Speaker 1: These AI softwares are getting through you know, they're finding
these bootlegged uploaded versions of these and I'm sure you
could do the same, right, I mean we did it.
We saw it with Napster, right, remember Napster in the nineties.
How we I mean we all used it too. I mean,
I don't know if we're supposed to admit it, but
we all everyone thought it was this great. Wow.
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Speaker 3: And welcome you are listening to and watching the Financial
Survival Network. I'm your host, Carrie Lutz. Well, AI is
all the rage. I'm using it daily in my work.
It hasn't reaped placed me on this podcast or on
the YouTube channel, but who knows it might happen in
the not too distant future. And that brings up a
very important concern that you're going to hear about from
my next guest, Kristen g Roberts, attorney, founder managing attorney
of Trestle Law out in California. Chris, we have like
an epidemic now of AI intellectual property theft, if you will,
because it could take a book, you could feed it in.
You could redo that book and it will bear absolutely
no resemblance, superficially on the surface to the original work,
and then you can go call it yours. I mean,
what are we supposed to do here?
Speaker 1: Well, I think that's a really great jumping off point,
an intrigues interesting starting point, Kerry, because you know, with
the example you gave of the book, right, you can
do that. Now you could take make a book that's
already written and go you individually and rewrite that book
to be a completely different book, but carry a lot
of the same themes. Like I'm allowed to write a
book about a school of wizards. I'm allowed to write
a book about, you know, a school of wizards where
somebody goes to the school and they get an invitation. Now,
whether or not that book is substantially similar enough to
constitute trade or to constitute copyright infringement, that's the legal question.
And that legal question still applies with AI and right
now people are saying, well, you know, AI is training,
is training the AI software on all of these copyrighted materials.
So it's sucking everything up off the Internet and learning
off of these, you know, resources that would otherwise be paid,
and they're not compensating the people who own the copyright.
And that right there is the crux right now in
the legal world. Is that training of AI fa use
is it? Is it a defensible use of copyrighted materials
or is it infringement? Do they have to pay? And
right now there are some cases that are moving through
the court system trying to answer that question because we
don't have an answer for it.
Speaker 3: You know, like makes me think, you know, I don't
know how many great legal minds they really are out
there now, But I think of like Clarence Darrow, what
would be what would his take be an AI? And
I guess we could ask chat GPT what it thinks
his take would be?
Speaker 1: Right, yeah, and you know what's you could do that?
But I also think it's interesting because a lot of
these sort of older attorney profiles, you know, famous lawyers
that you would say, what would they think? What would
they do? I don't even know if they could fathom
where we are right now when it comes to the
AI technology or how it would be applied, because there
is sort of two fast to it. There's the business
side of things, where you know, we champion in the
United States innovation in business and technology, and right now
the AI companies have been going to Congress saying this
is a matter of national security because if we are
not able to train our AI platforms, we are going
to get outpaced buy companies like China, our companies that
are coming out of countries like China, you know, and
other sort of competitor uh, you know, AI platforms. So
they're saying this is this is real national security stuff.
This isn't just you know, concerns about intellectual property. I
think it's an interesting argument. I'm not sure if I
if I buy it, but you know, it's interesting that
they're going there right now.
Speaker 4: Yeah.
Speaker 3: Well, like when businesses want stuff out of government, they
always call it a spot Nick moment, you know, and
that was not a Sputnik moment.
Speaker 4: I've used all of them.
Speaker 3: I've used Rock, I've used Chat, I've used a Claude,
and I've used deep Seek and I don't even bother
with deep seek anymore because it just occurred to me.
It's a front end, it's a query manager for other ais.
It's not really there. That's why they're able to cut
down the size of it. But it does raise interesting questions,
like it's kind of like if you read every if
you had it within your capability to read every single
book that was ever written, which obviously we as humans don't,
then you could do whatever you wanted with that information,
rewrite it or whatever. But the fact that a machine
can actually do it the whole sum total of human
knowledge as we know it, which there's always things that
aren't going to be there, that's really the issue. You
know that the machines can do it so much better
than us, and so much faster and completely so uh yeah,
I think in theory it's a matter of national security,
but in reality it's a matter of societal security because
it's going to start replacing broad swaths of workers in
the economy, and you know, you won't get any brownie
points for originality anymore, you know, Kristin, it's like, hey,
just get the job done.
Speaker 4: We don't care how you do it.
Speaker 1: And I also think it has to come it comes
down to money as well, because you know, if you could,
in your example, you know, if you could theoretically read
every book that was ever written, that would be fine.
You know, you could read every book, but you got
to pay to read every book, right, You can't just
go to the internet and find so these these AI
softwares are getting through, you know, they're finding these bootlegged
uploaded versions of these and I'm sure you could do
the same, right, I mean, we did it. We saw
it with Napster, right, remember Napster in the nineties. How
I mean, we all used it too. I Mean, I
don't know if we're supposed to admit it, but we
all everyone thought it was this great, Wow, we can
peer to peer share. Why not? Who cares? That sounds amazing?
And then it turned out to be copyright infringement, right,
But that law needed to be explored before. So there
was a there was at least a couple years of
just unfettered sharing. And I sort of like in what's
happening right now in this sort of explosion of AI
technology to that where it's like, Okay, it's getting access
to all of this stuff that is otherwise needing to
be paid for typically, and people are getting very upset
because they're like, well, hey, wait a second, if you
want to train your AI software on my book, on
my movie, you need to pay for that in order
for your you know, license it from us in order
to train it. And that makes sense to me. I
think that there does need to be some kind of
compulsory licensing like we have in music, So if you
play a song on the radio, there's an automatic license
that gets you know, applied, and I think the same
thing can be said about AI. I think the rub
is going to be when it comes to the licensing
structure or the ability to license. We already have heard
metas sort of higher ups coming out in deposition recently
saying well, we tried to reach out to the publishers,
but the problem is that the publishers don't own the
copyrights to a lot of these books. So it's not
like in music, where the publishing houses have the rights
to license out even though they don't own the underlying work,
but they're given the exclusive right to license right so
right now the publishing houses for books, That's not how
it's worked in print. Print you go to the copyright
owner and you ask them and they're like it just
took us too long to track down everyone we couldn't like,
So it wasn't they were like it was. They basically
said it was too hard in a deposition, So we
just decided not to do it. And I just think
it's funny because you know there are going to be
we need these sort of step by step this is
how it needs to happen. But in order to do that,
we kind of need a functioning Congress because that needs
to be an Act of Congress in order to pass
that kind of legislation. So I don't see that happening
anytime soon. So we're really relying on the courts to
make decisions about every case that comes past them. Because
they're deciding these cases very narrowly. They're not willing to
make a broad, sweeping statement saying this is how it's
going to be when it comes.
Speaker 3: To AI dangerous because.
Speaker 4: They don't really understand it.
Speaker 3: Let's face it, courts are the most conservative, reactionary in
a lot of ways institution in our society, and that's
the way they were designed to be. The way that
they've grasped technology and use it in most courts, Yeah,
they've gotten better, but still ineffect.
Speaker 1: I actually think that's why it's smart that they're going
very narrow and they're only deciding it on a case
by case because if you don't understand something very from
a very broad perspective, and I mean Congress, we can
say the same thing about Congress quite honestly, like they
don't understand that, you know, they were asking questions. I
remember a long time ago they were interviewing Mark Zuckerberg
for something and they said, well, can you tell us
what an algorithm is? And he was like, you know,
it was like how does it? How does it work?
Speaker 4: You know, it's like do I keep work?
Speaker 1: We're reay to be here for a while.
Speaker 4: And then it's like rolling his eyes, right yeah, and.
Speaker 1: He's going, oh god, we're here. We're at this, Like
we can't even get into the the salient points of
what we're talking about here because they don't even understand
the basics of how it works right or right And
the workings isn't always what even matters. It's the outcome
that we're looking for, right, Like how do you use it?
Stop trying to understand the like inner workings of it
and figure out what's the effect, what's the outcome and
what are you trying to do with it that that's,
in my opinion, that should be the goal when you're
applying technology, because do you remember when the Internet first started,
the World Wide Web, and everyone was everyone would be interviewed.
It was like Sally Jesse Raphael on her show, and
you know, all the talk shows were like what is
the world Wide Web? And they were like trying to
explain that how the internet worked. And you should have
just told them like, okay, this is what the Internet's
going to be able to do. That you could have
gotten more buy it in a lot faster.
Speaker 3: So I'm going to ask chat ept now how the
court should deal with the AI companies and the issue
of copyright infringement and fair comment.
Speaker 4: And all that fair use. Rather thank you all right,
and let's see what it says here, real time, great question.
Speaker 3: This issue is right at the heart of the current legal,
creative and technological debate.
Speaker 4: Let's break it down.
Speaker 3: Well, now, of course it couldn't just give me a
one sentence answer here.
Speaker 1: Well you could about you needed to ask it to
give you a one sentence answer.
Speaker 4: Well, I could say just yeah, I can say, all.
Speaker 1: Right, don't give me any analysis. Just give me the
answer out to the chase.
Speaker 4: Give me the answer in fifty words or less. Yeah. So,
I mean, yeah, you got to know the prompting.
Speaker 3: I didn't know it was going to give me everything
it was going to give me here, transparency and disclosure,
invest in licensing agreements, respect opt out systems, says everything
they don't want to do years in, Promote public domain
and open source.
Speaker 4: Okay, you can agree on that. Yeah, watermark AI generated content. Okay.
Speaker 1: So I think you know, because I'm seeing I think
a lot of it is going to come down to
it's going to it's going to common chunks. We're never
going to see this sweeping legislation where it all gets
packaged really nicely and it's dealt with on It's again,
we're seeing it in the sports already. It's going to
play out on a case by case basis. We've already
had one case come down. It was the Thompson Reuter's
case and it was against the Ross Ross AI Intelligence,
which was the the legal research. So of course it
started with legal research, right like the law, but west
law is sort of the pre you know, premier research
tool that lawyers use. I use it in my law firm,
and they have called case headings. Yeah, and the case
heading sort of you know, explains.
Speaker 4: That litigated, that was litigated with.
Speaker 1: It that was litigated. It just came down. Yeah, so
that and that that that decision just came down in
favor of Thompson Reuters basically saying is saying that use
ross using the case notes the head notes in West
Law that were that were free and open to the public,
like you can go look those up now without needing
a you know, but those were written by people and
they said, yeah, that's an infringement of the copyright. It's
not fair use. You can't just use those to train
your AI. But they only applied it in that like
very narrow case. So but we're starting to see it unfold,
and I think, you know, we're going to see it
unfold with other things as well. It's going to be writings,
it's going to be music, it's going to it's all
going to kind of come on its own. So we're
going to see this, We're going to see technology continue
to explode because in five years we're going to have
I mean, AI is going to be far beyond what
it is right now. And the law is still going
to be playing catch up twenty years in.
Speaker 4: My year, in a year, it will be.
Speaker 3: You know, interesting thing about that, the case notes, the squibs,
the I can't even remember right now what it was
so long ago, since I was in law school. But
we were always warned by the professor, don't trust the
case notes because they're often wrong because they're written by people.
I'll bet that those case notes are being written by
AI now. And honestly, AI doesn't need the case note.
It just needs the case It can create its own notes.
So they were kind of cheating and actually lessening their
final product by just scanning the case notes. You need
the case because you know the case notes are inadequate.
But shepherdizing that was it like the link between the
case notes and the shepherdizing it and all that.
Speaker 4: You don't need any of that anymore. Really it helps.
Speaker 3: You should never just take AI's word for a case
of finding or whatever. But it's easy enough to just
click click the link, and you're reading the case and
you know whether it's right or wrong. But it is
like kind of a fascinating I guess we're geeks. We're
kind of fascinated by nerds. But here it gave a
one line solution. Here the middle ground. AI companies want
to innovate, artists and creators want protection. The public wants
access and progress without as infringement. It's kind of reasonable.
The ideal solution is a system like how music royalties work.
Speaker 1: Look at what I said, like I think I.
Speaker 3: Think it read your paper honestly and plagiarized you. Probably
creators are compensated. AI systems can still learn and court
step in only when someone crosses the line.
Speaker 4: We may even see the creation of.
Speaker 3: A collective rights management body for AI training secret to
b M I or ask.
Speaker 1: Music publishing those are music publishing.
Speaker 4: How all your paper here? Man?
Speaker 1: I just exactly see good. But that's but that's really
that's really the smart thing to do, because we already
have a system that works that we can model in music. Right,
we already have that system. It's not it's not reinventing
the Yeah, but.
Speaker 4: What about China.
Speaker 3: They're not going to want to pay anything because they
steal ip for lunch for breakfast.
Speaker 1: They do that anyway, Right, We're still where we fight
that on a daily basis regardless, And so you.
Speaker 3: Know, maybe there's a way here where they just don't
get it unless they subscribe.
Speaker 1: That's above my pay grade.
Speaker 3: Carrie.
Speaker 1: I don't know how they would how we block them
from accessing certain internet site, you know, but maybe there
are you know, blocks or firewalls, or there has to
be more site, you know. I'll leave that to the
what cybersecurity professionals to figure out for us.
Speaker 3: All right, well, I think we got the issue. I'll
put this in the show notes. Kristen, where do we
find you? Where's the best site?
Speaker 1: Fign me on my website trussel Law dot com, t
R E S, T L E l a W dot com.
And I'm also on all social media champ you know, outlets, YouTube, Instagram, Facebook, TikTok, LinkedIn.
You can find me everywhere.
Speaker 3: All right, excellent, Well, we'll have a link to your
site in the show notes of this interview on Financial
Survival Network dot com.
Speaker 4: Will be careful not to scrape any of your data.
Speaker 3: And you've got a question for Kristain myself email kl
atcarrieluts dot com.
Speaker 4: And while you're.
Speaker 3: At the site, if you just sign up for our
free newsletter, like over seventy thousand, I think we're plus
seventy five thousand subscribers at signed up. We'd appreciate it.
It really helps with the algorithms because we have a
daily war with the YouTube algorithm, you know, suppressing our content,
suppressing me, and it luckily hasn't mattered much to me,
but I would like to defeat it by any means possible.
Christin pleasure, talk to you again soon.
Speaker 1: Thank you, Carrie, bye bye.
Speaker 2: Thanks for listening to Carrie Letz's Financial Survival Network, your
solution to today's trying times. For the latest, go to
Financial Survivalnetwork dot com. Financial Survival Network now more than ever,