We're back with another edition of the Federalist Radio Hour. I'm Emily Jasinski,
culture editor here at the Federalist. As always, you can email the show
at radio at the Federalist dot com, follow us on Twitter at fdr LST.
Make sure to subscribe wherever you download your podcasts as well. Today we're
joined by Neil Chilson. He is a senior research fellow at the Center for
Growth and Opportunity. He's also at the former chief technologist at the FTC,
the author of the book Getting out of Control, Emergent Leadership in a Complex
World, and he's got a subset as well. We're going to talk about
that in a bit. Neil, thank you so much for joining us.
It's great to be here. So the context here is we're talking the day
after Sam Altman's very first congressional testimony on generative AI. Obviously, he's the
CEO of Open AI, which is the parent company of chat GPT. So
there's a lot of conversation very suddenly, a lot of lobbying money being spent
very suddenly here in Washington, DC in regards to generative AI. Neil,
you wrote a subseack post on a modest proposal. When it comes to AI,
you're own sort of Jonathan Swift take on what could happen or what should
happen, perhaps regular on the regulatory front when it comes to AI, first
of all, tell us where people can find the substack post and flush out
the argument a little bit. Sure, So the substack post is at out
of Control dot substack dot com and it's the top post there and it will
probably be the pin post for a little while, so check it out.
The context for this was I was somewhat air quotes inspired by yesterday Senate hearing
where Sam Altman and a couple others testified to the Judiciary Committee about the role
of AI and the government in AI. And no, Sam and open AI
have introduced artificial intelligence to millions of people for the first time, I think
in a concrete way by opening up chat GPT last fall. They really started
a Cambrian explosion of innovation in this space, even getting some of the bigger
tech players who wake up and chick off the dust and try to jump into
the AI space where they had long had investments but maybe hadn't delivered products really
yet. So so that's great, and there's so much happening in that space,
and it was surprising to see yesterday to have Altman and his fellow testifiers,
as well as several of the Senators, essentially agree that there should be
a digital regulator or some sort of regulator for AI. I don't know that
I've ever seen in an industry that's his sort of nascent to the public mind
go in front of Congress and immediately be like, hey, yeah, but
also regulate us. We would really like that and actual AI agency right Like,
that's an open AI and he's not alone. Other people from open AI
have said we need like a regulatory agency for general AI. Yeah. I
think that's right. And you know, it wasn't one hundred percent clear what
he was asking for. I thought it was a bit more clear what Professor
Marcus was asking for. It wasn't clear what the scope of what Altman was
asking for, but it did seem like they generally agree that there should be
some sort of regulator, and in particular, Altman mentioned a sort of licensing
regime, which raised the hackles for many people who have experienced with occupational licensing
and other issues that have seen the real barriers to competition that they can provide
so so, but I don't want to. I don't want to read too
much into what Altman was supporting there. I mean, his position maybe more
nuanced than it came across in the hearing. But in any case, I
was somewhat inspired by that call for a regulatory agency on AI to to think
about, like, what was the problem that the Congress was trying to solve
here? And there was a lot of talk about AI, but nobody really
drilled into the specifics. Artificial intelligence is an incredibly broad topic. The only
thing that might be as I point out in my post, you know,
AI includes everything from health diagnostic software to autonomous vehicles, to the Dolli image
generation and some of the other tools that we're using to even predictive text on
your phones. I mean, they all kind of count as AI. And
the discussion yesterday didn't really drill into what they meant on AI. And so
it's so broad that the only thing that's probably broader than artificial intelligence is you
know, just playing old regular intelligence. And so so I wrote a sort
of modest proposal in the Swiftian style, calling for an agent SEE to regulate
intelligence. I said, you know, like, let's not. If we're
going to regulate artificial intelligence, let's not discriminate against it's it's uh, it's
it's it's natural counterpart. Yeah, so, you know. So the argument
was essentially a argument from the ridiculous torture ridiculous What would it look like to
have an agency that regulated all intelligence, because that's that's about as general and
so. Using the acronym that some of the open AI folks have have called
for, which is oasis, I uh you know, I ran through and
with the help of chat GPT wrote this essay arguing that if we're worried about
artificial intelligence and the harm that it could cause, how much more should we
be worried about human intelligence? After all, it uh, it created artificial
intelligence and so and has brought us to the brink of disaster many times.
Um. The main point here is that if you think it's too broad to
regulate all intelligence, to have an agency that would that would look at intelligence
and then try to regulate all its effects, probably too broad to have an
agency that's just looking at artificial intelligence and regulating all its effects. Instead,
we should be focused on the actual uses of artificial intelligence and how those impact
various things, and so, you know, we should probably have an agency,
we should look to an agency that's an expert in a vehicle regulation when
we're talking about autonomous vehicles, etc. And so, and these generative ais,
you know, they're sort of general purpose technologies, and so it's hard
to know what specific agency might focus on them, but it might be something
like the Federal Trade Commission, although they don't have a particularly good recent track
record in in you know, focusing on where consumers are injured, and it
tends to be much more of a politicize agency than it used to be.
Anyways, I'm rambling a little bit, but that's the sort of gist of
the quite short piece. But I hope, I hope your listeners will check
it out. It was fun to do well. It's it's actually really interesting
because that's the kind of chicken or egg dilemma when it comes to artificial intelligence,
is how it can fundamentally be disconnected from human intelligence. When it's a
product of human intelligence, it is fueled by human intelligence, and at a
certain point short it becomes divorced from human control. And I'm saying this as
somebody who's like fairly alarmist about AI We've done a bunch of episodes where I'm
like, man, this stuff is happening really quickly and it's really scary.
But we saw what happened with the restrict Act when it came to TikTok.
Typically, when you have big companies, major multinational companies, lobbying for regulation,
it should be setting off alarm bells because it means that they're they're trying
to stiff competition and curry favor with the government and all of that. So
I wonder Neil, as somebody who's actually been at the FTC, what your
perspective is or what your confidence level is as this technology is. I think
we all are in agreement, developing really rapidly and in some great directions and
some frightening directions. As Altman himself conceded at the hearing on Tuesday, what's
your confidence level in our ability to sort of keep up with it even where
like the most like libertarian type person would look in and say, ah,
yeah, we probably need to do something here because it's like actual fake election
video or something like worst case scenario. What confidence level do you have right
now? So you know, it's it's always challenging when you're looking at an
area of new technology. I think what makes it easier in some cases is
if your focus is on the harts that you're worried about and the harms here.
Let's set aside this sort of existential harms and I'm not poo pooing those.
I think there's we should think about those, for sure, But aside
from those, the types of harms that people are worrying about, our harms
that actually we've been talking about for a decade now. Most of them are
the result of digital communications much more so than they are how you might generate
them. Now, there might be a new method through which some of these
like disinformation or bias or you know, woke AI and things like that.
If you looked at the hearing on Tuesday, a lot of the concerns were
basically you could have subbed out AI and just put social media in there,
and it was like all the same. It's the same playbook that we've been
talking about for the last you know, at least five years in Congress.
And so so with that, I think not saying that we've solved those problems
at all, but we do have tools in place for many of those problems.
You know, consumer fraud. Uh, you know, UM lies to
lies to people about like elections, election fraud. Like, we have legal
constraints on those things. We have legal we have agencies that are charged with
policing those Um. Are those agencies effective? I think maybe not? But
that's that's that's sort of separate from the AI question, right, um.
And so the question should be what does AI bring that's new? Does it?
What does it ramp up as far as threats in this space? And
what might we need to do um to increase the capabilities of agencies? And
I think that's an easier question than it is to say, like do we
have to keep on top of every development of AI. Well, no,
maybe we just need to focus on what the effects are and focus on whether
or not we have the tools in place to address those effects. And I
think, um, I think the FTC traditionally has been you know, has
had a focus that is much more on effects. Right, does this cause
consumer injury? Does it harm competition? And if it does either of those
things, then the FTC has the ability to bring tools in Uh. Sorry,
my daughter's really being allowed in the background. Again, It's it's barely
coming up in the audio, so it is okay, great, um,
excellent. So yeah, so so that that would be my my approach.
I mean, that's how I think about keeping up with technology. And that's
why the FTC, despite having a very general statute, has been able to,
you know, become the primary privacy regulator of the US because it's taken
a case by case enforcement approach, which is more flexible than when you write
down a bunch of rules about how a company or an industry should operate.
That's that gets out of date very quickly. Well, and let's talk about
the licensing proposal that we heard come from people in the industry themselves, which
again I always see such a red flag, but it's a great example of
also they're just sort of putting it out in the open. You know,
you have the big guys coming in a asking for regulation and then be asking
for licensing. Is particularly an interesting sort of cocktail right there, and what
a recipe for you know, monopoly power and all that stuff. So could
you talk to us a little bit about potential pitfalls of licensing because of the
licensing regulatory approach, because I can actually see that in a new space kind
of being explained to members of Congress senators in a way that makes sense to
them. When something really scary comes up, they have the nightmare of social
media as they see it, sort of hanging looming over their heads. Bloomenthal,
I think said that directly yesterday made it very explicit, the comparison between
you know, being too late to regulate social media because they think stole the
twenty sixteen election blah blah blah, all this other stuff democracy. So that
in mind, I could just see licensing being something that members of Congress a
sort of fall for what potential pitfalls could come of that approach. Yeah,
you know, licensing is a a just a pit of cronyism waiting to happen.
Right. For the most part, licensing regimes historically have been one of
the best ways for incumbents at the top of the game to stay there without
having to compete in the marketplace, if they can raise the barriers to entry
in a way that aren't just you know, economic. We talk a lot
about this, and you know, Capitol Hill it was. It was a
bit strange because Capitol Hill has been super worried about the ability of some of
the large tech companies to raise barriers to entry to competition. The best way
to raise a barrier to competition is to make it illegal to compete unless you
pass you know, some set of certifications and and uh and so I think
that the licensing regimes have every risk of doing becoming a having an anti competitive
effect. And in a space that is as you know, you have so
many people jumping into this space in a way that I think Congress finds concerning
in many ways. Right, Like, we can't control this industry because there's
so many people. Anybody with a computer and a you know, a nice
chunky graphics processing unit can build one of these models. Now, and like,
what do we do about that? Um? You know, that's that's
a vibrate ecosystem of competition. And an easy way to shut that down would
be a licensing regime and and constrain that to you know, just the big
players you can afford to comply. And as you point it out earlier,
this is a playbook that's you know, it's surprising that it's happening this early
in this particular base, but it is a playbook that is pretty common even
and well known by some of the big players. You know, Microsoft is
a big backer of open Ai and Microsoft has played this game in the past,
and so I think they are quite aware of the potential of regulatory approaches
to raise barriers to entry. I'm not I don't know for a fact that
Sam Altman has that this is what he has in mind. If you look
at the sort of charter of open Ai, it has always contemplated as a
sort of cooperative frame with government in this space, and so he may not
be thinking about this particular effect as the motivation for a licensing regime. But
I do think that history tells us that that is the likely effect. That
a licensing regime will be one that raises barriers to entry, that makes the
space less competitive, and that preferences those who are already have, who are
already at the top of the pile. And that's a real concern for you
know, somebody like me who likes a dynamic, innovative space, even if
it feels maybe like it's a little bit out of control. The Watchdolt on
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You're probably one of the best examples of this from very recent histories, Like
a couple of years ago, Facebook now Meta started taking out ads in the
Beltway morning newsletters asking for section two thirty because they know they're the only ones
that can sort of absorb the blows in that space that will cover Sextra two
thirty reform. But that's where it's sort of frustrating, as someone who's like
candidly coming at this from a fairly alarmist perspective on how quickly generative AIM is
moving, is that you know, the sort of libertarian folks on the right
are not, i think, downplaying the potential dangers of AI. And then
at the same time, it's just hard to look at what a potential solution
to those those dangers are if there's basically a smothering of conversation about potential regulation.
I'm not talking about you in particular, but it just gets really hard
to have the conversation about envisioning that when you know it's saying, well,
the regulatory pitfalls are very real, and then everyone else is saying, well,
the dangers of AAR are really real. So I wonder, Neil,
what you think the best way to kind of and you know, this is
probably something that you've you've dealt with in the social media space too, what
the best way to kind of balance those concerns are It's almost impossible in this
media climate and this like partisan climate, But what is the best way for
people to start thinking about this that you avoid hitting that impass well? You
know, I think in some ways and in some ways, the AI discussion
might be a little bit easier than the social media discussion in that the social
media discussion is entirely around speech issues almost entirely around speech right, whereas AI,
like I said earlier, like there's a bunch of areas in which the
harms could be like physical right, like if you have AI medical devices or
if you have AI driven vehicles, you're talking about spaces that could actually,
if they go wrong, they could kill people, and we could talk about
like what the what our risk tolerance should be in spaces like that. You
know, lots of very powerful, useful drugs also can kill people, and
so we need to talk about like how how as a society or as individuals,
what is our risk tolerance for that type of benefit costs, you know,
trade off. But but that's that's easier in some ways than talking about
speech issues, where we have a strong constitutional right plus and limit on what
government can do. Plus um, the harms are much less tangible, although
they can be they can also they can feel severe, but they are often
less tangible when you're talking about speech and so so I think there's a better
I guess what I'm saying. I think there's a better justification for in specific
areas of and applications of AI, having a regulatory regime that looks similar to
like what we might have around drugs, or what we might have around medical
devices, or what we might have around you know, automobiles, and so
to the extent that AI is being applied in those areas, I think we
have frameworks for thinking about the risks balanced trade off. And you know,
again my priors are that in a bunch of those spaces we probably are two
risk averse um, and that we should allow more experimentation. But at least
we have you know, we're talking about the you know, where we might
draw the line on experimentation, you know, around automated vehicles or you know,
medical devices. So I guess my big picture is we should disaggregate.
We should stop talking about AI generally and try to find the one size fits
all solution for all different applications of AI, and we should focus on what
are the specific AI uses that we are worried about, what are the concerns
that are there, What tools do we already have in the toolkit to address
some of those, and if we need to supplement those That's a good idea,
right we should. That's that's where we should be focusing our attention rather
than and trying to like solve the whole big ball of wax of like artificial
intelligence, like how do we make it safe? Right? Um, we
should focus on it. How do we make AI in vehicles safe? How
do we make AI and medical devices safe? How do we make you know,
content generation AI, you know, work the way that people expect it
to work and that the companies make when they make promises about how it works,
it works that way, right, like things like that. No,
this is a really important point and it's um you know, it's one that
I've directed a lot of folks on the sort of new right many different times,
because in so many cases it's exactly what you're describing. We actually already
have laws, and we might not have an agency, but we do have
copyright laws. We do have medical malpractice laws. We do have laws,
you know, just like we have so many, so very many laws,
so many laws. We have all of the laws that can can be applied
in different circumstances. Like it's just a matter of making the lawsuits. It's
just a matter of you know, actually like being proactive and finding places where
there are elapses on that note, those places where we should be sort of
looking to make sure that that AI is being applied safely. I know that
you've talked about election issues. Josh Holly had a confrontation with Sam Altman a
little bit about that, and Altman himself obviously conceded, Yep, I'm pretty
worried about that. What spaces do you think the energy should be focused on
right now when it comes to conceiving safe uses and applications of AI. Well,
on that discussion, I did think like the it was. Altman's response
was pretty careful. As I recall, he said, yes, it's true
that you may be able to generate misinformation on these platforms, but that the
harm all comes from when you distribute it on social media. So he was
sort of like pointing at the previous guys. He's like, it's not us
so much, um, And I think, yeah, something of a point
um there that you could do something new at scale with AI. That's convincing.
And I do think that there are some concerns around election manipulation, but
I think that whole, that whole narrative has been way overplayed. I mean,
it's if you listen a little bit, it's like people are worried that
that other people are dumber than them, right, and that, and that
the average voter is going to somehow get tricked into voting a different way than
they would have if they just get the right combo of targeted advertisements, and
um, you know, if that's what you think about your average human citizen
or your average US citizen. Then um U, that's that's not a very
positive belief about the ability of democracy to make educated decisions. So so the
animating belief for many like journalists and technocrats like that is the one thing that
they now think needs to translate into new regulatory power and censorship and etc.
Well and and and it's and it's crazy to me, Like it's crazy to
me to think that, Oh you think that, Um you know that the
New York Times consistently having its frame on issues is is not going to change
people's minds. But you know, some targeted ads generated by chat GPT,
will I just don't understand that that sort of belief in the good ability to
shape minds. But then like a fear of like a bad ability to shape
minds. Um. But I do think that there are some are there are
some areas where I, you know, I do worry about the effect of
generative models ability to scale up bad behavior. And in particular, I think
cybersecurity is a big one. I mean phishing emails right now. You know,
I think we've all we all have an ability to spot the you know,
the send a thousand dollars to me if you would like, and I'll
send you a million dollars in gold bullying or something like that. Emails that
we get, but when those get much more targeted and realistic looking to a
particular individual, that that that is a problem that I think cybersecurity professionals are
concerned about. Um, you don't solve those necessarily by shutting down generative models.
But the way these generative models all work, they have a layer,
like a safety layer above them that can spot some of these patterns pretty quickly,
especially when they're being generated on mass on mass like they would have to
be in order to you know, to make a difference in the cybersecurity space.
Plus, you know, we have lots of other you know, two
factor authentication and things that we probably should all just be a little bit more
aware of what's coming into our inbox. I do think that in this there
will be a little sort of gap here when between when people learn to adapt
and when the companies learned to adapt to this, and when the you know,
the cyber criminals start using these tools. So so I am a little
worried about that space. I do think it's worth at tension both from us
as users of email and lots of other technology, but also from the companies,
and I think a lot of the generative AI companies are are are quite
concerned about that particular use case as well. And so for generative AI,
that's that's one that I'm particularly worried about. There's lots of other spaces,
like I've already mentioned, the ones that can actually result in the loss of
human life in a much more direct way where I think AI is. Yeah,
we should, we should pay a lot of attention to those those uses,
but those aren't really the ones that are are raised by generative AI at
this point right now, there are pretty serious geopolitical implications for the regulatory question.
Um you know, China I think recently just unleashed more regulation of its
own um generative AI industry and it's development of that industry, and so obviously
there are I agree with you, I think cybersecurity is the space to watch
for here, but there are questions about stifling um, you know, private
innovation in a way that puts us behind other countries and leaves us more vulnerable,
vulnerable in a national security sense. Do you have thoughts on that,
Neil, because that's I haven't really heard quite enough conversation on in that area.
Um, although it's it's obviously a major concern, um knowing how much
China has invested into generative AI. So if there were let's say, a
licensing regime to step in that would step into the picture or other, you
know, an agency that starts to regulate generative AI. We don't know exactive
the contours of that would look like. But um, what are the risks
in terms of like our geopolitical standing in terms of competition? Yeah, so,
you know, I wish the hearing on Tuesday had talked a lot more
about this. I didn't even hear a mention of China in the discussion.
The US right now has a enormous advantage in this space. We are set
up in the way that we treat software innovation to focus on the effects at
the end, right, and not on a licensing regime up front. This
is very different than how Europe is planning to do it. They have a
law that's pretty close to being in effect around AI specifically, and then they
have several other laws that already make it very difficult to do some of this
work. And then China, obviously, UM, you know, I've heard
people call it thoughtful regulation, but its goal is not the same as we
would have here. The goal of Chinese AI regulation is to protect the communist
party there and to ensure that you know, the populist does not get out
of hand with these types of models, and that they these they're not too
they're not powerful tools for you know, self expression in a way that would
threaten the leadership in that country. So all of that to say, we
have a we right now have a advantage in our regulatory approach, and that's
shown by the fact that these companies and the innovation is largely happening here.
It would be a huge detriment to us tom seed that ground to China or
even to like copy Europe and and and freeze our regulation in a way or
freeze our innovation in a way that would mean that China's applications would would lap
us. And so I do worry about the lot. There's there's no reason
for us to do that. We have, like he said, we have
the tools to deal with at least the concerns that we have now. We
also have the ability to adapt to that. You know, I keep going
back to the idea that the US is the land of you know, pioneers
and frontiersmen. We are the people who go out and forge into the unknown,
and we deal with the problems as they come up. If we sat
at home and try to imagine all the things that could go wrong and right
the right the rules that keep them from happening, we would never leave the
house. And that's sort of the europe model, um and so so we
should lean into that. We should lean into our strength in dealing with problems
as they come up, but innovating along the way, because because that's gotten
us, you know, the the innovation that we have now. And I
think I think we should we should revel in the fact that the US is
in the lead in this space and we should take advantage of it. It's
it's possibly the only way, and this is a little bit off topic,
maybe it's possibly the only way we're going to outgrow the massive federal debt crisis
that we're facing. So um uh is to you know, take advantage of
our ability to produce good products and services that make people's lives better and that
boost GDP through AI until we then tax all of that revenue and redistribute it
into inefficient government programs. You know, is there is there anything else that
we haven't touched on you think is an important um point or something. This
is pretty critical for people to understand about generative AI or AI more broadly.
There's there's two things I might add in here, and they're they're sort of
related to each other. Um what's really interesting about generative AI is that,
you know, I think it prevents it presents some great opportunities. It has
some threats to interesting groups of people at this point, right, content creators
I think are very nervous. The news media, I think is very nervous
about this technology because it works on you know, their tools of the trade
words and video and audio and images, and I think there's there's a huge
amount of productivity and creativity that's going to be coming out from these products.
But it's going to be very disruptive to the elites who kind of consider themselves
the tastemakers or the agenda centers of the world. And so we saw this
before. Our social media was in a similar way. It was a big
threat at least to the advertising model of some of the traditional media, and
no surprise, traditional media was not a big fan of many of these these
platforms. I think AI is even more personally a sort of threat to maybe
traditional models of journalism, and so I think you can expect to see some
coverage that would come from that frame. I don't think that so many of
these people were often concerned when automation threatened blue collar jobs, but suddenly,
yeah, I think they're concerned now. So it'll be interesting to see how
that plays out. And then the second point I think is around I do
think the AI is sort of the next front in the culture war that we've
been ongoing. I already said, you know, Congress finally figured out like
how to talk about social media in a way it kind of understands it,
and it understands the sort of political I say, figured out that they figured
out how to score political points by talking about social media, right, and
so on both sides. And so I think I think, like like all
things, AI is sort of going to be the next front in this culture
war. It's going to be people arguing about, like, hey, this
misinformation is you know, and we saw some of that in the hearing already.
This misinformation is going to shape elections or it's going to be woke and
it's gonna you know, suppress conservative ideas, and you know, I think
we should dig into those issues. We shouldn't just let them go. But
also I think we should see them for the sort of next step in what
is a continuing back and forth between the political parties, and that in many
ways it'll be less about the policy at the end of the day and a
little bit more about like who can score political points about this stuff. So,
um, those are just the two things that kind of jump out to
me as far as political dynamics in in DC. It'll be interesting to see
what coverage looks like, how it might be biased, and and you know,
who's going to be the who's going to be able to best and make
the political points from from accusing various AI platforms of shifting the narrative or distorting
the narrative. So, m no, it's more of the same, right
no. And it will be interesting because if you're also sort of in the
space where you're helping to prevent any possible competitors that might be you know,
for just one hypothetical like what Elon Musk is trying to do to Twitter um
or oral rumble like the rumble to the AI YouTube, then you might not
have much of a leg to stand on right right exactly, Neil, go
ahead, go ahead, No, I was just gonna say. Also,
the other thing that jumps out to me is that, you know, the
Biden administration has a lot of different documents that they've come out with around aim
they're calling for accountability, but they never really say to whom. I think
they basically mean accountable to the Biden administration, and so so we should think
really hard about like what that might look like. I think even they should
look I think pretty hard about what it might look like to have AI accountable
to the government agencies when those agencies are in the hands of people that they
don't agree with. So a word of caution, that's a great point.
I'm not sure they have thought about that. Neil Chilson is a Senior Research
Fellow at the Center for Growth and Opportunity obviously also a former de former Chief
Technologists add the FTC and he writes on substack, Neil, where can people
find your substack? So my substack is out of control dot substack dot com
and I am on Twitter at Neil underscored Chilson, and I hope people reach
out. This is a great topic and thanks so much for having me on.
Of course, the book, as we mentioned earlier, is to go
along with the theme of the sub Stack. Is God getting out of control?
Emergent leadership in a complex world. I'm em Elijah Shenski, Culture editor
here at The Federalist. We will be back with more Federalist radio hours soon.
Until that be lovers of freedom and anxious for the fray. I heard
the fame for the reason, and then it faded away.