Honest AI will not replace humans.

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Wait What Really OK. With your
host, Loren Weisman.
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This is a fully licensed theme
song for the
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show about stuff that makes you say Wait
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What Really OK. This is Loren Weisman.
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This is Wait What Really OK, The Brand
Communication and Optics podcast and today's
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title is loosely or its working title is
Honest AI will not Replace
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Human Beings over the last and you may be hearing a
little bit of wind or a lot of
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bit of wind, but it's a beautiful day, it's windy,
it's a little bit overcast where
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I am, and it's just this comfortable sort
of summer wind in May.
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And it's nice to be outside and with some things
that are happening that have kept
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me in bed and kept me inside. I just want to be
outside and I want to share this
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thing outside. So the brushes of wind in the
background, they may get louder,
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they may get softer. I spoke to Doug Fish of
Fish Stewarding Group about
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a week ago and he had said at one point, he said, I
really think that you should do
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a video talking about some of the future of AI and
some of the thoughts that we've
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discussed together and the trends that I've seen
and some elements about the motion
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of it and the right way to use it and the
wrong ways to use it.
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And I at first was thinking just
absolutely not.
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My views on the way that AI is being shared right
now was so much hype and so many
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people stating it or claiming to state what the
future is going to be, or for that
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matter, using AI to ask what the future is going
to be, and oftentimes in a very
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selfish sounding way, presenting it as what they
want it to be in their intention or
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inside of their business or inside of their needs,
as opposed to the motion of where
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it potentially can go, where it won't, where
it can't go, and so on.
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Then just yesterday I was having a great
conversation with Mark Simpkins and he's
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the CEO at aws, and we went into a
little bit more
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about AI and he said along the lines about
structuring and some of the same exact
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things. A conversation went on for a very long time
and the structure and the ideas
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and thoughts that I've had on AI for the
better part of 10 years.
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And as much as people say, oh, AI is
new, AI is new.
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AI has been around for a very,
very long time.
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Even in some of the modules and aspects, they
weren't as strong, but they were being
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used. And for many years, as in many decades,
it's now a lot more known it's
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now a lot more accessible, it's now being used that
much more by the public, and in
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some ways it's being exploited
that much more.
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So the goal inside of this episode, I'm
not going into an anti AI
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rant. At the same time, I'm not going into
necessarily a pro rant about it either.
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I'm coming from a middle standpoint, from viewing
the authenticity and the options
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of AI, as well as how I believe authentic,
authoritative businesses can apply AI and
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use standards that are strong, that are true to
heart, true to morals, true to
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professionalism and true to transparency.
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Now, this is not so common with how the
abuses of AI are taking hold
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and growing and growing and growing
at the same time.
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I'm going to throw out one of my forecasts of
what I see and a couple different
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options on that forecast because it really, right
now there is no clear path on AI.
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It could go a number of ways. Right now it's
continuing to move forward and yes,
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it's being abused already, but because of the lack
of regulation, because of the
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lack of understanding, because of the lack of
compliance, this is the wild west
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that's out there right now
regarding AI as is.
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Jump back. Let's jump back 20, 22 years
to 2003 and the wild
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west of what was happening around the
time of digital music.
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I put out in a press release, when I was part of
the music industry, I put out in a
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press release and I got pretty heavily
attacked for it at the time.
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My thoughts on what I saw happening with the
downloads, what I saw happening when
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you with Napster, what I saw with the early forms
of itunes, and there are many
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people that put many predictions.
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I think that if you're going to put out a
prediction, if you're in the business
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world, if you believe and you can justify what
you're saying and you stand by it,
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put it out in a press release. Put it in a genuine
press release, not something you
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call a press release and put for immediate
release now and some kind of crap on
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Twitter or X, but more so through a series of
different channels so that people can
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find this stuff. A year, two years, five years,
maybe even 10 years down the line of
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what you said. It's almost this blockchain and I
will reference AI and blockchain in
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this concept a little down the line, but it's
almost like a blockchain approach of
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proving and bringing the validity of what
you stated and showcasing.
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You genuinely stated it as opposed to being in a
group of people 20 years later.
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Saying no, I said this was to happen.
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I said, oh, when and how can you prove it?
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Did you write it in your book? Did
you put it here?
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Did you put it there? Can you
back that up?
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What I said a number of years back and I said it
when I was tied to a digital
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download company, one of ethics and one of
independent considerations for artists.
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I remember that release went out on.
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It was March 3rd of 2003, and there were a couple
releases that went out just short
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of the release of this company
and its product.
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And then a couple weeks afterwards, I don't
remember, I think it was the one before
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stating, the music industry is about to go undergo
a massive change and here's how
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it can potentially harm the artists.
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I wasn't worried as much about Napster.
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My viewpoints on Napster and the way that was being
done was, hey, we've had plenty
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of chances to set the regulation and the
compliance when it comes to copyrights,
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when it comes to publishing, when it comes to
licensing, there were for many years
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things were being brought up going all
the way back to Motown.
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And even before this goes all the way back to when
opera was being pressed on vinyl
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and people were taking over. I mean, even
mobsters taking over and forming
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some of the initial distribution companies and
making money with no consideration to
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authorship or who had the rights to a given
piece to when something became
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open use, so on and so forth. Go even back to the
time when some of you may not be
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as old, but you go into the Chili's or you go into
the Fridays or you go into the
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Applebee's. And for many, many years they had to
sing their variation of Happy
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Birthday because they didn't have the rights to
sing Happy Birthday in their given
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restaurant. But this is not to
get off track.
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But this still does kind of relate.
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I said the music industry was going to have a
massive nosedive when it came to
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profits, the understanding of profits and the
distribution of profits.
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I estimated that in a number of years, probably
about a decade, that artists would
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after that start selling off their entire catalogs
to get whatever value that they
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felt. Because the royalty systems with digital
downloads, with different forms of
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digital distribution and the issues arising with
physical distribution would make it
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no longer worth collecting that royalty check,
but more so just selling out the
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rights entirely. And as we've seen, major artists
across the board have sold off
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their catalogs. Money has dropped
out of the bottom.
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People that say, oh, I get this for
streaming, I get that.
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Some, yes, they're making it, others, they
aren't the music industry had an
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opportunity. And I get that AI goes beyond music,
but the music industry from a
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national standpoint, from an international
standpoint, there was the opportunity to
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meet, to discuss, to plan, to organize.
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Even before all the digital stuff, as the digital
stuff happened, as it went even.
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But the lack of accountability, the lack of
organization and the excess of people
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bitching and moaning and complaining about what
was wrong as opposed to coming
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together to figure out how do we make it right
was not being put together.
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We were not, you know, we as an industry,
I'm not part of it anymore.
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We're sitting here saying we've got all these great
ideas how to make artists money
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and yet no one was coming into stating where do we
set the commissions, where do we
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set something where we could start it on a county
level, bring it to the state,
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bring it nationally, bring it internationally,
how do we set these standards?
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How do we set these standards with
distributors?
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How do we police this, how do we
discipline this?
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Small little elements were set up.
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But still to this day, the music industry has
become even a bigger crapshoot.
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If I was starting, I mean, I started in the music
industry in 92, if I had to start
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in the music industry today, I wouldn't
have gone into it.
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I went into the music industry in 1992 as a
drummer, seeing the opportunity, seeing
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in some ways a lack of opportunity and knowing
that as being a drummer there was
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work. I don't think I would have gone in
as a guitar player.
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I saw the business side as much as I
saw the creative side.
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Now tie this all back to AI. We are in
a similar wild west
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situation. This has been growing, it's been
building, it's been building up.
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There's been some jumps in the last five years,
even in the last 10 years, we begin
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to see these companies saying they're AI, you
know, they're creating AI modules,
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they're creating AI businesses, AI consulting
firms, AI this, AI that's.
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And yet is it being done in a manner that
truly brings a level
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of authentic, organic,
authoritative expertise.
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AI has all the potential in the world to be
something so incredibly strong.
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At the same time, it has all the ability and has
become in many circumstances
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something that's absolutely evil, deceptive,
plagiarizing and creating these
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false prophet type self proclaimed experts that
claim to know everything because of
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a ChatGPT prompt where they're going in and
learning little ways to trick,
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fool and deceive audiences into
paying them.
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That part I can't stand. I want to jump to
the five key points I see of
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the future of AI, the stuff that I see
happening by 2030.
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But at the same time a lot of questions of what's
going to happen in the next two
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years, in the next three and four years.
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I think the advanced multimodal AI systems, those
are going to continue to grow now.
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Those are that kind of, you know, they deliver the
hyper personalized experience.
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This can be again a great thing
subjectively.
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At the same time it can be
incredibly dangerous.
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Okay, you want to for parody, you want to for
leisure, you want to for fun
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create some picture where you're sitting there
holding hands with Taylor Swift or
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you're presenting yourself, you know, or you're
presenting yourself on a, as an
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animation or you're doing something of just fun,
something you might send around to
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a couple different friends, something that you
might post out there and say isn't
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this funny? Something that you would put out
there but you wouldn't lie about.
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That's some of that multimodal AI.
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It's these hyper personalized experiences from
the audio, from the visual, even
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a touch of it going into broader
experiences in the text, elements
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of what can be put together. Now the bad side of
that and the bad side of some of
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these other ones. Now somebody puts an image of
them up on stage speaking to an
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audience that's not there, claiming to be an in
demand keynote speaker when the only
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thing that they've done is speak to their camera
or you know, or gone to one of
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those local little, you know, meetup talk things
where everybody gets seven minutes
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to speak. I have a problem with that.
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I have a problem with some of these AI photo
generators where it's make your
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headshot that much better. Okay, so some
nuancing in editing a photo, colors,
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lights, this and that. But when you're really
starting to overly enhance and then
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presenting a professional version
stating this is me.
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Where is the line in the sand where this is
deception to this is true.
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There's also the agentic AI and the
autonomous agents.
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Those are where you're starting to see and it's been
especially stronger in the last
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couple years of the personal assistants being
able to come out, the therapists.
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What I found too, and it's been a little bit of an
issue for my field and some of
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the people I work with, the strategic advisors
that now you can format this thing
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and say what would be this person?
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Or give me the answers of this person, this person
and this person, what they would
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say regarding this business. Like okay, these
again are giving you Ideas.
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But are they giving you the right ideas?
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I'm going to jump back to that in a bit.
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The parts of AI that I find the most
exhilarating, the most innovative
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and the most helpful are the last three, the
quantum AI for the specialized
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applications. This is that complex problem
solving, the stuff that can help a
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cryptography, material science,
drug discovery.
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The way that you can use quantum, you know,
this quantum computing in
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a much faster method where you're using
a series of absolute,
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objective, substantiated numbers, facts and
information and you're compiling that
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data and making it that much easier to read,
to review, to organize.
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This is the place where it saves hundreds of
hours and many, many different
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researchers. You're still going to need
those researchers.
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And I'll touch on that in a bit.
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But such a way to scan and learn in this
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quantum scale is absolutely amazing.
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And it goes into the reasoning and the frontier
models where again, mathematical
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elements, these further out
scientific elements, law.
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I mean really to have all that information,
all, you know, pretty much
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every true law case, every updated law case,
everything in the books there to be
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able to cross reference in that way, it
brings it to a new level.
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And lastly, the industry, specialized
AI applications.
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And this is where I think that it needs to go with
AI businesses specialized into
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specific areas. One of the first ones I like the
idea of, and that is growing is
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fraud protection, I'm sorry,
fraud detection.
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And that fraud detection I think should be, as this
part and module grows, that it's
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building as much for AI to be able to identify
some of the AI characteristics.
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Was this, was this just a simple prompt?
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Is this person stealing from here?
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How is this being done? But also when you go into
medical, when you go into finance,
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when you have these abilities where you could run
somebody's information, you know,
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their entire medical history and again, as long
as they were telling the truth,
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being able to have all of that together and then
not make a decision based on that,
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but then have the right doctors who receive this
data, using that to come to
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a preliminary conclusion, preliminary assumptions,
you know, this, these preliminary
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thoughts. And maybe together then from that data,
bringing it back into the AI
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module to say, okay, from what was asked, from
what was gathered, from what is in
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the discovery, now this information has been
returned with this information.
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These experts, these doctors, these scientists
have viewed it as this, are asking
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about this, are concerned about this, see this as
this, what are your thoughts on
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that? So it becomes this series,
this give and take.
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And that to me brings authenticity and
authority through the roof.
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Now take a Step back into what I was saying
before about the researchers
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or the strategists. Yes, There are a whole bunch
of people out there that are
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stating they're business experts because they can
run a check or they can run a
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prompt, or they can run some kind of advanced
prompt, or they took one of these
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thousands of AI courses. And the awful thing is
there's so many people out there
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creating AI courses for pennies on the dollar to try
to make whatever they can make,
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and yet they have no idea what
they're doing.
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And then they're getting conclusions off
of algorithmic learning.
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They're getting summaries, they're getting
answers that can be an answer
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from what data was captured, but they may not be
asking all the right questions for
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the particular situation that they're in.
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And their lack of expertise in analyzing that
data, in knowing what questions to
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ask, in knowing what red flags to raise, that's
where the problem runs in.
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That's why I think that honest AI will
not replace humans.
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I see it with a formidable, foundational,
authoritative business,
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or even AI business, from anything from
strategy to doctors to
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finance to fraud detection. It still
includes having a core group
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of experts, people that have the experience,
people that have the experience in
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the given field, that understand communication,
that understand compliance, that
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understand the law. Then you have the outer team,
which would be the individualized
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group. Okay, say you were, you know, you were
working, or let's say, for that
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matter, I was consulting with a team on a business
located in, I don't know, we'll
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say, Las Vegas, Nevada. I'm going to step in as
the communication and optics guy,
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the person looking at the messaging.
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I'm going to look at some of the comparative, the
competitive, the intention of the
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perception, the psychology, the experiences that
I've had in music, in tv, in many
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businesses around the world. I'm also going to
look to people that understand
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business on a different, on a different note,
people that understand building,
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people that understand exit strategies.
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For this particular thing, I'm going to want to
bring in team people that are right
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inside of Las Vegas. Are they
looking investors?
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I'm going to want the right people to
review investments.
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Now in that from a discovery, getting as much
information together, and that's
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something I've been doing for more than 10
years, is the initial.
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It's the initial brand messaging and
communication discovery.
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It's a lot of information in
the beginning.
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And in that, from that data, we're able to compile
and come up with a plan of action
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or an investment plan. Or a business plan or
standard operating procedures.
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Now, in the same way, when it comes to AI, if you
are not creating that initial
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discovery first before entering everything in
there, you're cutting corners and
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you're getting answers that may not apply to your
type of business, where your
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business is located, and many of the parameters of
how much money do you have, how
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much money do you have access to, what aspect of
reputation, what comes to land,
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what ties to real estate, what ties to so many
other variables that are oftentimes
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not thought of. And then you have that single
little AI self proclaimed expert.
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He doesn't worry about any of that.
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He's just popping in. I want to
build in Vegas.
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I want to do this, I want to do that.
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I need this much. Tell me how to do it.
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Give me a business plan. People are writing
business, but people are writing books.
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I think that part is absolutely pathetic.
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If you can't inside of this, if you can't state
how much AI you use inside of
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writing a book, I think there's a
problem there.
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It's fine to state, you know, maybe
you put on the back.
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I used AI to help me proofread.
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I used AI as a technical editor.
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I used AI to do this. These are the kind of
things, and I believe authentic, true
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authors putting that out there can help stand out,
whether they're choosing to go to
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a major publisher, a hybrid, or even self publish
against some of these awful.
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And I can't believe that they're allowed to
continue to advertise online.
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But that's the state where we are, that's
the state that we're in.
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All you have to do is come up with these 15
prompts and AI will write a book for
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you. And then you can say you have a book and
you'll look like an expert, you'll
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look like a plagiarist. And yet that stuff
is out there, advertised.
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Have you noticed so many of the ads out there or
appear as an expert even in some
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ways, some of these AI fraud companies and realize
they can't make you an expert,
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but they can make you appear as one.
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I believe we have to admit we have to be
transparent in what we use AI for, in
285
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how we use it, and in that transparency, in
that authenticity we can draw.
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It's not going to be everyone because there are
a lot of people that want a
287
00:23:37.143 --> 00:23:39.400
shortcut. There's a lot of people
that don't care.
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They want to do whatever they're going to do to make
their money to grab that client
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00:23:43.740 --> 00:23:48.404
and have no concern whatsoever they're putting
into the little legal elements.
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How do I create this contract so that if it all
falls apart, they can't come back
291
00:23:54.511 --> 00:24:00.364
and sue me? As opposed to, why don't you work on
your expertise so that you're not
292
00:24:00.364 --> 00:24:05.839
going to screw them? I mean, of course you want an
aspect of not being held liable
293
00:24:05.960 --> 00:24:10.231
for what a client may have done, but
it goes too far now.
294
00:24:10.231 --> 00:24:16.935
I mean, my thought about where this can
go when you have an
295
00:24:16.935 --> 00:24:23.240
AI organization or organization that uses AI in
this authentic way is that it's
296
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going to be amplified and furthered with
true human expertise.
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00:24:29.359 --> 00:24:32.840
You know, you look at some of these organizations
and like this is a top notch
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organization. There was a given, a higher level
consulting firm that has been,
299
00:24:39.393 --> 00:24:45.407
has been saying, you know, we use AI and they've
stepped away from sharing though
300
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the expertise, which I don't understand.
301
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They step away from sharing the expertise of these
individuals, the experts that are
302
00:24:54.279 --> 00:24:57.500
around them. It's not just using AI.
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The cornerstone of all of this, the foundation of
all of this to me is the expertise
304
00:25:04.459 --> 00:25:11.279
using AI. Because as AI grows from an
authentic, from a transparent,
305
00:25:11.279 --> 00:25:17.863
from an authoritative standpoint to truly
steward, to truly grow in some
306
00:25:17.863 --> 00:25:23.480
of these areas that are not as clearly
objective, where it's, you know,
307
00:25:24.720 --> 00:25:29.296
too many different parameters, you're going to
need the experts that are going to
308
00:25:29.296 --> 00:25:31.243
have to know how to ask, how to look.
309
00:25:31.243 --> 00:25:37.751
Some of these law firms right now that are
getting sued because some of the
310
00:25:37.751 --> 00:25:42.104
paralegals are cutting quarters, not researching,
not looking through, they're
311
00:25:42.104 --> 00:25:48.800
asking the wrong questions into AI prompts,
getting back simplified
312
00:25:48.800 --> 00:25:53.724
answers, giving that to the partners
or the attorneys.
313
00:25:53.724 --> 00:25:58.177
And unfortunately then the attorneys are using that
saying, okay, well they did the
314
00:25:58.177 --> 00:26:01.944
work, they found it, they're quoting where this
is, okay, great, let's go.
315
00:26:01.944 --> 00:26:05.839
And they're getting in trouble, they're
even getting fined.
316
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I believe this is a good thing.
317
00:26:09.204 --> 00:26:11.980
And it's one of the steps I'd like
to see with AI.
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I'd like to see an accountability, I like to see an
element of discipline, of fines
319
00:26:17.499 --> 00:26:20.607
and for lack of a better word, policing.
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Because if that's not in place, then the crazy
side of AI just gets crazier.
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I know that there's no way presently, and even if
some of this stuff comes into
322
00:26:31.511 --> 00:26:33.952
play, that you're ever going to be able
to stop the fraud.
323
00:26:33.952 --> 00:26:38.436
The frauds have been there forever and they're going
to pull their games and they're
324
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going to create things and they're going
to screw people over.
325
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That's going to continue. But we can set a standard
for those that are prepared to
326
00:26:47.679 --> 00:26:52.000
look a little bit deeper, for those that care about
their businesses, for those that
327
00:26:52.000 --> 00:26:54.880
care about their information to
set in place.
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00:26:54.880 --> 00:26:58.640
Say, here's how we operate. Here's how
we operate with AI.
329
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Here's our AI Statement of use.
330
00:27:00.839 --> 00:27:02.872
This stuff can go up on websites.
331
00:27:02.872 --> 00:27:04.216
This stuff can go to companies.
332
00:27:04.216 --> 00:27:09.149
This could be an internal thing stating back to,
you know, stating back to that
333
00:27:09.149 --> 00:27:12.544
paralegal that, you know, they
come in, or even.
334
00:27:12.544 --> 00:27:17.895
Or even a lawyer if you use this stuff and you
have not checked those links.
335
00:27:17.895 --> 00:27:22.864
And it's. It's funny because sometimes AI will send
you back links, you know, in a
336
00:27:22.864 --> 00:27:24.951
given prompt, and it's dead.
It's not true.
337
00:27:24.951 --> 00:27:30.291
And it's not that AI is trying to fool you, but are
you asking the right questions?
338
00:27:30.291 --> 00:27:35.271
Are you vetting the materials that you're coming
back to see if that's information
339
00:27:35.271 --> 00:27:40.307
that can be compiled correctly, or are you just
taking it at face value because it's
340
00:27:40.307 --> 00:27:46.792
AI? I've done some, you know, some people say,
google yourself, you know, AI
341
00:27:46.792 --> 00:27:50.055
yourself, ask some really broad questions.
342
00:27:50.055 --> 00:27:55.536
According to AI, I've done a lot more albums
than I actually did, and it's
343
00:27:55.536 --> 00:27:59.704
absolutely not true. I know how
many albums I did.
344
00:27:59.704 --> 00:28:06.568
Now, there are articles out there from
magazines, from stuff of when I was
345
00:28:06.568 --> 00:28:11.816
in music that have stated higher numbers
that were not true.
346
00:28:11.816 --> 00:28:15.160
They weren't shared by me, but they
were put out there.
347
00:28:16.079 --> 00:28:18.904
And yet that was where some of the
scrape came from.
348
00:28:18.904 --> 00:28:22.919
Now, one of these articles, as it came
through, boom, it goes up.
349
00:28:22.919 --> 00:28:25.880
It's viewed as this. It's compiled here.
350
00:28:25.880 --> 00:28:29.400
Now it states X. But it's not true.
351
00:28:30.079 --> 00:28:36.864
AI doesn't know that. When we compile information,
if we're not vetting it, we're
352
00:28:36.864 --> 00:28:41.760
not honoring the opportunities of how
great this research can be.
353
00:28:41.760 --> 00:28:45.187
We've got to test this. I mean, even.
354
00:28:45.237 --> 00:28:50.192
Even having peer reviews inside of AI, I
don't think is a bad thing.
355
00:28:50.192 --> 00:28:54.856
So in that, I mean, in that clarity,
that to me, is stronger.
356
00:28:54.856 --> 00:28:58.839
Now, coming back to what was said before, I don't
know what can be done about the
357
00:28:58.839 --> 00:29:00.359
lying elements. It is frightening.
358
00:29:00.400 --> 00:29:05.952
The videos that can be made, the images that can
be made, the things that can be
359
00:29:05.952 --> 00:29:08.780
said. And in that, it's got to be.
360
00:29:08.780 --> 00:29:15.275
It's got to be something where your defense is
not coming off defensive.
361
00:29:15.275 --> 00:29:20.539
There's a letter, a letter I'm
putting out.
362
00:29:20.539 --> 00:29:25.343
It's on a private matter. And I've thought about it
going like, wow, how could that
363
00:29:25.343 --> 00:29:27.135
get twisted? How could that get
blown around?
364
00:29:27.135 --> 00:29:31.624
How could that get messed up? So the
letter is going out as.
365
00:29:31.624 --> 00:29:36.932
It's an audio letter. It started as an audio and
the audio is being placed in one
366
00:29:36.932 --> 00:29:41.440
area and in a file. It's also transcribed on
a back page of my website.
367
00:29:41.440 --> 00:29:44.831
That is not optimized. It's a,
it's accessible.
368
00:29:44.831 --> 00:29:50.823
Not, not like, not, not like password secured, but
you've got to have the right link
369
00:29:50.823 --> 00:29:57.000
to find it. And it's also printed out having
certain elements like this to
370
00:29:57.079 --> 00:30:01.771
potentially prove that if someone was to take
something proprietary of yours and
371
00:30:01.771 --> 00:30:05.883
slightly adjust it and then claim that that might
be a step that we may need to
372
00:30:05.883 --> 00:30:11.780
take. That might be a step in secure documentation
and proof down the line at the
373
00:30:11.780 --> 00:30:15.019
same time with major things that you're
putting out there.
374
00:30:15.019 --> 00:30:18.985
Maybe it's making sure you're putting it
out there in major places.
375
00:30:18.985 --> 00:30:22.343
Returning to that point, this point
being blockchain.
376
00:30:22.343 --> 00:30:26.608
I am a big fan of the blockchain.
377
00:30:26.608 --> 00:30:28.863
Not, not the cryptocurrency aspect.
378
00:30:28.863 --> 00:30:33.120
It's much more so the blockchain.
379
00:30:33.120 --> 00:30:40.027
I believe that with, with information
that is not just
380
00:30:40.027 --> 00:30:45.295
on one given server right over here, but it's found
and dated and clarified that it
381
00:30:45.295 --> 00:30:49.247
shows up on all these servers and all
these different places.
382
00:30:49.247 --> 00:30:53.991
And then at the same time with the blockchain
security, some is, some have advanced
383
00:30:53.991 --> 00:30:57.792
to this, some it's still waiting to where somebody
makes a change and then something
384
00:30:57.792 --> 00:31:00.140
is pinged going, no, that's not right.
385
00:31:00.140 --> 00:31:04.051
Because here's 30,000 other servers,
computers, whatnot, stating X.
386
00:31:04.051 --> 00:31:09.100
And it was dated to, you know,
June 2, 2023.
387
00:31:09.100 --> 00:31:14.227
And all of a sudden something's been put out
and it's that exact document.
388
00:31:14.227 --> 00:31:19.888
But now it's had some massive changes and these
are wrong changes that, hey, this
389
00:31:19.888 --> 00:31:25.720
came a year later and this has been edited, this
has been adjusted, this is off,
390
00:31:26.000 --> 00:31:30.768
here's the original. I think that that's a
great level of protection.
391
00:31:30.768 --> 00:31:36.760
We're looking at some of these places that are
dealing in real estate holdings
392
00:31:36.760 --> 00:31:43.544
overseas in certain not as strong countries where
people have contracts for land,
393
00:31:43.544 --> 00:31:47.839
for homes, for businesses. And you have people that
go in and say, okay, we're going
394
00:31:47.839 --> 00:31:51.505
to take these things over. We're going to burn down
a bank, we're going to burn down
395
00:31:51.505 --> 00:31:55.177
a building. We're going to make sure to shred
these given contracts because there
396
00:31:55.177 --> 00:31:59.368
aren't really copies of them. On the smallest level
internationally, that could be
397
00:31:59.368 --> 00:32:01.979
of assistance of going, okay,
this goes away.
398
00:32:01.979 --> 00:32:03.680
At least it's located elsewhere.
399
00:32:04.000 --> 00:32:08.727
But on the largest level it's not just elsewhere,
it's so many different places.
400
00:32:08.727 --> 00:32:15.640
How can we begin to use aspects of AI and amplify
the authenticity and the authority
401
00:32:15.680 --> 00:32:21.320
of an individual? What they wrote, what they
found, when they found it, and that
402
00:32:21.320 --> 00:32:27.007
being backed up enough so that it's in tens of
thousands of places and then add on
403
00:32:27.007 --> 00:32:31.376
to that the security parameters that when
somebody puts that up.
404
00:32:31.376 --> 00:32:35.008
Here's your plagiarism detector or here's
your alteration detector.
405
00:32:35.008 --> 00:32:40.616
This study was putting out, I mean these third
party studies and like you know, a
406
00:32:40.616 --> 00:32:47.519
couple years ago I was speaking at the Miami, it
was a Miami Cannabis Expo, it
407
00:32:47.519 --> 00:32:53.512
was for cbd. And I stood up in front of a crowd and
I said, you know the number one
408
00:32:53.512 --> 00:33:00.192
problem with this industry right now, it's
not the people, it's not,
409
00:33:00.192 --> 00:33:05.156
it's not the distributors, it's not the sales
system, it's not the government.
410
00:33:05.156 --> 00:33:11.464
I said it's you. It's you people that are trying
to falsify, trying to hype and
411
00:33:11.464 --> 00:33:15.847
trying to shortcut these people saying oh we have
this great third party tester and
412
00:33:15.847 --> 00:33:19.600
that third party tester ends up being a lab
that they own that they've just
413
00:33:19.600 --> 00:33:21.100
structured under a different business.
414
00:33:21.100 --> 00:33:25.036
But accidentally it ties back to
their business.
415
00:33:25.036 --> 00:33:28.899
These elements where people just
shortcut for hype.
416
00:33:28.899 --> 00:33:34.240
It doesn't help them. But when we come to this
clarity, we come to this vetting.
417
00:33:34.359 --> 00:33:38.720
I'd love to see inside of whether it's the quantum
modules or, or you know, getting,
418
00:33:38.720 --> 00:33:45.456
getting back to the advanced multimodal
and, and these elements of
419
00:33:45.456 --> 00:33:50.216
fraud detection where things that are coming up
where it's the, you know, not, not
420
00:33:50.216 --> 00:33:53.551
just the response of the community notes
of well this is this.
421
00:33:53.551 --> 00:33:57.815
And somebody found one other thing to object it
and then all of a sudden they're
422
00:33:57.815 --> 00:34:00.818
changing it. I don't want you to find one
other thing to object it.
423
00:34:00.818 --> 00:34:04.251
It could be subjective. I want you
to find 30,000.
424
00:34:04.251 --> 00:34:09.359
You find a document that says X, you find a picture
that has been altered, that then
425
00:34:09.359 --> 00:34:14.263
all of a sudden this picture on the blockchain on a
number of, you know, a number of
426
00:34:14.263 --> 00:34:19.032
different websites too that we have scans going
across social media scans going
427
00:34:19.032 --> 00:34:24.039
across different. Our existing search engines,
new search engines, showcasing.
428
00:34:24.039 --> 00:34:30.676
Click down here to see the backed up
documentation of what is there
429
00:34:30.676 --> 00:34:32.948
now. Of course things can change.
430
00:34:32.948 --> 00:34:35.084
Study, you know, new things can
be learned.
431
00:34:35.084 --> 00:34:37.232
But who's making those changes?
432
00:34:37.232 --> 00:34:41.855
That's one thing. And that can be an edit
on the other side of it.
433
00:34:41.855 --> 00:34:46.535
Is someone trying to abuse this, okay, the pill
that's Hard for some people to
434
00:34:46.535 --> 00:34:51.928
swallow. And kind of coming around the last
couple laps here is the policing.
435
00:34:51.928 --> 00:34:56.459
I've talked to a lot of people inside of AI or that
are interested in AI and they're
436
00:34:56.459 --> 00:34:58.920
like, I don't want the policing, I don't want
the government policing.
437
00:34:59.119 --> 00:35:02.032
I don't want people, you know,
saying this.
438
00:35:02.032 --> 00:35:05.260
I don't think somebody should be fined.
439
00:35:05.260 --> 00:35:08.912
I think you're wrong. And here's why I
think you're wrong.
440
00:35:08.912 --> 00:35:13.622
I think that without that policing, without that
accountability, without the
441
00:35:13.622 --> 00:35:18.875
liability, without the discipline, it leaves us to
be the Wild west, just like it
442
00:35:18.875 --> 00:35:24.047
was in music, but on a much bigger scale and
affecting many, many more people.
443
00:35:24.047 --> 00:35:30.668
I'd like to see on, you know, on a state, on a state
level, on a national level, and
444
00:35:30.668 --> 00:35:35.303
even on an international level, whether it be
some kind of board, commissions,
445
00:35:35.303 --> 00:35:39.648
councils, getting something set up in stating,
here are the parameters that we're
446
00:35:39.648 --> 00:35:44.579
going to look toward and not something that's going
to take, you know, five years to
447
00:35:44.579 --> 00:35:48.920
build something of. Okay, here is our initial
committee, Here is what we're going to
448
00:35:48.960 --> 00:35:52.612
grow it into. Here is where we're going to
vote into these elements.
449
00:35:52.612 --> 00:35:59.199
Here's what we're going to come to agree on when
it comes to AI and then setting
450
00:35:59.280 --> 00:36:02.628
this, is setting certain standards on an
international level.
451
00:36:02.628 --> 00:36:06.880
And that if there's certain countries that don't
necessarily comply with that, that,
452
00:36:06.880 --> 00:36:13.807
okay, you're using this module, you're using
this, you don't know that
453
00:36:13.807 --> 00:36:19.960
this is absolutely safe. It's come to a time that
if we're not taking that step
454
00:36:20.679 --> 00:36:25.471
to have some kind of discipline, to have some kind
of, for that matter, punishment
455
00:36:25.471 --> 00:36:29.871
for doing wrong, then they're just going to
keep taking advantage.
456
00:36:29.871 --> 00:36:34.032
And the people that are doing right, I
believe, should be rewarded.
457
00:36:34.032 --> 00:36:37.519
Here's a, you know, here's this, here's
their AI statement of use.
458
00:36:37.559 --> 00:36:40.595
Here's how they're doing that, here's how they're
backing up, here's how they're
459
00:36:40.595 --> 00:36:45.065
walking through what they build, how they build it,
how they prompt the experts that
460
00:36:45.065 --> 00:36:51.832
look at this, here's our process, here are the
experts that look at the data with
461
00:36:51.832 --> 00:36:58.671
expert eyes and have the expertise to go back
and revamp the prompt or
462
00:36:58.671 --> 00:37:04.915
use that information in the best way for
whatever given industry, that to me,
463
00:37:04.915 --> 00:37:07.407
becomes so much stronger. That's your AI.
464
00:37:07.407 --> 00:37:10.760
To me, that's your AI ethical business.
465
00:37:10.760 --> 00:37:16.667
It's building businesses with the right people
and the right teams for the best
466
00:37:16.667 --> 00:37:23.400
data. And the only way that you're going to get
the A optimal effect of AI as
467
00:37:23.400 --> 00:37:29.840
it continues to grow into these new modules, into
this expanded element are going to
468
00:37:29.880 --> 00:37:35.736
be by having those people that know how to ask
the right questions and not just
469
00:37:35.736 --> 00:37:40.555
taking these AI things of, you know, take my 90 day
AI course, you're going to learn
470
00:37:40.555 --> 00:37:43.168
all these different prompts and all these words to
use and all these things not to,
471
00:37:43.168 --> 00:37:46.319
and here's how you apply it. And then you can
launch your business in 90 days and
472
00:37:46.319 --> 00:37:51.527
you're up and running. No, the differentiator
there inside of whatever the market
473
00:37:51.527 --> 00:37:57.767
is, whatever the trade is, that you have the right
people doing the discovery first,
474
00:37:57.767 --> 00:38:04.709
that it's AI based research that still can also
be mixed and vetted with actual
475
00:38:04.709 --> 00:38:11.331
research too that sets for a discovery that gets
the baseline information about a
476
00:38:11.331 --> 00:38:17.371
new thing, re establishing an old one,
whatever from all that data.
477
00:38:17.371 --> 00:38:20.095
Then to be able to say, okay, what are
you trying to do?
478
00:38:20.095 --> 00:38:21.079
What are you trying to accomplish?
479
00:38:21.079 --> 00:38:24.272
Where do you take this from? You know,
to this next step.
480
00:38:24.272 --> 00:38:30.639
And from the data that comes back going to the
expert or I'm sorry, the experts
481
00:38:30.679 --> 00:38:36.979
again that run through that data, that
strategically look at that, these supposed
482
00:38:36.979 --> 00:38:43.400
strategic consultants, they're popularized
answers that don't always relate.
483
00:38:43.400 --> 00:38:48.399
And it's something that I've even seen, you know,
a tick down in people going, oh
484
00:38:48.399 --> 00:38:54.620
no, I don't need your help. I'm, you know, I'm
using AI and of the people that have
485
00:38:54.620 --> 00:38:59.199
gone that route, I've watched a lot of mistakes
being made that's in the, you know,
486
00:38:59.280 --> 00:39:02.207
the, the agentic AI, the, the
autonomous agents.
487
00:39:02.207 --> 00:39:07.575
Oh, if you just ask the right questions and
here, and here's a whole bunch of
488
00:39:07.575 --> 00:39:12.391
questions you can ask. Yes, but you don't know or
have the experience that I have to
489
00:39:12.391 --> 00:39:15.964
ask the questions to ask a wide
array of here.
490
00:39:15.964 --> 00:39:17.607
Oh, and you can even ask in there.
491
00:39:17.607 --> 00:39:22.268
You can ask for someone like me, someone like
another expert that you like, some
492
00:39:22.268 --> 00:39:25.691
larger scale name. But what do you find?
493
00:39:25.691 --> 00:39:30.927
Are you only getting some major popular answer
that doesn't relate to you?
494
00:39:30.927 --> 00:39:33.112
Okay, it's a high level answer.
495
00:39:33.112 --> 00:39:37.731
It's been found in a couple different places
under a couple different examples.
496
00:39:37.731 --> 00:39:42.559
But still it's popularity response over
authority response.
497
00:39:43.239 --> 00:39:44.903
It's an impersonalized response.
498
00:39:44.903 --> 00:39:51.688
So I know I've kind of gone a little bit, a
little bit all around the map
499
00:39:51.688 --> 00:39:58.479
here when it comes to AI. To summarize it
up a little bit as best I
500
00:39:58.479 --> 00:40:05.072
can. To me, the most effective business model
and some of the most effective
501
00:40:05.072 --> 00:40:10.607
businesses for AI are still going to at the root
of them have to have experts.
502
00:40:10.607 --> 00:40:15.999
And for these people that are doing their little 90
day AI courses and prompting off
503
00:40:15.999 --> 00:40:20.855
of what they think and not having the humility or
the understanding that they may
504
00:40:20.855 --> 00:40:24.939
not be getting the type of data that they, they
might get the base data and they
505
00:40:24.939 --> 00:40:29.347
might get popular data, but it might not be
personalized or applicable or really,
506
00:40:29.347 --> 00:40:33.960
for that matter, professional data that applies to
whoever they got to hire them.
507
00:40:33.960 --> 00:40:39.599
That if you're going to start some kind of AI
business like this, and even if you
508
00:40:39.639 --> 00:40:43.576
want to start one of these, that you're bringing in
the experts to review this, that
509
00:40:43.576 --> 00:40:48.132
you're looking at the questions, that you're
taking every experience inside of AI
510
00:40:48.132 --> 00:40:52.000
and not trying to put it into a
template, simplified system.
511
00:40:53.119 --> 00:40:59.296
The exciting part about AI to me is that it will
continue to grow to collect data
512
00:40:59.296 --> 00:41:04.411
and information. How that data is collected and
that information is formatted is
513
00:41:04.411 --> 00:41:11.399
crucial. And the laws and the regulations that step
in, that's even more crucial to
514
00:41:11.399 --> 00:41:18.256
ensure that something is designated as, okay,
this is an opinion, this is a
515
00:41:18.256 --> 00:41:21.599
fact. Here's where it's backed up here, here's
where it's backed up there.
516
00:41:22.320 --> 00:41:28.640
The elements of getting into the fraud detection,
the elements of these blockchain
517
00:41:28.640 --> 00:41:32.768
like elements of stating, this is found
in this many places.
518
00:41:32.768 --> 00:41:39.040
This was adjusted, this was adapted for someone to
put out certain stuff that it has
519
00:41:39.040 --> 00:41:44.872
to tie back to them. And then lastly to the
individual's responsibility or the
520
00:41:44.872 --> 00:41:50.840
company's responsibility to state, this is how I
use AI and this is how I don't use
521
00:41:50.840 --> 00:41:55.079
AI. This is where I apply things, this is where I
don't apply things, this is where
522
00:41:55.320 --> 00:41:59.456
I set the standard, I believe that that
should be laid out.
523
00:41:59.456 --> 00:42:03.819
So even regardless if you're parody, if you're
just doing it for fun, that it's
524
00:42:03.819 --> 00:42:09.199
clearly stating there. And some of these AI,
you know, the graphic things,
525
00:42:11.079 --> 00:42:15.160
these modules, where it's clearly stating, okay,
you threw a couple words, you know
526
00:42:15.160 --> 00:42:17.776
the music ones. You threw a couple
words in and you create.
527
00:42:17.776 --> 00:42:22.707
And a song was created off of a couple
words and a couple chords.
528
00:42:22.707 --> 00:42:29.395
Are you really going around saying, I wrote this for
you, or can you be a little bit
529
00:42:29.395 --> 00:42:35.182
more honest and say, I used this thing and it
helped me create this for you
530
00:42:35.182 --> 00:42:41.744
together. In our honesty, in our authority, in our
integrity, in our transparency,
531
00:42:41.744 --> 00:42:48.059
AI has an opportunity to be something so amazing,
just as it has the opportunity to
532
00:42:48.059 --> 00:42:49.519
be something so incredibly dangerous.
533
00:42:50.320 --> 00:42:56.927
And while AI to a certain extent, and these
personal assistants and strategists and
534
00:42:56.927 --> 00:43:01.284
whatnot, these fake things that are just compiling
off of different information can
535
00:43:01.284 --> 00:43:06.691
be dangerous. I still believe the honest use of AI
will not replace the human beings
536
00:43:06.691 --> 00:43:10.567
and that we may end up seeing in these
next couple years.
537
00:43:10.567 --> 00:43:15.911
In this surge right now of people claiming to
know things they don't know is
538
00:43:15.911 --> 00:43:21.240
businesses that end up falling apart because of
bad decisions made based on bad
539
00:43:21.240 --> 00:43:26.255
information or partial information or incomplete
information or information that was
540
00:43:26.255 --> 00:43:28.751
not vetted and checked by experts.
541
00:43:28.751 --> 00:43:35.471
If we take AI to these next levels
with ethics, with
542
00:43:35.471 --> 00:43:42.380
transparency, with regulation and policing, I
believe we can get amazing things
543
00:43:42.380 --> 00:43:48.824
from it. Amazing new businesses, things that can
be formed faster, quicker, more
544
00:43:48.824 --> 00:43:54.400
affordably and also correctly. But in
that it might not be as.
545
00:43:54.679 --> 00:44:00.899
I mean, and in the affordability, it might not be
as cheap because it might still
546
00:44:00.899 --> 00:44:04.760
take more than one guy, you know, plugging
away prompts at his computer.
547
00:44:06.079 --> 00:44:10.366
I know this is a little bit of a ramble and a rant,
but I think this is an important
548
00:44:10.366 --> 00:44:15.552
thing. I think this is going to be a topic that is
going to be on minds for the next
549
00:44:15.552 --> 00:44:20.340
number of years to come. I think that it's
important that we begin to take these
550
00:44:20.340 --> 00:44:25.391
steps to get these committees into play to figure
out, you know, who's going to set
551
00:44:25.391 --> 00:44:30.640
the regulations, that it's not another situation
where just let whatever's going to
552
00:44:30.640 --> 00:44:35.520
happen happen, because it's already dangerous,
it's already impacting people.
553
00:44:35.520 --> 00:44:41.568
We can do better as this new and better
technology continues to grow.
554
00:44:41.568 --> 00:44:47.863
And if we do better, if we do honorably, and if we
treat this in love, in honesty
555
00:44:47.863 --> 00:44:54.820
and transparency, I believe AI can be something so
much greater, so much bigger, but
556
00:44:54.820 --> 00:44:58.239
still stand in a foundation of
truth and authority.
557
00:44:59.280 --> 00:45:05.170
This is Loren Weisman. This was a long
one, a bit of a rant.
558
00:45:05.170 --> 00:45:07.483
That's all I got.