Ep 224: AI and its Impact on Society – How it might look

Artificial Intelligence: Steering the Tide of Global Economic and Social Impact

The transformative force of Artificial Intelligence (AI) is being harnessed to foster global development. A pioneering approach leverages the power of communities to use technology as a problem-solving tool, going against the grain of traditional humanitarian aid models. The potential of technology to redefine the frameworks of international involvement avoids economic fallout, orienting towards sustainability and self-reliance.

Artificial Intelligence and the Labor Market: Data-Driven Revolution

AI is recalibrating the labor market dynamics and the structure of society. Propelling a data-driven revolution, it presents both risks and challenges. It underscores the acute need for well-informed policies and decision-making strategies to effectively navigate this rapidly evolving landscape. While some concerns are raised about potential impact on human labor, current dynamics underscore the need for rescaling programs and investments in new opportunities, promoting a promising future for the workforce.

Economic Safety Nets in an AI-Driven Economy

Architecting safety nets for AI-induced economic shifts is crucial. Concepts such as universal basic income (UBI) and government assistance are gaining traction as potential shields against abrupt changes. However, the viability of these initiatives varies across regions due to differing socio-economic structures and policy landscapes. The conversation around such economic aids should involve economists, policymakers, and other stakeholders to devise solutions best suited to region-specific challenges and opportunities.

Community Resilience and Tech Education: Building Capacity

Community resilience and capacity-building initiatives in tech education and innovation hold the key to managing AI-driven economic changes. A balanced approach includes investing heavily in education to prepare future generations for a more technology-centric future. It is critical to consider differing approaches to policy and government involvement in labor market safeguards against technological advancements. Different regions may have distinct strategies to ensure smooth transitions and positive societal outcomes.

Human-Centric Approach to AI

The role of AI in business operations should be evaluated with a human-centric lens. Considering the impact of their technology on all stakeholders enables companies to use AI responsibly and ethically. Implementing transparency frameworks like non-profit AI audit programs can foster constructive dialogues between businesses and the government to determine the need for legislation.

Preparing for Advanced AI: Reskilling and Refocusing

The advancing wave of AI encourages revisiting skill development strategies and refocusing labor market dynamics. Innovations in AI necessitate a robust approach towards designing learning experiences, equipping individuals with skills and knowledge applicable in an AI-driven world.

Harnessing AI responsibly and seeing it as an opportunity rather than a threat requires a strategic shift in perspectives from business owners and decision-makers. As AI continues to reshape the socio-economic landscape, ongoing dialogues surrounding policy implementation, education, and capacity-building initiatives are essential to take full advantage of the opportunities AI brings. The era of Everyday AI signifies innovation, growth, and an ethical approach to leveraging technology.

Topics Covered in This Episode

1. Role of AI in Global Development
2. Community-Driven Development and AI
3.  AI's Impact on Labor Market
4. Government Role in AI Implementation
5. Navigating AI-Driven Economic Changes

Podcast Transcript

Jordan Wilson [00:00:18]:
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 the way 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 Wilson, and I'm the host of Everyday AI. We're a daily livestream, 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.

Jordan Wilson [00:01:00]:
If 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 the challenges of being a livestream. Right? Is 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 prerecorded. But with that, don't worry. I'll probably still be in the, in the comments answering questions. So if you have any questions, feel free to still ask them.

Jordan Wilson [00:01:34]:
But with that, I'm extremely excited to bring on our guests for today's show. So please help me in welcoming James Hudson, the CEO of AI For Good Foundation. James, thank you so much for joining us.

James Hodson [00:01:48]:
Thank you, Jordan. It's a pleasure. Real pleasure to be here.

Jordan Wilson [00:01:52]:
Alright. 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?

James Hodson [00:02:00]:
Absolutely. And I guess, you know, just to head it off, I mean, the nice thing about it being a prerecorded show is I don't need to worry about, you know, saying the wrong thing. So, it's all all good. Right? So AI For Good Foundation is about 10 years old. It's a nonprofit based out of California, but operating around the world. As a nonprofit, our mission has been and and 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 from our name, and we try to think about how we can strength strengthen that society, how we can increase the resilience of that society through 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.

James Hodson [00:03:08]:
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 in the US and Canada, in in Europe in order to improve the ways that governments interact with technology and the way that companies use technology.

Jordan Wilson [00:03:29]:
And 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've I follow your guys' work, but maybe a lot of people don't. But, you have a large reach, you you know, both people on your team, board members, etcetera. 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 and how just this AI for good even works, you know, as a as a mechanism, for for using AI for good.

James Hodson [00:04:10]:
That's a fantastic and fair question, I I would say. So we have two aspects to how we operate. Right? 1 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 we talk about human first technology. The other side is we are a bit of a global advocacy network.

James Hodson [00:04:33]:
Right? We were born out of the academic research community and the economic and policy making community. And as a result of that, we have a fairly big reach around the world as you mentioned. Now the the organization itself is around 70 full time staff around the world, and that staff kind of shifts around as we as we build stuff. We're often referred to as kind of a SWAT team. SWAT team that comes in, helps governments, helps, you know, organizations to change, and then kind of builds that capacity, right, to do good, but doesn't we don't try to stick around forever. Right? We realize as a nonprofit, our mission is to experiment, 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 or 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 knowing our place and and creating that innovation potential.

Jordan Wilson [00:05:50]:
You know, I love I love how you said that almost like a 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 US. And, yeah, like, when you start in with your mission, you always hope that you aren't needed. Right? You you hope that you can go in and 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 you know, if your mission is successful. Right? So maybe you can either walk us through, a 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 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 to show, for your work in these areas?

James Hodson [00:06:43]:
Okay. We have a variety of programs around the world. Right? And and it I think it 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 kind of, global organizations, including a 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.

James Hodson [00:07:41]:
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 LifeForce 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.

James Hodson [00:09:00]:
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 2 anecdotes, and, obviously, we can go into much more detail than that.

Jordan Wilson [00:09:19]:
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, etcetera. Should we be looking at artificial intelligence, not in that same path? Because I I I know it's not an apples to apples comparison, but is there also this this this concept or this thought in your organization where the rest of the world needs AI for for economic development? In the same way, they may need, you know, access to clean water, access to high quality education. Is that a a a train of thought that the organization holds, or is that just me, you know, kind of with with some random thoughts?

James Hodson [00:10:09]:
No. I I think that's actually a really good way of of explaining of explaining it. So kind of 2 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.

James Hodson [00:11:01]:
The other aspect of this is that, you know, with with any kind of 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 and I'd say that I still hold very much a private sector point of view when I think about these these topics, and I I think I hold quite a kinda economically driven view of how we should build, these solutions, is that humanitarian aid in kind of the classical sense of 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, you know, we could go on for hours and hours talking about humanitarian aid and, obviously, the Ukrainian context. You know, 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. You know, anything from Red Cross handing out Coca Cola to IRC not actually spending the bulk of its money in Ukraine. So, you know, I 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.

James Hodson [00:13:08]:
And, you know, being a US based organization, we also have to be very mindful of the reputation that the US has getting involved in places around the world, and I think that being community driven and community first is a big step forward from from where we have been in in the past.

Jordan Wilson [00:13:25]:
You know, James, one thing I wanted to dive into a little bit deeper there is is you talked about how, you know, you can using this this technology, using artificial intelligence as a stabilizing force. But I think, you know, there's 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 and cities and countries, but then there's, you know, the other side too. So can we talk a little bit about, you know, what you're whether you wanna talk personally or or through the through the lens of, you you know, AI for good? But when we talk about the impact of artificial intelligence on the labor market, when we talk about, you know, I I think everyone, regardless of where you are, has a healthy either, respect or, an outlook on, okay, will AI come and and disrupt our our community, our country, or even our our personal jobs? What's your thought on that and and kind of the balance between using it as a stabilizing force versus it can be economically disruptive?

James Hodson [00:14:30]:
So we yeah. That that's a again, it's a great question, and and, 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 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 that 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 ago. The level of computation availability in society is massive compared to, you know, 5 years ago, 10 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.

James Hodson [00:15:28]:
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 a reckoning in our society about what we really want that future to look like was a data driven future. Right? We have risks. We have risks such as the risks of, identity theft. Right? And ultimate identity theft risk means deep fakes. It means kind of the whole gamut of 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.

James Hodson [00:16:13]:
And, you know, I would I would say that these are not new challenges in society, but they're certainly challenges that we 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 it 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 with the policy and with our with our decisions.

James Hodson [00:17:04]:
To look at the labor market quickly, because you mentioned the 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 kinda 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 getting it's creeping into every aspect of our of our work, but humans are adapting. Right? Governments are starting to build very, very good rescaling programs in certain areas, not everywhere. It is unlikely that we're gonna see a hollowing out of the labor market because of technology anytime soon, but we will see sectoral refocusing. We will see large swathes of certain sectors quickly shifting to a technology enabled stance, and that will require that we invest heavily in giving people new opportunities.

James Hodson [00:18:25]:
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 to do it? Right? 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 and Canada and and, maybe in in Western Europe. And, you know, 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 and make sure that we're being proactive in in addressing them.

Jordan Wilson [00:19:16]:
And 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 US, but then, yes, we do have, you know, big audiences in other countries, you know, specifically, you you know, in Europe that maybe have a different outlook toward technology. But, you you know, one thing, James, I wanted to, you know, dive into a little deeper is, you know, when when when I asked about, you know, the labor market, you did bring up policy. Right? And I know this is 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 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 US, 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.

Jordan Wilson [00:20:31]:
So what's what's your take on kind of finding that balance, right, between this this, you know, yes, this western US free market enterprise, versus protecting the labor market because, yeah, AI can be disruptive.

James Hodson [00:20:45]:
Well, the 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 gonna 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 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 what's gonna work best? That depends a lot upon kind of how consumers react and and kinda how employees react and on the pace of technological shift. And I 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.

James Hodson [00:22:22]:
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 kinda 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, ultimate ultimately accelerating a more structured process.

Jordan Wilson [00:23:26]:
Is there any concern, you know, especially even if we were just to draw the the parallel, you know, between US and and and the EU? Is their concern, you you know, is that just 2 just starkly different approaches, what that could mean for the rest of the world. Right? Because I'm I'm I'm very interested, you you know, with, you know, the 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 is changing, around AI. So, you know, now that you do have it, it seems like all of this momentum, you know, happening now. Is there concern with with 2 just such different approaches and what that might mean for for everyone else?

James Hodson [00:24:17]:
Well, you know, to take a bland and and silly example, but just to kind of open up the conversation, the US and, Italy have completely different regulation, as to cheese imports. However, the fact that these 2, you know, big cheese economies, do very different things when it comes to which cheeses come into the country and what the tariff structure looks like doesn't actually cause massive problems on a global economic level. I I would say that, you know, each country and each block and each region, right, is gonna set economic policy according to the behaviors and the expectations of the actors, the entities that are acting economically within that sphere. The US is taking a very different tack. Britain is taking a very different tack. The EU is taking a different tack. And by the way, African Union and and South American countries are also going in their own direction. You know, you know, does that mean they're gonna come to loggerheads? Not necessarily.

James Hodson [00:25:25]:
Right? However, you know, it is an opportunity to to learn, as I said before. Now one thing I will mention quickly while 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 nonprofit driven AI audit program for the private sector. Now why would we do that? Right? 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 gonna maximize our economic potential over the long term and give the next generation the best chance at living high quality lives.

James Hodson [00:27:06]:
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 is really what we're what we're after. Like, what and and if, should we be should we when when should we be getting involved and how? Right? That's the the question.

Jordan Wilson [00:27:33]:
Yeah. And I think I think it's something I'm even thinking a lot more. Right? Like, I I I talk to experts literally every day. I I read about AI. And I think now more than ever, I have my, you know, my 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 you know, what happens when we start to see agents. Right? Because that's what a lot of companies now are working on. And and what happens when we do start to see, you know, kind of, what what we were talking about earlier, you know, when, you know, reskilling in certain organizations or sectoral refocusing, like you mentioned.

Jordan Wilson [00:28:17]:
What what kind of safety nets should 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 where should the conversation go on that? And, you know, is that a private? Is it a is it a public? Is that a government? Like, who should be involved in those conversations?

James Hodson [00:28:45]:
So I think that, most of the people who have been pioneering discussions about what the right economic shift 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 reengage with economists and policy makers rather than basically putting tech executives, right, on under the limelight and asking them or people who develop 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. Right? Historically, the question about universal basic income is not just one related to technology. Right? It's one that you can choose, right, in a welfare state, right, to pursue under a variety of circumstances.

James Hodson [00:30:01]:
Right? 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, you know, 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 in the US is built around the fact that we're encouraging growth and innovation. Right? So UBI may not be the best approach in the US, right, because it may stifle innovation, and and that's kind of a main engine.

James Hodson [00:31:06]:
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 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 confluence right now. It again, it's not about, you know, 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 wanna be discussing in broader terms in terms of how we build effective welfare states.

James Hodson [00:31:59]:
Right? By the way, in the US, UBI would be very difficult simply because of our entrenched health care system. Right? Simply because of how we run our education system kind of at state level. It's it's much more complicated than just saying we need to give money to a certain, you know, 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, kind of, fears or projections about technology change. It should be driven by, kind of principled decision making about the kind of society that we wanna build over the long term. Right? And we're nowhere near having those conversations yet, unfortunately.

Jordan Wilson [00:32:41]:
Yeah. And 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 and when maybe government should be involved when it comes to, you know, artificial intelligence and and creating social safety nets. But maybe as as we wrap up, what is maybe your one important takeaway that you want people, to to hear today, specifically when it comes to how artificial intelligence is impacting and will continue to impact society?

James Hodson [00:33:17]:
So for me, the 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 gonna 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 hyperlocal context and allowing communities to have that voice and those capabilities and those resources, which is gonna keep us able to transform and innovate and and, build. Right? Which is, by the way, what, you know, has made America so strong in in the past.

Jordan Wilson [00:34:49]:
That's so much so much good content here. I 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 Hodgson, CEO of AI For Good Foundation. James, thank you so much for joining the Everyday AI Show. We really appreciate it.

James Hodson [00:35:08]:
Thank you, Jordan.

Jordan Wilson [00:35:09]:
And, hey, as a reminder, there's a lot of different initiatives that James mentioned, 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 everyday ai.com. We're gonna 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, in the newsletter. So thank you for joining us, and we hope to see you back for more everyday AI. Thanks y'all.

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