Latest / Financial Survival Network / Legal Chaos Looms Over AI - Kristen Roberts - #6269

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Legal Chaos Looms Over AI - Kristen Roberts - #6269 · Financial Survival Network

• 0:00
  Speaker 1: These AI softwares are getting through you know, they're finding
• 0:05
  Speaker 1: these bootlegged uploaded versions of these and I'm sure you
• 0:08
  Speaker 1: could do the same, right, I mean we did it.
• 0:10
  Speaker 1: We saw it with Napster, right, remember Napster in the nineties.
• 0:14
  Speaker 1: How we I mean we all used it too. I mean,
• 0:16
  Speaker 1: I don't know if we're supposed to admit it, but
• 0:17
  Speaker 1: we all everyone thought it was this great. Wow.
• 0:20
  Speaker 2: You were listening to Carrie Lutz's Financial Survival Network, where
• 0:24
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• 0:28
  Speaker 2: to thrive in today's trying times. You need the Financial
• 0:32
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• 0:37
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• 0:41
  Speaker 2: Survival Network now more than ever.
• 0:48
  Speaker 3: And welcome you are listening to and watching the Financial
• 0:51
  Speaker 3: Survival Network. I'm your host, Carrie Lutz. Well, AI is
• 0:55
  Speaker 3: all the rage. I'm using it daily in my work.
• 0:59
  Speaker 3: It hasn't reaped placed me on this podcast or on
• 1:02
  Speaker 3: the YouTube channel, but who knows it might happen in
• 1:05
  Speaker 3: the not too distant future. And that brings up a
• 1:08
  Speaker 3: very important concern that you're going to hear about from
• 1:12
  Speaker 3: my next guest, Kristen g Roberts, attorney, founder managing attorney
• 1:18
  Speaker 3: of Trestle Law out in California. Chris, we have like
• 1:22
  Speaker 3: an epidemic now of AI intellectual property theft, if you will,
• 1:29
  Speaker 3: because it could take a book, you could feed it in.
• 1:32
  Speaker 3: You could redo that book and it will bear absolutely
• 1:35
  Speaker 3: no resemblance, superficially on the surface to the original work,
• 1:41
  Speaker 3: and then you can go call it yours. I mean,
• 1:45
  Speaker 3: what are we supposed to do here?
• 1:47
  Speaker 1: Well, I think that's a really great jumping off point,
• 1:50
  Speaker 1: an intrigues interesting starting point, Kerry, because you know, with
• 1:55
  Speaker 1: the example you gave of the book, right, you can
• 1:58
  Speaker 1: do that. Now you could take make a book that's
• 2:00
  Speaker 1: already written and go you individually and rewrite that book
• 2:04
  Speaker 1: to be a completely different book, but carry a lot
• 2:07
  Speaker 1: of the same themes. Like I'm allowed to write a
• 2:11
  Speaker 1: book about a school of wizards. I'm allowed to write
• 2:14
  Speaker 1: a book about, you know, a school of wizards where
• 2:17
  Speaker 1: somebody goes to the school and they get an invitation. Now,
• 2:20
  Speaker 1: whether or not that book is substantially similar enough to
• 2:24
  Speaker 1: constitute trade or to constitute copyright infringement, that's the legal question.
• 2:29
  Speaker 1: And that legal question still applies with AI and right
• 2:33
  Speaker 1: now people are saying, well, you know, AI is training,
• 2:37
  Speaker 1: is training the AI software on all of these copyrighted materials.
• 2:41
  Speaker 1: So it's sucking everything up off the Internet and learning
• 2:45
  Speaker 1: off of these, you know, resources that would otherwise be paid,
• 2:48
  Speaker 1: and they're not compensating the people who own the copyright.
• 2:52
  Speaker 1: And that right there is the crux right now in
• 2:55
  Speaker 1: the legal world. Is that training of AI fa use
• 3:01
  Speaker 1: is it? Is it a defensible use of copyrighted materials
• 3:05
  Speaker 1: or is it infringement? Do they have to pay? And
• 3:09
  Speaker 1: right now there are some cases that are moving through
• 3:11
  Speaker 1: the court system trying to answer that question because we
• 3:15
  Speaker 1: don't have an answer for it.
• 3:17
  Speaker 3: You know, like makes me think, you know, I don't
• 3:20
  Speaker 3: know how many great legal minds they really are out
• 3:23
  Speaker 3: there now, But I think of like Clarence Darrow, what
• 3:27
  Speaker 3: would be what would his take be an AI? And
• 3:30
  Speaker 3: I guess we could ask chat GPT what it thinks
• 3:36
  Speaker 3: his take would be?
• 3:37
  Speaker 1: Right, yeah, and you know what's you could do that?
• 3:40
  Speaker 1: But I also think it's interesting because a lot of
• 3:42
  Speaker 1: these sort of older attorney profiles, you know, famous lawyers
• 3:47
  Speaker 1: that you would say, what would they think? What would
• 3:49
  Speaker 1: they do? I don't even know if they could fathom
• 3:52
  Speaker 1: where we are right now when it comes to the
• 3:55
  Speaker 1: AI technology or how it would be applied, because there
• 3:58
  Speaker 1: is sort of two fast to it. There's the business
• 4:01
  Speaker 1: side of things, where you know, we champion in the
• 4:05
  Speaker 1: United States innovation in business and technology, and right now
• 4:09
  Speaker 1: the AI companies have been going to Congress saying this
• 4:12
  Speaker 1: is a matter of national security because if we are
• 4:15
  Speaker 1: not able to train our AI platforms, we are going
• 4:19
  Speaker 1: to get outpaced buy companies like China, our companies that
• 4:23
  Speaker 1: are coming out of countries like China, you know, and
• 4:25
  Speaker 1: other sort of competitor uh, you know, AI platforms. So
• 4:29
  Speaker 1: they're saying this is this is real national security stuff.
• 4:33
  Speaker 1: This isn't just you know, concerns about intellectual property. I
• 4:36
  Speaker 1: think it's an interesting argument. I'm not sure if I
• 4:39
  Speaker 1: if I buy it, but you know, it's interesting that
• 4:42
  Speaker 1: they're going there right now.
• 4:44
  Speaker 4: Yeah.
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  Speaker 3: Well, like when businesses want stuff out of government, they
• 4:50
  Speaker 3: always call it a spot Nick moment, you know, and
• 4:54
  Speaker 3: that was not a Sputnik moment.
• 4:55
  Speaker 4: I've used all of them.
• 4:56
  Speaker 3: I've used Rock, I've used Chat, I've used a Claude,
• 5:02
  Speaker 3: and I've used deep Seek and I don't even bother
• 5:05
  Speaker 3: with deep seek anymore because it just occurred to me.
• 5:08
  Speaker 3: It's a front end, it's a query manager for other ais.
• 5:14
  Speaker 3: It's not really there. That's why they're able to cut
• 5:18
  Speaker 3: down the size of it. But it does raise interesting questions,
• 5:23
  Speaker 3: like it's kind of like if you read every if
• 5:27
  Speaker 3: you had it within your capability to read every single
• 5:30
  Speaker 3: book that was ever written, which obviously we as humans don't,
• 5:37
  Speaker 3: then you could do whatever you wanted with that information,
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  Speaker 3: rewrite it or whatever. But the fact that a machine
• 5:43
  Speaker 3: can actually do it the whole sum total of human
• 5:46
  Speaker 3: knowledge as we know it, which there's always things that
• 5:50
  Speaker 3: aren't going to be there, that's really the issue. You
• 5:53
  Speaker 3: know that the machines can do it so much better
• 5:56
  Speaker 3: than us, and so much faster and completely so uh yeah,
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  Speaker 3: I think in theory it's a matter of national security,
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  Speaker 3: but in reality it's a matter of societal security because
• 6:15
  Speaker 3: it's going to start replacing broad swaths of workers in
• 6:19
  Speaker 3: the economy, and you know, you won't get any brownie
• 6:24
  Speaker 3: points for originality anymore, you know, Kristin, it's like, hey,
• 6:28
  Speaker 3: just get the job done.
• 6:29
  Speaker 4: We don't care how you do it.
• 6:31
  Speaker 1: And I also think it has to come it comes
• 6:32
  Speaker 1: down to money as well, because you know, if you could,
• 6:36
  Speaker 1: in your example, you know, if you could theoretically read
• 6:39
  Speaker 1: every book that was ever written, that would be fine.
• 6:41
  Speaker 1: You know, you could read every book, but you got
• 6:43
  Speaker 1: to pay to read every book, right, You can't just
• 6:46
  Speaker 1: go to the internet and find so these these AI
• 6:50
  Speaker 1: softwares are getting through, you know, they're finding these bootlegged
• 6:54
  Speaker 1: uploaded versions of these and I'm sure you could do
• 6:57
  Speaker 1: the same, right, I mean, we did it. We saw
• 6:59
  Speaker 1: it with Napster, right, remember Napster in the nineties. How
• 7:03
  Speaker 1: I mean, we all used it too. I Mean, I
• 7:05
  Speaker 1: don't know if we're supposed to admit it, but we
• 7:06
  Speaker 1: all everyone thought it was this great, Wow, we can
• 7:09
  Speaker 1: peer to peer share. Why not? Who cares? That sounds amazing?
• 7:13
  Speaker 1: And then it turned out to be copyright infringement, right,
• 7:16
  Speaker 1: But that law needed to be explored before. So there
• 7:20
  Speaker 1: was a there was at least a couple years of
• 7:23
  Speaker 1: just unfettered sharing. And I sort of like in what's
• 7:26
  Speaker 1: happening right now in this sort of explosion of AI
• 7:29
  Speaker 1: technology to that where it's like, Okay, it's getting access
• 7:33
  Speaker 1: to all of this stuff that is otherwise needing to
• 7:37
  Speaker 1: be paid for typically, and people are getting very upset
• 7:40
  Speaker 1: because they're like, well, hey, wait a second, if you
• 7:42
  Speaker 1: want to train your AI software on my book, on
• 7:46
  Speaker 1: my movie, you need to pay for that in order
• 7:50
  Speaker 1: for your you know, license it from us in order
• 7:52
  Speaker 1: to train it. And that makes sense to me. I
• 7:56
  Speaker 1: think that there does need to be some kind of
• 7:58
  Speaker 1: compulsory licensing like we have in music, So if you
• 8:01
  Speaker 1: play a song on the radio, there's an automatic license
• 8:04
  Speaker 1: that gets you know, applied, and I think the same
• 8:07
  Speaker 1: thing can be said about AI. I think the rub
• 8:11
  Speaker 1: is going to be when it comes to the licensing
• 8:15
  Speaker 1: structure or the ability to license. We already have heard
• 8:20
  Speaker 1: metas sort of higher ups coming out in deposition recently
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  Speaker 1: saying well, we tried to reach out to the publishers,
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  Speaker 1: but the problem is that the publishers don't own the
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  Speaker 1: copyrights to a lot of these books. So it's not
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  Speaker 1: like in music, where the publishing houses have the rights
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  Speaker 1: to license out even though they don't own the underlying work,
• 8:36
  Speaker 1: but they're given the exclusive right to license right so
• 8:40
  Speaker 1: right now the publishing houses for books, That's not how
• 8:43
  Speaker 1: it's worked in print. Print you go to the copyright
• 8:47
  Speaker 1: owner and you ask them and they're like it just
• 8:49
  Speaker 1: took us too long to track down everyone we couldn't like,
• 8:52
  Speaker 1: So it wasn't they were like it was. They basically
• 8:54
  Speaker 1: said it was too hard in a deposition, So we
• 8:56
  Speaker 1: just decided not to do it. And I just think
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  Speaker 1: it's funny because you know there are going to be
• 9:03
  Speaker 1: we need these sort of step by step this is
• 9:06
  Speaker 1: how it needs to happen. But in order to do that,
• 9:09
  Speaker 1: we kind of need a functioning Congress because that needs
• 9:11
  Speaker 1: to be an Act of Congress in order to pass
• 9:13
  Speaker 1: that kind of legislation. So I don't see that happening
• 9:17
  Speaker 1: anytime soon. So we're really relying on the courts to
• 9:20
  Speaker 1: make decisions about every case that comes past them. Because
• 9:24
  Speaker 1: they're deciding these cases very narrowly. They're not willing to
• 9:29
  Speaker 1: make a broad, sweeping statement saying this is how it's
• 9:32
  Speaker 1: going to be when it comes.
• 9:34
  Speaker 3: To AI dangerous because.
• 9:37
  Speaker 4: They don't really understand it.
• 9:39
  Speaker 3: Let's face it, courts are the most conservative, reactionary in
• 9:43
  Speaker 3: a lot of ways institution in our society, and that's
• 9:47
  Speaker 3: the way they were designed to be. The way that
• 9:50
  Speaker 3: they've grasped technology and use it in most courts, Yeah,
• 9:54
  Speaker 3: they've gotten better, but still ineffect.
• 9:58
  Speaker 1: I actually think that's why it's smart that they're going
• 10:00
  Speaker 1: very narrow and they're only deciding it on a case
• 10:02
  Speaker 1: by case because if you don't understand something very from
• 10:05
  Speaker 1: a very broad perspective, and I mean Congress, we can
• 10:08
  Speaker 1: say the same thing about Congress quite honestly, like they
• 10:11
  Speaker 1: don't understand that, you know, they were asking questions. I
• 10:13
  Speaker 1: remember a long time ago they were interviewing Mark Zuckerberg
• 10:16
  Speaker 1: for something and they said, well, can you tell us
• 10:19
  Speaker 1: what an algorithm is? And he was like, you know,
• 10:22
  Speaker 1: it was like how does it? How does it work?
• 10:25
  Speaker 4: You know, it's like do I keep work?
• 10:28
  Speaker 1: We're reay to be here for a while.
• 10:31
  Speaker 4: And then it's like rolling his eyes, right yeah, and.
• 10:34
  Speaker 1: He's going, oh god, we're here. We're at this, Like
• 10:36
  Speaker 1: we can't even get into the the salient points of
• 10:39
  Speaker 1: what we're talking about here because they don't even understand
• 10:42
  Speaker 1: the basics of how it works right or right And
• 10:45
  Speaker 1: the workings isn't always what even matters. It's the outcome
• 10:48
  Speaker 1: that we're looking for, right, Like how do you use it?
• 10:50
  Speaker 1: Stop trying to understand the like inner workings of it
• 10:53
  Speaker 1: and figure out what's the effect, what's the outcome and
• 10:56
  Speaker 1: what are you trying to do with it that that's,
• 10:58
  Speaker 1: in my opinion, that should be the goal when you're
• 11:00
  Speaker 1: applying technology, because do you remember when the Internet first started,
• 11:04
  Speaker 1: the World Wide Web, and everyone was everyone would be interviewed.
• 11:08
  Speaker 1: It was like Sally Jesse Raphael on her show, and
• 11:11
  Speaker 1: you know, all the talk shows were like what is
• 11:14
  Speaker 1: the world Wide Web? And they were like trying to
• 11:17
  Speaker 1: explain that how the internet worked. And you should have
• 11:19
  Speaker 1: just told them like, okay, this is what the Internet's
• 11:21
  Speaker 1: going to be able to do. That you could have
• 11:23
  Speaker 1: gotten more buy it in a lot faster.
• 11:26
  Speaker 3: So I'm going to ask chat ept now how the
• 11:32
  Speaker 3: court should deal with the AI companies and the issue
• 11:35
  Speaker 3: of copyright infringement and fair comment.
• 11:41
  Speaker 4: And all that fair use. Rather thank you all right,
• 11:47
  Speaker 4: and let's see what it says here, real time, great question.
• 11:51
  Speaker 3: This issue is right at the heart of the current legal,
• 11:54
  Speaker 3: creative and technological debate.
• 11:56
  Speaker 4: Let's break it down.
• 11:57
  Speaker 3: Well, now, of course it couldn't just give me a
• 12:00
  Speaker 3: one sentence answer here.
• 12:02
  Speaker 1: Well you could about you needed to ask it to
• 12:04
  Speaker 1: give you a one sentence answer.
• 12:06
  Speaker 4: Well, I could say just yeah, I can say, all.
• 12:09
  Speaker 1: Right, don't give me any analysis. Just give me the
• 12:11
  Speaker 1: answer out to the chase.
• 12:14
  Speaker 4: Give me the answer in fifty words or less. Yeah. So,
• 12:20
  Speaker 4: I mean, yeah, you got to know the prompting.
• 12:23
  Speaker 3: I didn't know it was going to give me everything
• 12:25
  Speaker 3: it was going to give me here, transparency and disclosure,
• 12:28
  Speaker 3: invest in licensing agreements, respect opt out systems, says everything
• 12:33
  Speaker 3: they don't want to do years in, Promote public domain
• 12:36
  Speaker 3: and open source.
• 12:37
  Speaker 4: Okay, you can agree on that. Yeah, watermark AI generated content. Okay.
• 12:43
  Speaker 1: So I think you know, because I'm seeing I think
• 12:45
  Speaker 1: a lot of it is going to come down to
• 12:48
  Speaker 1: it's going to it's going to common chunks. We're never
• 12:51
  Speaker 1: going to see this sweeping legislation where it all gets
• 12:55
  Speaker 1: packaged really nicely and it's dealt with on It's again,
• 12:59
  Speaker 1: we're seeing it in the sports already. It's going to
• 13:01
  Speaker 1: play out on a case by case basis. We've already
• 13:03
  Speaker 1: had one case come down. It was the Thompson Reuter's
• 13:06
  Speaker 1: case and it was against the Ross Ross AI Intelligence,
• 13:09
  Speaker 1: which was the the legal research. So of course it
• 13:13
  Speaker 1: started with legal research, right like the law, but west
• 13:16
  Speaker 1: law is sort of the pre you know, premier research
• 13:19
  Speaker 1: tool that lawyers use. I use it in my law firm,
• 13:22
  Speaker 1: and they have called case headings. Yeah, and the case
• 13:27
  Speaker 1: heading sort of you know, explains.
• 13:29
  Speaker 4: That litigated, that was litigated with.
• 13:31
  Speaker 1: It that was litigated. It just came down. Yeah, so
• 13:35
  Speaker 1: that and that that that decision just came down in
• 13:38
  Speaker 1: favor of Thompson Reuters basically saying is saying that use
• 13:44
  Speaker 1: ross using the case notes the head notes in West
• 13:47
  Speaker 1: Law that were that were free and open to the public,
• 13:49
  Speaker 1: like you can go look those up now without needing
• 13:51
  Speaker 1: a you know, but those were written by people and
• 13:55
  Speaker 1: they said, yeah, that's an infringement of the copyright. It's
• 13:58
  Speaker 1: not fair use. You can't just use those to train
• 14:00
  Speaker 1: your AI. But they only applied it in that like
• 14:03
  Speaker 1: very narrow case. So but we're starting to see it unfold,
• 14:08
  Speaker 1: and I think, you know, we're going to see it
• 14:10
  Speaker 1: unfold with other things as well. It's going to be writings,
• 14:12
  Speaker 1: it's going to be music, it's going to it's all
• 14:14
  Speaker 1: going to kind of come on its own. So we're
• 14:17
  Speaker 1: going to see this, We're going to see technology continue
• 14:20
  Speaker 1: to explode because in five years we're going to have
• 14:23
  Speaker 1: I mean, AI is going to be far beyond what
• 14:25
  Speaker 1: it is right now. And the law is still going
• 14:27
  Speaker 1: to be playing catch up twenty years in.
• 14:28
  Speaker 4: My year, in a year, it will be.
• 14:30
  Speaker 3: You know, interesting thing about that, the case notes, the squibs,
• 14:36
  Speaker 3: the I can't even remember right now what it was
• 14:40
  Speaker 3: so long ago, since I was in law school. But
• 14:43
  Speaker 3: we were always warned by the professor, don't trust the
• 14:46
  Speaker 3: case notes because they're often wrong because they're written by people.
• 14:50
  Speaker 3: I'll bet that those case notes are being written by
• 14:54
  Speaker 3: AI now. And honestly, AI doesn't need the case note.
• 15:00
  Speaker 3: It just needs the case It can create its own notes.
• 15:03
  Speaker 3: So they were kind of cheating and actually lessening their
• 15:07
  Speaker 3: final product by just scanning the case notes. You need
• 15:10
  Speaker 3: the case because you know the case notes are inadequate.
• 15:14
  Speaker 3: But shepherdizing that was it like the link between the
• 15:18
  Speaker 3: case notes and the shepherdizing it and all that.
• 15:21
  Speaker 4: You don't need any of that anymore. Really it helps.
• 15:25
  Speaker 3: You should never just take AI's word for a case
• 15:29
  Speaker 3: of finding or whatever. But it's easy enough to just
• 15:33
  Speaker 3: click click the link, and you're reading the case and
• 15:36
  Speaker 3: you know whether it's right or wrong. But it is
• 15:40
  Speaker 3: like kind of a fascinating I guess we're geeks. We're
• 15:43
  Speaker 3: kind of fascinated by nerds. But here it gave a
• 15:48
  Speaker 3: one line solution. Here the middle ground. AI companies want
• 15:53
  Speaker 3: to innovate, artists and creators want protection. The public wants
• 15:57
  Speaker 3: access and progress without as infringement. It's kind of reasonable.
• 16:02
  Speaker 3: The ideal solution is a system like how music royalties work.
• 16:07
  Speaker 1: Look at what I said, like I think I.
• 16:09
  Speaker 3: Think it read your paper honestly and plagiarized you. Probably
• 16:15
  Speaker 3: creators are compensated. AI systems can still learn and court
• 16:19
  Speaker 3: step in only when someone crosses the line.
• 16:22
  Speaker 4: We may even see the creation of.
• 16:24
  Speaker 3: A collective rights management body for AI training secret to
• 16:29
  Speaker 3: b M I or ask.
• 16:31
  Speaker 1: Music publishing those are music publishing.
• 16:32
  Speaker 4: How all your paper here? Man?
• 16:34
  Speaker 1: I just exactly see good. But that's but that's really
• 16:39
  Speaker 1: that's really the smart thing to do, because we already
• 16:43
  Speaker 1: have a system that works that we can model in music. Right,
• 16:47
  Speaker 1: we already have that system. It's not it's not reinventing
• 16:50
  Speaker 1: the Yeah, but.
• 16:52
  Speaker 4: What about China.
• 16:53
  Speaker 3: They're not going to want to pay anything because they
• 16:55
  Speaker 3: steal ip for lunch for breakfast.
• 16:57
  Speaker 1: They do that anyway, Right, We're still where we fight
• 17:00
  Speaker 1: that on a daily basis regardless, And so you.
• 17:04
  Speaker 3: Know, maybe there's a way here where they just don't
• 17:07
  Speaker 3: get it unless they subscribe.
• 17:11
  Speaker 1: That's above my pay grade.
• 17:13
  Speaker 3: Carrie.
• 17:13
  Speaker 1: I don't know how they would how we block them
• 17:16
  Speaker 1: from accessing certain internet site, you know, but maybe there
• 17:20
  Speaker 1: are you know, blocks or firewalls, or there has to
• 17:23
  Speaker 1: be more site, you know. I'll leave that to the
• 17:26
  Speaker 1: what cybersecurity professionals to figure out for us.
• 17:30
  Speaker 3: All right, well, I think we got the issue. I'll
• 17:32
  Speaker 3: put this in the show notes. Kristen, where do we
• 17:36
  Speaker 3: find you? Where's the best site?
• 17:37
  Speaker 1: Fign me on my website trussel Law dot com, t
• 17:40
  Speaker 1: R E S, T L E l a W dot com.
• 17:42
  Speaker 1: And I'm also on all social media champ you know, outlets, YouTube, Instagram, Facebook, TikTok, LinkedIn.
• 17:49
  Speaker 1: You can find me everywhere.
• 17:50
  Speaker 3: All right, excellent, Well, we'll have a link to your
• 17:52
  Speaker 3: site in the show notes of this interview on Financial
• 17:55
  Speaker 3: Survival Network dot com.
• 17:57
  Speaker 4: Will be careful not to scrape any of your data.
• 18:00
  Speaker 3: And you've got a question for Kristain myself email kl
• 18:04
  Speaker 3: atcarrieluts dot com.
• 18:06
  Speaker 4: And while you're.
• 18:07
  Speaker 3: At the site, if you just sign up for our
• 18:09
  Speaker 3: free newsletter, like over seventy thousand, I think we're plus
• 18:13
  Speaker 3: seventy five thousand subscribers at signed up. We'd appreciate it.
• 18:17
  Speaker 3: It really helps with the algorithms because we have a
• 18:19
  Speaker 3: daily war with the YouTube algorithm, you know, suppressing our content,
• 18:24
  Speaker 3: suppressing me, and it luckily hasn't mattered much to me,
• 18:28
  Speaker 3: but I would like to defeat it by any means possible.
• 18:31
  Speaker 3: Christin pleasure, talk to you again soon.
• 18:33
  Speaker 1: Thank you, Carrie, bye bye.
• 18:35
  Speaker 2: Thanks for listening to Carrie Letz's Financial Survival Network, your
• 18:39
  Speaker 2: solution to today's trying times. For the latest, go to
• 18:43
  Speaker 2: Financial Survivalnetwork dot com. Financial Survival Network now more than ever,