Everyday AI Podcast – An AI and ChatGPT Podcast - EP 224: AI and its Impact on Society: How it might look

Episode Date: March 8, 2024

Awesome Stuff From Our Partner, NVIDIA -Register for the FREE virtual NVIDIA GTC Conference or buy tickets to the in-person event and fill out this form here: https://www.youreverydayai.com/nvidia-giveaway/AI is going to have a huge impact on society. It already has impacted the labor market and other parts of society. Will AI be more disruptive than we think, or can it be an overpowering force for good? James Hodson, CEO of AI For Good Foundation, joins us to discuss the future of society with AI.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode pageJoin the discussion: Ask Jordan and James questions on AI in societyRelated Episodes:Ep 202: The Holy Grail of AI Mass Adoption – GovernanceEp 206: There is No AI Hype – This is how the world works nowNext Episode: Break Things That Are Already BrokenUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:01:40 About James and the AI For Good Foundation04:33 International organization born from academic and policy community.07:41 Economic development through technology and infrastructure.11:01 Rethinking humanitarian aid and leveraging technology's potential.13:25 Exploring AI's impact and potential economic disruption.17:04 AI impact on labor market analyzed, adaptation needed.20:45 Government role in technology shift and regulation.25:25 Promoting AI audit program for ethical technology.28:45 Reengaging economists and policymakers for economic shift.33:17 Community resilience crucial for technology adoption and innovation.Topics Covered in This Episode:1. Role of AI in Global Development2. Community-Driven Development and AI3.  AI's Impact on Labor Market4. Government Role in AI Implementation5. Navigating AI-Driven Economic ChangesKeywords:Artificial Intelligence, Global Development, Community-Driven Approach, Traditional HumanitariSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. Artificial intelligence is going to have a tremendous impact on society.

It already has, right? We've seen over the last year and a half this gen AI boom change away the lot of us even work, the way a lot of us even function. So I'm extremely excited to be talking about that today on today's episode of Everyday AI. So welcome. My name is Jordan Will. And I'm the host of Everyday AI. We're a daily live stream podcast and free daily newsletter helping everyday people like you and me,

not just learn what's going on in the world of Gen AI, but how we can all actually leverage it, right? It doesn't mean anything if we can keep up with the news and the tools and the techniques. We can't ethically and responsibly use it to grow our companies and to grow our careers. So that's what everyday AI is all about. And we talk to people from all over the world. And, you know, that's one of the challenges of being a lot. live stream, right?

Sometimes there's people from other time zones that we can't always bring on live. So that is today's. So if you're listening to this, yes, we are debuting it live, but it was technically pre-recorded. But with that, don't worry, I'll probably still be in the comments answering questions. So if you have any questions, feel free to still ask them. But with that, I'm extremely excited to bring on our guest for today's show. So please help me in welcoming James Hodson. the CEO of AI for Good Foundation. James, thank you so much for joining us.

Thank you, Jordan. It's a pleasure. Real pleasure to be here. All right. Can you tell us a little bit about, you know, not just the AI for Good Foundation, but obviously, you know, what you do in your role heading the Foundation? Absolutely. And I guess, you know, just to head it off, I mean, the nice thing about it being a pre-recorded show is I don't need to worry about, you know, saying the wrong thing. So it's all good, right? So AI for Good Foundation is about 10. 10 years old, it's a nonprofit based out of California, but operating around the world. As a nonprofit, our mission has been and is today economic and community resilience through

technology. So we look at the world through the lens of technology and AI in particular, as you can imagine, from our name. And we try to think about how we can strengthen that society, how we can increase the resilience of that society to difficult, complex situations. And we help governments, private entities, NGOs around the world to be able to create, plan, deploy, and operate infrastructure that uses advanced technologies in order to kind of build those systems and improve those outcomes.

That means operating in disaster areas. So it means operating in places like Ukraine. It means operating in countries like Ethiopia that are going through massive economic development and technological change. It also means operating here at home in the U.S., in Canada, in Europe, in order to improve the ways that governments interact with technology and the way that companies use technology. And tell us just a little bit. So, I mean, you already mentioned, you know, international reach, you know, trying to use artificial intelligence in a positive way. but can you just tell us a little bit about the size of the organization? You know, I follow your guys's

work, but maybe a lot of people don't, but you have a large reach, you know, both people on your team, board members, et cetera. So can you just talk a little bit about even just kind of bringing people from, you know, highly visible parts of the world, you know, business leaders into the fold and how just this AI for good even works, you know, as a mechanism for using AI for good? That's a fantastic and fair question, I would say. So we have two aspects to how we operate, right? One is, of course, we're building, right? We're out in the communities.

We're building. We're developing technologies, and we're making sure those technologies are responsive to human needs. We talk about human-first technology. The other side is we are a bit of a global advocacy network, right? We were born out of the academic research community and the economic and policymaking community. And as a result of that, we have a fairly big reach around the world, as you mentioned. Now, the organization itself is around 70 full-time staff around the world. And that staff kind of shifts around as we build stuff.

We're often referred to as kind of a SWAT team. SWAT team that comes in, helps governments, helps organizations to change, and then kind of builds that capacity, right, to do good. but we don't try to stick around forever, right? We realize as a nonprofit, our mission is to experiment, to find the way forward, and then to hand off that capability to others who can scale it. So it's not ever been our aim to become, you know, a 10,000-person organization and to be, to be massive, but it is to get into those situations where there are difficult problems to solve

with the right people, with the right way of thinking about it. and that's why we talk about economics and technology coming together. And therefore, you know, knowing our place and creating that innovation potential. You know, I love how you said that almost like a SWAT team for good, right? And, you know, even my own background, I spent almost 10 years working at a nonprofit, you know, all over at least here in the U.S. And yeah, like when you start and with your mission, you always hope that you aren't needed, You hope that you can go in and solve problems and you don't have to have, you know, a permanent presence, right?

But what is what does it look like right now that, you know, if your mission is successful, right? So maybe you can either walk us through a simple use case, but what does it look like to implement AI for good, whether it's in a community, a city, a country? Like what does that tactically look like? And what's the impact kind of, you know, after or, you know, what are the results that, you know, you're kind of able to show for your work in these areas. Okay. We have a variety of programs around the world, right? And I think each time we go in, we're not looking at the same impact metrics.

Each time we go in, we're not thinking about it in a templated way. But I'll give you a few anecdotes, right, that can maybe paint the picture of how we go about doing our work. So I mentioned Ethiopia before. So we were in the privileged position of being able to work. with a series of global organizations, including the Tony Blair Institute out of London, from 2018 through 2020, in order to build the economic strategy for Ethiopia that would basically transform the way they digitize their society and use technology. But it included also thinking about mega infrastructure projects.

So, for example, in Ethiopia, there's the largest hydroelectric. structure in Africa that's being completed. It's called the Grand Ethiopian Renaissance Dam, caused a bit of a geopolitical mix up with Egypt, as you can imagine, because of it being on the Nile. But the potential of those massive infrastructure projects, when you think about kind of today's data as currency, right, and electricity being kind of the marginal provider of innovation potential within many of these contexts, rather than labor costs, as we may have seen historically. What that means is that countries like Ethiopia find themselves in a position where economic development can actually hop, right?

Make a big, big jump forward versus other countries that maybe aren't going through such deep transformation. And technology in those senses can be a transformative vector. So there is designing policy, but then there's also creating technology. So we have, for example, in Ukraine, we operate a platform, a platform called Lifeforce. And Life Force essentially takes everything where government ends and provides a social safety net for people to be able to interact in their communities to get everything that they need in real time. And that's intermediated by artificial intelligence, right? but it's a human-centric platform.

It's about connecting people at the right moment to get the things that they need, to fulfill needs, and to be able to manage resources effectively and optimize that within the social context. So just to give you two anecdotes, and obviously we can go into much more detail than that. You know, I think a lot of people, when they hear a nonprofit that does work all over the world, I think the first thing that pops into a lot of people's head is, you know, education or access to clean water, you know, eradicating disease, et cetera.

Should we be looking at artificial intelligence, not in that same path? Because I know it's not in apples to apples comparison, but is there also this concept or this thought in your organization where the rest of the world needs AI for economic development in the same way they may need, you know, access to clean water, access to high quality education. Is that a train of thought that the organization holds or is that just me, you know, kind of with some random thoughts? No, I think that's actually a really good way of explaining it. So kind of two quick responses to that. The first one is absolutely, right, a core tenet of what we do is building capacity to use technologies within the communities that we serve.

So it's not my aim to be colonial about the use of technology, right, despite the British accent. It's my aim to bring communities the ability, right, to build and deploy those technologies that they need to solve the problems that they understand for themselves. And that's why we always build the technology with our communities involved. And it's why we always hand off those technologies to the communities to be able to run them and operate them themselves. And the policies have to also follow that same template. The other aspect of this is that with any advanced technology, right, you of course, have great potential for change and to scale that change quickly. Now, what I've learned in the nonprofit sector over the last 10 years, and I'd say that I still hold very much a private sector point of view when I think about these topics.

And I think I hold quite a kind of economically driven view of how we should build these solutions is that humanitarian aid in kind of the classical sense of the word is actually what's been holding us back in our response to major crises around the world. and I see it continuously being a stumbling block in our ability to actually build resilience in the communities that are having the toughest challenges today. So actually, as an organization, we're pushing back quite hard against aid being the cornerstone of response towards building the resilience within the communities

so that the communities can drive their own response, select what the best way to react is, not have an economic fallout as a result of disasters to the extent possible, and therefore use technology as a stabilizing strata within that response. It's a very different way of thinking, but we could go on for hours and hours talking about humanitarian aid and obviously the Ukrainian context. To put it lightly and shortly, I would say that a vast amount of money

has been wasted by Western NGOs in Ukraine before that money ever even reached Ukraine. And the things that they did in Ukraine are well understood by the local communities to not have been useful within the Ukrainian context. Anything from Red Cross handing out Coca-Cola to IRC not actually spending the bulk of its money in Ukraine. So, you know, I would say that we have an opportunity

with technology to really rethink a lot of the ways in which we get involved around the world. And being a U.S.-based organization, we also have to be very mindful of the reputation that the U.S. has getting involved in places around the world. And I think that being community-driven and community-first is a big step forward from where we have been in the past. You know, James, one thing I wanted to dive into a little bit deeper there

is you talked about how, you know, you can using this technology, using artificial intelligence, as a stabilizing force. But I think, you know, there's different ways that you can view artificial intelligence, right? There's obviously, I think, the tremendous upside and the optimism around how it can change communities and cities and countries. But then there's, you know, the other side, too. So can we talk a little bit about, you know, whether you want to talk personally or

through the lens of, you know, AI for good? But when we talk about the impact of artificial intelligence on the labor market, market. When we talk about, you know, I think everyone, regardless of where you are, has a healthy either respect or an outlook on, okay, will AI come and disrupt our community, our country, or even our personal jobs? What's your thought on that and kind of the balance between using it as a stabilizing force versus it can be economically disruptive? Okay. So we, yeah, that's a, again, it's a great question. And, and, uh, We could dive into it head first and never come out again.

What I will start with is I'll say that we are living through a data-driven revolution in terms of how we operate as society. And that's visible through every facet of our lives, right? It's visible from the way the governments run political campaigns. It's visible from the way we do work, right? We work a lot more digitally-natively today than we did even 10 years ago, 20 years. years ago. The level of computation availability in society is massive compared to, you know, five years ago, ten years ago. And that's propelling a lot of the advances in algorithmic capabilities, and it's allowing all the cool stuff that we're seeing, right, with these large language

models and transformer-based technologies in society. It's also driving a lot of worries about what it means to be able to use data, right, like it's tap water. And it's going to, I think, lead to a lot of a reckoning in our society about what we really want that future to look like as a data-driven future, right? We have risks. We have risks such as the risks of identity theft, right? And ultimately, identity theft risk means deepfakes. It means kind of the whole gamut.

of issues that come with that. We have risks when it comes to targeting, right, being able to very, very quickly identify how people are, how they act, what their likely behaviors will be and how we can influence them. And, you know, I would say that these are not new challenges in society, but there are certainly challenges which we are going to exacerbate to the last possible mile. And we need to learn kind of how we want to deal with that. We need to come up with policy. that affects the dynamics. And ultimately, I think, you know, policy is about dynamics, right? The dynamics of the situation and the incentives that we want.

So the policies that we put in place may not be different from what we would put in place without AI. However, AI is forcing us to really consider what we want as society in a way that we could kind of kick the can down the road before, right? Scale is not the issue so much as the dynamics. that we're trying to attack with the policy and with our decisions. To look at the labor market quickly, because you mentioned the labor market, and I don't want to kind of leave that unaddressed completely.

But together with my colleagues on more of the academic side, economic and kind of AI side, we did publish last year a very detailed, and what I think is probably the flagship paper at the moment in the academic community that kind of understands and looks at the dynamics of AI in, industry and in society. And right now, what we're still seeing is the dynamics are very favorable to human labor, right? We're yet to see a big shift in the structure of human labor because of technology. However, what we are starting to see is that humans are adapting, right? And as I mentioned, it's creeping into every aspect of our work. But humans are adapting, right? Governments are starting to

build very, very good reskilling programs in certain areas, not everywhere. It is unlikely that we're going to see a hollowing out of the labor market because of technology anytime soon, but we will see sectoral refocusing. We will see large swaves of certain sectors quickly shifting to a technology enabled stance, and that will require that we invest heavily in giving people new opportunities. It will require that we invest heavily in education, right? And we, that we get our high schoolers and our university graduates prepared for a future, which will be even more heavily technologically focused than it has been in the last decade. Now, if we can't do that in the US and if we can't do that in Europe,

then, you know, where would we be able to do it? Again, I'm not trying to take a Western stance necessarily for this podcast, but I'm guessing most of the audiences in the US. in Canada and maybe in Western Europe. And we have the innovation capacity to take care of these challenges. These are not challenges that are insurmountable. But we just need to be mindful and make sure that we're being proactive in addressing them. And I think the thing that I'm always even thinking about personally is the dynamics.

The dynamics I think are sometimes hard to understand and hard times to balance. because, yes, like I'd say the majority of our audience listening is, you know, from the U.S., but then, yes, we do have, you know, big audiences in other countries, you know, specifically, you know, in Europe that maybe have a different outlook toward technology. But, you know, one thing, James, I wanted to, you know, dive into a little deeper is, you know, when when I asked about, you know, the labor market, you did bring up policy, right? And I know this is difficult, right, because you all do work throughout, throughout the world. But at what point should that, you know, policy or government overlap with our jobs, with protecting the labor market, right? So I think the EU, you know, with their AI Act, has been a little more, I guess,

protective of the labor market, one could say, or maybe not. And then in the U.S., it's been a much more hands-off approach, at least from a legislative perspective, you know, really with only an executive order and some informal governing. So what's your take on kind of finding that balance, right, between this, you know, yes, this Western U.S. free market enterprise versus protecting the labor market because, yeah, AI can be disruptive. Well, the role of government in this is to smooth the transition, right, and ensure that the right resources are in place so that it causes kind of net positive outcomes for society, right?

So you can have multiple views on what's going to work best in order to achieve that outcome, right? You can believe that the market will get there by itself, right? And the companies operating will know where to invest in order to kind of create the resources that they need and ultimately shift the playing field in the direction that's right or you can believe that you need to be a bit more protectionist towards people so that you don't have kind of too much of a jarring shift in employment now europe has always taken the approach of more protections for employees right and so it's not surprising at all that there would be a that similar kind of dynamic playing out now and that Europe would be leading in trying to legislate and regulate certain aspects of the rise of

technology within the labor market and within our economy. What's going to work best? That depends a lot upon kind of how consumers react and kind of how employees react and on the pace of technological shift. And I think it's not very useful to make predictions about that. But what I would say is it's actually very interesting and probably useful. to be able to see both approaches play out, at least in the short term. And I think the US is receptive also to seeing what's working around the world and to adopting and adapting to that reality as it takes place.

Right. We're seeing a very interesting set of arguments taking place now around copyright law in the US. Right. And the US pioneered effective copyright protection, right, when it comes to industrial revolution. and kind of that shaped a lot of American innovation potential over the kind of next 200 years. So it wouldn't surprise me at all for the US to adopt some level of regulation that still can promote innovation over the long term. Now, remember, sometimes protectionism, like copyright law,

is actually there to encourage innovation, not to stifle it or to slow it down. So we shouldn't always think about regulation as something that is necessarily a, like a bottle stop, right? Sometimes it can it can be a way of creating and ultimately, ultimately accelerating a more structured process. Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI Assistant, now live in the Adobe Firefly app, the all-in-one creative AI studio. Powered by Adobe's Creative Agent, Firefly AI Assistant lets you start with your vision, Just describe what you want and shape the outcome as it takes form with the assistant.

The assistant orchestrates multi-step workflows, drawing on 60 plus pro-grade tools across Adobe Creative Cloud apps, including Photoshop, Illustrator Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible, so you can refine, redirect, or take over at any time.

You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly.adobie.com. Is there any concern, you know, especially, even if we were just to draw the parallel, you know, between U.S. and the EU, is there concern, you know, is that just two just starkly different approaches, what that could mean for the rest of the world, right? Because I'm very interested, you know, with, you know, AI for good, you all have been around for, you know, 10 years, right?

Or, you know, almost 10 years. And I think the conversation is changing around AI. So, you know, now that you do have, it seems like all of this momentum, you know, happening now. Is there concern with two just such different approaches and what that might mean for everyone else? Well, to take a bland and silly example, but just to kind of open up the conversation, the U.S. and Italy have completely different regulation as to cheese imports. However, the fact that these two big cheese economies do very different things when it comes to which cheese, has come into the country and what the tariff structure looks like doesn't actually cause massive

problems on a global economic level. I would say that, you know, each country and each block and each region, right, is going to set economic policy according to the behaviors and the expectations of the actors, the entities that are acting economically within that sphere. The U.S. is taking a very different tack. The Britain is taking a very different tack. The EU is taking a different tack. And by the way, African Union and South American countries are also going in their own direction. Japan has a very interesting set of approaches to regulation of AI, which are being drafted. Now, you know, does that mean they're going to come to log ahead? Not necessarily, right? However, you know, it is an opportunity to learn, as I said before.

Now, one thing I will mention quickly while we're at it, because we're on very close to this topic, is we launched last year what I think is the only non-profit-driven AI audit program for the private sector. Now, why would we do that? Well, first of all, it's to help organizations to develop algorithms that take into account kind of a human-centric approach, and also for those organizations to be able to say and actually have done a lot of thinking about how their technology, their data use, impacts their stakeholders and the people who use their products. The second part of it is actually that we want to help organizations to figure out what type of regulations, what type of guardrails would actually be useful in different contexts,

and by that create essentially a wealth of information at the intersection of companies and the government to be able to have a reasonable conversation about what we should do going forward, as a united set of stakeholders that are all interested in maximizing innovation, right? Because we want the US economy to be strong. We want to invent. We want to create jobs. We want to create new companies and new ways of doing things. But we also want to do it with the maximum number of wealthy, well-educated consumers,

which is going to maximize our economic potential over the long term and give the next generation the best chance at living high-quality lives. And so, you know, you can see this as being our attempt at getting at that wedge in between government and the private sector so that we can act as a conduit for, you know, putting in reasonable legislation if legislation is necessary, right? And the if is really what we're after. Like what and if should we be, should we, when should we be getting involved and how, right? That's the question. Yeah. And I think, I think it's something. I'm even thinking a lot more, right? Like I talk to experts literally every day. I read about AI.

And I think now more than ever I have my eyes and my focus set on, okay, what happens when this happens? What happens when AI is maybe more powerful than we think, right? And not even talking about, you know, AGI, but, you know, what happens when we start to see agents, right? Because that's what a lot of companies now are working on. And what happens when we do start to see, you know, kind of what we were talking about earlier, you know, when, you know, reskilling in certain organizations or sectoral refocusing, like you mentioned? What kind of safety nets should we be building? I mean, should we be having conversations about universal basic, you know, universal basic income?

Should we be having conversations around, you know, government assistance for, you know, affected areas? where should the conversation go on that? And, you know, is that a private? Is it a public? Is it a government? Like, who should be involved in those conversations? So I think that most of the people who have been pioneering discussions about what the right economic shifts should be because of AI are not qualified really as economists to be thinking about the dynamics of the economic system that we're in. And I think we need to kind of re-engage with economists and policy makers, rather than basically putting tech executives right on under the limelight and asking them or people who developed certain aspects of new AI technologies. You know, what do they think

society should look like, right? What society should look like is a conversation that we all need to be involved in. It's a conversation that involves thinking, kind of economically, strategically, and from an incentive kind of basis. So I would say that, again, there are many ways that you can run society. There are many different economic approaches that you can take. Historically, the question about universal basic income is not just one related to technology. It's one that you can choose, right, in a welfare state, right, to pursue under a variety of circumstances. Universal basic income was not a necessary component during previous kind of large economic transformations and disruptions.

However, that doesn't make it something that you discount and throw out as a potential policy instrument. A lot of it depends also on how you intend over the long term to promote innovation, right? Again, economic growth is driven by transformation. And if you don't have that transformation and if you don't kind of create, the innovation capital, then innovation, or economic growth will stagnate, right? Your fiscal entries will stagnate, and you will end up in a regressive economy,

which doesn't really do very much. And that's not good for anybody because kind of our entire capitalist system in the US is built around the fact that we're encouraging growth and innovation. So UBI may not be the best approach in the US, right, because it may stifle innovation. And that's kind of a main engine.

Again, in the EU, there is more of a footing towards kind of growing that innovation capacity, especially since Britain left the European Union. The EU has been trying to reposition itself as an engine for growth. Right. And by the way, Ukraine long term plays into that as well, because Ukraine has a huge technical kind of labor force, right? lower marginal labor costs, a lot of innovation capacity. And so all of these conversations kind of have a confluence right now.

Again, it's not about universal basic income because we're going to eradicate human employment. We're nowhere near eradicating human employment. However, that doesn't mean that UBI is not something that we want to be discussing in broader terms, in terms of how we build effective welfare states. By the way, in the US, UBI would be very difficult simply because of our entrenched healthcare system, simply because of how we run our education system at state level.

It's much more complicated than just saying we need to give money to a certain segment of the population every month. It's a kind of coherent economic strategy across the whole of society, and it should not be driven primarily by, by fears or projections about technology change. It should be driven by kind of principled decision-making

about the kind of society that we want to build over the long term. And we're nowhere near having those conversations yet, unfortunately. Yeah. And James, this has been such an insightful conversation. You know, we've been able to touch on so many things from, you know, changes in the labor markets to how and when maybe government should be involved. when it comes to, you know, artificial intelligence and creating social safety nets. But maybe as we wrap up, what is maybe your one important takeaway that you want people

to hear today, specifically when it comes to how artificial intelligence is impacting and will continue to impact society? So for me, the biggest topic today is economic and community resilience. and that's why we talk about kind of community resilience being at the core of technology adoption. And as a result, building the capacity of our local communities to use technology effectively, to be knowledgeable about technology, and to choose how that technology gets integrated into their everyday lives is crucially important. So from that perspective, strengthening, you know, tech-based education, right strengthening the public's ability to understand the changes that are taking place

and also again building that capacity at the very local level to start businesses and innovate not to wait on big tech to do the innovation for us but to have innovation really take place at the grassroots level i think that's what's going to actually enable our economy to weather any set of transformations, right? However fundamental they may seem when we discuss them now, but it's really bringing it down to that hyper-local context and allowing communities to have that voice and those capabilities and those resources, which is going to keep us able to transform and innovate and build, right, which is, by the way, what has made America so strong in the past. that's so much so much good content here i i can't wait for everyone to be able to to you know

hear this conversation and to even read about it more so james hodson CEO of ai for good foundation james thank you so much for joining the everyday AI show we really appreciate it thank you jordan and hey as a reminder there's a lot of different initiatives that james mention some different pieces of the work that they're doing throughout the world. So make sure if you haven't already to subscribe to our daily newsletter at your EverydayAI.com, we're going to be recapping this conversation and even getting to things that we didn't have the time to touch on. So make sure you check that out in the newsletter.

So thank you for joining us. And we hope to see you back for more Everyday AI. Thanks, y'all. Meet Firefly AI Assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio. Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop, Premiere Express, and more in one conversational interface.

You direct the outcome while the assistant accelerates execution. Stand control with the ability to step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit Your EverydayAI.com and sign up to our daily newsletter so you don't get left behind.

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