Introduction

“If we start to think about humans plus AI, this mindset begins to shape what we are trying to create.”

– Ross Dawson

What you will learn

• Exploring the dual attitudes toward AI: replacement vs. enhancement
• Introduction to the amplifying cognition podcast by Ross Dawson
• Overview of the Maven cohort course on AI-enhanced thinking
• Debating the future of work with insights from Sangeeta Paul Chattery
• How AI can amplify human cognition and decision-making
• Understanding the potential for a positive future of work
• Inviting listener feedback and discussion on the future of jobs

Link to report:

Please let Ross know your thoughts and comments on future job prosperity:

LinkedIn: Future Job Prosperity

X/Twitter: Ross Dawson on Future Job Prosperity

Episode Resources

• Maven cohort course
• Pew Research Center
• hyperstition
• Mobile money agents
• Augmented reality designer
• Neural interface design
• AI auditing
• Prompt engineering
• Sangeet Paul Choudary
• The Economist (Noah Smith)

Transcript

So this episode is a bit different than usual. It’s just me today. And like to share this mini report I’ve just written about making the case about why we should believe that the future of jobs will be prosperous. And one of the most popular episodes in the podcast has been episode 39 recently with Sangeet Paul Choudary, where we had a kind of a debate around the future of work where he was somewhat less positive, particularly around the evolution of the skill premium in jobs. And I was making the case for a more positive perspective on the future of work. And if we think about the future of humanity, perhaps the most important issue is the future of work. This is how we create value for ourselves for society, the way that we feel we have value we express our personality, our capabilities, we achieve our potential, it’s there’s nothing more important in a way than the future of work though how it is that we contribute and create value in our work, I recall this survey by Pew Research just quite some years ago, but where they asked around 2000 Supposed experts in the future of work around whether they believe that the future of work would be positive, or would be negative, and 48%, were negative. And they painted these sometimes extremely dire predictions of technological mass unemployment and massive disparities. And this really quite bleak view of the future of work. Whereas 52% painted a positive future, sometimes just on balance, feeling as positive, sometimes believing that we could move to a world where we could do whatever we felt was the right things for ourselves and our spirits in the world, and we could fulfill our fullest human potential. So that’s around 50-50. And the issue is we don’t know. 

And today with the rise of AI, this is making it even more deeply uncertain. There are many views, I’m sure you’ve read many around what will happen with the future of work. I bet that more of the ones you have read have been fairly negative around the prospects for AI replacing workers. But the thing is, we simply don’t know. There’s this marvelous word hyperstition, which is essentially a self fulfilling prophecy. If you believe something and you frame it, then it starts to literally come true. And I think there’s a real risk of that with the sort of the talk that we have around how AI will replace jobs and the attitudes we have to how we use AI to be able to substitute rather than to compliment human workers. But I think in the same way, we need to be able to articulate the positive case as to AI and other technologies. Another shift in society can create a very positive future of work, and hopefully that being able to engender a self-fulfilling prophecy and once we can envisage it, to see that we understand that it is possible to be able to drive that and I think there’s a key point being around. You have to believe something is possible in order to make it happen and I think some people are floundering in finding that positive view of the future of work. And I’d like to be able to make the case that it is possible or potentially even likely if we do the right things. Of course, this is all about this idea of humans plus AI, where if AI comes in, well, you’re not looking to say, well, how does AI replace humans, trying to make it a substitute for humans, but always looking for how humans and AI together can do far more than they could ever do before. And that is also of course, about amplifying cognition, using tools, which could be anything from meditation to large language models to amplify our ability to achieve our intent to think better to make better decisions to shape the future of the world that we want. So this mini report, which was titled future job prosperity, and subtitled 13 reasons to believe in a positive future of work. 

So I’ll just run through this report. And I will give it a little bit more detail in that report. And when I say report, it’s, you know, just a couple of 100 words, or one or 200 words on each point. It’s quite succinct, and might all just expand a little bit on some of the ideas and lay out this case for each of these reasons why we should believe in a positive future for work. And I also want to make a point that I would like your feedback, I want to be able to hear, are there any other reasons that I’ve missed? Or are there better ways to articulate those reasons, or, indeed, that you have some counter arguments and be able to hear some of the reasons why you think the case I’m making is not strong, will help me to reinforce it either as this is the first version of it is report. 

Now we’ll build on that and continue to try to create as strong and solid a view as possible that we can have future job prosperity. So let’s start with Reason one, and reason one is what I described as the potential for humans plus AI. And simply this is around the mindset. If we start to think about humans plus AI, this all starts to put us in this in what we are trying to create in AI being able to complement the values of humans to be able to create greater value. And whilst there are domains where AI exceeds human capabilities, if we start to reframe the nature of work, then we will find more and more that humans and AI collaborating will create superior outcomes and either working individually, if it’s very data driven, AI will work well. But more and more domains of value creation are ones where humans plus AI collaborate, and part of it is that there is a rapidly growing movement of leaders and thinkers and doers who are putting their energy into thinking about this. And I’ve been very encouraged over the last couple of years, seeing more and more people thinking about this frame of humans plus AI. And that means that we can start to design and to craft and to create a world in which we design for humans plus AI the reality of the incredible capabilities of AI, but designed in order to be able to complement humans. 

The second point, and some of these points are interrelated, is that AI enhances value generating skills. So we can use AI to augment our intelligence to replace low level tasks. And so we can increase the value of people who are working, and those who use AI to enhance their value and their nature, their work will be able to increase their skill premiums and be able to charge more for their work because they are creating more value. Many research studies across different industries in different contexts have shown that AI most often gives a greater boost to the work capabilities of lower skilled workers than higher skilled workers. And so this narrows the gap between the value of these works and potentially this is a force which could move against the value polarization that we’ve seen across the work domain for a number of decades now. And so, it democratizes the ability to create value to be valued workers, because people can use AI to be able to do that. So this the scope of generative AI means that this can be applied, certainly to complex tasks such as strategy consulting, it can be applied to a lot of the work which is done today by many people and to enhance the impact they can have and even to physical labor and go how it is you would go about things most effectively. 

Point three is perhaps the very often quoted one of the creation of new jobs and throughout human history, we have destroyed jobs and we’ve always created more than we have destroyed. So I think that we can see right now that there are more new jobs being created than ever before. And there’s many rapidly growing roles, which are quite significant now, which did not exist very long ago: telehealth nurse, digital identities specialists, mobile money agents, particularly in Africa, for example, augmented reality designer, and so many more. And these are all new roles. And there are many more that are starting to emerge, particularly AI and neural interface design, AI, auditing, cognitive enhancement, AI, ethics, prompt, engineering, and so much more. So, I think part of the thing is there are many new rules that will emerge, which are not just directly tied to technologies, but for example, and how it is we deliver health care, aged care, different social support, for example. So we have already created many jobs. And I think there’s a fair case or very good case that we will continue to create new jobs at an extraordinary pace. 

Point four is that this technology starts to make the uniqueness of our human capabilities even more relevant. In the last century, we started designing jobs and boxes so that anybody can fit into them, and we could replace them. And we’ve generally evolved the nature of work over the last few years. So that we are encouraging people to have unique capabilities to draw out their specific perspectives, looking at diversity of how people are thinking, or their backgrounds or their experience or their education. And as we start to design work to bring out those most distinctive individual capabilities, this will mean that it’s harder and harder to replace us. And so this will draw out our unique capabilities by using AI and be able to complement our distinctive perspectives using AI. So that we are more and more specific in the nature of our value creation. 

So this leads on to the next point, which is that specialization reduces substitutability. So, the more specialized you are, the less substitutable you are. And of course, in any economy. If you can substitute something, then that drives down its price. And we are trying to build a world of work where people are less and less substitutable, they are more and more individualized than we’ve just expressed. And as we shift to these more distinctive and unique human capabilities, which can be assisted by AI and AI supported education will be harder to substitute for individual workers. And this will be accelerated by the fact that the most successful companies will be designing work to tap the most specialist individual skills. If the organization is built on commoditized work, then it will ultimately create commoditized products and services, and they will have no competitive advantage. So in an increasingly dynamic economy, companies do need to seek ways to be more distinctive, and that ultimately depends on their ability to hire, and to engage and to amplify the uniqueness of the people who work for them.

Point six I think is absolutely critical, which is around enhanced education and learning where AI enables extraordinary ability to learn faster, better, and that is available to everyone, almost everyone on the planet. Now. It is realistic that democratization of these learning tools will help people to assist them with marketable skills to transition into new roles as these new skills become more available, and to be able to drive a world where because we have AI education, we can transition, we can grow, we can make ourselves more relevant. It will be a far more dynamic work environment, there’s no question. But our ability to be able to use tools which can be personalized to our learning styles, the way in which we think they’re quite interesting most, to be able to engage us and to help us to grow our capabilities, our understanding of our learning to be relevant in a rapidly changing world. 

Point seven is about comparative advantage and this comes from a recent article by The Economist Noah Smith, which I’ll put in the show notes. There was also in the New York Times picked up on this idea. It’s quite complex. But to summarize, the economic theory of comparative advantage says that, you know, whether you’re an individual or organization or just economic entity, you focus on where you have the greatest differential inefficiency. So where it is the biggest gap, whether in order to be over others nor to be able to do that. So the argument goes that even if AI is better than humans at every single task, it should still be applied to where it has the greatest advantage. And so this will still leave Apple jobs for humans, where AI is advantages smaller. So this is predicated on this fact that, you know, they’re essentially there are limited resources. And even if they are extraordinarily large, still, AI will be applied to where it can create the greatest advantage. And there will still be the ability for humans to be able to do the things where they have a smaller where AI has a smaller advantage over them. So there’s some interesting debates around what happens when you take this to an extreme as the moment in fact, humans are far far far around 10 to the 13, more energy efficient than AI. And so if we have energy as a scarce resource, in fact, humans will have a very significant Vantage. So if this starts to narrow, and the AI starts become far more efficient, and will have to become, you know, many orders of magnitude, bit more energy efficient, then it is possible that, you know, energy for electricity or other things that we require, will could be appropriated by AI. And you know, this is I think we’re talking probably centuries rather than decades, or something like this. But in this case, this could be addressed by, for example, regulation to inquire that require that humans have preferential access to resources over AI. And that would very simply bring us back to the fact that whatever AI is doing even with even doing many roles, which humans already have, there will still be ample, or unlimited work for humans to do. 

Point eight is around the attraction of talent. And I think this is pretty fundamental for leaders in thinking about, you know, essentially two attitudes they can have to AI. One is they say, Oh, this is wonderful, we can sack lots of people, and we can have AI do their jobs instead. Or the other attitude is say, this is a wonderful tool to amplify and to grow, the potential and the capabilities and the productivity view, productivity of all the people who are working for us. And, you know, there’s a few shades in between, but I think most leaders will fall into one camp or the other. And the reality is that those organizations are looking to augment there are people to focus on the humans and how AI can complement them to be able to create more value to grow and develop will find it massively easier to attract talent, and those organizations that are focused on AI replacing people. So we still will live in talent probably more than ever before. And even if you’re looking to hire the people who are driving those AI systems, to be able to grow things, this will be a critical differentiator. So essentially, companies will succeed based on their attitude to human labor relative to AI. 

And as such, the companies that will grow the most track the most talent, be able to drive the most value creation will be the ones who prefer humans over AI, or use AI to support humans rather than to replace them no points around work redesign where essentially every organization needs to redesign the work centrally, the role of humans and how it is they create value, this is being transformed at a rapid pace. And every board, every executive team, every leader needs to be considering what might we believe in the future shape of the organization, and the relative roles of humans and technology and how they come together to be able to create value and what our organization will become. And to be able to design those workflows, make them as flexible as possible, and to support the people to grow into the capabilities that will be relevant in those configurations. So understanding those roles of humans plus AI in this redesign of work. So those organizations that are doing that now, in being able to reorganize themselves to envisage these humans plus AI models will have a massive advantage, because they will then be framing and understanding the ways in which humans plus AI can come together and create far more effective organizations that can bring in the best people and amplify the value of all of the people that they engage in higher point turns around. 

Yes, very simply that humans are proven to be amazingly adaptable. For well, as long as there have been humans. And for Ice Age, we did pretty well at working out how to deal with that. There have been many other transitions since we’ve created all sorts of inventions, gunpowder, Steam, the internet, and a lot of other things we have adapted. And you know, a nice example of human adaptability fairly recently is, in 2020, we had a pesky virus called COVID. And it was pretty confronting, but we managed to adapt to that, in fact, the economies around the world did very well. And most people did very well in shifting to remote and flexible work and found Well, actually, this works. So we have proven that we are pretty adaptable when needed. Yeah, I often think about Alvin Toffler, his book, Future Shock, which came out in 1970, where essentially, he said that, you know, the increasing pace of change would lead to us, essentially going into a state of shock and not being able to deal with the pace of change. So that was 54 years ago. And we’ve done pretty well, it’s yes, it has been fairly challenging at times and dealing with the state of change, but we have managed, and I think we’ve been proven to be exceptionally resilient. And I have faith that humans are unlimitedly adaptable. And I think we are demonstrating that at the moment and how we are shifting, even though it is raising concerns and stresses and uncertainty, we are exceptionally good at dealing with data. I think that defines what it is to be human. And we will continue to demonstrate that ability to adapt through our human agenda changes in coming years, decades, centuries, and fingers crossed millennia.

Point 11 I think it gets down to some pretty nitty gritty points around the fact that there are so many roles where humanity is expected. And part of the job, you know, emotional engagement, so personal services, healthcare, aged care, education. So we don’t want an AI to care for us as is aged care more in terms of anything which we require, we don’t want an AI to be our teacher, or they’re an AI may help with will be very valuable as an educational aid, there’s not going to inspire us as to what we can do with our lives. We know they’re not human. And so they’re not going to provide that emotional engagement, that human touch that ability. You know, in a more specific context, your organization can only be effective if everyone within that has emotional skills, social skills where they can work with others, collaborate, generate ideas, and create an environment where people want to work. So we know if we have lots of AI there, then humans aren’t going to feel very welcome. Whereas we have lots of engaging people there that will create that. And then of course, every business depends on their customer relationships. 

And if you want trust and loyalty, people do not express trust and loyalty usually to AI. In fact, the trust measures of AI are pretty low these days. So trust and loyalty will require human connection, emotional intelligence, this means that the people are valuable. And this is a really central role is the you know, there’s this issue, that emotional and human connection will grow in importance grow in value, and more and more roles will require that support that and we will expect it has to be that and even when AI is better, we will still want humans to do the roles in many aspects. 

So if we think that most people will want to prefer to read a novel written by a human writer, rather than an AI writer, because they know that it comes from human experience, they know that they’re, they’re engaged with somebody that has created a work of art based on their experience. We want to work with a financial advisor who understands what it means to be stressed about money or to be worried about our future rather than just being a set of data. Now even if a Robot waiter comes on and they are very witty and how they interact with us at the table will still want human waiters. And there’s so many roles where I believe fundamentally that we will want humans and possibly AI will be cheaper. But we will still be prepared to pay a premium for human delivered services, human delivered interactions. And over time that premium for humans will increase substantially. Even if the quality is comparable, or the AI is superior. We want humans to be working with us. 

And the final 13th point I make is around this idea of designing for inclusive economic prosperity, where there has been a divide in the allocation of value in the economy. And since the 1960s. In the United States and many other economies, we’ve seen that more of the productivity gains, more of the value add has been appropriated by corporations rather than workers. And so we’re seeing this greater split between the wealth and income across the economy. Now, taking this further, it leads to a situation which nobody wants. If you are a large corporation, you need people to be affluent enough to be able to buy your products and services. If you are a wealthy individual, you don’t want a whole bunch of people with pitchforks outside your house, you want a place where everyone, as many people are as happy as possible and engaged so that we have this situation where everybody loses pro social fragmentation, which is the ultimate result of disenfranchisement of work. And everyone benefits. If we start to see more participation, more inclusion, more ability to build a society where everybody can contribute and share in the value that’s created. So everyone will be aligned and still doesn’t mean that we can map that path. But that intent can certainly lead to that design and realization of inclusive prosperity.

So these 13 ideas or frames around why we can believe in a positive future of work, are starting points for thinking about the positive potential of where the world of work and jobs can go. And at the moment has said this, we don’t know we don’t know which way it’s going to go. But it is open for us to create. It is not inevitable that we go down a negative path because we can create a positive Well, it’s not inevitable that we create a positive world of work, because there are many things that can go astray and a lot of bad decisions which can take us down a negative path. So what we need to do is, first of all, acknowledge that there are some deep challenges, particularly in this, the scope of the impact on jobs, and the the the scope of the transition, and moving from two from quite different economy, and quite different work landscape to but the first point is to understand what are the forces and the factors that are unfolding here, and what are the ones that could lead us to a more prosperous future of jobs. And I believe that there are very, very positive possibilities open to us, we can create a world where people enjoy their work more than ever before, there are more opportunities for people to choose their own path to discover who they are through their work, that we can express human potential uncover that, more than ever before that we can participate in the value which is created augmented by AI and other technologies. So we do need to be able to act, it is taking the right actions which will shape us and take us on the more positive paths. So whether corporate and government leaders, obviously are fundamental to that entrepreneurs and those who are building companies are shaping this world in many ways. And as individuals, we all make choices and how we do that. So it’s probably for another conversation to lay out some of the specific guidelines on what we need to do to be able to shape that. I think the first point is to be able to understand there are so many ways, so many factors that could drive us to a very positive future of work. And so that’s where we need to be focusing on that belief. So please let me know any thoughts reflections on whether this has helped you have a more positive frame on the future of work, whether you have any other arguments to make any other ways to use be able to any counterpoint, a way to be able to strengthen these arguments, and make them more specific, so that we can communicate this potential for a positive future of work, which can lead us to take any actions will make that happen. Thank you for listening. I am looking forward to seeing what we can create together and a wonderful future of work.