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Listeners welcome back to this episode of the HumAIn podcast. I’m your host, David Yakobovitch, and today we have two special guests from the Partnership on AI³. We have both Katya Klinova¹ and B Cavello², who are involved with research and AI labor, and the economy.
And what we all know this year is everything AI, labor, and the economy has been nothing but normal. It’s been a very unusual year. So it’s going to be a fantastic episode to hear about the research and work that they’re both working on. Katya and B, thanks for joining us on the show.
What a pleasure to be here. Thank you, David.
Well, as we’re wrapping up 2020 very quickly, we’re looking forward to 2021. And that means a lot of fresh breaths of air and what is the future of life and business and work. And one of the hot topics we’ve seen this year has been about AI and the future of work, whether it’s a major organization funding with technology or with business ideas. There’s so much going on. So love to hear from both of you, what are you seeing around this topic of artificial intelligence and the future of work?
Let me start. And then I would love, also, to go over to B. When the year got rolling, and then, of course, the major event that happened in everyone’s life was COVID, there was a moment in which I personally thought, okay, now people are going to stop worrying about AI and its impact on labor and labor market, but that was wrong. And pretty soon people realized that COVID and the lockdown and the economic fallout that ensued, really, only exacerbated the trends that have already been in place.
And that AI and technological change have been contributing to in terms of the polarization of labor market skill bias, being introduced into the labor market, because what we saw as the pandemic is that people with college degrees, people who have the opportunity to work remotely have been hit economically much less comparatively with people who are not able to work remotely. And that’s disproportionately people who did not have access to higher education and college degrees. So it’s, again, the very same trends that were already being surveyed by AI and technological change that now only got deeper with COVID.
And to add to that, there’s just such an interesting dynamic whenever we talk about the future of anything, but especially the future of work, kind of thinking about whose work counts as the future of work. Maybe the future of dentistry is very different from the future of web design, or call centers or any other thing.
So it’s really interesting to see whose work is considered in these conversations. And backing up even before COVID, a lot of the future of work conversations centered around being able to be remote, being able to be distributed, which was very interesting because a lot of companies prior to the pandemic actually were pushing back on that. I used to work at IBM, which was undergoing a major process of actually bringing people back into the workplace.
So it’s something. There’s like the pointy skinny, high heeled shoe with the thick wedge high heel shoe. And we see these trends come and go. Perhaps this time around the kind of distributed work setup is going to be the new normal, but some of the things that really come out of those trends toward distribution are also more of this kind of on-demand work or gig work, as it’s sometimes framed, in terms of seeing a lot more folks gravitating toward, or seeking out work where they don’t have necessarily the traditional formal employment, but looking to drive in a ride hailing service or do digital on-demand work.
And so that that’s a trend that also has been exacerbated by the pandemic. We see a lot of formal sector jobs falling away as a result of precautions taken to manage the virus. But as a result of this, we also see a proliferation in oftentimes lower wage on-demand or gig work playing out.
And there’s a lot of exciting stuff to talk about in the future of work, too. I don’t mean to just be a naysayer here. There’s a lot of really exciting stuff happening around. I’m really a big proponent of all of these amazing digital communication technologies that we have new ways of socializing and interacting with each other.
Recognized folks in the disability activism community have been saying for a long time that we need more remote and distributed work options. And so, in many ways, there are many, several silver linings to take from this trend that we’re seeing playing out, but there are also a lot of highly disruptive technologies in the space of robotics and information technology, especially in the AI space, that could lead to possible exciting futures, but they could also lead to some less ideal outcomes.
And that’s really something that the work that we’re doing is really focused on, is how we can think about the quality of work that people have, as people trend toward these more distributed on-demand work options? While also thinking about the availability of work, especially in a pandemic, where jobs are so front of mind for so many people. How do we think concretely about making sure that as technologists, as innovators, as people paving the way toward that #futureofwork, we’re thinking about a work world that includes everyone.
And a work world that includes everyone is all about simulations, what is possible and what is probable. And when we think back through 2020 as the year, that could be and the year that was COVID was not predicted by the actuaries. COVID was not predicted by most of the AIs, but now that it has come and it is here, the models have been disrupted.
They’ve changed. There’s new inputs, there’s new drivers. And the new simulation says, well, there was a COVID 19, but could there be a COVID forever? And that’s how do you work with quality and availability in this world? So many companies have gone digital-first, and we’ve heard this from leading big tech companies in Silicon Valley through the real estate leaders in New York City.
Some companies have said where in-person first and post #COVID, we are in-person first and others have said, we’re going all digital. Is this stark reality of having such a polarization of in-person versus digital, is this the right way to think about it? Or has society? It’s just an election year. We just polarize everything. And perhaps it’s more what B and Katya you’re hinting at. We’re moving less necessarily towards just a remote-only world, but a distributed or maybe a hybrid world.
There is definitely more polarization and it’s more acute than before, and it is probably here to stay. Because I don’t think COVID is going to end overnight and it’s not even in terms of, at the time horizon, but the transition back to normalcy is probably going to be gradual. And that normalcy might be, even if it’s not for healthcare concern reasons, but it might still be different than pre COVID because some people might have found out that they’re just as productive working from home, and they save time commuting. So some companies might have discovered that they’re saving a lot of money on the office space. So they might choose, even if it’s not because of healthcare considerations, they might choose to stay remote. And that might become more of a norm.
So that in some sense, might be positive, might be seen positively. Because it creates choice for people, but at the same time, if there is more expectation around the needs to be connected and to be online and to have the setup at your home, both in terms of time quietness, not having disruptions and quality of your connection. Well, it’s your equipment to be able to access economic opportunities that deepens and exacerbates digital divide, and it has already become this COVID, but it might stay and more important thing for us to tackle because as half the world’s remain so flying, they’re essentially cut out of this access to jobs.
And , what you were talking about in terms of availability of jobs and access to, and the quality of jobs is in some sense, it doesn’t even matter what the quality is if people cannot even access the jobs that increasingly are now online.
There might be some really great jobs. In the early 2000’s, everyone was excited about the beanbag chairs and the provided lunch and all of these great things available to the scooters that tech workers zoom around on. But if those jobs are only available to people in very special circumstances, you have reliable internet access, you have the home environment that is really conducive to doing that type of work. We see a whole new level of disparity across the board. The office, the #workplace is in some ways a leveler, in that everyone has access to the same coffee machine, the same conference room, the same equipment, but as more of our work is distributed, that might not be the case.
And some might say, Oh, well, that’s fine, we’re going to have automation taking place. We’re going to have more distributed work patterns take place. And what that’ll mean is greater flexibility for workers, it’ll mean people more in control of their environment, and some jobs are going to get automated, but it’s okay. Because it’ll present a net good. There’s going to be higher productivity. There’s going to be more production as a result of automation. We can do things faster, cheaper, better. But what we’re seeing is that some of those trends that we’ve seen in the past that looked like these sure bets in terms of the ways that technology and innovation affect our economies actually might not hold in this situation.
And Katya has really highlighted really well some of the ways in which those extrapolations, those ideas about what the future of work looks like, and how that sense of a rising tide lifting all boats might not actually carry over into the world of AI and into the work that we’re seeing take place, especially in light of the global pandemic.
Now in a world where the pandemic did not occur, if we were living in an alternate reality, distortion field, perhaps we would have seen more of these net gains, and perhaps we still will see the net gains. We just don’t know yet where technology is moving at its pace. I know in the late part of 2020, there’s been talks that Moore’s law is now displaced by a new law.
Actually, this new law is based on the founder of NVIDIA. It’s about that you can speed greater than a twice increase every year. In fact, AI has gone, some would say, more than 200 or 300 times acceleration in the last 10 years. And that’s all based on what we’re seeing with companies like NVIDIA and ARM and other large chip makers that are using AI to expand technology. So there’s definitely a net gain in compute, though the big question remains, where does it go down the line? And if it’s not leading to jobs, what is the future of work getting wrong? What is it overlooking?
And, it’s so interesting, the chip space in particular, like reality is in some ways. Moore’s law can’t keep up with physics, the size of transistors, the size of the connections that are being made are actually running into physical limits.
They use certain wavelengths of light to actually build these different pathways. And we’re getting to the scale of nanometers where you can build a filter, if you will, that can refract light that precisely. So in some ways it’s not a surprise that we’re running into the limits of Moore’s law and coming up with other laws. But it’s also the case that, just as you mentioned, there is a really interesting trend around how the incredible speed ups and capacity that we’ve seen in what technology can do doesn’t necessarily translate into shared prosperity for everyone. And I do want to point out one thing, even if I’m probably guilty of this myself, but there’s this habit that we have when we talk about technology, where we say, technology will do this, instead of saying, technologists will do that.
Where we anthropomorphize technology as though it is this thing, this unstoppable force that has a mind of its own and is on this path that sometimes downplays the role that those in the technology space can actually play in shaping where technology heads and what technology will do in the future, so as we think that there is this trend that we’re seeing, which is certainly happening, I also want to shine a spotlight on the role that we human beings are playing in the process of facilitating the development of these technologies. And while we recognize that, we’re building incredibly fabulously capable #machines, really continue to interrogate to what end and to whose benefit those are being built.
I couldn’t agree more with that. Thank you, B. David, to your question of what does the future of work debate get wrong? It is way too obsessed with trying to predict what technology is going to do instead of asking what do we want technology to do for us? And what do we want technologists to do for the economy, for the labor market, for people in the labor market who are now pretty much expected to be left behind in this technological progression.
And so, you’re absolutely right that we’ve seen incredible gains in compute, but we haven’t seen them being translated into productivity growth at all. So we have not seen AI in the economic numbers yet. And so the question is, what kind of AI do we want? To see productivity growth and to see productivity growth being shared across the economy.
And not only be concentrated among a handful of companies, and really, a tiny sliver of a population that has certain kinds of advanced degrees and are able to benefit from this economy that has been created in front of us. So taking a more active stance in the future of work debate, and being more deliberate about choosing the direction of technological change when it comes to AI and other technologies as well is what is missing.
We have to be active. And you both said it perfectly that often we take the side seat and you wait to see technology change and then you get left behind. I get left behind, we get left behind. And that’s what, as a society we’ve seen throughout COVID not just in America, but this is a global pandemic, that education needs to change very quickly so that people can catch up and be part of the next wave of technology and the next wave of jobs. Our listeners of the show will know that I’ve scaled training for General Assembly and Galvanize, and now for a single store in the database industry. And what we see with all people, whether we are students in K through 12 or adult learners is everyone can learn.
Everyone wants to learn. Everyone’s willing to learn. Those everyone given the chance, that equal chance, learn. And that’s one of the areas that have not been solved from an economic perspective, especially in the pandemic because schools went online very quickly.
There were not all the resources for teachers to change and provide this remote-based learning. And we’ve seen additional students, especially in K through 12 fall behind when many of these students are the ones who could be learning AI today to be our next leaders, to work with different chips and to transform the new industries that don’t even exist yet. So the question I’ll ask is how can we be more active? What can we tell listeners here of the show to take a stance on the future of work?
That’s an excellent question. I’ll quickly comment on the educational outcomes and the importance of that. Again, I couldn’t agree more with the need to provide the equal chance to access education. It definitely is not active. It wasn’t equal before COVID, it is even more unequal right now, but I also want to caution, and this is to the point of where we would like listeners to take a stance.
I want to caution against using this #upskilling call to action or mantra as a cop-out for not thinking, and as an excuse for not thinking about the kind of burden and the kind of costs that technological change inflicts on society and on the workers and on the very people who might have very limited opportunity to access retraining, either because of time, money or anything. And again, when we’re talking about online education, not everyone is online. I want the world and the quality of online education. As you said, schools quickly went online. The results of that, the impact, potentially negative impact on the quality of educational outcomes is unknown.
This might be lifelong earnings lost for the kids who’ve missed by now two quarters of school or more. So we need to be realistic about our ability to quickly enough upskill everyone globally to keep pace with the technological advancement and think about how do we lower the barrier to entry, lower the barrier that’s needed in terms of skill requirements for people to be able to use these technologies to their economic advantage and extract economic value from that and be able to use it for their earning opportunities.
So in terms of stance, I would really love for society to expect that technologies are created by design to meet the society and its people where they are in terms of their skills and be creating gainful job opportunities and earning opportunities for the workforce that we have today and not the workforce that we wish we had in some ideal world. Then this is paraphrasing Ricardo Hausmann quote here.
It’s turning a lot of assumptions on its head here. When we think about the automation of the past, when we think about the industrial revolution and what we saw was skilled craftspeople, people who took years to really hone their trade. And we took those skilled craft people as an economy and we chopped them up into lots of little pieces and we turned them into assembly lines where you didn’t have to apprentice and spend years learning how to be a furniture maker. Suddenly you could walk in off the street one day and be handed a screwdriver and you just do your one little bit of that system.
And we took something that required a lot of skill and we actually turned it into something that required less. And I don’t mean to say that was a costless endeavor, but it transformed the playing field in terms of who could enter the workforce in a different way.
And what we’re seeing with AI is instead of, for the most part, taking really complex high-skilled things and breaking them down into little parts that anybody off the street could do. Instead, what we’re seeing is that all of those assembly line jobs that we chopped up previously are now being automated away.
So the people who previously could walk in off the street to do a job suddenly are being encountered with jobs that require you to have had many years of experience, and I’m curious about this. I genuinely don’t, this is my gap and understand, but I’m genuinely curious to what extent certain jobs that are considered as low skilled or high-skilled, which we recognize as the flawed language of economics, where we’re really what we’re referring to is educational attainment and how much pre-training someone has.
But there are incredibly high skilled jobs. I follow the Twitter account of a union that represents a lot of farm workers and they show these videos of people picking strawberries, just incredible rates, things that people do that frankly require so much skill to do well. But part of why those jobs are considered low scale in my mind is because you’re not actually expected to have mastered it before you walk up to the job. Whereas, when we expect someone to become an AI engineer or something like that, we’re expecting someone to have already done that training. There’s even this huge problem in the industry of all of these junior developers who have trouble getting jobs because you must have done React for 15 years.
I was like, well, that’s impossible. This doesn’t make any sense at all. And so we see these ridiculously high expectations for people entering the job market. So while this is within the context of the US where we have relatively high educational attainment, and I’m a huge believer of continuing education and access to education for everyone. But I also recognize the degree to which we’re somewhat shifting the burden on society rather than us learning in our jobs and #training people on the job.
There’s this increased expectation that, Oh, you should have learned all this stuff before you started. And anyone who doesn’t already have those skills, it’s on you to figure out, it’s on you to finance, it’s on you to figure out how you’re going to upskill yourself.
And that that’s a real difference in the pattern that we’re seeing from the past, where we chopped up these high skilled things into something that someone could walk in off the street and start doing to the trend that we’re seeing now, where we’re automating those jobs, but we’re increasingly creating new opportunities in a space where we expect you to have a wealth of experience in technology.
Now, I would love for everyone to be super technologically literate, just because, especially in a democratic country, you would hope that. To have an informed citizenry. You’re going to need people to understand these things that are increasingly shaping our entire, our global context.
However, at the same time, I also want to be real about where folks are coming from and what kind of burden is being placed on their shoulders. I benefited so much from my educational experience, but I didn’t have to juggle the amount of things that so many people, especially now during the pandemic are juggling. And so, when I think about where the future is headed, well, how could a technologist today think to himself what’s that skilled craftsperson mentality? What’s that furniture maker? What’s that thing that right now, today, does require someone to know a lot. And instead, break that down into easier taxes pieces.
And we see a proliferation of no code apps. We see a proliferation of tooling that hopefully trends in that direction, but that’s starting from already an incredibly advanced baseline. When you have to remember that we sit in such a privileged position, that we just presume literacy, for instance, like the assumption is, Oh, you’re going to be able to use a no-code app because you can read.
And I was having a conversation with someone just this week about how you design mobile interfaces for people, for whom their first device is a smartphone, that’s the first time they’ve ever accessed any sort of IT. And all of these presumptions, we have an underlined word means that it’s a link, like all these things that you just assume people are going to automatically know, that’s actually not true for a lot of folks.
So when we’re thinking about what does it mean to say someone can walk in off the street, or start wherever they are in and get access to this new economy, this new proliferation of things that we’re talking about, you really have to examine, well, what I am assuming from my cultural context and what are the things that are actually available to folks wherever they are.
And this burden about access and who takes it on, whether it’s society, the government or private public-partnership. We’ve started to see that evolve in the last few years. When I worked for Galvanize, we worked with the New York City Economic Development Corporation, NYCEDC, where we actually take new yorkers off the street who work in, we’ll call it low skilled jobs, making less than 40,000 american dollars a year and put them through a data analyst bootcamp to then come out, making at least 60 or 70,000 a year.
That’s considered the upskilling from a retail worker to a data analyst and that success in New York City translated to San Francisco with the Office of Economic and Workforce Development, where we’re also running that same program. And it’s not just Galvanize, it’s General Assembly, who I used to work for. And even the manufacturing companies. In New York City I’ve had the chance to talk a lot about labor.
Some of these topics that we’re talking about here. I’d love to invite you to New York in the post COVID world, because I sit on the manufacturing and industrial innovation council and we’re talking every month about jobs using CAD machines and drilling and saws and mechanical jobs that are vocational, as if building the furniture that you shared with before, B, that still relevant today. And these jobs don’t pay $40,000. They can actually pay close to six figures and be unionized to have benefits from society for each worker.
It’s so true. There’s so many, that’s that coming back to that question of whose jobs are considered the future, there are so many industries that are adapting with technology and so many really interesting and exciting ways. And what we want to encourage is there’s a world in which people who are doing a job can actually make decisions about what kinds of technologies might support them in doing that work.
Like most of us who’ve done work, know some things about our work that could be a little bit better, and many people actually recognize that the folks who are doing the job, the folks who are working in a factory making the furniture, so to speak, they have a real experience and perspective that spotlights that expertise in terms of how they could actually improve their working conditions and improve the output, the efficiency and the quality of their work.
But so often the benchmark that we hold our technology against is not these questions of what would make a worker’s job easier or their output better. But rather this question of, is it going to be able to perform at the level of a human? can we make a technology that will make a person, that will then be able to do whatever a person can do?
And there’s this sort of fetishization in the AI sphere. And it comes from a really beautiful, fascinating space. The scifi nerd in me does really wonder, Oh man, what would it be like to create other ways of thought, what would it be like to develop these thinking machines. But at the same time, there’s this distraction that comes from that when we’re so excited about building a #technology that can do what a person can do instead of lifting up the person who can do the thing already. If you want to, I sometimes joke that, if you want to make a bunch of general intelligences like we, human beings have been doing that for millennia, we’ve really gotten that one down. It’s probably going to be a baby boom, following this pandemic. We’ll see.
And there might be a lot more general intelligences entering the world. So this idea that the thing that we should be striving for is human level performance is sort of an interesting philosophy that he thinks sometimes prevents us from building really exciting technologies that aren’t about doing something that a human can do. But instead, thinking about what are the problems that humans have that we really wish we could solve and how can technology help us solve them?
Exactly. We have something like 8 billion humans, those humans now more than ever are in need of gainful jobs. And if we think of technological progress as the type of technological change that helps society prosper and overcome its economic condition, the last thing that we need to do is to be building machines that do what humans can already do better than them. And creates competition for those humans.
That’s not the right moment in history to be doing that, but it is the right moment in history to be creating technology that doesn’t come with skill bias attached, doesn’t come with extra, too burdensome, educational upskilling requirements attached to it, but allows people to have their productivity boosted and be more valued in the labor market.
So we need technological helpers, not technological displacers. And to get there, we have to make sure that every person is cared for or taken care of by society. And one thing that we’ve all experienced globally, as a result of COVID, is a displacement of income and resources.
In the previous election, we know one of the leading candidates coming up was Andrew Yang and he was the big proponent for universal basic income, saying we got to do this. We can start in New York. We can take it everywhere. And as if there was a prophecy, COVID happened and then Nancy Pelosi and our Commander in Chief said, Oh, we’re going to give out Universal Basic Income, although temporarily, to 25 million Americans. We’ll call it the pandemic unemployment payment program. We’ll give out $600 a week for a few months. And that program came and gone and what did you both see being leaders in the labor and economy markets? How did that work out and as a UBI experiment?
So obviously, this is still going to be analyzed more, and longer term effects are going to be analyzed. But it’s pretty obvious that some of the UBI scares, that people are just going to spend it all on alcohol and entertainment and hurt themselves with this extra money. They just resoundingly were proven wrong. And this money was meaningful to people. And I’m very pro UBI. And expanding social safeness is very important in all societies. I also do want us to not think about UBI as just this one universal answer to.
A silver bullet.
Exactly. The silver bullet and the panacea. When we are thinking about how we lead the society through the period of economic transition without generating pain for most of it, because you’ll be out, it’s just not going to be enough to address that. And UBI, despite its name, it’s never really been considered as a universal program, meaning it is not spanning the globe, but it’s not crossing the borders, but technology does whether we want it or not.
But once the technology is developed in one country that might be experiencing certain economic conditions and certain economic incentives around automation, then suddenly, it spills over around the globe and you fly into the Delhi Airport, then you see self check-in kiosks there. Even though there are a billion people who all need jobs, gainful jobs in the formal sector that are being eliminated by that technology.
So thinking about technology being global, but UBI not being global is a very important factor to consider when we measure up the viability of UBI to really address all of the concerns that are being brought about by the disruptions that can accompany technological deployment
And with where we’ve seen UBI today, going through its iterations and with the thoughts about how we create shared prosperity. It’s clear that we’re not there yet, but there could be frameworks to get us there. This is important to talk about today because throughout COVID, it’s been well publicized that some of the leading billionaires in the United States have made many times that during the pandemic.
But the 98% or 99% of the rest of us have either gone flat or down, which has resulted in, what’s known as this case-shaped recovery, but does it have to be that way forever? Perhaps there’s new frameworks and I know Katya and B, you are both working on a framework at the Partnership on AI about shared prosperity.
We are, indeed, and we encourage our listeners to check it out. You can read more about the partnershiponai.work/shared-prosperity. It is a project that thinks about the redistributive power of AI. So as you just said, technology has this power to redistribute wealth and income and economic power. And if the trends that we’re seeing are going to continue, then we might, we have a risk of ending up in the world where this economic power is concentrated in really a handful of companies, countries, and even individuals.
So the AI Shared Prosperity Initiative really thinks about what is the responsibility in the hands of innovators themselves of AI of the industry to think about these redistributive outcomes that they’re bringing both for the society, and to actively steering AI in such a way that these redistributive outcomes that are actually empowering for the population at large. And they’re not concentrating the gains in increasingly, a small number of hands, or just doling that out to AI developers, which are really under 1% of the global population today.
And we are thinking about this from a practical perspective using the parallel with the environmental responsible business movement. So if you think of that movement, as of today, it is very clear when society asks businesses to be environmentally responsible what we actually mean by that in practice.
So it is clear what goal you as a business can set for yourself. This is something around emission reduction or zero emissions, how you measure your ambitions and what are some of the off-the-shelves policies around energy management, waste management that you can apply to make progress towards that goal like that.
Now, if a society wants the company to be responsible when it comes to its impact on inequality and economic inclusion, and if we just tradition of economic opportunity, what’s the right goal to set there? Pretty unclear. How would you measure that you are making progress towards that goal? What are some of the off-the-shelf solutions and policies that we can offer you as an AI company that actively doesn’t want to exacerbate inequality, but actually wants to be making people better off economically? All of that is quite weak right now, but it doesn’t have to stay that way. And this is what we’re working on, the initiative.
We are really, very very grateful for the involvement of our partners. This is not just B and I who are working on that. We’re benefiting tremendously from the thought leadership and the engagement of leading thinkers from across different disciplines. That’s not only the economics and technology industry. There’s also leaders from the labor movement and labor organizers who work with workers directly. Ethicists, if not the first social scientists. And this is a really diverse group that is on the steering committee of the initiative, but we’re also actively looking for input and suggestions from anyone really interested.
So. You can subscribe on our website, then be in touch with us, be receiving updates on the initiative and be invited to our events, to provide input on the early work. This is really early days and any ideas. Listen to us, to my half, for us would be really well received.
Definitely, it’s sometimes folks working in this space have an attitude that it’s a little bit like the Luddites too. Unfortunately in history they have been mis-characterized as senselessly trying to destroy technology that threatened them. I’ll just be honest. I’m really excited about technology. I work in the AI space because that can be a thing that does bring about incredible opportunity and prosperity and new horizons of understanding and collaboration that we haven’t even seen before.
And that’s really, really exciting to me. So, I wanted to just clarify that this stance is not one that says we shouldn’t have AI. We shouldn’t go down this road. We shouldn’t build these technologies, but rather, that this technology isn’t moving on its own, it’s moving because our hands are doing the work, at least for the time being, who knows, maybe there’ll be some future Skynet-style AI that can build and improve itself, but we’re not there right now.
And so we actually have the power to decide what we want our technologies to do. And what do we want that future world to look like? And that, to me, is such an exciting moment. It’s such a cool time to be an innovator, to be in the technology space.
And that folks who are listening to this are often, and you’re the people who are most situated to do this work, to think critically about what that future world looks like. And so. The work that we’re doing at the partnership on AI and with this, as Katya mentioned, this broad reaching set of collaborators that we’re so fortunate to work with, we’re really trying to ask the question, how can we do this? Well, how can we do this? How can we act responsibly to think about how we can create that future together? And we are really interested in hearing from other folks who have been thinking about these topics, or who are eager to get engaged on these topics. Katya mentioned our website partnershiponai.org/shared-prosperity.
And that’s a space where we’re sharing some of the thoughts from the leading thinkers in the form of these impulse talks, these questions posed to the world by some of these leading thinkers. And if you have responses to those ideas, or if you have ideas of your own, just share.
We’d really love to hear because the work that we’re doing is in the very early stages. And there’s so much possibility ahead of us and so many exciting things yet to do. So we really look forward to collaborating with folks to make this world a reality.
And these collaborations are best put as putting the eye back into AI. Just like we talk about on the show of HumAIn, humans and AI together. I hear a lot of that common thread in the excitement that Katya and B both bring to this conversation that shared prosperity is possible. And when I think back to how my father and my grandfather worked in the industry, there were days when it was common to be part of unions. It was normal to have pensions.
It was a standard practice to share in the equity and the wealth of the companies and the society that everyone builds. And perhaps some of where the world’s gone has been on a different direction. And now we’re having this new awakening to say, look, we’ve got this fantastic technology. And if we can use AI for good, if we can partner it with the labor and the economy, then that’s moving us towards an enriched world. And that enriched world can be with humans as the inputs, not only #data as the input.
Couldn’t agree more.
I love that framing and I love this idea too, that we, at the end of the day, all of these systems, there’s a lot of talk in conversations about structural issues and structural change. At the end of the day, these structures are built by us as people, the humans in the AI loop, and we have the power to shift it. And we also have the power to do things that we couldn’t do before.
There’s conversations around thinking of data as labor, conversations around different ways of having joint ownership of technologies. There’s all these exciting things that are yet to come. And those are the kind of ideas that we hope people will continue to explore. As we make this future, maybe course correction, perhaps that we make this intentional choice about the world that we wanted to build.
Well , Katya and B, any other call to action you’d like to share with our HumAIn listeners today on the show?
I just wanted to say, if you want to reach out to us as individuals, we both are on Twitter. We’ll share our Twitter handles in the description as well. We hope that you’ll join us in the AI in shared prosperity initiative work. And also, if you’re someone who’s thinking about different ways that these kinds of data inputs factor into our AI systems, the labor that goes on behind the scenes to generate and label data sets. There are so many ways we’ve been talking about the downstream impacts of AI, but there are so many upstream impacts in intersections of labor and economy as well.
So we haven’t touched on that too much today, but if that’s an area that you’re interested in or working in, we’d love to hear from you and really build toward bringing these two ends together, the inputs into the AI systems and the outputs, the downstream effects of the AI systems to build a full close loop, thinking about the different ways in which AI impacts labor and economy.
And that would love to share a fun and interesting fact, is it, is it forcing back one of our steering committee members, that Lisa Hope reminded us that sharing in the fruits of scientific progress is actually a human right. So dear listeners, please remember you have that right. And are liable. How do you say that?
Exactly. Thank you. And expected we are all entitled to it, and this is really no innovation just yet invented on its own or a few years on its own only thanks to the effort of the immediate team, but it always stands on the shoulder of all the scientific advances that society as a whole achieved before that.
And frequently all of that research was funded through taxpayer money. So people do have a right to say, a right to have a say in which way technology goes and what direction it takes. And they do have a right to be sharing the fruits of it as well.
Well, Katya and B from the Partnership on AI. Thank you for joining us on the HumAIn podcast.
Thank you so much.
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