributor. And this particular paper concluded it was technology and it made the argument and has the line, like if you wanna go back to higher levels of manufacturing employment, pretty much the only policy solution is to smash the machines. Um, so I don't think. We should be at a point where we're saying, yes, smash the machines or tax the machines to slow adoption. It should be more of an openness to innovation and to growth, also acknowledging that there are other policy tools maybe that, that we could look at.

Kyle 18:06

a lot of this feels like it's, it's largely based on, there's a lot of fear around how, what will happen to labor. Most of this, like most of this conversation that we're having is fear around labor. So how could reforming maybe, you know, unemployment insurance or raising some of those caps or worker training deductions or something, you know, how could that maybe, you know, help,

Alex 18:27

I would say the sort of best way in, in principle to address, um, the disruption that introducing a new technology, uh, would have is to make it easier for people to. Transition to doing something different, uh, or in a different, and, and put in a different way, sort of lean into different skills, uh, or, or, or applications for their, their, uh, you know, alternative applications for their existing sets of, of skills. we're the tax foundation I'm focused, focused on, on tax angles. And I don't mean to say that this is a, a comprehensive policy menu, but I think these are the, the relevant policies in the tax code to think about. Um, the first is unemployment insurance, um, unemployment insurance in the United States. Uh, the tax rates. Are, uh, uh, you know, vary by employer and relate to their experience with the unemployment system. And the sort of justification here is that, and, and, and you know, your rates go up if you have more unexperience with the, the unemployment system, which is means that like, you know, you've. Fired people, uh, uh, before, and, you know, the, the thinking there feels very, very intuitive. It's like we don't want people to, um, be, be laid off and so will tax companies more that are, are laying people off. But I think the, the. Real effect here is that people are, are, are firms are like more worried about, uh, risky hires than, uh, uh, they would otherwise be because they know that they're, if, if somebody, you know, oh, this, this, this candidate has a lot of potential, but also. Might really not be a fit for this role. Um, they know that they may well face a tax penalty in the future if the, that just isn't right. Um, and so I think that's a, a particular concern for people who are looking to change careers, uh, or. Looking to move from, from something, um, uh, that, you know, might only be tangentially related to what they previously worked in. And they might, you know, think that, that this, this, you know, I, I really couldn't apply my skills, uh, in this other, other career path. Um, and so, you know, if you're worried that new technology that is coming down the pipe will, um. Make certain forms of, uh, certain skills or certain particular occupations sort of, uh, largely automated away then. This policy, the, the basing, the unemployment, uh, uh, tax rates on experience rating could sort of dissuade companies from taking a cha taking chances on people who are looking to, to shift careers. Um, the other, uh, uh, angle would be how, uh, of a tax code treats, uh, company investment in, uh, worker training, and particularly training for new roles. Um, there's a cap on the deduction for. Investment in training for existing roles. It's a non-deductible, uh, for training in new roles. part of the reason I guess, uh, to, to like justify why that policy would. Where it is. Like there are you, you do, you do sometimes worry in, in the tax code of having sort of non uh, uh, taxed, uh, worker compensation. So I think that that's the sort of original like thought process of, not having ways to do like non wage compensation. That's, that's UNT taxable. Um, but. The effect of not having this, this deduction available is that there isn't, uh, much of an incentive for companies, uh, or the very least there. There's a disincentive, I guess, for companies to retrain workers who may be, are no longer, um, you know, productive or necessary in their original role, but may still be like, you know, you think you're, they're like solid workers who, who are like diligent and will. Um, might be fits for alternate employment in the company. And so, um, those are two sort of option, the employment insurance and tax treatment of worker training or retraining. Um, that. Those are like t like, like policy changes in the regular tax toolkit. Um, that would be sort of sound structural improvements sort of regardless of what, uh, uh, happens with, uh, uh, artificial intelligence, which again, there's a very wide spectrum of outcomes and like if this is a whole uh, uh, you know, nothing burger, then it would still be good that we made those changes.

Kyle 23:09

Real quick, just to kind of follow up to make sure I understood this correctly. It's kind of like based. The way you're setting this up is like, okay, a company X could invest in said software and deduct that, but they can't deduct the same thing for investing in people at that work for them.

Alex 23:28

So they can take a deduction. It's up to, I think,$5,250 for, uh, like worker training. Um, but uh, that is supposed to be sort of related to their, uh, uh, current role. Uh, and like full sort of retraining, uh, is non-deductible. there is a justification here where you don't want to have, um, uh. Things that are effectively a form of employee compensate or might kind of be a form of employee compensation that's deductible at the firm level and also non-taxable at the individual level. That's like a common concern at the margins of tax policy. Um, but in this particular case, you know, you could have some sort of cap. Uh, uh, it might not be unlimited, but, uh, having, you know, more than, than zero, uh, uh, you know, uh, uh, limit, um, could, could be effective.

Erica 24:27

this reminds me of a book that Glenn Hubbard wrote in like 2022. So before AI was really being discussed, but the book is called The Wall on the Bridge, and it's like policy ideas. To help build bridges for people to respond to things that are disruptive. So a lot of the ideas he talks about in there, they expand beyond tax policy, but like unemployment insurance reform, rethinking how social insurance works. So if it is a technological disruption that's causing hardship for people, don't block the disruption, like bridge people to deal with that in a, in a productive way. So I think like those ideas you, you mentioned are. A perfect fit with that kind of concept,

Kyle 25:06

was just realizing it's like I, I think our bookshelves are, are radically different, what you have on your shelf and what I have on my shelf. I was like, I don't think I have any economic books like.

Erica 25:17

I was like my, one of the, my favorite books I've read, and I talk about that book all the time because it's so applicable, whether, whether people are upset about like. trade policy disrupting people or new technology disrupting people. Now AI disrupting the the workforce, there's always going to be some kind of disruption happening. The answer isn't stop disruption. It's let's be more agile in response to disruption. So bigger picture when we're thinking about like the federal budget situation and the sustainability of debt, we all know that it's unsustainable. Deficits are already really large, and one of the things people talk about with AI is what. What will the impact be on the federal budget? it going to make the deficit situation worse? Um, you know, if these labor doomsday scenarios come, come into play, do income tax revenues go in the tank or will it help growth and help reduce the budget deficit? Where, where do you think the, the truth of the matter is?

Alex 26:16

Yeah. So beyond the like first order answer, which is, I don't know, uh, which I, I think is, is like. The most a hundred percent accurate answer. It's true. I like, I don't know the future. Um, and I think this area, like in in particular, um, like people, people don't know, um, exactly what the effect of this, this new technology will be on all kinds of things. Um, but I think the, like putting a whole lot of belief in the strong versions. Of either prediction, I, I, I think is, is, uh, um, a mistake. Um, there is this sort of Optimus story where the, you know, great that, that AI will unleash like great productivity growth and that will, uh, um, increase, uh, tax revenue and that will, you know, solve a lot of structural, uh, the long-term sort of structural problems, uh, in the us uh, fiscal picture. And then the sort of negative, uh, uh, um, sort of pessimistic story that, you know, the, the labor disruption means that the individual income tax, which is the sort of workhorse of the, uh, us uh, uh, federal revenue, um, you know, if revenues from that and then, you know, payroll taxes too, you know, go through the floor. Now we've gotten even worse, uh, a fiscal situation. I, uh. If anything, you know, generally you'd expect if AI like improves productivity growth, you'd expect that to directionally, uh, uh, positively contribute to the US fiscal situation. Just generally, um, we expect productivity growth to mean like more, more revenue. Um, on that, there are a bunch of different like little interactions where, based on how certain programs are calculated, but on net this is a, a deficit generally like. Productivity growth should mean like reduced deficits. Um, but the promise of dramatically improved productivity growth as a solution to uh, uh, long-term fiscal problems is just like. A classic like siren song of, classic wishful thinking. Um, and I certainly wouldn't, you know, count on that or, or have a lot of saying, you know, oh, well, well AI's on the way, we'll have this, this incredible productivity growth and you don't really have to worry about, but have a set. Um, I would be very wary of that. particularly because baseline budget protections already include productivity growth. Like there's some productivity growth already in forecasts and that's gotta be coming from somewhere. And like, maybe AI is like good for, for productivity growth, but that's just all the stuff that's in the budget, you know, forecast and economic outlooks already. the other thing with the pessimistic story that, that, you know, all of a sudden labor is going to be replaced, or the very least, you know, depleted, uh, substantially. Thanks to AI technology. Now, this is, uh, uh, where it makes sense to think about things in a, in a historical context and not sort of, assume AI is dramatically different from historical examples of technological change or, or disruption. And when you look at the, the labor share of income, you know, measured properly, uh, over the course of, you know, the 20th century into the 21st, so far, labor share of income is quite stable. Um, and so assuming that things will be dramatically different and that will sort of warp, uh, the, the structure of, uh, uh, tax revenue, uh, I, I, I don't think that's a, a sound bet.

Erica 30:12

That measured properly point that you just mentioned is like the key because like today there are some charts going around with. share of gross income rather than labor share of net income. And if you look at the gross income picture, it does look like labor share is declining. But the real big story there is like depreciation and, and taxes have have gone up. Um, and of course, depreciation and taxes aren't income that actually goes into anyone's pockets. So you wanna net out those things that income to anyone, and then look at how it's split between capital and labor. And there you do see this really. Really stable share. Um, you know, some, some slight changes since the eighties, but nothing dramatic. It's really close to that average, and it has been since, like you said, the, the 1930s. Um, so assuming a big deviation from that would, would be a big jump.

Kyle 31:02

Yeah, and we already we're taxing corporate profits right now, and we are the only developed country actually that doesn't have a value added tax. Um. So in instead of, you know, inventing new AI taxes, should we just be fixing the tax system we already have?

Alex 31:21

Anthropic, which is one of the big AI research labs. Um, did like a symposium recently of economists coming up, sharing, you know, ideas and, and for different policy scenarios. And some of them I, I think makes have some of the ideas I think are good and some of them i, I, I think are not so good. Um, but I think the. Idea that some people who buy into the pessimist story, um, have proposed a, so as a solution, uh, would be to introduce a, a, a consumption, taxes or, or, uh, instead of income taxes. Um, because consumption is, is more stable and, um, it's easier to tax than, than income, uh, generally. Um, and. While I might not buy the, the pessimist sort of story here, um, consumption taxes are more efficient than income taxes. And so if this is a reason to switch from income to consumption taxes or somewhat replace, uh, uh, the, uh, some of the income tax with consumption tax, um, I think that would be, that would be a good outcome. Um, and it would be, again, a sort of sound reform that I think would be good regardless of scenario. Um, but if you're particularly worried about the pessimist scenario, I, I can see how that is an appealing, uh, idea as well.

Erica 32:48

So, so let's wrap it up. Let's say like in 60 seconds or less, if you were talking to a policymaker and they were concerned about AI had ideas about taxes, what would you say that they need to be thinking about going forward?

Alex 33:02

I would say the biggest point is to not assume a radical scenario. As your, you know, as the building block for your, your policy solution, I think you should draw on the lessons of different waves of technological change. Uh, and both the, the fact that, you know, investment in new technology is important in. Long-term economic growth, uh, and that you shouldn't, you know, turn away from new technology. Um, but at the same time, you know, draw, uh, while avoiding, you know, penalizing new technology, just coming up with sort of positive ways to help people, uh, adjust to the, the changes in disruptions that it, it, it will bring areas of, of technological change, you know, you know, brought as well. Um. I guess the, the other sort of big picture point is that I wouldn't look to tax, uh, uh, for any social problem that you are worried about. we've been focused, as I said at the beginning on. Economics and, and you know, how AI will change the production of goods and services at a relatively broad level, maybe at a sector level. Um, but there are a lot of sort of social concerns that, that people might bring up with new technologies. Uh, like, you know, uh, people have a lot of concerns about the effect social media has had. Um. But I would be skeptical of designing, uh, uh, tax instruments for, uh, a lot of these, these concerns you should keep in mind that there's a, a wide array of like policy tools available for a whole variety of social ills. Uh, uh, and tax just is probably not the right. Tool to pick. And, and most of them, um, you know, I was thinking about with social media, if you're worried about, uh, if you're worried about social media, would you put a tax on like digital technology and like, the 1990s? And that ends up also hitting like Google Sheets because you can like, share you, you're, you're, you're sharing information with somebody else, you know? Um, and so I'd be skeptical of these sort of specific concerns that are valid. Um. Just getting sort of lumped in, uh uh, with a sort of broad policy on AI as well.

Kyle 35:33

There is at least one super niche AI tax that I would like, which is, I don't know. I'm sure you guys have seen this, is that there are. podcasts and as a podcast host, I find myself vaguely concerned about this. We created an outline for this podcast and I was like, oh man, I wonder what would that podcast would be like if we fed it to them? And I would like, maybe we just need to tax that. Like all AI podcasts get heavily taxed and we maybe just push those down for a little while so I can at least retire. Yes. But that's actually a real.

Erica 36:04

but I, I think we can compete. I, I think people will like us better than an AI SLAP podcast.

Kyle 36:11

I'd like to think so.

Alex 36:12

I believe, Kyle, you have many, many valuable skills that would, would make you, um. Valuable, uh, uh, uh, contributor in other forms if such, if such a, a technology, um, was spread.

Kyle 36:26

Thank you. I appreciate that. And Alex, thank you for being on this show today. Erica, thank You for being here. today. And before we. Completely sign off. As always, if you have burning questions on taxes, you can send them our way. You can drop a comment on YouTube. You can email us at podcast@taxfoundation.org. You can slide into our dms at Deduction Pod on Twitter or in many other ways. We're on Instagram. We're on TikTok. You'll find us. Thank you for listening.