Hello and welcome to the very first episode of
our new podcast series, The Purpose Brief. It's
a space to help you connect with everything to
do with creating more social good in the world.
What's not to like? To kick things off, I'm joined
by Nathan Chappell, a trailblazer at the intersection
of philanthropy and technology. He's chief AI
officer at Virtuous, founder of Fundraising AI,
and co -author of The Generosity Crisis. It's
a book that says the real challenge for modern
giving isn't really about the lack of money out
there in the world. It's a lack of connection,
human connection. Nathan's also just released
a new book, which we'll talk a little bit about,
called Nonprofit AI, which explores how artificial
intelligence can be used responsibly to strengthen
trust, empathy and impact across the social sector.
He's spent over two decades exploring how technology
can help us give better, not just faster, and
how to keep generosity human in a world run by
those pesky algorithms. He's an inventor, he's
a dad, and someone who still finds time for a
long cycle ride to clear his head at the end
of the day without his phone. It's a thoughtful
conversation to start the series about trust,
about belonging, and what generosity might look
like in the years ahead. So you ready to join
us for this journey? Let's dive into the first
episode. Nathan, hello. How are you? I'm doing
well, James. How are you? Really good to see
you. Thank you so much for joining us on what
is essentially the first edition of our Purpose
Brief podcast. Thank you very much for agreeing
to do it. Yeah, absolutely an honor. It was great
to be able to meet you up in York. And, you know,
I'm so glad you reached out. Congratulations
on your book. And that's been out for a few months
now. Let's talk about our first top level question.
What is your purpose? What do you do? That's
a big question to start with. Like, what is your
purpose? I don't know if you've ever seen the
movie The City Slickers. It was an old movie
I grew up in. Well, I grew up in, I was born
in the seventies, but probably grew up in the
eighties movies. And there was this question
in, you know, it was like, what is your one thing,
your one thing in life? And that really, like,
I don't know. I grew up at a time where that
movie was formative and I, it bothered me that
I didn't know my one thing. And so if people
don't know this movie, it essentially is Billy
Crystal. And he goes on this little escapade,
a ranch, and he essentially finds his one thing
in life. For the most part, I was drawn to philanthropy
early on at a very young age. Actually, I did
my first fundraiser when I was eight years old,
but I never thought about philanthropy as a career.
I landed into it as an accidental fundraiser
in the year 2000, ended up raising money for
many years. And it took me a while to understand
my one thing. And I think it actually came to
me when I was provided an opportunity to leave
my job. And when I left, I remember telling the
person that, I worked for that I was really driven
by the idea of scaling generosity. At the truest
sense, my purpose was to scale generosity and
being a technologist, someone who had started
several tech companies, sold those companies,
super early adopter, always curious about what's
next. It was really this idea of scaling generosity
through technology. And so that's been really
my purpose ever since I came across that. It
just felt my mantra in life. And while I believe
humans are amazing and they're capable of amazing
things, they're not scalable on their own. So
it's really this idea of the intersection of
generosity and AI, which I've been on this path
since about 2017 now. A great movie reference
there. When you talk about social good, what
does it mean to you? Because we're obviously
very passionate about through our business, but
what does it mean to you specifically? Yeah,
I mean, social good is a broad term that can
mean anything. I mean, ultimately, what I was
raised to believe and what I, you know, believe
as an adult and instilled in my children is that,
you know, no matter what you have, there's always
a responsibility to, you know, there's always
opportunity and responsibility to give back.
And so, you know, social good for me is really
a state of mind, not something that you do. It's
a way of being. And, you know, when I became
an accidental fundraiser, in fact, I fell into
this on accident. But for my first seven years
running a really small grassroots nonprofit,
I never felt like I went to work. I felt like
it was a way of life. And, you know, from a biological
perspective, humans are these, you know, pro
-social creatures that tend to like biologically
we're wired to actually help others even at sometimes
a cost to us. So for me, social good is tying
into that primal instinct. It's something that
we as humans are intended to do, to give back.
This is why our brain releases dopamine and serotonin
when you help. It's why we release oxytocin when
we have empathy for others. I mean, we're biologically
built for the idea of social good. It's really
the noise and the distraction in societies. that
keep us from living in that kind of truest sense.
But, you know, I think that is probably the foundational
belief are people, you know, inherently good
or evil. I don't know. I mean, I guess you'd
go back to the biblical days and, you know, Adam
took a, you know, bite of the apple. But, you
know, at the end of the day, I do believe that
people are wired to give back and they're wired
to be in community. And so social good for me
is the expression of that, that goodness. So
in a way, your work in AI is a kind of counterpoint
to that in the sense that in the world of impacted
by algorithms that we're starting to see that
has a negative effect on community and kind of
cohesion. You feel that through your work, AI
can be a force for good. Is that against algorithms
and everything that social media is unlocking?
Yeah, that's a great question, you know, and
I get that a lot in the sense of that belief
that maybe, you know, technology and automation
is, you know, morally in opposition of community.
And maybe it's because I like a challenge and
I, you know, don't like to do easy things. But
to be honest, like I think about AI as any other
technology, like, I mean, no different than,
you know, a hammer or a saw or. typewriter. It's
a technology that doesn't know the difference
between right or wrong. It's essentially in the
hands of humans that will either use it for good
or bad purposes. And so while inevitably there
could be more bad actors than good actors in
the world, or those bad actors will use this
technology in ways that will not be beneficial
to humanity, I do believe that the technology,
again, that doesn't know the difference. can
be a force multiplier for, especially for social
good, for, you know, social impact organizations.
And when you think about it, like humans are
amazing. Like we are, I host dinners when I travel
called dinners of extraordinary humans, because
I believe that every human, like we're, we're
walking miracles. Like we are like, there's no
reason why like we're even here and having consciousness
and all these like amazing thoughts and ideas.
And we can do these things. We are extraordinary,
but we're not scalable on our own. We have always
needed technology. Humans have always, progress
is always capped by the technology that lets
us amplify our intentions. And so whether it
be electricity or whether it be the typewriter
or the printing press or whatever it might be,
while humans are incredible, we need technology
to amplify. And so I think AI is the greatest
force multiplier for... the amplification of
ideas if used well. And so while I'm very bullish
on the idea of AI being used for good, I'm also
deeply concerned that with a lack of information
or without a lot of foresight or thought about
unintended consequences, that the technology
could even purposefully or accidentally be used
in a way that moves people apart. And so I find
it... Most of my passion work, my full -time
volunteer job now with fundraising .ai is educating
people, not advocating for the use of AI, but
advocating for the responsible and beneficial
use of AI, which means that it supports us both
in the short term and in the long term. You've
just completed the summit that you had over the...
I think it was about a month ago, wasn't it?
And that was kind of record numbers for you.
People from all across the world from not -for
-profits getting together. Was there a sort of
takeaway in terms of the outcomes and the discussions?
You know, it's interesting because fundraising
AI started out as this, you know, grassroots
volunteer effort. Well, really 2018 and no one
really cared about it, to be honest. Like AI
was not very accessible. It's not very affordable.
And so, I mean, we're talking, we're a few hundred
people. And then in 2022, Chanchi PT came out.
I gathered about, I don't know, 75 people. We
decided to do this summit. And a few months later,
we had our first summit, which brought, we thought
about 500 people would come and we had 5 ,000
people. And then the next year, 7 ,500 people.
This year, 11 ,000 people from 130 countries.
I've seen the evolution from. total skepticism
and people probably hopefully hoping that AI
was never going to come. It would be a fad to
curiosity. And now we see, you know, a kind of
widespread adoption, but not in any strategic
way. And so I think the observations from this
year are we've crossed the barriers of for the
people who resist change, which are. 30 % of
people resist change. 50 % of the people sit
on the sidelines. So, you know, we're talking,
you know, a vast majority, 80 % of people are
not going to be your, your, you know, front runners
in this. They're now brought along. We're in
this like middle of the adoption, but there's
not a lot of strategic use. They've accepted
that this isn't going away, but it's still very
much in its kind of infancy in terms of using
it in ways that are. not really formative. There
are ways that are just slightly, you know, incremental
on the sides. And to be honest, with the headwinds
facing our sector, societal changes facing our
sector, incremental changes don't work in an
exponential world. And so that's the part where
I think the fundraising .ai kind of movement
is really to help educate people to get people
away from just using shadow AI to improve a letter
once in a while to changing their orientation.
to thinking from the first bit of work they do
in the morning is how can AI help? And do you
think that adoption changes the human purpose
within the organizations? I mean, I think that
worry that people will have or a lot of people
do around adoption and their future jobs and
what does the future of work look like? I mean,
is that something you see as being adopted more
readily by fundraisers who already have constrained
budgets? Yeah, you know, it does vary by country
quite a bit because the ethos of the country
and kind of the sediment around what AI represents
does kind of dictate this. And so, of course,
the U .S. has taken this very much rogue, like
anything goes, just try everything. And when
something really bad happens, we're going to
regulate it. Whereas the EU is taking a much
more pragmatic approach to say, well, let's.
put some guardrails around AI, have people think
about some of the really unintended or the bad
use cases of it and not let people do those.
And let's regulate before something bad happens.
So it does change a little bit of that. But I
do think the fear factor is starting to creep
in. I mean, we're starting to see, you know,
for early days, it was like, well, AI is not
going to replace jobs. But people who use AI
will replace those that don't. That was essentially
and still probably largely the most popular belief
that AI won't replace humans, but humans that
use AI will replace those that don't. We're actually
starting to see that change. Like we're actually
seeing AI replace jobs and we're going to need
to figure out like what do those people do? And
now this is not new. I mean, every technological
revolution has had these same types of things.
But never at this scale and never at this pace.
And so I do think that there is quite a bit of
fear, but the bar is being raised at the same
time. So fundraisers that are using AI to elevate
their ability, whether it's, you know, practicing
or essentially rehearsing an ask before you go,
whether it's, you know, really dialing in, understanding
donor sentiment and dialing in communication
to a donor, whatever that might be. I do think
the bar is starting to increase. And I think
those that are really diving into this will very
quickly outperform others. And so they'll find
themselves at the forefront of the wave. It's
really interesting talking to different types
of not -for -profits and fundraising teams about
how they're adopting it. And I wonder whether
there's more of a challenge for big organizations
who will be much... bigger in terms of the governance
expectations versus small not -for -profits.
I mean, you talked about a few great examples
of somebody who is the chief exec of a charity
in the US and has one fundraiser and that's it,
you know, to do everything. So how they scale
and change their approach is much, this could
make a huge difference to them in their ability
to just deliver funds. versus big organizations
like higher ed institutions that might be more
cautious for obvious reasons, that have multiple
different priorities. That's a big change. So
I started working in AI in 2017 in machine learning,
so predictive AI, machine learning and deep learning
to predict which donors are likely to make a
gift. And, you know, to be honest, only... the
big organizations could afford to do that type
of work. The barriers to leveraging machine learning
and deep learning, either you had to hire a PhD,
in early days you had to hire a PhD pretty much,
or a statistician, mathematician, you know, kind
of cross. And it was not easy. I mean, we spent
a year and a half building our first algorithm,
you know, very long -handed, lots of code. What's
interesting is that... Early adopters tended
to be the ones that had kind of philanthropic
research and development budgets, so like philanthropic
R &D. And those almost entirely, almost 100 %
of those organizations were the large organizations
because they were big enough that they could
afford to experiment a little bit if it didn't
work. And there was a lot of skepticism whether
it would work or not. But that's almost reversed
entirely. Like, I think that's what the huge
shift has been with the advent of generative
AI, which is... Basically free or nearly free,
depending on what models you're using. It's put
AI in the hands of everyone. And when you think
about nonprofits and the idea of like need is
the mother of invention, like small nonprofits
with one person, two people, three people, they
need to extend their reach. And AI is peanut
butter and jelly for a nonprofit that is resource
constrained. And interestingly enough, is that
the big organizations that were first are now
last. Because now all of a sudden those big organizations
are mired in bureaucracy and policy. They can't
agree on what to do next and what tools are approved.
In fact, I have a friend who was one of the earliest
adopters in AI at a fairly large children's hospital
in 2017, 2018. He's using less AI now in his
organization than he was four years ago. So it's
reverted backward, whereas these small nonprofits
are just power boosting through this movement,
which is... Great to see, honestly, from a scale
perspective. And do you think that's unlocking
more funds for them? Is it more different types
of donors? Is there any kind of key trends coming
out of that? You know, I think it's starting
at the lowest denominator, which is just like
improving efficiency. And so for the most part,
you know, it's helping those small nonprofits
make the best use of their resources. And so
the average. nonprofit could save 20 % of their
time that provides, you know, per employee an
extra day a week. And so, you know, if you could
use AI to really create efficiency that gives
you back 20 % of your time. And I can tell you
like my second book, nonprofit AI was written
in four months because I had a research assistant.
I had something to bounce off ideas. I had something
to help me create analogies to do. help me find
case studies, my first book took two and a half
years. So a nonprofit that's going to dive in
and be like, hey, this is part of what we're
going to do, 20 % of their time, that's a low
bar. When we think about from a resource development
perspective, let's say still predictive AI is
the most common way of actually using AI to predict
who's going to make a donation and then have
more targeted outreach, but generative AI being
used. for sediment analysis to really understand
donor populations. And then ideally take the
predictions from machine learning and deep learning
and then personalize asks. And so that is still
probably the most common use case right now.
Second to that, I think we're seeing a lot in
prospect research because I used to have four
prospect researchers, full -time people with
master's degrees working for me. there's zero
doubt that one person now could do the work of
four. And so, I mean, that is a significant power
boost for nonprofits. And so even an average
fundraiser who wants to be prepared before they
go for an ask has this research tool that if
they know how to use it well, would be the equivalent
of a person with a master's degree that's going
to spend several hours doing work for you. So
can we imagine a future where there will be fundraising
bots that a major gift manager would have working
for them producing a data looking at the prospect
analysis most up to date and this is what you're
doing this week yeah you basically just pulled
a page out of my notebook that i keep i i have
a room in my house that there's no phones allowed
it's it's it's a no phone zone and it's like
a little library nook where i go for my first
cup of coffee And especially in this day and
age, I encourage everyone to do it. It's amazing.
You know, if you can put that down and leave
it in another room, no distraction. Yeah. About
a few months ago, I was thinking about the fundraising
shops that I had led. I mean, I started out in
small, very small grassroots, and then I ended
up my career with 250 employees, which included
all fundraisers and prospect research and donor
relations and all this stuff. And throughout
all of those, I actually took my notebook one
day and I was like, you know, I'm curious whether
I had two employees where I wore lots of different
hats or I had 200 employees where I wore a fraction
of a hat. How many actual job functions are there
in, you know, truly job functions? And so I really
started like racking my brain and I. I came up
with a 20 job function. So like no matter how
big or how small your organization is, there's
about 20 core job functions that a nonprofit
person does. And then I, you know, for the purposes
of the exercise was curious about in what near
future state could bots essentially augment or
highly, highly augment or even automate these
jobs? Like how many of these 20 jobs? could be
highly supported by AI. And I started with like
five easy, easy prospect research, prospect,
you know, donor relations, stewardship and things
like that. And then I got to 11 and then I kind
of got stuck at like 13. And then I came back
the next day or the day after. I'm like, wait
a minute. You know, literally the conclusion
is that all 20 jobs, like there is not a single
job in nonprofit that can't be highly supported
and augmented by AI, if not in some cases replaced.
And so I do see a marketplace as we move into
the next wave of AI, which is agentic AI, AI
that makes autonomous decisions. It's very ideally
intuitive. It's still not intuitive, but will
be very soon. This type of agentic AI will be
able to string together lots of different projects
into one thing. And I could see a fundraiser.
going to a Gentic marketplace and being like,
I need my prospect research bot. I need my donor
relations bot. I need my whatever. And literally
have these bots essentially populate a donor
relations plan. That's perfect for this person,
a communications bot, a research bot and so on.
So I think you've nailed it. I absolutely, without
a doubt, it's inevitable that that will happen
in not in five or 10 years, like two to three
years will. we'll have that marketplace. Yeah,
wow. That's quite a turnaround. But I suppose
from my experience as someone who has led big
fundraising teams, where the challenge is always
how do you argue the case for more resource,
more staff person resource? And now actually
we can think, well, and probably, you know, senior
leaders in... not -for -profits and universities
are starting to go, well, you know, we haven't
got much wiggle room there. So therefore, how
do we use that envelope and really think seriously
as leaders across those organizations about what
is the human intervention points and what kind
of roles do we need? So in a way, they're a little
bit more hybrid than somebody being created just
to look at data or somebody being created to
look at stewardship. some of the challenges through
the years have always been about people and teams
not talking to each other. So bots, and those
bots are on the market. I mean, there are companies
in the States already working on fundraising
bots. Yeah. Now, and you can go to an extreme,
an unhealthy extreme, which is essentially replacing
fundraisers with bots, like deep fake looking
bots, which I'm morally opposed to and pretty
vocal about. I believe that. A bot can give you
information, but it can't make you feel heard.
And I think, you know, in this highly digital
age where everything is undoubtedly digital forever,
humans are still analog and human to human connection,
you know, can still be truly kind of this idea
of being analog and make you feel heard. But
optimizing a analog person with lots of digital
bots and strategies around them And this is where,
you know, humans will always lose in the race
against AI bots, mainly because bots have perfect
recall. It's like having multiple PhDs, like
all the PhDs just waiting to help you. What it
does is it changes the person that we hire and
it changes the person we promote and it changes
the person that succeeds and kind of moves up
the career ladder very quickly. To be honest,
it's not a person that gains more intelligence.
It's the person that connects dots better than
the other person. And so truly the key to success
in the age of AI is about curiosity and connecting
dots, not about gaining more subject matter expertise.
That's a foundational shift, completely. I mean,
a radical shift from the people that we've hired
and promoted over the past, you know, forever.
Are you starting to see that? come into workplaces
or with organizations? I mean, we talked earlier
before we started recording about some examples
there. Yeah, yeah. I mean, I've seen the curious
generalist outperform the person that has like
subject domain expertise in one subject and literally
leapfrog from a career ladder perspective. I
have a friend of mine who was hiring an executive
assistant and she was presented with two candidates.
One was a 15, 20 year veteran executive assistant,
highly qualified, had served very high level
CEOs. The other person had been in the military,
never went to school. And in the interview talked
about how he loved AI and that he thought it
was just so interesting for him and how it can
elevate his work. surprising, not surprising.
Of course, the end of the story is that she hired
the curious generalist without a lot of experience
because of his mindset, not because of his experience.
And so we're seeing this play out quite a bit.
Now, I just wrote an article about this the other
day is that I've audited about a thousand job
descriptions that I found in the Chronicle of
Philanthropy for the words artificial intelligence
as a business requirement or as a desire. And
less than 5 % actually mention AI as a AI fluency
as a job requirement. So it's such an obvious
thing, right? And anytime I tell a leader, it's
like, well, look, if you want to look at the
future of your workforce, look at who you're
hiring today. If you're hiring the same people
that you hired three years ago, five years ago,
or 10 years ago, you're going to have the same
type of organization. And so they're like, oh
my gosh, I hadn't even thought about that. And
so. We need to really switch things up and start
to prioritize AI fluency and who we're recruiting,
but then also bring AI fluency into not just
as a professional development exercise, but just
as an ethos of how every day you operate and
incentivize curiosity. Yeah, there's absolutely
something there about future -proofing. yourself
as a professional right around that fluency and
i mean presumably your recommendation is there
it's all open source you can immerse yourself
in whatever way you can right well i thought
it was silly because the publisher you know wiley
after writing the first book which had it actually
still has pretty good success surprisingly it's
still it i don't think it's ever left the top
50 in amazon in the charity category but the
second book I had not planned on writing a book
on AI. I had actually planned on writing a sequel
to my first book. And I was already down the
road with that. And they were like, why don't
you write a book on AI? And I was like, why?
Because if anyone wants to know how to use AI,
why wouldn't they just go ask it? And so like,
it was such a foreign thing to me to think about,
well, I guess some people need to look at chapters
one through 12 and kind of feel better about
this decision. But for me, it was so obvious
that like. There's no secret to be like, if I
want to know how AI can support my role, all
I have to do is ask it. Like, you don't need
to be a prompt wizard to do that. Literally just
have a conversation with your AI and be like,
I'm a fundraiser. I don't know how to, you know,
work with you. Like, what are the ways and, you
know, best strategies of optimizing, you know,
my work with you? And it's like, you don't need
a book for that. Lo and behold, I guess some
people do. Yeah, no, I mean, as you say, it's
that ability to process things in a different
way, but it's interesting. So just to go back
to that, you were saying about how you used AI
to write the book and be a prompt and a librarian,
which people don't think of AI like that, but
it's a great librarian to go off and find and
verify when you're writing. That's a really important
skill set. But tell me about how you found that
and what was the response? I suppose that's the
other thing as well. How did people perceive
that? It was interesting because our publisher
was not happy. So, you know, they asked us to
write a book about AI. So I brought in one of
my my number two, Scott Rosencranz, who we worked
together since 2017. And we're like, let's do
this together. And, you know, we're like, of
course, like we can't be hypocrites. We if we're
going to write a book called Nonprofit AI, we
need to use AI to help write the book and to
to help augment. Now, of course. AI can't write
a full chapter on its own, or now it can, but
at the time it couldn't. And it definitely couldn't
write a whole book. And it will be able to in
the near future, like in the next year. It's
just horsepower. How much are you willing to
pay? And when I reflect back on my first book,
it took two years, two and a half years to write.
And it was either through research or even more.
painstakingly like slow was coming up with analogies
for things. And you realize the limitation of
a human being analog is that we can only relate
to the experiences that we have. So I had two
coauthors in that book and we would sit around
every Tuesday night and we'd be like, does anyone
know a nonprofit that did something like this?
Or do you know of a correlation between this
and this? And man, we would like, I mean, there'd
be times that we'd spend an hour and a half on
a Zoom call, two hours, and we'd get nowhere.
And we're like, well, let's think about it and
we'll get back. The biggest benefit of using
AI in the new book was not being analog. It has
perfect recall. It's like I can give you 100
analogies of how this is like this. And most
of them are way better than what humans can come
up with just on their own, just in recall. So
we wrote. The book and the whole book is edited
by humans. And there's, you know, it's very,
you know, we didn't like copy and paste any part
of it. It would have been gibberish. But we did
at the very end, I had AI, I think I would use
chat GPT on this to write basically a one page
statement of how we used AI to help augment and
support us in the book. And it wrote this like
brilliant one page. And I went to Scott and I
was like, Scott, if I edit this page. I'm going
to make it worse. This is literally like, there's
nothing I as a human can do to this page that
will actually make it better. And I think that's
the only page that we actually didn't edit in
the book because it just said it so perfectly
because it had been on this journey with us for
months. Like we had been using Claude and ChatGPT
a lot just to reflect and, you know, gain ideas
back and forth. And so, yeah, it was a pretty
interesting experience. And do you, are there
things that annoy you about the use of Chuck
GPT or AI when you're writing? I mean, I always
think Chuck GPT is a little bit like our AI's
know -it -all friend. We've all got those. You
know, so he always knows a little bit more. it
likes to please. Yeah, there's a couple of tricks
there. I mean, and to your point, generative
AI foundation models are built with two goals
in mind. The first is to please, to your point,
and that's why they do what they do. And they
want to keep you in conversation. And number
two is to be right as often as possible, but
not in the opposite order. So they're not aimed
to be right all the time. They're aimed to please
you first and then be right as often as possible.
And so one of the things that I think a lot of
people fail to do And one of the easiest things
you do, especially pay for a model that has memory,
is that for since November 2022, so we're coming
up almost in three years, which is crazy, of
when ChatGPT was released. I've been every LinkedIn
post, every article, everything that I've done
that I've had it work with me on, then I've edited
and I at the end take my final edits and I paste
it back into ChatGPT and I say, save this for
your memory. And so with that point, like when
I go to work and I'll be like, OK, it's time
for another, you know, article that's going to
be blah, blah, blah. It knows my final product
so well. And if it if you're only like extracting
it, you're like, OK, and then I edit it and then
I send it off to my boss. it never understands
essentially what your final product is, like
how you actually speak. And so people end up
in this perpetual cycle of frustration of like,
well, it just never really gets me. It's just
trying to please me. So that's a big one. But
there's still, you know, the challenges with
it and the things that, I mean, mine are really
pet peeves. And to be honest, if you haven't
like yelled at your AI, cried with your AI, like
walked away in frustration and slammed the door
and then come back to it, you haven't gained
that AI first mindset. And so like you have to
go through all the stages of grief with your
AI to like fully extract the most out of it.
But even still like em dashes for me, even though
they actually look better grammatically, I hate
em dashes because everyone thinks, oh, you just
use AI. And so now I feel like I can't use em
dashes, but the text editing function of AI.
prohibits it from not using em dashes. And so
I just gave mine simple instructions that anytime
I use the word hashtag pineapple, it will take
my final product and remove all hashtag or all
em dashes and replace them with regular dashes.
So I have to give it a secondary prompt, but
also like the word delve, I've never used the
word delve or vibe in my normal kind of speech.
I'm like, why all of a sudden are we talking
about vibing and delving all the time? Like,
stop it and so very yeah it's a very naughty
phrase i constantly modify my settings to just
kind of adapt to whatever new model comes out
and all of a sudden the new model is using delve
all the time i mean it's kind of like i have
a friend that's annoying you probably don't tell
them but you just like kind of put up with it
let's jump on to a discussion about the ethics
because you talk a lot about that in the book
and ethical ai and there is and will always be
a kind of pushback and a backlash. There are
obviously implications for the business use and
from a sustainability perspective about AI. But
tell us about your views on that. Yeah, my views
are fairly distinct in that, you know, starting
in this process in 2017 and moving until today,
they've evolved over time. You know, early on,
I looked for frameworks of what was called responsible
AI, RAI. And RAI, early on was mostly grounded
in ethics because there was a lot of fear around
bias and using predictive AI was going to reinforce
bias. If your data set was largely constructed
of rich white men, it would actually penalize
anyone who was not, and then it would promote
anyone who was. We learned how to overcome, for
the most part, those types of bias. Now, all
data is bias, but... We learned how to build
models that are transparent and explainable.
And so we could actually look at the math behind
the model very easily. And actually, it turns
out predictive AI is much easier to evaluate
from an ethics perspective or a bias perspective
than generative AI. Ethics being a minimum expectation
of what responsible AI is. It's not the maximum
because responsible AI includes things like.
yeah, privacy and security and ethics, but also
authenticity and transparency and explainability.
It gets into even environmental sustainability.
And, you know, a few years ago, I was still bothered
by this idea that my framework for a responsible
AI that hold everything I just said looked an
awful lot like Microsoft and Amazon and Google
and Nike and Samsung. And I thought, well, how
could this be? Because if we operate in the currency
of trust, like we're not selling cell phones
and tennis shoes and cloud software, we were
essentially exchanging trust for money. Like
how could, how is it even possible by design
that our framework looks the same? And so I really
went, this is probably one of the hardest noodling
I did for a few months and talked about this
with, with a lot of different people, the fundraising
AI advisory council, we sat in a room and it
just dawned on me. It's that, AI, like our framework
in the nonprofit sector that exchanges trust
for money, can't only concern itself with AI
that supports our organizations in the short
term. It also has to burden us with the implications
and unintended consequences in the long term.
And so that became a really clear distinction
of how the nonprofit sector can't evaluate it
in the same way that the private sector does,
that we have to consume. ourselves with this
idea of responsible ai and beneficial ai so ai
that is again helpful in the short term and also
mitigates harm in the long term and this isn't
any different than say social media where we
look at a technology that by design was intended
to bring people together you know and make people
money but by design it was intended to bring
people together And what has occurred since then,
right? The misuse of that same technology or
overuse of a technology that has increased anxiety
and depression and decreased happiness and all
those things, because essentially there were
lots of unintended consequences of how the overuse
of that technology might prevail in the future.
And so I think this is where in the book and
in my work, it's probably the biggest departure
where we were like. I think the nonprofit sector
has more clarity around what AI that serves humanity
looks like, far more clarity than the private
sector by design, because we don't have the same
financial incentives to scale AI at any cost.
Yeah, that's really interesting. So your recommendations
is around, and it's all open source, people can
access this, but the kind of ethical frameworks
that can be put in place from a governance perspective
for different types of nonprofits. Yeah. Yeah.
And in fact, that wasn't always my philosophy.
I mean, early on, 2017, 2018, I left nonprofit.
I started a company. We got two patents on machine
learning and gratitude prediction machine learning.
And it wasn't until after getting the patents,
which took a few years, that I realized that
essentially patenting an AI in the nonprofit
sector. essentially is to not share, is to not
show what is behind it. And I thought, well,
if the center of every algorithm is trust, that
we need to be able to look in the algorithm to
understand how is that preserving and protecting
trust. And so I became a really big proponent
at the time and thought, well, patenting algorithms
a really bad idea. What we really need in the
sector is open and transparent and explainable
AI that can be shared with whoever to say, you
know, this is what we're doing. This is how we're
doing. And for the most part, our organizations
need to be grounded in how we're using AI. It
needs to align with the values of our organization.
Every organization will be different. But we
also need to disclose that we're using AI to
donors, which we've studied now. We've done two.
two studies, the largest longitudinal study of
donor perceptions of AI. And now it's over 2000
donors that have shared that they're very much
in favor of nonprofits using AI, as long as they
disclose that they are using it. And presumably
a lot of that is going back to what you were
saying around gratitude learning, that a lot
of organizations could benefit from having more
of that, that links to customer experience. So
I am a donor, I wish to donate to x cause and
i go onto the website and it's clunky or it's
a exactly not great interface presumably all
that's wrapped together it's about efficiency
and agility as much as it is about donor experience
right because donors are consumers right and
donors you know they look at a non -profit either
as in the same way that they would have bought
something online and then either have a feeling
of like why does this feel so different and impersonal
and difficult Where I could go onto this Amazon
and it already knows what I'm going to buy and
makes it so easy to, you know, with one click,
I can just have it literally in this afternoon.
So I think this brings up the biggest question
for nonprofits in this age is that, well, you
really have to determine, is your organization
an amplifier of a person's generosity? Or is
it a barrier to their generosity? And if you
are a barrier to generosity, like there's extra
clicks and it's cumbersome and it's impersonal
and people don't feel like you know them, then
people will leave. They'll go somewhere else.
And they may not go to another nonprofit. They
may go to GoFundMe or to purchase something from
Tom's Shoes or Bombas Socks or some social good
or corporation that has a double bottom line.
So essentially what you're saying is that there's
also some changes there around trends about what
people identify or causes that people identify
with in the social good space. So it wouldn't
necessarily just be their local charity, a hospice.
It might be ethically sourced products. And it's
a whole sort of shift, isn't it, around the mindset
of locally produced. And so people are making
more broader discussions around the ethics of
that. I guess that's what you meant to say. some
ridiculous amount on an overpriced t -shirt and
still get the same hit of dopamine and serotonin
that I would have been had I made a gift to a
nonprofit. But the advantage is I get that hit
of dopamine and serotonin because I feel like
I saved the home planet. But the added benefit
is I also got a t -shirt. And so at the end of
the day, I think this is what the changing landscape
of the sector that really makes us realize that.
We have to evaluate the way we fundraise for
a long time. And if we have a best practice that
predates November 30th, 2022, the day that Chachi
PT came out, then it's an outdated practice.
And so, you know, the world has shifted massively
in a few years. And so I think this is an opportunity
and responsibility for every nonprofit to kind
of rethink everything they think they know about
fundraising. No, it's a real call to action,
which is great. And a massive shift over the
past few years, but that is going to be escalating
much more, isn't it, in the next 18 months? Yeah.
You know, we are at AI's infancy right now. I
mean, the acceleration will not slow down. People
might hope it will. It will. It will only speed
up. AI is considered an exponential technology,
which means it's no longer dependent on humans
to actually improve. It's what's called a recursive
self -improving technology. And so it just, again,
will go faster and faster. So change and agility
is probably the number one thing that organizations
need to pour into to really help their staff,
especially since 80 % of people don't really
like change, only 20 % do. That helping people
through change in a kind of a perpetual. adaptive
way that we're just going to always be you know
changing for that to be grounded in your values
I think that's going to be really important but
we live in an era now where information doubles
around every 12 hours what will enter at the
end of 2027 to sometime in 2028 is called the
information explosion by all accounts that will
mean that information is doubling every few hours
and so you know what worked for you in the past
no longer works for you in the future You know,
it's time to rethink everything. So doing things
the old way will not yield better results in
the future, for sure. But in some ways, will
humans become, for their need to switch off from
all that information, which will always be out
there, they just need to manage their human time,
which seems a silly thing to say. But I think
there's a real shift around how we manage our
own mental health and our engagements in that
space, because we cannot be all things. to all
people and humans need to be really switched
on to that and i think you know social media
in some ways does help as much as it hinders
more now than ever yeah i mean i call it opportunity
overwhelm when anything is possible it's it can
be you know debilitating and so for myself who
works in ai and spends a lot of time thinking
about the future i have had to create very concrete
boundaries for myself of when and when i do not
use ai like all of my social media apps that
I have are not on my homepage. They also don't
have the red alert. It's turned off and they're
in a folder on like my third or fourth page.
I've had that for a couple of years, but I now
have, again, a room in my house that no phones
are allowed. That is just literally a thinking
place. Also because I travel a lot, I've made
airports a place that I just, I leave my phone
to have my boarding pass, but I tend to not use
my phone at an airport because I find it's a
really good reminder. of where humanity is at.
When I look around an airport and I see people
that are six to 96, all looking down, scrolling
300 feet on their phone a day, not talking to
each other, it's a pretty stark reminder about
what's important. And so use AI for ways that
support your work, but create boundaries that
will support your soul and the community around
you in really powerful ways. And I think... You've
got to be very, very intentional about that because
behind every swipe on your phone is an algorithm
that is essentially custom designed to gain your
attention and to try to drive an action. If you
just allow that to be the case and you don't
create those boundaries, well, the average person
scrolls 300 feet on their phone a day. So the
hours will go by and then inevitably you'll be
watching cat videos before you know it. Cat videos
are always in there. And cats and dogs, Nathan,
thank you so much for this insight. I hope you'll
come back at some stage and have a chat with
us again. Is there anything you want to call
out? You've got your book. People can follow
me on LinkedIn. I tend to post about every week
or every other week. I tend not to do kind of
short form. garbage anymore. I find myself needing
to reflect deeper. And I don't know that anyone
reads my articles, but I find them very satisfying
to write. And so I tend to write an article at
least a week or every other week at the latest.
But they can also go to my website at nathanschapell
.com. They can actually listen to an audio version
of both of my books that were created by AI using
an application called Notebook LM. And if they
want to see AI in action, it's... Pretty amazing,
to be honest. And in that case, if you like the
short 18 -minute podcast, buy the book. And if
you don't, then you just saved yourself $30.
So you're good to go. Good advice. Nathan Chappell,
thank you so much for your time today. Absolute
pleasure. We'll catch up soon. Yeah, definitely.
Let's do it again soon. Thanks.