AI for Good: Transforming Society
Key Points
- The podcast opens by contrasting everyday hardships—like accessing medicine or power during blackouts—with widespread fears about AI’s disruptive potential, setting up a discussion on AI’s positive role.
- Guest James Hodson, founder of the “AI for Good” initiative, explains that his belief in AI as a force for beneficial change stems from a decade‑long effort to harness technology for sustainable societal impact.
- He traces AI’s evolution from early hype in the 1950s through successive commercialization waves, noting that we are now in a transformative era where AI’s capabilities are becoming tangible (e.g., self‑driving cars).
- Hodson’s organization was created to fill the knowledge gap between emerging tech and society, offering expertise that strengthens community resilience, optimizes limited resources, and builds a forward‑looking, harmonious future for the next generation.
Sections
- AI for Good: A Positive Shift - In the opening of the AI in Action interview, the host highlights everyday hardships and fears surrounding AI before asking James Hodson how his AI‑for‑Good vision can turn technology into a beneficial force for humanity.
- AI for Community Resilience - Explains how combining AI expertise with economic insight empowers communities to build lasting, technology‑driven resilience.
- Tech Foundations and Advocacy Amid Conflict - The speaker outlines how their organization prioritizes basic technological infrastructure and community engagement, using Ukraine as a case study, to enable societal transformation while stressing that ongoing conflicts impede global development objectives.
- Beyond GDP: Rethinking Productivity Metrics - The speaker argues that traditional measures like GDP fail to capture true human productivity or societal progress, calling for new metrics that link work, output, and broader social goals, especially when faced with uncertainty such as war.
- Tech-Driven Solutions: Fires and Equality - The speaker explains how integrated hardware and real‑time data create a coordinated wildfire mitigation system in British Columbia, then shifts to highlight the ongoing challenge of achieving gender equality in the workplace, noting that women still lag behind men in career advancement.
- Public Cultural Fit Scorecard Initiative - A speaker outlines a forthcoming public scorecard ranking tens of thousands of U.S. companies on cultural‑fit metrics for employees, investors, and customers, while urging computer science and AI to adopt engineering‑style risk mitigation comparable to traditional infrastructure disciplines.
- Teaching AI for Societal Impact - The speaker stresses that AI education must combine technical knowledge with real‑world problem‑solving mindsets, enabling individuals to start small, test responsibly, and apply AI to broader community challenges.
- Corporate Role in Unlocking Untapped Potential - The speaker argues that businesses can boost their bottom line by solving societal inequities—such as unequal access to technology, education, and healthcare—thereby unlocking the economic contributions of disenfranchised populations and creating shared value with communities and NGOs.
- Hopeful Closing and Donation Appeal - The speaker wraps up with optimism about AI’s future, thanks the guest, and urges listeners to support the nonprofit AI for Good.
Full Transcript
# AI for Good: Transforming Society **Source:** [https://www.youtube.com/watch?v=8P0tYXWiGds](https://www.youtube.com/watch?v=8P0tYXWiGds) **Duration:** 00:25:58 ## Summary - The podcast opens by contrasting everyday hardships—like accessing medicine or power during blackouts—with widespread fears about AI’s disruptive potential, setting up a discussion on AI’s positive role. - Guest James Hodson, founder of the “AI for Good” initiative, explains that his belief in AI as a force for beneficial change stems from a decade‑long effort to harness technology for sustainable societal impact. - He traces AI’s evolution from early hype in the 1950s through successive commercialization waves, noting that we are now in a transformative era where AI’s capabilities are becoming tangible (e.g., self‑driving cars). - Hodson’s organization was created to fill the knowledge gap between emerging tech and society, offering expertise that strengthens community resilience, optimizes limited resources, and builds a forward‑looking, harmonious future for the next generation. ## Sections - [00:00:00](https://www.youtube.com/watch?v=8P0tYXWiGds&t=0s) **AI for Good: A Positive Shift** - In the opening of the AI in Action interview, the host highlights everyday hardships and fears surrounding AI before asking James Hodson how his AI‑for‑Good vision can turn technology into a beneficial force for humanity. - [00:03:01](https://www.youtube.com/watch?v=8P0tYXWiGds&t=181s) **AI for Community Resilience** - Explains how combining AI expertise with economic insight empowers communities to build lasting, technology‑driven resilience. - [00:06:06](https://www.youtube.com/watch?v=8P0tYXWiGds&t=366s) **Tech Foundations and Advocacy Amid Conflict** - The speaker outlines how their organization prioritizes basic technological infrastructure and community engagement, using Ukraine as a case study, to enable societal transformation while stressing that ongoing conflicts impede global development objectives. - [00:09:16](https://www.youtube.com/watch?v=8P0tYXWiGds&t=556s) **Beyond GDP: Rethinking Productivity Metrics** - The speaker argues that traditional measures like GDP fail to capture true human productivity or societal progress, calling for new metrics that link work, output, and broader social goals, especially when faced with uncertainty such as war. - [00:12:27](https://www.youtube.com/watch?v=8P0tYXWiGds&t=747s) **Tech-Driven Solutions: Fires and Equality** - The speaker explains how integrated hardware and real‑time data create a coordinated wildfire mitigation system in British Columbia, then shifts to highlight the ongoing challenge of achieving gender equality in the workplace, noting that women still lag behind men in career advancement. - [00:15:40](https://www.youtube.com/watch?v=8P0tYXWiGds&t=940s) **Public Cultural Fit Scorecard Initiative** - A speaker outlines a forthcoming public scorecard ranking tens of thousands of U.S. companies on cultural‑fit metrics for employees, investors, and customers, while urging computer science and AI to adopt engineering‑style risk mitigation comparable to traditional infrastructure disciplines. - [00:18:51](https://www.youtube.com/watch?v=8P0tYXWiGds&t=1131s) **Teaching AI for Societal Impact** - The speaker stresses that AI education must combine technical knowledge with real‑world problem‑solving mindsets, enabling individuals to start small, test responsibly, and apply AI to broader community challenges. - [00:21:56](https://www.youtube.com/watch?v=8P0tYXWiGds&t=1316s) **Corporate Role in Unlocking Untapped Potential** - The speaker argues that businesses can boost their bottom line by solving societal inequities—such as unequal access to technology, education, and healthcare—thereby unlocking the economic contributions of disenfranchised populations and creating shared value with communities and NGOs. - [00:25:08](https://www.youtube.com/watch?v=8P0tYXWiGds&t=1508s) **Hopeful Closing and Donation Appeal** - The speaker wraps up with optimism about AI’s future, thanks the guest, and urges listeners to support the nonprofit AI for Good. ## Full Transcript
Do you know where to go to get medicine when your child gets sick? Do you know
where to go to recharge your devices when the power has been out for 20 hours?
Are you able to communicate with other people in your society?
How the hell do you find out what benefits you're entitled
to from the international community or from your government?
Because of the situation that you find yourself in
when you've been in a blackout for three days?
In a world where AI is a terrifying,
culture changing behemoth, is there another side to the story?
A side where AI is actually out there making positive change
and impacting humanity for the better?
My guest today, James Hodson, would like to believe so.
He's a researcher, leader and entrepreneur,
as well as the visionary behind AI for Good.
James, thank you so much for being here.
Welcome to AI in action.
Fantastic pleasure to be here, to be with you today.
Thank you so much for inviting me. For sure.
We're going to really enjoy picking your brain,
but first we're going to start with the elephant in the room.
We know that AI is scary to a lot of people.
So when did you start to think that instead it could also be a force
for positive change and good?
Fantastic question. It's been a really long journey.
The foundation was started around ten years ago,
but the idea that we need to use technology in society
in more sustainable ways and to effectively attack
kind of challenges that we face, is something that's age old, right?
It's not something that we came up with. For us, it was in the late 90s.
Over time, right during the 2000s, and you have to remember with AI,
we've had multiple waves of the expectation of commercialization
and the anticipation that AI is going to transform the universe.
And it's been like that since the 50s, and now we're in a wave
where we are actually seeing structural, transformative
change with the technologies, and it's extremely exciting.
It's also, for many people, seeing it in person, right, interacting
with technologies that their parents even would not have been able to imagine
or seeing a self-driving car stop
for them at a crossroads in a city,
it's a little bit, you know, takes them aback.
And I can see why people would be anxious about what could happen next.
For us, that's what, that vacuum in terms of the understanding of how technology
interacts with society, was the reason for starting our organization.
We wanted to be the providers of expertise, kind of a backbone
for society to understand how to best
utilize emerging technologies in a way that's
going to strengthen our resilience, it's going to strengthen our communities.
It's going to make us better problem solvers overall.
It's going to make us better able to use the resources that we have on this earth,
which are not infinite, in order to give our children a better future
right, and live more harmoniously together so that we're actually
building a positive, forward looking force in the world.
I love that overall commitment.
Give me some examples though.
I want to hear what are some ways that you've really found
that you can use AI for forces of positivity?
Our mission as an organization can be best described
as economic and community resilience
through technology.
And it's the through technology lens which changes kind of how we think about
what we're doing.
In the back, we are, yes, technologists, right.
And I've been a researcher in AI for two decades,
and I've worked across a whole variety of problems,
and I've seen a lot of what can be done with the technologies.
But we are also economists and economists are people who study human behavior.
They study the structure of society and try to understand
what kinds of changes will have the impact that we desire,
and what's the most effective way of achieving that end result.
You have to bring those two parts together in order to have an impact on the world.
You can't just design a technology
and expect that it's going to go out there and have good.
You need to do it in context.
You can't design a strategy for a whole nation state
and their approach to technology and society,
and how they can attack certain challenges that they're facing
without actually being within that community.
We prefer to strengthen the communities with the skills
and the resources and the ideas that are required.
So that they can build things for themselves
that are going to have a long lasting impact on adoption.
Now, let me dive into the examples that you asked for.
A few years ago, we were approached by the Tony Blair Institute,
based in London, to work with them and the government of Ethiopia
in order to develop a forward
thinking strategy for the next 10, 20
years of economic development and societal transformation in Ethiopia.
We’ll detach this conversation
from how Ethiopia has developed politically since that stage.
So, for example, in Ethiopia, they have the same amount
of internet bandwidth for the whole country.
As a few blocks around my house in California.
Imagine how that constrains your ability in the modern world
to build an innovative society that's solving its own challenges.
It's a massive bottleneck, right?
People actually don't need much to be entrepreneurial problem
solvers in the modern world, right?
Laptop, good internet connection, and...
good coffee, right? Right.
When you are lacking one of these kind of foundational columns.
Right. You need to start thinking about
how can you quickly get infrastructure in place.
It turns out the strong internet backbone and that kind of infrastructure
is actually really important when it comes to health care.
In a country that's as massive as Ethiopia, with you know, more than 100
million people, most of them living in rural areas, most of them farming, right?
Most of them not really having any background in technology
and not thinking about opportunity through a technological lens.
You need to actually reach them as a first stage.
So a lot of what we then ended up thinking about was,
what's the basic infrastructure that you need to put in place first,
and how do you get people on board with these ideas?
So that's the first example that a lot of the work we do actually is
kind of advocacy oriented
in communities to make them understand that the transformative
or the foundational layer that they need in order to be able
to build with technology, be able to transform their society,
it's not that far away from where they are
now, but you do need some resources in order to enable that to take place.
Another example on the other side, we're very involved in Ukraine.
Now, you know, obviously some of the viewers will have seen that.
I'm wearing a, rather bright outfit today.
Right.
Now, this is a traditional Ukrainian Vyshyvanka. Right.
It's an ornate set of patterns related to particular regions of Ukraine.
And for us, as an organization,
we started
to enable better solutions to these challenges. Right.
2014, they were ratified by the United Nations.
And that's when we also started.
And that's the taxonomy that we use for thinking
about the problems that we want to solve in the world.
And if there's one thing in the world right now which is causing us to fall
even further behind on achieving these goals, it's
the fact that we have massive conflicts that are liable to spill over
and are already having deep economic effects around the world.
So we use the fact that,
we have the technology expertise, the scalability
expertise to solve problems, to also help in Ukraine.
We have 50 staff on the ground.
We have about eight different locations that we work across,
and we're active
with the entire Ukrainian government and every municipal authority in the country,
which means that we're developing
technologies that are used by Ukrainians on a daily basis.
We're developing strategies and policies based on data
analysis and machine learning and and AI to enable
the Ukrainian economy to withstand the invasion.
In all of known history, whenever there's been an all out invasion
of a country, there has been a collapse of the banking system, for instance.
And you need banks in Ukraine because of the way that the economy
was being managed.
There was no run on the banks, there was no crisis in the banking system.
It's one of the few examples of where good economic thinking
actually was able to prevent something that could have
then led to a much, much, much deeper set of problems.
And as a result, you actually have a functioning society, right?
Still.
And that means that we're able to go in and use technology to advance that.
Of course, if you didn't have that layer of well-operating, well-oiled society,
then you would have challenges putting AI and other technologies into place.
And all of this starts, of course, as you mentioned, with the strong foundation,
you've got to have that infrastructure that’s set on up and then you can build.
Can you give me some more ideas
in terms of how can we think about AI outside of the
the traditional scope of productivity and actually enhance that?
I love this because, you know, we're, we're getting into conversations
that impinge both upon kind of modern economic thinking and how
we understand society and our relationship with productivity and growth.
And so we use measures like GDP, right, and GDP is an economic measure.
It shows you basically how money cycles through the economy, right.
And how quickly it moves around right from the available pool of capital.
It's not actually a very good measure
of how productive human beings are.
So we have these measures that are kind of divorced from,
you know, how productive are we being sat here?
Right. Maybe it's a net negative.
We don't have good ways of knowing what accelerates our ability
to solve the problems that are important, or reduce the amount of energy
that we need to expend to solve the problem.
Right?
Or to make a sale or to develop a new product or to build infrastructure.
We don't know actually what the relationship is between how many hours
we work and how much we're paid, and what actually we're
building in society, and how much closer we are to achieving what we want.
So I try to step back from that
and not worry too much about the productivity angle,
because it's not useful for actually putting technology
into the context where it can be used for societal transformation.
So I'm going to take
an example.
Imagine that you have a war. There's a lot of uncertainty.
How do you find the resources that you need in order to stay calm,
stay productive,
stay alive, and thrive as much as possible and in such a situation.
So you might imagine, okay,
do you know where to go to get medicine when your child gets sick?
Do you know
where to go to recharge your devices when the power has been out for 20 hours?
Are you able to communicate with other people in your society?
How the hell do you find out
what benefits you're entitled to from the international community
or from your government because of the situation that you find yourself in
when you've been in a blackout for three days?
However, also consider
outside here, right in New York City.
How do people find out about the opportunities that they're entitled
to? How do they make good decisions about their plan, plans for the future?
How do they make sure they're getting the training that they need
and the support that they need psychologically?
Right, in terms of family planning, in terms of their relationships
with, with the community and how they actually interact.
Can you give me some more examples of how AI for good works?
Maybe on not as large of a scale, but a little bit more intimately.
So we've, we've had the pleasure of working also
on a very municipal level, right, around the world,
including in Brazil and Canada, here in the US and Europe,
looking at ways that we can understand and analyze the challenges
that are being faced in the community and respond to challenges,
but in a way that then we can take those solutions
and potentially scale them to other places that that need them.
For example, in British Columbia, we played a role in developing
what is now an interconnected wildfire mitigation system, which allows
all of the different agencies that are needed in order to respond
to potential situations where fires get out of control
in a way that's coordinated and in a way that gives them
the information that they need in real time.
This is the type of thing where it's not just
about artificial intelligence, it's about the underlying infrastructure.
It's about the hardware. Right.
What are your ground observation beacons?
How are you getting the overall view of the situation that's happening?
How are you choosing where to put resources so that you can respond
most quickly to a specific point where the flare up is most likely?
Also, how do you maybe identify ahead of these situations
where the risks are so that again, you're being proactive about mitigating risks
rather than dealing with a fire, which is obviously much more costly,
much more dangerous, and is going to lead to much more damage,
to people's lives, by having to live through it.
On the other hand, we can go to another example, which is workplace.
So workplace equality.
Right.
We have as one of the Sustainable Development Goals, gender equality.
And today, as a society, we're still very, very far behind on this goal.
So for women in particular, it is very difficult
to achieve the same career success as men.
And it's more difficult today than it was ten years ago.
How do you attack this kind of situation?
We're not going to be able to get into the DNA of every single company
and really solve it on an individual basis.
But one thing we can do with technology is we can bring more transparency
to the signals that people can use in order to understand
the culture of a company, in order to understand the current structure
and how that might be contributing to outcomes,
and by doing that, by bringing transparency to an area,
we can change the approach that corporate leaders take
to managing their culture and make them focus on these questions more.
So that's the economic idea behind it.
With technology, well, AI is fantastic at aggregating data.
It's also fantastic at identifying patterns that we might not
be able to see, or precursors to patterns that we're not going to be able
to associate, right, with kind of manual, old school
traditional methods and so one thing that we do is we work with a variety of data
partners, including organizations that have been collecting,
you know, resumé and job applications for decades
in order to look at the relationship between hiring and companies,
the structure, the internal structure of those companies
and how promotions happen and how people are rewarded
for their work, and also how happy people are, within these organizations.
One thing that we're now coming kind of to the to the point where
we're going to be releasing it publicly is a scorecard
of tens of thousands of companies in the US by metrics that are important
to understanding whether this is a culturally good fit for somebody.
So a culturally good fit from the perspective of an employee,
culturally good fit from the perspective of an investor,
and culturally good fit from the perspective of a customer.
You shine a light and let the market show the way forward.
Right.
And so what we also try to do with technology is to bring more light
to these areas.
I'd say it's less about saying AI needs a special way of doing things
than, well, let's look at, you know, how do other
engineering disciplines cope with risk and risk mitigation?
When we build a bridge, for instance, do we go out there, kind of stand
right looking across the chasm and think, all right,
you know, I think I need a piece of steel that's about 600ft long.
All right, let's see, let's see what happens.
Right? Usually we don't do it that way.
It's not that we are saying that we should do something wildly
different with AI, but computer science in general has avoided
being pinned down as an engineering discipline for decades.
Now, when we think of critical infrastructure in society,
it's not highways, rail, electrical, water.
You know, it's cyber and communications, right?
That is pretty much the underpinning
of everything else that we're doing now because it goes away.
And you don't have a banking sector anymore, you're not going to have reliable
water supply because it's all being basically managed
by an interconnected information system.
Right. The electrical grid is going to be able to balance your power.
You're going to have surges that break all of your appliances at home.
That backbone has been built by computer scientists,
by AI scientists, by statisticians.
And it's an engineering discipline.
You know, we should have come to terms with the fact
that it was a real engineering discipline
and put proper procedures in place decades ago.
But the reality is we've always treated it as ah, it's like an art, right?
Programing is an art, right?
It's an art that apparently we think is possible
to just come out of a language model because it's artistic, right.
So we're going to generate it
and it will kind of approximate the thing that we want it to do.
But we need to constrain that art, just like bridge building is an art now, right?
We have many beautiful bridges, but it's also, at its core,
a mathematical engineering based discipline
that needs to have rules about how we go about identifying the problem
that we're solving, ensuring that we know right and can trust
all of our understanding of the base that we're building upon.
Just like you wouldn't build a bridge on quicksand.
Oh, it didn't look like quicksand when when I was observing it.
We need to make sure that we're doing the right thing.
We need to test things appropriately at scale.
Right. So start small, build up.
And we need to ensure that when we're educating people, when we're building
the next generation of people who are going to work in this discipline,
that we are not only giving them
the mathematical scientific knowledge that they require,
but that we're immersing them in how to solve problems in society.
And when we have that type of thinking, you know, what else will happen?
What's that?
They're going to see other opportunities
that go beyond what they're doing in their job.
It won't just be, oh, I've got to deploy a chat bot today
that responds to questions on behalf of, this podcast on our website.
It's going to be, well, you know, when I was walking into work, I saw that,
you know, there's clearly an inefficiency in how we're,
you know, managing kind of pedestrian routes
during construction or something like that.
You know, we start to provide people
with a basis for thinking more broadly about their skills and capabilities
within the community and society, and we engage with them on this level.
And, you know, people naturally want to solve problems.
And I think that we need more of this approach.
On a practical level, can an individual coder start to use AI for good today?
I think we're at a really interesting time.
So I started programing in, the mid 90s.
Right.
And there was magic when I started programing, and I realized
that I was one individual with a toolset
that could scale and touch people around the world.
Once you internalize that, it's extremely empowering.
And it was true in the 90s as well as it's true today.
But today we can harness
per person thousands of kilowatt hours more in electricity than I was able
to harness in the 90s to solve problems, which means that we can solve problems now
at an unprecedented scale, as an individual, right?
We have ability to tap into resources that no single person would have been able
to access with their idea at any point in history before.
And ultimately, you know, if we put it in crude terms, innovation
and the economy is about energy consumption, okay?
And what we're doing right now with AI
is we're consuming energy,
which is allowing us to build solutions, right, with small teams
that are extremely sophisticated and have far reaching potential.
It sounds like you're placing a lot on intention,
on focus in terms of how we can use AI.
Businesses and nonprofits, sometimes their interests don't always align.
So how can we think about AI for good?
Both your organization, but then also the theory, the philosophy.
If you're a business person who's listening to this right now,
if you're a person who's really focused on the bottom line
in the business right now, how can all of this make sense for them?
Right now in the United States, because of the unequal access
to technology and opportunity, education, health care,
infrastructure, there is an enormous amount of untapped economic potential
in the US from people that have been disenfranchized from the system.
If as a corporation, you focus in on helping
to solve the challenges in society that have impacted that,
it will actually unlock an enormous amount of economic value.
Because ultimately, what is a society
if only half of it is contributing to solving a problem?
Right?
Without the private sector, governments today
don't have the expertise or really the ability
because of kind of political deadlock in some sense,
to really fundamentally rethink how we solve problems.
While in some sense corporate America, the NGOs,
civil society more broadly has a level of flexibility
that allows us to not be constrained by special interests.
And employees at these corporations have even more power
because ultimately they hold the keys to the engine, right?
And the engine needs to work for everybody, right?
Not not just for kind of a powerful elite at the top.
There are benefits that come from operating in a community with an attitude
of that community being consequential to your business in the future, right?
Not a resource to be used,
but an effective network
in which we can operate to bring positive outcomes for all.
Positive outcomes for all.
I'm going to take that now,
and I want to go back to where we started this conversation.
There's a lot of fear surrounding AI.
Why should we not be as afraid as we are excited?
We are at a time where if we can invest more as a society in
creating with, creating
the precedents with technology that underpin
big solutions to grand challenges like climate change.
Which obviously is, you know, a framework problem that we all need to be thinking about,
not just from, you know, how do we capture carbon in the atmosphere at scale,
but also what are we doing every day in our own lives that's impacting this?
And what technology can play a role in bringing that
to the forefront of people's attention and so on.
I've always been in a situation throughout my life and career
where the technology that I'm using could have power
to do good and power to do bad in catastrophic ways on both sides.
And yet we have always chosen as society, eventually,
the path of hope
and positive outcomes from the technology rather than the path of destruction.
And I think that we will continue to choose this in the future.
Again, that doesn't mean that we don't need to be eternally vigilant.
You can be pretty positive about the amazing things
that we're going to be able to achieve over the coming years and decades.
You know what?
I kind of want to just keep that as a mantra now.
So, James, thank you for such an enlightening
but also a very encouraging conversation today.
I believe, and I really hope, that everybody who's
been joining us in this conversation has also found this equally empowering.
So thank you again so much for joining us.
It matters.
Folks, AI for Good is a nonprofit, so their funding does
come from people like you and me.
So please go check out their website and consider donating at aiforgood.org.
Again, thank you all for joining us. We'll see you next time.