March 8, 2026 • 34 mins
We dive into how AI is reshaping marketing law and what agencies can do today to protect work, clients, and brand trust. Sharon Toerek shares a practical playbook for policies, contracts, and IP strategy while courts and states sort out the rules.
• AI ownership and liability questions for agencies
• Copyright cases on training data and outputs
• State patchwork versus federal pressure on AI rules
• Practical guardrails and written AI policies
• Contract terms for AI use, warranties, and indemnities
• Insurance stack realities and cyber coverage gaps
• SEO, watermarks, and useful AI content
• IP triangle: trademarks, copyrights, trade secrets
• Attribution limits and proving substantial similarity
• Authenticity, disclosure, and consumer trust
• Refreshing contracts and policies more often
Guest Contact Information:
Website: legalandcreative.com
LinkedIn: linkedin.com/in/sharontoerek
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SPEAKER_00 (00:01):
This is the unknown secrets of internet marketing.
Your insider guide to thestrategies top marketers use to
crush the competition.
Ready to unlock your businessfull potential.
Let's get started.
SPEAKER_01 (00:15):
Howdy, welcome back to another funfold episode of
The Unknown Secrets of InternetMarketing.
I can't even talk today.
Today has been one of thosedays.
It's been one of those weeks.
I hope everybody is doing well.
There is a lot happening in theworld of SEO, content, online
marketing.
Hopefully, through the pastguests, I would encourage you to
(00:36):
go check it out.
We've had some phenomenal gueststalking about what is happening
with AI.
And AI is really coming intothis and changing the game.
There's a lot of governanceissues with how to use it,
what's going on.
So I thought it'd be really goodto bring on someone that would
talk about trademarking becausewe're starting to see a lot of
that, copywriting, uh socialmedia law, ad law, marketing to
(01:01):
kind of uh build a frameworkaround how we should be looking
about these things.
So, Sharon, welcome to the show.
SPEAKER_02 (01:08):
Thanks, Matt.
Happy to be here.
SPEAKER_01 (01:10):
And this is Sharon with legalandcreative.com.
So I'll let you talk more aboutit at the end.
Uh, but uh tell us a little bitabout your background and how
you got got involved in this andkind of what you're seeing on on
the horizon as far as uh what'shappening today.
SPEAKER_02 (01:25):
Sure.
Well, so I am the founder ofToric Law, which serves
primarily independent marketingagencies in the United States.
And so we help them basically inone of three areas: intellectual
property, protection,enforcement, contract
development and negotiation, andthen regulatory compliance with
(01:45):
all the rules and regs thatgovern marketing and advertising
and things like that.
Um, I'm an IP lawyer by trainingand uh started my career as an
IP lawyer, began working moreheavily in the marketing space,
and then uh founded the firmthat I own and run now to serve
independent agencies in thatarea.
SPEAKER_01 (02:06):
Fantastic.
Well, I'm so I'm so glad to haveyou on because there's uh so
many things happening.
I mean, what are the things Iguess that are the biggest uh
hiccup points uh for peopleright now that you see over and
over again?
Let's just get the the basicsout of the way.
SPEAKER_02 (02:23):
Yeah, I think, you know, I feel like I can't either
host my show or talk withsomebody on their show without
saying A and I next to eachother.
And say I think that the interms of the legal and
regulatory landscape right now,uh everybody's got big questions
about what will happen withrespect to AI adoption, how it's
(02:48):
going to impact intellectualproperty rights to work that
gets created, um, what it'sgoing to mean for things like
content authenticity, contentfakery, and then also what it
means in you know in theadvertising world, what it means
in terms of creating honest andum you know, honest impressions
(03:10):
of a brand to a consumer.
And so um we're seeing a couplethings, and there's a couple
things we're watching right nowfrom a regulatory and a legal
perspective.
Uh, we have copyright cases thatwe're seeing weave their way
through the federal courts, theuh appellate courts right now to
determine what are theguardrails and boundaries gonna
(03:32):
be around these gigantic AIplatforms' ability to digest
content that somebody owns thecopyright in, whether it's
novel, a script, um, a marketingcampaign, a logo, whatever it
might be, um, what are theguardrails gonna be around their
ability to digest into theirtraining data all of that stuff?
(03:55):
And then who is in the secondquestion being, well, who is
gonna be responsible if anyinfringement occurs on the other
side with the output from AI?
So that obviously raises a lotof intellectual property
questions, a lot of ownershipquestions.
I would say the big question Iget on this point, just from our
clients who happen to be ownersand leaders of marketing
agencies, is first of all, whoowns the content if we're using
(04:18):
generative AI to create it?
And second of all, who'sresponsible if something goes
sideways once the content is outthere in the public and it does
infringe on somebody else's IPrights?
So I think I would start thereand say those are the big
questions that we see right nowfrom a regulatory perspective
around the impact of AI oncreative work of all kinds.
SPEAKER_01 (04:42):
Yeah, I mean, there's not a ton of guidance.
I know that in Texas, there's alaw, a law that passed on the
first where they're creating acouncil, which is kind of taking
a leadership role.
We got Colorado uh trying to uhprovide consumer rights in in
some different areas, and thenof course, California uh and
kind of adopting uh kind of GDPRkind of regulatory environment,
(05:06):
which scares me because there'sa lot of uh administrative
overhang to be able to operatein in that environment.
Um, there's a number of thingsthat you hit on that I look at
from a little bit differentlens.
Um, and also understanding likeutilizing these tools
internally, have having uh aprogram set up to uh evaluate
(05:28):
these different tools, how totrack what's happening.
Um there's just a lot ofconcerns and and not a lot of
clarity on on what's gonnahappen.
I mean, I'm even seeing withsocial media, uh uh there's a
lawyer here here in Texas thatjust um took took them uh took
uh Mark Zuckerberg in front ofuh like I don't know, I don't
(05:51):
know if it was the congressionalor whatever, but he basically
was asking about the algorithmcausing depression, right?
And they they're looking at thatimpact of that.
And then I start thinking thealgorithm with AI is influencing
how people are interpretingbrands, how people are looking
at brands, what if what if froma regulatory environment it
tells you to do something thatthere's a hallucinization, and
(06:14):
then you you you take actionbased upon that, where are the
legal implications there?
So there's there's this wholebox of things that I think is
starting to get unpacked and andregulation is starting to catch
up, but it's not there yet.
I mean, so what are the what arethe recommended even guardrails
that you would say for peopleoperating in this environment to
(06:36):
start considering or looking ator trying to do their best to
protect themselves?
Um and and you you list a wholeslew of other things that they
need to be thinking about aswell.
And I mean, what's the guidanceyou're giving people?
SPEAKER_02 (06:50):
Yeah, well, I do have some practical takeaways
for anybody who's listening interms of what are some things
you can actually implement in ina business of any size to sort
of start dealing with andgetting your arms around this.
But I would I, you know, to myreaction to what you just shared
about the regulatory environmentis that what we were expecting
(07:11):
to see um with regulatoryactivity around AI was what we
have seen historically regardingum the regulatory landscape for
data privacy.
And what I mean by that is thatEurope is simple.
There's GDPR, it covers most ofEurope, and it's one set of
(07:32):
standards, and they're strict,but once everybody understood
what they were and and theyhaven't evolved much since they
were enacted, it's a it's aplaying field that people are
getting more and morecomfortable navigating.
And in the US, though, we'venever had a federal standard for
data privacy.
What we instead have is thisstate patchwork of data privacy
(07:54):
laws.
You know, we we play toCalifornia because that that is
the strictest set of standards,the closest to GDPR.
But there's state activity inother areas that is, you know,
sort of catching up.
So that's the landscape withdata privacy.
I thought that's what we wouldsee for AI.
And to some degree, it is whatwe're seeing.
(08:15):
However, laid over that, you'vegot the federal government
putting a lot of pressure on thestate government and state
governments in the United Statesnot to regulate the use of AI.
You've got some states stillmoving forward and and and doing
so.
Some states have laws regardingrequiring disclosure if you've
(08:37):
used AI in creating the content.
Um, New York State has umsynthetic content creation
rules.
Um, there are SAG-AFTRA unionnegotiations around the whole um
issue of use of AI-generatedcontent likenesses, et cetera,
et cetera.
So we're still seeing somepatchy state-by-state
(08:58):
regulations, but then we'reseeing this tension between the
federal government and thestate.
The federal government didn'tget involved at all in
preventing states from enactingtheir own data privacy rules.
You know, go for it, is prettymuch the approach they've taken.
I doubt anybody said it thatway, but that's kind of how it
is rolled out.
But with AI, the federalgovernment has been very um
(09:20):
specific, if you will, about umnot wanting the states to get in
their way in terms of whateverdecisions we might make in the
United States around governingusage of AI.
So, what do you do about allthat?
As somebody who's trying to owna business and keep on top of
all this and limit your risk,and there's a few things.
(09:42):
First of all, um, you reallyshould be, if you're a service
provider, especially aprofessional service firm, for
example, um, you should behaving conversations with your
clients, your vendors, yourindependent contractors around
their AI use practices.
What platforms do they use?
(10:03):
Um, if it's your clientorganization, what platforms do
they allow you to use?
Um, what information are theygiving you that has been
generated out of AI because itmay make its way into the NWork
product, right?
Um, what information are theygiving you that is confidential
or proprietary that they want tomake sure you don't input into
(10:24):
any AI platform?
Um so have come having crucialconversations with key parties
in your business life, whetherthat is strategic partners,
clients, customers, whomever.
Secondly, is have, even if it'sa skeleton or an outline form at
this point, progress is betterthan perfection.
(10:45):
Have a written AI policy.
SPEAKER_01 (10:47):
Yes.
SPEAKER_02 (10:47):
Have one internally that you socialize with
everybody on your team.
Have an external facing policythat can be shared and shareable
with people outside yourorganization about how you use
AI, you know, and what yourpractices are around it.
Um, and then I would say third,look at your contracts and
(11:11):
ensure that you are addressingany responsibility or liability
around AI usage.
Um, you know, and we weren'tdoing this 24 months ago
candidly, even in the, I mean,we we create and negotiate
hundreds of contracts every yearon behalf of our marketing
agency clients.
And 24 hours, 24 months ago, weweren't um addressing AI
(11:32):
specifically.
I mean, yes, we've always hadindemnification and liability
language, but but now we areaddressing it specifically.
And it's probably time for mostof your listeners to be thinking
about doing that as well.
So those are three things to bethinking about.
And and you know, and thenbeyond that, I would say um
having the internal trainingconversations, even informally
(11:54):
with your teams about riskmanagement around adopting AI.
Um these are things you can doand scale no matter what your
resource levels are and nomatter what size you are as a
business.
SPEAKER_01 (12:07):
Yeah, I actually uh just did a uh a survey on on
some of this stuff on kind ofwhere where business owners are
at uh that I'm gonna bepublishing very soon.
And uh real really interesting,I would tell you also, or I
guess my question to you is Idon't think that arrows and
emissions insurance, thelanguage covers any uh of this
sort of thing, right?
(12:28):
And so how how from like we'regonna probably start seeing
cases pop up at some point ofyou know a misuse, and you got
like shadow AI, and then likeyou're putting stuff in a GPT,
and then you move companies, andthen somebody else, you know,
starts use like there's gonna beall these things that start to
pop up.
(12:49):
Um and and I think having agovernance policy is is super
important, but but I I mean, isthere any kind of other risk
protection that you can do ifsome of these things happen?
SPEAKER_02 (13:02):
Right.
It's a great question.
I mean, you know, uh the I justgot this question actually when
I was speaking to a group ofagency owners um two weeks ago.
It's funny that you asked itexactly the same way that uh a
person at the meeting asked it.
And there aren't any productsyet that specifically address,
(13:24):
at least to my knowledge,liability or responsibility
around something going sidewaysum out of using generative AI or
out of breaching confidentialityor data privacy.
So you we're left with lookingat our normal insurance stacks,
right?
Our our general liability, ourerrors and omissions.
(13:46):
Cyber, I think, is probably theclosest product to um uh have
the potential to evolve intomaybe covering specific AI
situations.
But uh there are no AI uh oopsproducts out there yet.
And so um you really just haveto look at your insurance stack
as a business, probably belooking at, I mean, measuring
(14:08):
the degree to which you're goingto be assuming the risk of
giving some of these tools andum adjusting your coverage
accordingly, so that maybeyou're carrying a little bit
more than you might have been acouple of years ago, um, with
particular attention probably toyour umbrella and your cyber
insurance policies around thisspecific issue.
SPEAKER_01 (14:29):
Gotcha.
You know, one of the things asas you talk about, right?
18 months ago, where were we?
Um there was a number ofpodcasts that came out, and
Google is starting to putwatermarks on uh anything that
you're using to generate, let'ssay images, for example.
So you're generating a nanobanana or whatever it's called.
Uh uh, and you know, they'reputting a little Gemini uh
(14:54):
watermark on it, and then itgets tagged automatically when
you publish that, that this wasgenerated with Gemini, which I
think is a great marketingstrategy as well.
I think putting the you knowfrom iPhone is how it kind of
went went viral as well.
Um, and they did a podcast, theythey have a webmasters podcast,
and and they this was a coupleyears ago around images, and it
(15:16):
was saying from a search enginestandpoint, right?
So there's the legal side ofthings and then there's the
search side of things that AIgenerated images are are okay,
right?
Because they I I felt like theywaved the the white flag a
couple of years ago when peoplestarted generating content
because it was like, is it humangenerated?
Is it um well useful?
They said useful content, ifit's AI generated, it's not um
(15:40):
you know, bad, or uh you know,now the term is AI slop, I guess
is what people are are saying inthe industry.
But if it's useful and helpfulit and it's generated, the
search engines are going toindex it.
And then from an imagestandpoint, it is a unique image
if it's not utilizing stock.
So there is the issue ofutilizing uh licensing on
(16:01):
images, and now you can kind ofmove into uh AI generated image,
and then there's not clarityexactly, but from a search
standpoint, it's unique content,and that's how it's being
treated, and so it's beingviewed favorably by the search
engines.
And you know, I I don't knowfrom a I really haven't dug into
(16:22):
it too much on the uh AI systemsfrom a image indexing standpoint
of uh how how it's uh presentingthose, but I would love to kind
of move uh more back towards thetraditional uh things that we
can maybe cover kind of socialmedia law, ad law, um, as well
as maybe uh copyright law, whichyou know, I I think it AI is
(16:47):
kind of the direct like I think75% of all content's gonna be
generated in AI, if not higher,very soon.
Uh and that's gonna be adegradation on the models.
And so that's why they'rewanting human input and trying
to trying to make sure thesemodels don't collapse.
But I'd love to kind of get yourbroader view as we fan out into
(17:08):
some of your other um uh skillslike experience sets to share
some of that.
SPEAKER_02 (17:14):
Right.
Well, so one of the main, youknow, one of my main personal
passions and one and sort of thethe foundation of my background
that led me to decide to focuswhere we focus the work at my
firm is you know, my honest umpassion for intellectual
(17:34):
property creation andinnovation.
I named my own podcast after theterm innovation.
I just I think thatentrepreneurial companies who
innovate um move the needle oncommerce and they move the
needle in our culture.
And I think that the legalsystem should support creators
(17:58):
and innovators.
And so IP is a huge part of whatwe do at my firm, and whether
that is helping to create aclear pathway for protecting IP,
for example, in the trademarkrealm, where um, you know,
companies are brandingthemselves or branding new
products or services that theymight want to put out into the
(18:21):
market, um, whether it isenforcing um the trademarks uh
that protect the brands of ourclients, um, or whether it's
monetizing the intellectualproperty, whether it's a
trademark license, for example,in the franchise world,
trademark licensing is a hugecomponent of franchising, as one
example, or uh, you know, andthen sliding over from trademark
(18:45):
to copyright.
Um, there's another point of theIP.
I use a triangle analogy for myrubric and evaluating the IP
than any business has.
There's brand, which isprotected by trademark, then
there's your actual content, thestuff that you create, um, most
of which you sell.
Um and there is a copyrightstrategy or a trade secret
(19:08):
strategy, depending upon how yougo to market with what it is
that you're creating.
If your market advantage isbecause it's your it's your
unique secret sauce, then youknow, copyright's probably not
going to be the strategy foryou.
Trade secret protection is gonnabe the strategy for you.
But if it's work you'republishing, if you're a digital
course creator, if you are um amovie maker, if you are a
(19:31):
software developer creating opensource tools, copyright may be
the most valuable mechanism forprotecting your work because
your work's gonna be out therefree for people to see and
access.
Um, and then the transactionspoint of the triangle: this is
how you make money from thestuff that you create or
(19:52):
innovate and then sell.
And that could be a transactioninto your business because
you've used a strategic partnerto help you create it, or you've
used a contractor who doesn'twork for you to help you create
it, or it could be transactionsout, which could be the way you
make money by licensing yourstuff.
It could be the terms andconditions of a software
license.
So that's kind of the way weanalyze the body of work and how
(20:18):
you protect it.
And I think as a rule,entrepreneurial companies tend
to undervalue the amount of IPthat they create.
Um, they tend not to leverageit, maximize the leverage of it
as much as they can.
So this is just my point ofview, and this is one of the
reasons why we focus where wefocus.
And it just so happens that youknow marketing agencies create a
(20:41):
ton of IP.
And so they're a good fertileground for us for this kind of
work.
SPEAKER_01 (20:47):
Yeah, no, commercial use is is really, I think,
important when you're uhapplying for these trademarks
and patents and things of thatnature.
Um, I one of the things that'sfascinating to me, again, going
back to AI, is as I'munderstanding how these
algorithms work, your work thatcan be ingested can influence
(21:10):
the output and influence theinterpretation of what's being
presented, but it doesn't alwaysgive clear reference to you.
So it's kind of like it's theit's like bumping into you, but
it's not calling it out, right?
And it's just kind of moving itin a certain direction.
So there's this real question ofinfluence of how do you know
(21:35):
that your work is influencingthe AI and you're not getting
cited?
Um and and then I guess later onum the the legal framework to
say, well, this is influencingthis large language model or the
the public model, uh how do youhow would you even track that
back?
Like how would you even in yourhead try to figure out how If it
(22:00):
was doing that or not, and howto measure it.
SPEAKER_02 (22:02):
Yeah.
Only through diligence, and thisis the problem, right?
The the attribution models arejust not available to the
average creator.
And certainly none of the bigAI, none of what I call big I
big AI is going to help acreator whose content it has
ingested to, you know, train itsdata sets by telling them, oh,
(22:26):
this is where you'll find it andthis is the output it showed up
in.
It's just not going to happen.
So the average creator is eithergoing to find an infringement
because they've stumbled upon itor somebody they know has
stumbled upon it, or they've orthey've experienced actual
confusion in the marketplacebecause somebody thinks they're
another brand.
(22:46):
Or they find their work, youknow, um cribbed, you know, they
find a substantial similaritybetween their original work and
some other work that they seeout there.
So the the systems to helpprevent the lack of attribution
are not yet accessible.
I'm not saying they don't existbecause I, you know, I know in
(23:08):
my heart of hearts that theythat they do exist, but they're
not accessible to the averagecreator.
And so we're gonna have to waitand see how that evolves, and
we're gonna have to wait and seehow some of these court cases
evolve in terms of theresponsibility of some of these
AI platforms for the outputsthat infringe on the work that
got appropriated and put intothese engines, if you will,
(23:31):
because that's the part of theequation that isn't being
addressed yet in these lawsuits,at least with an opinion yet,
that is helpful to creatorsright now.
SPEAKER_01 (23:40):
So, like a rule of thumb that um we've we've seen
with uh content creation,whether it be writing or imagery
um or graphic design, is istypically like over a 20%
deviation difference, um, aslike a rule of thumb.
Have you like how would youmeasure it, or is that not a
(24:01):
good rule of thumb to use?
SPEAKER_02 (24:03):
You mean for determining whether there's an
infringement on a there's youknow that's a helpful factor,
but it's only one of multiplefactors.
It's not always the amount ofthe content that was
appropriated, but it could bethe part of the content.
You could take 20% of somebodyelse's work and either have it
(24:25):
be the most significant, 20% ofthat work be the heart of the
work, um, or have it be, youknow, the marginal part of the
work.
And so for that reason, when acourt analyzes an infringement
claim, it's looking at multiplefactors.
How much did you take?
Was it at the core of what wastaken?
(24:45):
Um, will it impact the marketfor the original work?
Um, which is one of the reasonswhy copyright law exists to
protect the economic rights ofcreators.
Um, and there are a host ofother factors, which the court
will all weigh, you know,they'll weigh them all, not
anyone in front.
I can tell you that, you know,the ability, losing the ability
(25:06):
to monetize your own creation issomething that would be very
persuasive in situations likethis.
So um, but you got to prove theaccess and you have to prove the
substantial similarity of theoutput.
And most creators don't have thefinancial means and wherewithal
to go through that forensicprocess.
SPEAKER_01 (25:27):
Do you think this is going to be a tort?
Or do you think this is gonna bewell?
SPEAKER_02 (25:32):
It is a tort.
I mean, copyright infringementis a tort of of a type, if you
will, but I think that do Ithink there'll be a specific
cause of action?
I think we're a long way fromthat happening.
I like to always say that youknow, technology always leads,
business, you know, puts on itsjogging shoes and runs after it,
sometimes fast, sometimes not asfast.
(25:54):
And then the law follows behindwith push brooms and sweeps up
the mess that gets left behind.
And so the law is always gonnatrail um the realities that
businesses face adapting thetechnology.
So I think it's gonna be a whilebefore we are gonna see any
meaningful progress on creatorrights.
(26:15):
Um, there are, you know, there'sthere are lawsuits.
Um, I I have personal friendswho are part of the anthropic
suit right now because they'reauthors and their works were
imported without permission uminto um anthropic's engines.
And so um, you know, but it'sgonna take a while for creators
(26:35):
to actually realize, you know,compensate being compensated for
these kinds of things.
SPEAKER_01 (26:41):
So, Sharon, it it one of the other things that
comes to mind is uh we had aclient uh probably 24 months
ago, roughly in in that range,and they're they're big company,
uh publicly traded, andessentially they were still
getting comfortable with AI,they were actually not
comfortable with AI, and theywere using a certain tool to
(27:02):
determine if there was any AIwritten in in the article, and
and basically we were submittingarticles that were done by a
human writer, and this was youknow it was pretty nascent as
far as like uh heavy usage, uh,but it kept coming back like 85
to 95 human writing, and theywere rejected, they're like, no,
(27:23):
this is AI written.
And it made me think of like thethe study that came out with
like the Bible, and it was like,oh, the Bible had written this
much AI.
The reason AI, uh these thesereaders are determining that if
it's AI because it's based onhuman writing, like there's
certain kind of tells orgiveaways of how content's
structured, but but it was likewe couldn't get the thing to not
(27:48):
say that there wasn't a certainpercentage of AI writing because
it was based on human writing,and we kept kept getting content
rejected.
Uh and it, you know, it's justthe the the the complete
opposite end of what we'retalking about now, right?
But it was a it was a really uhinteresting kind of uh thing
that we were trying to tackle.
And then I'm taking this uhethics uh and compliance AI
(28:11):
course from Oxford, and I askedthe same question.
I said, Can these AI uhdetection devices like how
accurate are they?
And he basically said, with deepfakes and everything that's
coming online, it's almostimpossible to tell the
difference as it gets better.
And so how are we gonna knowwhat's real and what's not real?
(28:34):
And how are we gonna know what'sAI and not AI um unless you you
you have a basis to measure itagainst and and even like
certain content structures andsentences, I'm sure you know
there's a likelihood that somepeople are gonna form some
sentences the same way.
SPEAKER_02 (28:51):
Yeah.
I think at the heart of it, thequestion you're asking uh is
before it's a legal question,it's a technology and an ethics
question, right?
Yeah, because these are theseare issues that I am confident
the technology will evolve to beable to assist and then they
become more democratized, right?
So more of us have access tothem, more of us can afford
(29:12):
them, more of us can access, youknow, use them.
Um, and then there's the ethicsissue, which is, you know, and I
have been, I don't know aboutyou, Matt, but I have sat in
live simulations at conferenceswhere people cannot always tell
the difference between AIgenerated and human generated
content.
But what is also equally true isthat if they know or suspect
(29:35):
that is AI generated, they don'ttrust it as much as they trust
the human-created content.
So brands are gonna have todecide the authenticity problem
for themselves.
They're gonna have to weigh andbalance the amount of cost
savings that can be achieved,the amount of time savings that
can be achieved, with thepotential for um consumer or end
(29:59):
user mistrust of the endproduct.
Because I've actually sat insimulations um at conferences
for marketing agency ownerswhere um a brief was created of
marketing strategy responsive tothe brief was created.
They were split into two teams,a human team, an AI team.
(30:20):
Um, and then the audience livevoted on which one they thought
was AI generated.
It was 50% evenly split.
Nobody could tell, basically,bottom line.
Um, and then you know, resultswere mixed in terms of which
strategy actually won theapproval of the audience because
they were competing against eachother.
(30:41):
So, but we do know is that thetrust is not there, and and you
know, that's a bigger issue thana legal issue.
It's as like I said, as much asmuch an ethical issue as
anything else.
Um, we're gonna have to see, youknow, hopefully some of the
court cases will start toresolve some of the legal um
challenges and that will createa higher degree of confidence
(31:02):
for creators, and then we'llhave some more clarity on some
of this other stuff.
SPEAKER_01 (31:05):
Well, wow, this this has been great.
I I feel like we need to haveyou back on as things evolve to
kind of do it to to some of uhthe developments that are
happening.
Um, is there anything that wedidn't cover that you thought
might be good to add into thisconversation?
SPEAKER_02 (31:23):
I uh, you know, I think one of the points that I'd
like to stress is this is agreat time for establishing your
foundation or revisiting yourfoundation legally in your
business with your contracts,with your policies, um, with the
protections you have in placefor the critical pieces of
intellectual property thatyou've created.
(31:44):
It's time to make sure thebasics are covered because um,
and you need to revisit yourbasics a little bit more
frequently than you used to haveto because the regulatory
landscape and the technologylandscape evolve so much more
quickly now.
So that would be my partingshot, um, you know, to
everybody.
And again, these are things thatyou can do no matter what the
(32:06):
what size your business is orwhat kind of resources you have
in hand.
SPEAKER_01 (32:11):
Absolutely.
And Sharon, how is best peopleto follow you, follow your work,
get in touch with you, that sortof thing.
SPEAKER_02 (32:18):
Thanks.
Well, first of all, I appreciatebeing on the show today.
I've really enjoyed theconversation.
Um, you can find me a couple ofplaces.
I'm very active on LinkedIn.
It's uh Torek, T-O-E-R-E-K.
Our firm, uh Torek Law, doesbusiness as legal and creative
in the agency world.
So legalandcreative.com.
Um, and I'm also a podcaster.
(32:40):
So uh the innovative agency iswhere I host guests who talk
about innovation in themarketing agency world.
So love to have you join usthere.
SPEAKER_01 (32:49):
Fantastic.
Well, everybody, thanks so muchfor listening.
I know things are evolving, andthis is really important, like
she said, of what you need to belooking at and updating and
thinking about.
I think that there was reallythis push to understand it and
then kind of prompt engineering,get trained on it, utilize it,
interpret it, get it, get it,well, interpret it, but
(33:11):
understand how theinterpretation's happening,
getting it utilized in yourbusiness.
And now the compliance layer,the risk layer, um, really need
to look at that, revisitingcontract language because need
to understand what theguardrails are, need to
understand your indemnificationsand protection.
So I would encourage you all toreach out to Sharon or somebody
(33:31):
like Sharon to revisit some ofthat stuff.
And uh, I think this is reallyimportant.
Until the next time, um, if youwant to grow your business with
the largest, most powerful toolon the planet, the internet, and
now I think AI as the nextrevolution, reach out to EWR for
more revenue in your business.
We uh do provide all kinds of LMvisibility tools.
(33:53):
Uh, we're launching newproducts.
Um, there's a lot going on.
Uh, so go check us out at EWRDigital.
You can also find out more at uhbestseo uh.com,
bestseopodcast.com.
Uh until the next time,everyone.
My name is Matt Bertram.
Bye bye for now.
This is the unknown secrets of internet marketing.
Your insider guide to thestrategies top marketers use to
crush the competition.
Ready to unlock your businessfull potential.
Let's get started.
SPEAKER_01 (00:15):
Howdy, welcome back to another funfold episode of
The Unknown Secrets of InternetMarketing.
I can't even talk today.
Today has been one of thosedays.
It's been one of those weeks.
I hope everybody is doing well.
There is a lot happening in theworld of SEO, content, online
marketing.
Hopefully, through the pastguests, I would encourage you to
(00:36):
go check it out.
We've had some phenomenal gueststalking about what is happening
with AI.
And AI is really coming intothis and changing the game.
There's a lot of governanceissues with how to use it,
what's going on.
So I thought it'd be really goodto bring on someone that would
talk about trademarking becausewe're starting to see a lot of
that, copywriting, uh socialmedia law, ad law, marketing to
(01:01):
kind of uh build a frameworkaround how we should be looking
about these things.
So, Sharon, welcome to the show.
SPEAKER_02 (01:08):
Thanks, Matt.
Happy to be here.
SPEAKER_01 (01:10):
And this is Sharon with legalandcreative.com.
So I'll let you talk more aboutit at the end.
Uh, but uh tell us a little bitabout your background and how
you got got involved in this andkind of what you're seeing on on
the horizon as far as uh what'shappening today.
SPEAKER_02 (01:25):
Sure.
Well, so I am the founder ofToric Law, which serves
primarily independent marketingagencies in the United States.
And so we help them basically inone of three areas: intellectual
property, protection,enforcement, contract
development and negotiation, andthen regulatory compliance with
(01:45):
all the rules and regs thatgovern marketing and advertising
and things like that.
Um, I'm an IP lawyer by trainingand uh started my career as an
IP lawyer, began working moreheavily in the marketing space,
and then uh founded the firmthat I own and run now to serve
independent agencies in thatarea.
SPEAKER_01 (02:06):
Fantastic.
Well, I'm so I'm so glad to haveyou on because there's uh so
many things happening.
I mean, what are the things Iguess that are the biggest uh
hiccup points uh for peopleright now that you see over and
over again?
Let's just get the the basicsout of the way.
SPEAKER_02 (02:23):
Yeah, I think, you know, I feel like I can't either
host my show or talk withsomebody on their show without
saying A and I next to eachother.
And say I think that the interms of the legal and
regulatory landscape right now,uh everybody's got big questions
about what will happen withrespect to AI adoption, how it's
(02:48):
going to impact intellectualproperty rights to work that
gets created, um, what it'sgoing to mean for things like
content authenticity, contentfakery, and then also what it
means in you know in theadvertising world, what it means
in terms of creating honest andum you know, honest impressions
(03:10):
of a brand to a consumer.
And so um we're seeing a couplethings, and there's a couple
things we're watching right nowfrom a regulatory and a legal
perspective.
Uh, we have copyright cases thatwe're seeing weave their way
through the federal courts, theuh appellate courts right now to
determine what are theguardrails and boundaries gonna
(03:32):
be around these gigantic AIplatforms' ability to digest
content that somebody owns thecopyright in, whether it's
novel, a script, um, a marketingcampaign, a logo, whatever it
might be, um, what are theguardrails gonna be around their
ability to digest into theirtraining data all of that stuff?
(03:55):
And then who is in the secondquestion being, well, who is
gonna be responsible if anyinfringement occurs on the other
side with the output from AI?
So that obviously raises a lotof intellectual property
questions, a lot of ownershipquestions.
I would say the big question Iget on this point, just from our
clients who happen to be ownersand leaders of marketing
agencies, is first of all, whoowns the content if we're using
(04:18):
generative AI to create it?
And second of all, who'sresponsible if something goes
sideways once the content is outthere in the public and it does
infringe on somebody else's IPrights?
So I think I would start thereand say those are the big
questions that we see right nowfrom a regulatory perspective
around the impact of AI oncreative work of all kinds.
SPEAKER_01 (04:42):
Yeah, I mean, there's not a ton of guidance.
I know that in Texas, there's alaw, a law that passed on the
first where they're creating acouncil, which is kind of taking
a leadership role.
We got Colorado uh trying to uhprovide consumer rights in in
some different areas, and thenof course, California uh and
kind of adopting uh kind of GDPRkind of regulatory environment,
(05:06):
which scares me because there'sa lot of uh administrative
overhang to be able to operatein in that environment.
Um, there's a number of thingsthat you hit on that I look at
from a little bit differentlens.
Um, and also understanding likeutilizing these tools
internally, have having uh aprogram set up to uh evaluate
(05:28):
these different tools, how totrack what's happening.
Um there's just a lot ofconcerns and and not a lot of
clarity on on what's gonnahappen.
I mean, I'm even seeing withsocial media, uh uh there's a
lawyer here here in Texas thatjust um took took them uh took
uh Mark Zuckerberg in front ofuh like I don't know, I don't
(05:51):
know if it was the congressionalor whatever, but he basically
was asking about the algorithmcausing depression, right?
And they they're looking at thatimpact of that.
And then I start thinking thealgorithm with AI is influencing
how people are interpretingbrands, how people are looking
at brands, what if what if froma regulatory environment it
tells you to do something thatthere's a hallucinization, and
(06:14):
then you you you take actionbased upon that, where are the
legal implications there?
So there's there's this wholebox of things that I think is
starting to get unpacked and andregulation is starting to catch
up, but it's not there yet.
I mean, so what are the what arethe recommended even guardrails
that you would say for peopleoperating in this environment to
(06:36):
start considering or looking ator trying to do their best to
protect themselves?
Um and and you you list a wholeslew of other things that they
need to be thinking about aswell.
And I mean, what's the guidanceyou're giving people?
SPEAKER_02 (06:50):
Yeah, well, I do have some practical takeaways
for anybody who's listening interms of what are some things
you can actually implement in ina business of any size to sort
of start dealing with andgetting your arms around this.
But I would I, you know, to myreaction to what you just shared
about the regulatory environmentis that what we were expecting
(07:11):
to see um with regulatoryactivity around AI was what we
have seen historically regardingum the regulatory landscape for
data privacy.
And what I mean by that is thatEurope is simple.
There's GDPR, it covers most ofEurope, and it's one set of
(07:32):
standards, and they're strict,but once everybody understood
what they were and and theyhaven't evolved much since they
were enacted, it's a it's aplaying field that people are
getting more and morecomfortable navigating.
And in the US, though, we'venever had a federal standard for
data privacy.
What we instead have is thisstate patchwork of data privacy
(07:54):
laws.
You know, we we play toCalifornia because that that is
the strictest set of standards,the closest to GDPR.
But there's state activity inother areas that is, you know,
sort of catching up.
So that's the landscape withdata privacy.
I thought that's what we wouldsee for AI.
And to some degree, it is whatwe're seeing.
(08:15):
However, laid over that, you'vegot the federal government
putting a lot of pressure on thestate government and state
governments in the United Statesnot to regulate the use of AI.
You've got some states stillmoving forward and and and doing
so.
Some states have laws regardingrequiring disclosure if you've
(08:37):
used AI in creating the content.
Um, New York State has umsynthetic content creation
rules.
Um, there are SAG-AFTRA unionnegotiations around the whole um
issue of use of AI-generatedcontent likenesses, et cetera,
et cetera.
So we're still seeing somepatchy state-by-state
(08:58):
regulations, but then we'reseeing this tension between the
federal government and thestate.
The federal government didn'tget involved at all in
preventing states from enactingtheir own data privacy rules.
You know, go for it, is prettymuch the approach they've taken.
I doubt anybody said it thatway, but that's kind of how it
is rolled out.
But with AI, the federalgovernment has been very um
(09:20):
specific, if you will, about umnot wanting the states to get in
their way in terms of whateverdecisions we might make in the
United States around governingusage of AI.
So, what do you do about allthat?
As somebody who's trying to owna business and keep on top of
all this and limit your risk,and there's a few things.
(09:42):
First of all, um, you reallyshould be, if you're a service
provider, especially aprofessional service firm, for
example, um, you should behaving conversations with your
clients, your vendors, yourindependent contractors around
their AI use practices.
What platforms do they use?
(10:03):
Um, if it's your clientorganization, what platforms do
they allow you to use?
Um, what information are theygiving you that has been
generated out of AI because itmay make its way into the NWork
product, right?
Um, what information are theygiving you that is confidential
or proprietary that they want tomake sure you don't input into
(10:24):
any AI platform?
Um so have come having crucialconversations with key parties
in your business life, whetherthat is strategic partners,
clients, customers, whomever.
Secondly, is have, even if it'sa skeleton or an outline form at
this point, progress is betterthan perfection.
(10:45):
Have a written AI policy.
SPEAKER_01 (10:47):
Yes.
SPEAKER_02 (10:47):
Have one internally that you socialize with
everybody on your team.
Have an external facing policythat can be shared and shareable
with people outside yourorganization about how you use
AI, you know, and what yourpractices are around it.
Um, and then I would say third,look at your contracts and
(11:11):
ensure that you are addressingany responsibility or liability
around AI usage.
Um, you know, and we weren'tdoing this 24 months ago
candidly, even in the, I mean,we we create and negotiate
hundreds of contracts every yearon behalf of our marketing
agency clients.
And 24 hours, 24 months ago, weweren't um addressing AI
(11:32):
specifically.
I mean, yes, we've always hadindemnification and liability
language, but but now we areaddressing it specifically.
And it's probably time for mostof your listeners to be thinking
about doing that as well.
So those are three things to bethinking about.
And and you know, and thenbeyond that, I would say um
having the internal trainingconversations, even informally
(11:54):
with your teams about riskmanagement around adopting AI.
Um these are things you can doand scale no matter what your
resource levels are and nomatter what size you are as a
business.
SPEAKER_01 (12:07):
Yeah, I actually uh just did a uh a survey on on
some of this stuff on kind ofwhere where business owners are
at uh that I'm gonna bepublishing very soon.
And uh real really interesting,I would tell you also, or I
guess my question to you is Idon't think that arrows and
emissions insurance, thelanguage covers any uh of this
sort of thing, right?
(12:28):
And so how how from like we'regonna probably start seeing
cases pop up at some point ofyou know a misuse, and you got
like shadow AI, and then likeyou're putting stuff in a GPT,
and then you move companies, andthen somebody else, you know,
starts use like there's gonna beall these things that start to
pop up.
(12:49):
Um and and I think having agovernance policy is is super
important, but but I I mean, isthere any kind of other risk
protection that you can do ifsome of these things happen?
SPEAKER_02 (13:02):
Right.
It's a great question.
I mean, you know, uh the I justgot this question actually when
I was speaking to a group ofagency owners um two weeks ago.
It's funny that you asked itexactly the same way that uh a
person at the meeting asked it.
And there aren't any productsyet that specifically address,
(13:24):
at least to my knowledge,liability or responsibility
around something going sidewaysum out of using generative AI or
out of breaching confidentialityor data privacy.
So you we're left with lookingat our normal insurance stacks,
right?
Our our general liability, ourerrors and omissions.
(13:46):
Cyber, I think, is probably theclosest product to um uh have
the potential to evolve intomaybe covering specific AI
situations.
But uh there are no AI uh oopsproducts out there yet.
And so um you really just haveto look at your insurance stack
as a business, probably belooking at, I mean, measuring
(14:08):
the degree to which you're goingto be assuming the risk of
giving some of these tools andum adjusting your coverage
accordingly, so that maybeyou're carrying a little bit
more than you might have been acouple of years ago, um, with
particular attention probably toyour umbrella and your cyber
insurance policies around thisspecific issue.
SPEAKER_01 (14:29):
Gotcha.
You know, one of the things asas you talk about, right?
18 months ago, where were we?
Um there was a number ofpodcasts that came out, and
Google is starting to putwatermarks on uh anything that
you're using to generate, let'ssay images, for example.
So you're generating a nanobanana or whatever it's called.
Uh uh, and you know, they'reputting a little Gemini uh
(14:54):
watermark on it, and then itgets tagged automatically when
you publish that, that this wasgenerated with Gemini, which I
think is a great marketingstrategy as well.
I think putting the you knowfrom iPhone is how it kind of
went went viral as well.
Um, and they did a podcast, theythey have a webmasters podcast,
and and they this was a coupleyears ago around images, and it
(15:16):
was saying from a search enginestandpoint, right?
So there's the legal side ofthings and then there's the
search side of things that AIgenerated images are are okay,
right?
Because they I I felt like theywaved the the white flag a
couple of years ago when peoplestarted generating content
because it was like, is it humangenerated?
Is it um well useful?
They said useful content, ifit's AI generated, it's not um
(15:40):
you know, bad, or uh you know,now the term is AI slop, I guess
is what people are are saying inthe industry.
But if it's useful and helpfulit and it's generated, the
search engines are going toindex it.
And then from an imagestandpoint, it is a unique image
if it's not utilizing stock.
So there is the issue ofutilizing uh licensing on
(16:01):
images, and now you can kind ofmove into uh AI generated image,
and then there's not clarityexactly, but from a search
standpoint, it's unique content,and that's how it's being
treated, and so it's beingviewed favorably by the search
engines.
And you know, I I don't knowfrom a I really haven't dug into
(16:22):
it too much on the uh AI systemsfrom a image indexing standpoint
of uh how how it's uh presentingthose, but I would love to kind
of move uh more back towards thetraditional uh things that we
can maybe cover kind of socialmedia law, ad law, um, as well
as maybe uh copyright law, whichyou know, I I think it AI is
(16:47):
kind of the direct like I think75% of all content's gonna be
generated in AI, if not higher,very soon.
Uh and that's gonna be adegradation on the models.
And so that's why they'rewanting human input and trying
to trying to make sure thesemodels don't collapse.
But I'd love to kind of get yourbroader view as we fan out into
(17:08):
some of your other um uh skillslike experience sets to share
some of that.
SPEAKER_02 (17:14):
Right.
Well, so one of the main, youknow, one of my main personal
passions and one and sort of thethe foundation of my background
that led me to decide to focuswhere we focus the work at my
firm is you know, my honest umpassion for intellectual
(17:34):
property creation andinnovation.
I named my own podcast after theterm innovation.
I just I think thatentrepreneurial companies who
innovate um move the needle oncommerce and they move the
needle in our culture.
And I think that the legalsystem should support creators
(17:58):
and innovators.
And so IP is a huge part of whatwe do at my firm, and whether
that is helping to create aclear pathway for protecting IP,
for example, in the trademarkrealm, where um, you know,
companies are brandingthemselves or branding new
products or services that theymight want to put out into the
(18:21):
market, um, whether it isenforcing um the trademarks uh
that protect the brands of ourclients, um, or whether it's
monetizing the intellectualproperty, whether it's a
trademark license, for example,in the franchise world,
trademark licensing is a hugecomponent of franchising, as one
example, or uh, you know, andthen sliding over from trademark
(18:45):
to copyright.
Um, there's another point of theIP.
I use a triangle analogy for myrubric and evaluating the IP
than any business has.
There's brand, which isprotected by trademark, then
there's your actual content, thestuff that you create, um, most
of which you sell.
Um and there is a copyrightstrategy or a trade secret
(19:08):
strategy, depending upon how yougo to market with what it is
that you're creating.
If your market advantage isbecause it's your it's your
unique secret sauce, then youknow, copyright's probably not
going to be the strategy foryou.
Trade secret protection is gonnabe the strategy for you.
But if it's work you'republishing, if you're a digital
course creator, if you are um amovie maker, if you are a
(19:31):
software developer creating opensource tools, copyright may be
the most valuable mechanism forprotecting your work because
your work's gonna be out therefree for people to see and
access.
Um, and then the transactionspoint of the triangle: this is
how you make money from thestuff that you create or
(19:52):
innovate and then sell.
And that could be a transactioninto your business because
you've used a strategic partnerto help you create it, or you've
used a contractor who doesn'twork for you to help you create
it, or it could be transactionsout, which could be the way you
make money by licensing yourstuff.
It could be the terms andconditions of a software
license.
So that's kind of the way weanalyze the body of work and how
(20:18):
you protect it.
And I think as a rule,entrepreneurial companies tend
to undervalue the amount of IPthat they create.
Um, they tend not to leverageit, maximize the leverage of it
as much as they can.
So this is just my point ofview, and this is one of the
reasons why we focus where wefocus.
And it just so happens that youknow marketing agencies create a
(20:41):
ton of IP.
And so they're a good fertileground for us for this kind of
work.
SPEAKER_01 (20:47):
Yeah, no, commercial use is is really, I think,
important when you're uhapplying for these trademarks
and patents and things of thatnature.
Um, I one of the things that'sfascinating to me, again, going
back to AI, is as I'munderstanding how these
algorithms work, your work thatcan be ingested can influence
(21:10):
the output and influence theinterpretation of what's being
presented, but it doesn't alwaysgive clear reference to you.
So it's kind of like it's theit's like bumping into you, but
it's not calling it out, right?
And it's just kind of moving itin a certain direction.
So there's this real question ofinfluence of how do you know
(21:35):
that your work is influencingthe AI and you're not getting
cited?
Um and and then I guess later onum the the legal framework to
say, well, this is influencingthis large language model or the
the public model, uh how do youhow would you even track that
back?
Like how would you even in yourhead try to figure out how If it
(22:00):
was doing that or not, and howto measure it.
SPEAKER_02 (22:02):
Yeah.
Only through diligence, and thisis the problem, right?
The the attribution models arejust not available to the
average creator.
And certainly none of the bigAI, none of what I call big I
big AI is going to help acreator whose content it has
ingested to, you know, train itsdata sets by telling them, oh,
(22:26):
this is where you'll find it andthis is the output it showed up
in.
It's just not going to happen.
So the average creator is eithergoing to find an infringement
because they've stumbled upon itor somebody they know has
stumbled upon it, or they've orthey've experienced actual
confusion in the marketplacebecause somebody thinks they're
another brand.
(22:46):
Or they find their work, youknow, um cribbed, you know, they
find a substantial similaritybetween their original work and
some other work that they seeout there.
So the the systems to helpprevent the lack of attribution
are not yet accessible.
I'm not saying they don't existbecause I, you know, I know in
(23:08):
my heart of hearts that theythat they do exist, but they're
not accessible to the averagecreator.
And so we're gonna have to waitand see how that evolves, and
we're gonna have to wait and seehow some of these court cases
evolve in terms of theresponsibility of some of these
AI platforms for the outputsthat infringe on the work that
got appropriated and put intothese engines, if you will,
(23:31):
because that's the part of theequation that isn't being
addressed yet in these lawsuits,at least with an opinion yet,
that is helpful to creatorsright now.
SPEAKER_01 (23:40):
So, like a rule of thumb that um we've we've seen
with uh content creation,whether it be writing or imagery
um or graphic design, is istypically like over a 20%
deviation difference, um, aslike a rule of thumb.
Have you like how would youmeasure it, or is that not a
(24:01):
good rule of thumb to use?
SPEAKER_02 (24:03):
You mean for determining whether there's an
infringement on a there's youknow that's a helpful factor,
but it's only one of multiplefactors.
It's not always the amount ofthe content that was
appropriated, but it could bethe part of the content.
You could take 20% of somebodyelse's work and either have it
(24:25):
be the most significant, 20% ofthat work be the heart of the
work, um, or have it be, youknow, the marginal part of the
work.
And so for that reason, when acourt analyzes an infringement
claim, it's looking at multiplefactors.
How much did you take?
Was it at the core of what wastaken?
(24:45):
Um, will it impact the marketfor the original work?
Um, which is one of the reasonswhy copyright law exists to
protect the economic rights ofcreators.
Um, and there are a host ofother factors, which the court
will all weigh, you know,they'll weigh them all, not
anyone in front.
I can tell you that, you know,the ability, losing the ability
(25:06):
to monetize your own creation issomething that would be very
persuasive in situations likethis.
So um, but you got to prove theaccess and you have to prove the
substantial similarity of theoutput.
And most creators don't have thefinancial means and wherewithal
to go through that forensicprocess.
SPEAKER_01 (25:27):
Do you think this is going to be a tort?
Or do you think this is gonna bewell?
SPEAKER_02 (25:32):
It is a tort.
I mean, copyright infringementis a tort of of a type, if you
will, but I think that do Ithink there'll be a specific
cause of action?
I think we're a long way fromthat happening.
I like to always say that youknow, technology always leads,
business, you know, puts on itsjogging shoes and runs after it,
sometimes fast, sometimes not asfast.
(25:54):
And then the law follows behindwith push brooms and sweeps up
the mess that gets left behind.
And so the law is always gonnatrail um the realities that
businesses face adapting thetechnology.
So I think it's gonna be a whilebefore we are gonna see any
meaningful progress on creatorrights.
(26:15):
Um, there are, you know, there'sthere are lawsuits.
Um, I I have personal friendswho are part of the anthropic
suit right now because they'reauthors and their works were
imported without permission uminto um anthropic's engines.
And so um, you know, but it'sgonna take a while for creators
(26:35):
to actually realize, you know,compensate being compensated for
these kinds of things.
SPEAKER_01 (26:41):
So, Sharon, it it one of the other things that
comes to mind is uh we had aclient uh probably 24 months
ago, roughly in in that range,and they're they're big company,
uh publicly traded, andessentially they were still
getting comfortable with AI,they were actually not
comfortable with AI, and theywere using a certain tool to
(27:02):
determine if there was any AIwritten in in the article, and
and basically we were submittingarticles that were done by a
human writer, and this was youknow it was pretty nascent as
far as like uh heavy usage, uh,but it kept coming back like 85
to 95 human writing, and theywere rejected, they're like, no,
(27:23):
this is AI written.
And it made me think of like thethe study that came out with
like the Bible, and it was like,oh, the Bible had written this
much AI.
The reason AI, uh these thesereaders are determining that if
it's AI because it's based onhuman writing, like there's
certain kind of tells orgiveaways of how content's
structured, but but it was likewe couldn't get the thing to not
(27:48):
say that there wasn't a certainpercentage of AI writing because
it was based on human writing,and we kept kept getting content
rejected.
Uh and it, you know, it's justthe the the the complete
opposite end of what we'retalking about now, right?
But it was a it was a really uhinteresting kind of uh thing
that we were trying to tackle.
And then I'm taking this uhethics uh and compliance AI
(28:11):
course from Oxford, and I askedthe same question.
I said, Can these AI uhdetection devices like how
accurate are they?
And he basically said, with deepfakes and everything that's
coming online, it's almostimpossible to tell the
difference as it gets better.
And so how are we gonna knowwhat's real and what's not real?
(28:34):
And how are we gonna know what'sAI and not AI um unless you you
you have a basis to measure itagainst and and even like
certain content structures andsentences, I'm sure you know
there's a likelihood that somepeople are gonna form some
sentences the same way.
SPEAKER_02 (28:51):
Yeah.
I think at the heart of it, thequestion you're asking uh is
before it's a legal question,it's a technology and an ethics
question, right?
Yeah, because these are theseare issues that I am confident
the technology will evolve to beable to assist and then they
become more democratized, right?
So more of us have access tothem, more of us can afford
(29:12):
them, more of us can access, youknow, use them.
Um, and then there's the ethicsissue, which is, you know, and I
have been, I don't know aboutyou, Matt, but I have sat in
live simulations at conferenceswhere people cannot always tell
the difference between AIgenerated and human generated
content.
But what is also equally true isthat if they know or suspect
(29:35):
that is AI generated, they don'ttrust it as much as they trust
the human-created content.
So brands are gonna have todecide the authenticity problem
for themselves.
They're gonna have to weigh andbalance the amount of cost
savings that can be achieved,the amount of time savings that
can be achieved, with thepotential for um consumer or end
(29:59):
user mistrust of the endproduct.
Because I've actually sat insimulations um at conferences
for marketing agency ownerswhere um a brief was created of
marketing strategy responsive tothe brief was created.
They were split into two teams,a human team, an AI team.
(30:20):
Um, and then the audience livevoted on which one they thought
was AI generated.
It was 50% evenly split.
Nobody could tell, basically,bottom line.
Um, and then you know, resultswere mixed in terms of which
strategy actually won theapproval of the audience because
they were competing against eachother.
(30:41):
So, but we do know is that thetrust is not there, and and you
know, that's a bigger issue thana legal issue.
It's as like I said, as much asmuch an ethical issue as
anything else.
Um, we're gonna have to see, youknow, hopefully some of the
court cases will start toresolve some of the legal um
challenges and that will createa higher degree of confidence
(31:02):
for creators, and then we'llhave some more clarity on some
of this other stuff.
SPEAKER_01 (31:05):
Well, wow, this this has been great.
I I feel like we need to haveyou back on as things evolve to
kind of do it to to some of uhthe developments that are
happening.
Um, is there anything that wedidn't cover that you thought
might be good to add into thisconversation?
SPEAKER_02 (31:23):
I uh, you know, I think one of the points that I'd
like to stress is this is agreat time for establishing your
foundation or revisiting yourfoundation legally in your
business with your contracts,with your policies, um, with the
protections you have in placefor the critical pieces of
intellectual property thatyou've created.
(31:44):
It's time to make sure thebasics are covered because um,
and you need to revisit yourbasics a little bit more
frequently than you used to haveto because the regulatory
landscape and the technologylandscape evolve so much more
quickly now.
So that would be my partingshot, um, you know, to
everybody.
And again, these are things thatyou can do no matter what the
(32:06):
what size your business is orwhat kind of resources you have
in hand.
SPEAKER_01 (32:11):
Absolutely.
And Sharon, how is best peopleto follow you, follow your work,
get in touch with you, that sortof thing.
SPEAKER_02 (32:18):
Thanks.
Well, first of all, I appreciatebeing on the show today.
I've really enjoyed theconversation.
Um, you can find me a couple ofplaces.
I'm very active on LinkedIn.
It's uh Torek, T-O-E-R-E-K.
Our firm, uh Torek Law, doesbusiness as legal and creative
in the agency world.
So legalandcreative.com.
Um, and I'm also a podcaster.
(32:40):
So uh the innovative agency iswhere I host guests who talk
about innovation in themarketing agency world.
So love to have you join usthere.
SPEAKER_01 (32:49):
Fantastic.
Well, everybody, thanks so muchfor listening.
I know things are evolving, andthis is really important, like
she said, of what you need to belooking at and updating and
thinking about.
I think that there was reallythis push to understand it and
then kind of prompt engineering,get trained on it, utilize it,
interpret it, get it, get it,well, interpret it, but
(33:11):
understand how theinterpretation's happening,
getting it utilized in yourbusiness.
And now the compliance layer,the risk layer, um, really need
to look at that, revisitingcontract language because need
to understand what theguardrails are, need to
understand your indemnificationsand protection.
So I would encourage you all toreach out to Sharon or somebody
(33:31):
like Sharon to revisit some ofthat stuff.
And uh, I think this is reallyimportant.
Until the next time, um, if youwant to grow your business with
the largest, most powerful toolon the planet, the internet, and
now I think AI as the nextrevolution, reach out to EWR for
more revenue in your business.
We uh do provide all kinds of LMvisibility tools.
(33:53):
Uh, we're launching newproducts.
Um, there's a lot going on.
Uh, so go check us out at EWRDigital.
You can also find out more at uhbestseo uh.com,
bestseopodcast.com.
Uh until the next time,everyone.
My name is Matt Bertram.
Bye bye for now.
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