Welcome to The Vegan Report. My name is Ryan.
Today we're diving into how artificial intelligence
is becoming a real game changer for vegans, for
animal rights activists, and for animals themselves.
Have you felt its impact yet? To explore this
topic, I'm joined by Thomas Mannendar Richardson.
He's the director of research at Bryant Research.
We've welcomed one of his colleagues, Billy,
on the show last September to talk about why
cats should be vegan. He's also the lead data
consultant at Greener by default. I asked Thomas
whether he thinks AI is becoming sentient and
what we should make of that idea. We also get
into why AI models aren't as bad for the environment
as you've been led to believe. If AI models have
an anti -vegan bias, and why he thinks AI models
are key to giving animal rights activists a leading
edge against Big Ag. And much, much more. He
also gives us the best tips for using AI as a
pro. If you want to access free AI training for
animal rights activists, visit the link in the
episode's notes. Now, the tips I learned in this
episode, I'm using them in my activism, but also
in my work and in everyday life, so don't miss
on learning about them. And share this episode
with the vegans you know. This is how we move
this cause forward. By staying informed and having
important, sometimes difficult, but important
conversations on our advocacy efforts. It matters.
Follow the show for more great discussions. And
thank you so much for your support. I wanted
to start this conversation with the obvious thing
that people think about when talking about AI,
which is are they going to take over the world?
Well, uh, maybe, maybe, and it won't be, it won't
be chat GPT or Gemini. Um, I don't think, uh,
I think if you've used it, you might've seen
the power, but you're not. Um, but yeah, you
probably. don't get the impression it's gonna
take over the world anytime soon. But who knows,
in five years, when we have AI agents running
around the place, things could get a bit interesting.
And what about the question of sentience? That's
something too that fascinates people, mostly
weekends. When are they going to get sentient?
And are we going to even realize it once they're
sentient? Yeah, that is a great question. There's
an organization that's quite concerned with this,
they're called Sentient Futures. Not only do
they address this issue of AI, animals and digital
minds, as they put it. And but they also do kind
of courses that people can sign up to to to learn
more about this and and discuss these kind of
topics and And yeah in terms of you know, when
would we even know if they become conscious?
I think that is it's a very scary question because
At the moment we have we have effectively the
way we train these model these modern AI models
like chat GBT and Gemini We just build them to
to just copy to just copy humans and but it's
and but then after we've trained them we kind
of we we give them this we put them through this
regime called reinforcement learning which is
basically where we give them um we we talk to
them they produce responses and then we say that
one's good that one's bad that one's good that
one's bad don't talk about this talk about that
and in doing that um there is a possibility that
we may do something like if it shows if it expresses
that uh it is upset or uncomfortable or sentient
in some way, that could be tamped down or basically
trained out of them in the reinforcement learning
step. Now, I mean, to be clear, I don't think
there's much reason to expect that current models
are sentient, but this is like something that's,
you know, in the future, if we move to a different
way of building these models, like a new paradigm,
it would be something we should probably watch
for because... yeah because for example if during
training chat gbt were to say you know i don't
want to answer this i i don't like this or i
um or stop yelling at me or something um that
would have been that would have basically been
kind of um not beaten out of it but like trained
out of it during the uh in the reinforcement
learning step um of the of building these models
so um and it may not necessarily make it go away
it might just like kind of silence the ai's ability
to to do those things so yes it's a worrying
thing for the future probably five or more years
at least yeah and but it could be potentially
quite worrying and I guess another thing to think
of is that so in the animal movement we're starting
to come around to for example the plight of of
shrimp and insects and the idea there is that
although we are not 100 sure that they are sentient
because there are so many of them, even a tiny
probability of sentience or a tiny amount of
sentience would still add up when we add all
those numbers up. And so we can imagine a future
where we have thousands of AI agents per human,
doing all sorts of things in our economy, doing
every little task for us. And if each of them
only has a fraction of a mind, that could still
add up very quickly to to a to a lot of um kind
of beings worth of uh worthy of consideration
that's fascinating and i think it ties well with
the first question i asked um you know usually
in those hollywood movies uh those ai rise up
against humanity as a revenge after, you know,
years of servitude, you know, you see the robots
attacking us and all of that. And so I wonder,
you know, even if we get to prove that they are
sentient, are we going to treat them as we should,
since you know, we're not even giving that level
of concern or consideration to insects or shrimps?
Yeah, well, there may be slight some slight differences
in the sense that we will probably be able to
establish whether these AI models, whether AI
is or isn't sentient, it'll probably be more
easy than with some animals because we can test
them in different ways. So for example, Anthropic,
who are the organization that create the Claude
models, they have done some fascinating kind
of studies of almost, they almost call it like
digital neuroscience, where they're looking inside
the network of Claude's mind, or a smaller version
of Claude, and they are identifying where concepts
are, like where the concept of Paris is, or where
the concept of the Eiffel Tower is in that network.
So there are some research methods that we are
capable of doing with AI that we are not yet
or not able to do with animals. So it may well
be that we can establish their sentience with
greater certainty. But what we do with that information
is another thing. think we should take it for
granted that if we could establish very confidently
that they are sentient, that humanity would choose
to, uh, choose to kind of grant them full, full
rights or any rights at all. Um, yeah. And I
do worry about that a little bit. I love how
veganism, you know, for me, veganism is about
following ethical principles. It's about the
welfare of animals, of sentient beings. Um, but
I love how veganism is also the Way of life of
the future, you know, it's inclusive. It's, um,
helping us, you know, um, be inclusive to the
diversity that we see in 2025. You know, you
have people from all faiths and cultures and
veganism is often, you know, this universal diet
that everyone will accept, but it also, you know,
prepares us for the AI future that is coming.
Yeah, yeah, it's that I think we are, I think,
for example, organizations like Sentient Futures
and also academic philosophers. There is overlap
in the people who care about animal minds and
who think about that and how we should treat
them and people who are concerned about potential
future digital minds as well. There is that overlap.
There are a lot of academic philosophers. who
tackle one topic often tackle the other as well
alongside them. And there are there even conferences.
So not to bang on about sentient futures too
much, but they they put on conferences every
year. And these are these deal with the topics
of AI animals and digital minds altogether. Yeah,
I knew about them, but I'm happy to learn more
about you know what they do. Okay, I guess the
third concern that comes to vegans minds when
talking about AI is how it's horrible for the
environment. And I've heard, you know, so many
statistics. So what is the real, you know, environmental
footprint of AI? And is it truly does it truly
deserve our concern? Yeah, so it's a it's a great
question. And it's one that Like everybody has
this question, it's something that people have
understandably very concerned about. And if you'd
bear with me, there is kind of multiple parts
to this question. I kind of want to give it the
nuance it deserves. So firstly, I would say that
if people are, the people who are concerned about
the environmental impact of AI, you are right
to be. concerned. And if you're skeptical about
the the motives of these AI companies, you are
right to be skeptical, right? Because, you know,
OpenAI and Google, they're not really they are
they're big corporations. They're not your friends.
And as we learned with companies like Facebook,
they if we don't, if we don't get if we are not
skeptical enough about tech companies, they can
do some real they can do some real damage. And
so companies like Google and OpenAI probably
will. Sacrifice the environment to to make money
and so we should approach like a default stance
to these things is to be wary and skeptical however,
we've also got to look at the facts and the the
current yeah, the current state of the facts
is that the environmental impact of AI is is
tiny almost not worth worrying about and but
you're right to be confused because like it's
because the There's a couple of things to it
that firstly AI is progressing so very quickly
So it's very hard to get a handle on some of
these numbers and they change quite quickly as
well. So for example the Not only has so AI energy
AI use has gone up dramatically. So chat GBT
is the most quickly adopted software product
in history AI itself overall generative AI might
be one of the fastest adopted technologies that
humanity has ever has ever adopted. And so things
change very quickly. So your AI use today might
be 100 times greater than it was at the start
of even this year, depending on the tools you've
picked up. And so these things can quickly get
out of hand. However, another thing to bear in
mind is that the models have been getting much,
much more efficient over time too. And so and
and and that's kind of obvious when you think
about it because Energy use is electricity and
you have to pay for electricity, right? So like
Google has to pay for electricity to power its
AI models It has to pay for this the chips it
has to pay for the data centers and so it is
very much in Google's interest to to to increase
the efficiency of these models and of their AI
services in general because it costs them money.
And so we have seen that although AI use has
been exploding like hundreds of thousands of
times, the efficiencies have actually been keeping
pace. So we are talking like hundreds of times
worth of efficiencies for some technologies.
Another thing is to put this into perspective,
right? So when we see something in the news,
and we might see a large data center near a small
town, and then we hear big numbers like water
use in the millions of gallons, it's very hard
to know what that... That sounds quite scary,
but it's hard to actually properly contextualize
that. So I think a better thing to do is to think
of it in terms of your own personal... usage,
right? So how much of your personal carbon emissions
come from the AI you might be using? How much
of your personal water footprint comes from AI?
And when we crunch those numbers, we find that
actually it can be like less than 1%. In fact,
the average Americans daily water, well the average
for energy, a single chat GBT prompt is like
0 .0007 % of your daily emissions so if you prompt
chat gbt like you can prompt chat gbt thousands
of times a day before it even amounts to one
percent of your daily emissions um and the the
case is similar with water as well so um they
fire like most kind of most studies find that
the um what is it let me find the the exact numbers
but there was when it comes to uh when it comes
to water it was um your your lifetime, what is
it, the water that would be used by you using
ChatGPT for the equivalent of a human lifetime
is about the same water as goes into a single
pair of jeans. Yeah, because some things are
really water intensive and we just don't think
about them, right? And I mean, something that
would be more familiar to our audience is meat,
right? Animal agriculture takes a staggering
amount of water. And if you total up um kind
of the energy use and the water use from your
from chat gbt usage and you put it alongside
things like um uh like meat uh meat and dairy
um then you find that actually it's really just
a drop in the bucket what you're saying is all
very reassuring um i i was really disappointed
to You know face that barrage of no, don't use
AI. It's Really horrible for the environment
because of this and that Because for me AI is
a necessity now If you want and I should actually
ask you the question Why do you because I know
you also share that belief. Why do you think
AI is a necessity? Yeah, and I think it just
it's It's just such a multiplier on your on your
impact and in terms of I mean specifically thinking
about work and so it's Yeah, it's a big multiplier
on your impact. So to give you some figures Bryant
research where I'm at We you know, we're a social
science consultancy that exclusively works with
animal advocacy organizations and alternative
protein companies So we deliver research reports
and I estimate that this year we have delivered
two, maybe three projects, 25 % faster because
of our AI use. We've also managed to complete
two or three projects. Oh, by the way, there's
like five of us. And we've managed to complete
three projects that would have not been possible
without AI. And these are projects that are making
tangible differences for animals. And when we
deliver a project faster, that means we can have
an impact quicker, but it also means that we
can pass those cost savings on. to our clients,
which are cash strapped animal organizations.
They can save that money and they can use that
money for important other things like their campaigns.
And so by having this multiplier, it allows us
to go further and have more impact for animals.
And as a movement that is so under -resourced
and underfunded, we've got to take every improvement,
like every multiplier we can get. And also, I
think, really, to put it into perspective is
that everyone else is going to be using these,
including the factory industrial animal agriculture.
And so we can't afford to let them have this
advantage and not take this advantage ourselves.
And there may even be potential that if we get
this right as a movement, and if we really lean
into it, then we might be able to outmaneuver
them on this and gain an additional and gain
an advantage over them. Yeah, which could be
quite exciting because there are very few of
those. We have very few advantages over our enemies,
aside from being right, of course. Music to my
ears. I mean, sincerely, this is this is a game
changer and we should embrace it and use it to
its full extent. I worked with an organization
about a year ago, I think, and they were delivering.
AI training to kids. And they were pointing out,
you know, the social disparities in adopting
the AI technology. So everyone is adopting the
AI technology, but not everyone has access to
training to how to use it in an optimal way.
And yeah, they observed that in private schools,
they had already, you know, classes, workshops,
and all of that to prepare the kids to use AI,
but not in the public sector. So we should invest
in training our advocates, you know, vegans,
in using the AI and making a difference. And
that's what you ended up doing. Please share,
you know comment on what I said and share about
your recent initiative To your to your question.
Yes. So AI adoption is uneven as well it's there
is the potential for for almost everyone to adopt
AI because The the tools are the tools are very
affordable, right? There are free plans to most
and AI tools and even though the pro plans are
definitely better, they often are quite affordable.
So for example, chat GBT can be 20 pounds a month.
Whereas if you compare that to differences in
technology that in other areas, I guess one way
to think about it is that like, Jeff Bezos has
access to only marginally better AI than anyone
on the planet who can scrounge up $20 a month.
And so and that's So there is a potential for
this to be very democratized. But we also have
other things that, for example, nonprofits are
often very pressed for time and often don't.
And so they may miss the wave. And also when
it comes to training, yes, a lot of the training
costs money. And a lot of animal nonprofits may
not be able to afford it as well. And we think
it's like incredibly important that we that we
catch this wave and we get this right and and
so me and a few other AI consultants from the
animal movement have we've kind of banded together
and started offering free AI training for open
to the entire movement. So last Tuesday we wrapped
up the first cohort of of Amplify for Animals
and that was a 12 week zero to hero AI course
open to the whole animal movement taught by four
of us. We had two different time zone tracks
so that activists from all over the world could
engage. We had practical sessions, we had webinar
style sessions, we had office hours where people
could drop in and just talk about their, bring
their problems, we would hack them out and We
also had some really cool things. We also had
peer learning meetups where we would have sessions
tailored to specific roles. So we would have
one for leadership and management, one for operations,
one for research teams, one for fundraising,
that kind of thing. And lastly, we invited other
animal advocates to come on and showcase the
way they are using AI in their... in their daily
work. And so we had some really cool use cases
of advocates from across the movement coming
in and showing how they use AI as well. And so
we learned a few things. And yeah, the course
was free. It was backed by some generous funders
from the animal movement. It went really, really
well. And we're currently planning what courses
we'll offer in 2026. And so if you're so looking
up and you watch this space and we'll be teaching
some new things in the new year. Yeah, I expressed
to you how disappointed I was for having missed
that training. And then you sent me a link to
everything. So you recorded those sessions and
they are accessible to anyone with the link.
Yes, yeah, yeah, I'll make sure that's in the
in the show notes will well yeah, we're trying
we're gonna find a permanent home for the recordings
all 12 weeks and Yeah, so they should be available
to we want them to be available for free indefinitely
to anyone in the animal movement because yeah,
of course not everyone heard about the training
and Those who could not everyone could make it
as well. So um, yeah, we want to make that as
accessible as possible That's amazing. Thank
you so much for that initiative Okay, so what
are some of the AI hacks that we can use in our
day -to -day advocacy work? Yeah, so the way
I see it, there's a lot of this stuff can be
just, a lot of the best AI stuff can be achieved
with a very small number of tools. So for example,
some people some people are very overwhelmed
by the number of AI tools there are out there
and there are a lot and you see these lists online
of 20 best AI tools for marketing and you think
what do you mean 20 tools then but honestly most
of the benefits of AI can be realized with just
a single kind of core AI model. Those are the
big ones. We've got ChatGBT, Gemini, and Claude.
It honestly doesn't matter which one you use.
People keep asking me which is best, but this
is a race that is constantly ongoing. So, you
know, currently, last week Gemini was clearly
in the lead and then This week, ChatGBT released
the new model, so they've caught up, and then
probably next week, Anthropic will release a
new version of Claude that will make it even
better. So I would really go with what one you
either already use, one is already paid for by
your work, or one that suits you for whatever
other reason. But you can go a long, long way
with just that, without anything else. So...
Some tips I would give you is the first one is
not to just use it as a question and answer machine,
right? Treat it like a thought partner, right?
I joke that you should schedule a meeting with
ChatGPT as if it was just another person at your
organization and say, okay, hey, let's talk about
our fundraising strategy for the next quarter.
Or let's do it like... let's research this topic
together let's come up with a new campaign because
you can not only can you ask it questions but
you can also ask it to ask you questions so you
can say hey so and that can allow a more personalized
response so say I'm doing a research project
I can say hey I'm I'm doing a research project
on let's say it's like Scottish factory salmon
farming And I'm going to say, hey, I'm doing
a new project on this. We are looking into the
environmental costs of this industry. Ask me
five questions to better understand what I'm
looking for in this project. And then ChatGBT
will respond, and it will give you five questions.
And then by answering that, I'm giving it more
context, and I'm giving it more information about
myself. And that's going to allow it to personalize
its responses. So often we ask AI questions and
it gives overly broad or vague responses. And
that's just because it can't read your mind.
It doesn't know about you or your work. So you
need to give it that context. I think probably
the most important thing you can do to get better
results out of AI is to give it as much context
as you can. And so that can be things like asking
it to interview you. So like ask me five questions
about my... about my job or my topic. Another
thing that a lot of organizations do is they
build up an organizational context document.
And so this can just be a Google Doc, all about
your organization, what you do, your staff, what
your goals are, your values are, your campaigns,
and things. And then you can give it to that
model when you have conversations with it. So
you can upload it to ChatGBT and then say, right,
let's talk about fundraising for next quarter
and it's going to have all that context because
these models can they can hold thousands and
thousands of words in their kind of quote unquote
mind at once and um yeah so you can if you give
it that context it will use that context to personalize
your responses. So we have one at Bryant Research.
In fact, I joke that we have an AI employee,
our vice president of strategy is just a custom
gem built in Gemini. And all it is is we've given
it a couple of thousand words on Bryant Research,
what we do, types of projects, our values, our
people, our goals. As an organization and I can
talk strategy with it And I put in the prompt
say like, you know, you are a hard -nosed expert
in strategy. Don't give me Don't give me Sometimes
you need to give me harsh truths. Feel free to
do that you know help us with our strategy and
And it's great. It's really good. Like it's a
it's a it's like having a thought another employee
who is very knowledgeable about strategy and
very knowledgeable about us so I can say something
like Okay, we're thinking about working with
we're thinking about building a data dashboard
for this project Is that a good idea or not?
And then it will come back and it will say well,
how many days is that going to take you? What's
it? Do you have the skills in the team? Like
I don't think we would be able to hire someone
who has those skills So maybe you shouldn't do
it. Maybe you should focus on something else
like it can it can give extremely detailed strategic
advice about the business and sometimes it aligns
with what I'm thinking which is nice but sometimes
it disagrees with me and then I can go back and
forth and it will say no I think you're wrong
because of these things and and sometimes it's
right sometimes sometimes I can it convinces
me to its point of view so that it can be a it
can be very so we can use AI as we can go beyond
this question and answer thing, and we can instead
use it as a thought partner to get kind of greater
insights into our work and stuff. Those are all
amazing tips, truly. I will implement them in
my work. Thank you. Then what should we not do
with AI? For instance, I talked about that organization
I worked with. One thing they taught kids was
don't anthropomorphize the AI. Don't treat it
like, you know, don't say good morning and thank
you and please. So yeah, what do you think of
that? And what kind of things we should avoid
doing with AI? Yeah, so I mean I think it's fine
to to kind of talk to it like to say, you know
Maybe please and thank you to to Gemini and I
know a lot of people do and some people feel
very strongly About being polite to AI that that
they couldn't imagine being blunt and treating
it like a like a soulless Kind of tool and and
I think to be honest, it's fine either way it
used to be about a year ago with earlier versions
of these models. It used to be that you would
actually get better quality results if you were
polite to it. That's not the case with more modern
models, but it actually used to be that saying
please and thank you to Chachibuti got you better
results. See, you're updating my knowledge here.
Yeah. And so, yeah, I don't think there's too
much of a risk of anthropomorphizing these models.
I would say interact with them the way you would
feel comfortable. In fact, I think in a lot of
cases, thinking of AI in a kind of way that you
would think of a human can be beneficial. So
the thing about these models is they're not like
traditional software, right? With traditional
software like Excel, if you click a button, a
thing happens 100 % of the time, right? Software
is deterministic. There is no like, if I press
like the... the chart button in excel a chart
will appear 80 percent of the time like that's
not how it works right software is um is yes
or no right it works or it doesn't same thing
with computer code with a lot of technology whereas
with these ai models they're a little bit more
like humans where it's often a probability if
you ask chat gbt the same question five times
you're gonna get five slightly different answers
and um if you have chat gbt do say every morning
you you wake up and say hey give me um the latest
news on um you know on on aquaculture in my area
um it's gonna it's not going to execute that
task exactly the same every time um kind of like
a human and so it's not gonna spell it's not
gonna spell words correct every time as well
so um thinking of it in terms of a human can
actually be a little bit more a little bit better
for understanding the drawbacks of these tools
as well. But in terms of things we shouldn't
do, so there is something that I think we're
all going to have to navigate, which is how we
can use AI without getting stupider, basically.
And so the thing is, there is a risk that if
you use AI for everything and just turn your
brain off, that you might start to lose skills,
or you might start to lose your abilities and
your competence in certain tasks. So for example,
we all use calculators. And you might have in
school learned to multiply three -digit numbers.
I don't know if you can now, but I struggle.
And it's because we have calculators, right?
And things like that. So there are people who
grew up without Google Maps, and they were very
good at knowing their way around a city by street
names. But then later generations that have Google
Maps don't have that ability. And maybe you once
knew how to navigate streets, but because you
now use Google Maps for everything, you lost
that ability. And so I don't think that's inherently
bad because ultimately there's a question of
like, do we need to know these skills? And all
the time you spent learning directions and all
that kind of brain capacity it takes up, you
could be using it for other things, right? Like
the average person who drives a car does not
know how to fix a car and they don't know how
a car works on a mechanical level, right? And
we all just agree that you probably don't need
to know how, you know, the internals of your
combustion engine. Or we don't need to know how
lithium batteries work, right? There are just
some things that we can abstract away. But I
think we need to have a kind of dialogue about,
in the age when AI can do all sorts of things,
it's increasingly able to do, like, I don't know,
it's most cognitive work that we encounter. We
need to have a think, like what cognitive skills,
what skills do we want to keep and what skills
do we want to delegate to AI and perhaps lose
over time. So I think there's worth thinking
about that. I mean, there's some more concrete
things. So for example, I recommend when I talk
to organizations about their AI policy, every
org should have an AI policy now and or at least
should work on one if you don't have one. And
but one thing I recommend going into most AI
policies is to say that any public facing communications
that features AI generated images, you should
be very careful about generating images that
look like they are real. And then and passing
them off as real, right? So you shouldn't be
passing off AI generated images as real. But
you should also be mindful that depending on
how you present them, people may interpret them
as being, as suggesting that they are real when
they're not. So say I'm presenting about some
research I've done on British farming, and I'm
presenting like, and we did a survey of 50 farmers.
If my presentation is full of photorealistic
AI generated images of farmers, then some of
the audience might think these are pictures of
farmers that I did the study with, right? And
yeah, and so that might not be, it might not
be good to do that, right? Because people might
feel lied to, and yeah, they might feel like
you're kind of misrepresenting yourself. So there
is a risk there. I think AI... images have have
a role to play, they can be really great for
all sorts of things, but there is that thing
of like, we shouldn't be using it to misrepresent
the truth. Similarly, I don't think we should
be generating kind of AI images of factory farming,
even if we are generating images of things that
we know are real. We have, I mean, thanks to
the work of organizations like We Animals, we
have access to to pictures that show what is
truly going on in animal agriculture. So I think
we don't need to kind of create these kind of...
Well, they are fake, but they might be representing
something real, but I would still call them fake
in this case. Because there's a reputational
risk there, right? There's a risk that if they
are found out to be AI generated, people think
that, okay, well, these animal activists are...
essentially they are lying about how things are,
and so it can undermine our credibility as a
movement. So I'd probably say the two types of
things we should be avoiding is the first one
is we should have a think about if I'm using
AI for a thing, am I skills in that thing going
to degrade over time? And if so, is that okay?
And then the second thing is Uh, if I'm using
AI to generate writing or pictures or videos
or audio, um, is that, is it going to undermine
my credibility if my audience like finds out,
uh, knows that, that it is AI generated? I think
those are the key ones. I want to touch on, um,
the, the bias that some of those AI models have.
Um, I think the most. hilarious example that
I came across of that is when Gemini was launched,
I think, and people started asking, you know,
who are the founding fathers and you had pictures
of like, women and, you know, diverse people
and it was really funny. But it showed a bias,
you know, and it wasn't functioning properly
because the developers had a sort of bias. Now
is there an anti -vegan, you know, anti -animal
rights bias in those systems because, you know,
I've asked a few things and, you know, about
is there, you know, pus in milk that we drink
and the answers I got were surprising and I would
argue with some of them, you know, how true they
are or, you know, Tell me about the history of
slaughterhouses. And what I got was not really,
I guess, reflective of the reality, which is
harsh and horrifying, but more like, you know,
something you could tell children. And, you know,
you could argue, you know, what kind of nuances
that AI should use in storytelling or delivering
information, like what to highlight versus what
to put on the side. So it's a complex question,
the question of bias. Have you thought of that?
I know you have, but what are your thoughts on
that topic? Yeah, yeah. So it's definitely something
to be concerned about, right? Because I mean,
really, yeah, we should be concerned about bias
in any of the in any of our kind of systems that
we build as humans really and yeah so this is
this is a case where chat gbt actually again
performs more like humans than like kind of tech
so right there's this stereotype that software
or tech is objective whereas i mean it often
isn't but with large language models like you
know chat gbt and gemini they are They're more
like humans and they've internalized the biases
of the data that was used to create them and
that data Mostly just amounts to like a large
swath of the internet plus most like plus a ton
of books and basically any data that these companies
could get their hands on but so it's going to
reflect a lot of biases that are already in there
and I found that when it comes to their bias
when it comes to the biases uh that it shows
it's often it will show bias in areas where um
large amounts of the internet shows that same
bias so for example one of our researchers Billy
Nicholls who was on this he was on the podcast
actually and um yeah he so he does work on plant
-based pet food right and he used uh chatgbt
to generate to generate a deep research report
on plant -based pet food and the reported generator
was quite biased towards meat -based pet food
being totally fine. And the reason why was because
most of the sources online about pet food come
from the pet food industry, and plant -based
pet food is such a small topic that there just
isn't a huge amount about it online. And because
of that, the AI model was just unable to, it
was unable to find a lot of it, and it wasn't
in its training data. And so there are those
kind of issues where you might see bias when
it comes to information that isn't readily available.
So I think as a good kind of heuristic that,
like, if you can't find a piece of it, well,
whatever the consensus of the first couple of
pages of Google suggests is kind of where ChatGBT
is going to... like start in its opinions. However
these models are capable of quite a lot of like
critical thinking they can critique themselves
and so they do I find that they can be very good
at recognizing their own bias or they can you
can kind of almost prompt sometimes you can kind
of prompt bias out of them. So for example if
you go onto an image generator and say make a
picture of a bunch of professionals sitting around
a table having a meeting. It might generate all
men. It might generate all white people. But
unlike humans, you can just say something like,
generate a picture that is diverse in gender
and race. And it will do that. Or you could do
a thing where... something I'm interested in
is how we might be able to use these models to
overcome our own biases. So, for example, say
you're the comms team and you're responsible
for your tweets and your LinkedIn posts. What
you could do is, before sending out a, you know,
putting something out into the world, you could
say, you could upload it to Geminar ChatGBT and
say, hey, how would, you know, how... how would
this be perceived by certain communities? So
you'd say like, how would the autistic community
perceive this campaign, right? You know, would
they be upset and why? Or like, how would the
trans community respond to this LinkedIn post
and things? Now, obviously, this isn't a substitute
for actually going and asking those communities
themselves. Like, this is something we should
always try and do. But like, to be quite honest,
it's just not always... possible, right? And
it's certainly not possible for every single
tweet your organization puts out, right? And
so it can often be a very good proxy. If you
ask ChatGBT, like, what would a young male from
Yorkshire think about this thing? It's usually,
like, relatively good. And so we can use this
to essentially uncover our own biases, where
we can say, OK, like, this is our new campaign,
how is it going to be perceived by these different
diverse communities? You could say, is our new
campaign insensitive to people who have suffered
from miscarriage or who were held in concentration
camps and things like that, or refugees? So we
can do that kind of stuff too and we can also...
Yeah, well, basically that's it. That's it. We
can use it to be I think we can use it to to
be to be better essentially Yeah, it's funny
to see George Washington with my curly hair but
you know, there are there is danger in those
biases and do you think we can Contact the developers
the people behind, you know the AI to ask them,
you know, hey we're vegans, we're from an animal
rights organization, and we saw that this is
the kind of answers that your AI model gives,
and it's not truthful. And those are our suggestions.
Is that a possible thing we can do? It is possible.
I don't know how helpful it'll be. So one thing
you can do is anytime for most AI tools, there's
after it gives an answer, there's a little thumbs
up and a thumbs down option. If you click a thumbs
down, you can say this was incorrect right one
thing to note about that is um it's kind of obvious
when you say allow but a lot of people don't
realize it that will send your entire conversation
that entire conversation to the developers and
they will keep it to use it as training so like
be wary that you you haven't you know discussed
breaking into a factory farm earlier in the conversation
and um and so yeah we can we can express our
feedback um we can also another thing we can
do is a lot of these models, to assess the quality,
the models are evaluated against benchmarks,
right, and these models, because they all want,
you know, Chachi Buti wants to be the best, Gemini
wants to be the best, Claude wants to be the
best, they're all trying to outdo each other
on getting the highest scores on all these benchmarks,
and that can be programming quality, it can be
like... the wittiness of its writing, that kind
of thing. So there are some organizations, once
again, Centium Futures in there, but also other
organizations such as OpenPause, who are developing
basically measures, tests that you can put AI
models through, and it reveals how much bias
against animals they have, right? And so these
can even even measure how speciesist these models
are. And so once we have those benchmarks, we
can start basically lobbying the companies to
be like, look, this is a benchmark that you should
take seriously. And every time you release a
new model, you should be aiming to try and get
the model to improve on this benchmark. Now,
they're not always going to listen, but they
might, and it's worth trying. And another thing
we... can do when it comes to improving these
things is that they are just getting their training
data from the internet and so for example the
reason why chat gbt will produce a a report on
plant -based pet food that is biased towards
the meat -based pet industry is because there
just doesn't exist that much stuff on plant -based
pet food online so but once we start putting
that stuff out there it's going to end up in
the training data and it's going to come become
reflected in in these models' opinions and views
of the world. So, for example, these models have
quite good, they have quite nuanced views on,
for example, factory farming and plant -based
nutrition. So if you say, like, if you ask Chachipati
and say, you know, like, is veganism unhealthy?
And it's going to come back and say, no, a well
-planned, like, it will say studies repeatedly
show that a well -planned vegan diet can be perfectly
healthy or even more healthy than the average
and the reason that it says that is because that
is the scientific consensus and it has ingested
a lot of those papers right and so when it comes
to steering AI one thing we can do is just the
information we want to that we we want to be
kind of in there we can just put it out into
the world so you can write story you could write
you know science fiction you could write fiction
stories about that about a future where we are
all kind of we are all kinder to animals or post
factory farming society and that's you know you
could blog about you can blog about animal issues
you can post on twitter all of that stuff is
going to end up in the in the models because
they're scraping as much of the internet as they
can and and so they will hoover up the stuff
that you put out there for better or worse and
so if you put pro -animal stuff out there then
it will it will end up in the model. Unfortunately,
there's, you know, there's not that many, there's
not that many of us vegans in the world. But
if, yeah, people should just know that like the
work that you're putting out there is, is getting
seen. That's, that's the assumption. But if we
can lobby them, can Big Hag also lobby them?
Like here, take this Millions of dollars and
yes, have that bias against those animal rights
people. And another thing they could ask for
is data from animal rights activists. Is that
a risk we should consider? Yeah. So you're right
in that anything we can do, there's a chance
that industrial animal agriculture will will
also do. One advantage we have is that they're
all for -profit companies that are competing
with each other, so they're not very incentivized
to provide a lot of that information for AI model
training. So, you know, if you personally, if
any listeners here have tried to investigate
a lot of these big corporations and found that
some information is frustratingly private, you
know, that's because they're They are, they're,
they're for -profit companies that are competing
with each other. So they don't want to put all
of that online. And so a lot of it's just not
going to end up in the training data for that,
that reason. I meant, sorry, sorry. I meant they
could, you know, ask for our data, you know,
private data, what we are inputting in those
AI models. Oh, I see what you mean. Yes. So,
well, so basically, so a lot of these, uh, The
companies take privacy very, very seriously because
ultimately they want you to keep paying for the
service. So these model providers are very concerned
with privacy. So they wouldn't just, for example,
I would be extremely surprised if any company
could pay OpenAI to hand over chat GPT data.
I strongly doubt that's the case. However, One
thing to bear in mind is that depending on the
settings you have on AI, these models may be
storing more or less information about you. So,
for example, if you go into ChatGBT, there will
be, in the settings, there's an option called
improve the model for everyone, which sounds
very benevolent. But what it actually means is
that OpenAI reserved the right to keep... a record
of all the chats you've had, and when they build
the next version of ChatGBT, they will use your
conversations to train it. Basically, they will
have automated systems that will analyze the
conversations, and they'll figure out, okay,
was this a conversation where ChatGBT gave you
what you wanted? In which case, you know, we
want more of that. And where are the conversations
where ChatGBT didn't give you what you wanted?
And then the new model will be trained to not
do that. And so your data, the things you put
into these models will end up, could end up kind
of shaping the future ones, which might be good
or it might be bad, right? If it's your private
data, you might not want it in there. But you
also might want your opinions and values to end
up in the model in some way. So that's something
to be aware of. Another thing is that because
it's storing this information, depending on the
country you're in, this will vary by law, like...
law enforcement may be able to like subpoena
it basically like they may be able to um yeah
so like if you are doing that kind of work um
then it may be that law enforcement is able to
acquire your chat gbt logs to um yeah if if they
think it is relevant to an ongoing case um so
that's something to be very aware of um usually
you can mitigate most of these things quite simply
so for example in chat gbt you can go into the
settings and you can turn off, improve the model
for everyone. And then also, if you right -click
on any particular chat you've had with ChatGBT,
you can just delete it and then OpenAI will basically,
is basically required to get rid of that within
a few months. And so, and that's usually sufficient.
But again, this depends on the data protection
laws of where you are. So for example, in the
UK, And in Europe we have like GDPR, whereas
in the States you have different kind of laws
as well. So it's worth looking into those things.
I don't think industrial animal agriculture will
come for your chat GBT logs, but it may be that
depending on the situation, the police might
manage to get a hold of them. So it's something
to be aware of. Also, your social media activity
might also be used for AI training. Um, I disabled
that on my LinkedIn. Um, but it's also in my,
uh, Instagram. I, I need to figure out how to
disable it. Uh, but yeah, be careful about, um,
the privacy aspect of, of AI. Yeah, definitely.
And so the, I mean, yeah, you raise a good point,
particularly around things like LinkedIn, right?
Because for example, so the average person probably
doesn't think that Like, why would LinkedIn collect
data for AI? Like, I've never seen a LinkedIn
AI thing. Like, you know what I mean? But, yeah,
companies, lots of companies are trying to integrate
AI into their products. And for them to do that
effectively, they need lots of their users' data.
So it is really something where, like, basically,
I know this is gonna be tedious, but, like, every
piece of software you use, every app, every website
that you... contribute data to, you should be
digging through the settings just in case they
are using that data for the training of new AI
features. I mean, this isn't something that is
actually new, to be honest. So it has always
been the case that a lot of these companies,
websites, apps have been trying to record as
much information about you as possible. In the
past, they would have just sold packets of that
information to data brokers or used it for targeted
advertising. But now we've got this added dimension
that it might be used for building AI features
as well. So it's worth looking into the privacy
settings and things. It is worth noting, though,
that typically, if you get... There are often...
free versions of stuff, paid versions of stuff,
and then there'll be enterprise versions of stuff,
right? So you can get an enterprise version of
Gemini for your company. And enterprise versions
usually have the strictest privacy. So for example,
if your company gives you an email through Gmail,
then Google has pledged not to... to use your
personal emails to create software products.
And that's always been the case. And now that
extends to, say for example, Google Gemini. Whereas
on the other hand, if you're using a free model
or a free version of a tool, you should be very,
very careful about checking the privacy policies
because as the old saying goes, if something
is free, then you are the product. Um, that's
not always true with AI, but like the, yeah,
it may be the case that some of these tools are
free because they are hoping to collect as much
data from you as possible. Um, but, uh, so you
could look into, is that the case? And if so,
can I turn it off or find alternatives? Yeah.
Thank you for including all software systems.
You know, I had to do it with a co -pilot and
word. Um, for privacy, but also because it was
slowing down the whole thing experience. So,
yeah. Wonderful. Richie, I think we covered lots
of ground. Did you want to add something before
we stop the conversation? Yeah, I mean, I just
want to because here we've talked about like
addressing concerns. We've talked a little bit
about the benefits, but I do want to like to
emphasize them a little bit more, like we've
got, you know, in terms of some case studies
and things, because I really do think that the
animal movement has a huge amount to gain by
leaning into these tools. And I'm seeing it more
and more. So, for example, one case study I'd
like to highlight is that we had, there's an
organization in the UK called the Conservative
Animal Welfare Foundation. So they're the voice
of animal welfare in the Conservative Party.
And one of the founders, Chris Platt, he's an
older gentleman, but he has really leaned into
AI. He was one of our most engaged participants
on our Amplify for Animals course. And one thing
he told me was that it's a very small org, less
than 10 people, but two of his org went on maternity
leave this year. And with an org that small,
that would often mean kind of grinding to a halt,
essentially, or just drowning in work. But he
said that because he has been making so much
use of AI, he still waits for them to return
and he couldn't replace them with AI, but he
could manage to keep kind of everything running
without burning out by greatly increasing his
own productivity using AI, which is amazing because
this is a small org that is doing valuable work
and something like double maternity leave can,
it's just one of those things that you often
can often come out of nowhere and all of a sudden
you lose the ability to kind of keep having that
impact for animals. But he's managed to use AI
to keep the ship going and things like that,
which is just really amazing to hear. And another
thing as well on the front of we've had Another
organization that I do work with, Greener by
default, they help caterers to shift to more
plant forward diets. And so I've been building
out the data analytics side of their org because
I'm a data scientist by training. And so I've
built a system that kind of mostly automates
all of the data analysis that they need as an
organization. And I estimate that using AI coding
assistants, like programming assistants, I have
been three to four times more productive this
year than I was pre these assistants, right?
Like in terms of the amount of code I have shipped,
the amount of stuff I've delivered, like three
to four times, right? It's as if, you know, it's
as if there are several of me in the organization.
These are the potential improvements where...
we're talking about here. And because it's such
a general purpose technology, it can help you
write donor reports, it can help you research
for campaigns, it can help you with your HR policies.
It's such a general purpose tool that it means
that there is almost every role in the whole
movement. can make use of AI and can see those
benefits. It's not just for techies. It's not
just for young people or people in the West.
It is really for all of us. And kind of to that
point, I think it's just about experimenting,
really. The more you experiment with it, the
more you're likely to find these benefits. So
I think if we constantly experiment with these
tools and we share them, We share the results
with each other. We share the wins. We share
the the learnings. Then I think as a movement,
we can really catch this wave and and just and
and really kind of use it to have like a huge
like a much, much bigger impact for for animals.
I love that. I love hearing those stories. Thank
you for sharing. And yes, please, people follow
the footsteps. become more efficient in your
advocacy work by using AI. I also use AI. You
know, I'm fundraising consultant. I tell my clients,
you know, your money is precious. I want to use
it to be more productive and do more with what
you've hired me to do. So yes, it is like I said
in the beginning, you know, it is a necessity
and people need to start learning to use it.
And yeah, thank you. Thank you so much, Richie.
And thank you. Thank you for your advocacy work.
Thank you for having taken the time to answer
my questions. This has been very insightful conversations
I've learned a lot and I'm sure listeners too.
So we're all very grateful. Thanks. Yeah. Thanks
for having me. And to all the listeners in the
new year, keep a lookout for... Thank you everyone
for listening. I kindly invite you to share this
podcast with the vegans you know. Let's encourage
more people to take action. Again, thank you
so much for caring, and I will see you next Tuesday
for a new episode.