Paul Daugherty: Radically Human

Beatrice Di Caro: From the World Economic Forum, I'm Beatrice Di Caro, and this is the Book Club Podcast. In this episode, we're joined by Paul Daugherty, Group Chief Executive - Technology and Chief Technology Officer at Accenture and co-author of the book Radically Human: How New Technology Is Transforming Business and Shaping Our Future. Radically Human is the follow up to Human + Machine, which looked at the ways leading companies were using artificial intelligence to transform their processes and grow their business without displacing humans. Paul and co-author James Wilson saw the shift towards a more human-centered use of AI technology accelerate during the pandemic and in Radically Human, they argue AI will drive four key areas for companies to be successful in the future: talent, trust, experiences and sustainability. Accenture is working with the World Economic Forum and Microsoft to create a Global Collaboration Village in the metaverse, which will be further developed at the Annual Meeting. My colleague Kate Whiting joins us again to interview Paul and she starts by asking him to explain what Radically Human is about.

Paul Daugherty: The fundamental premise of Radically Human is that there's all these stunning, amazing, exponential advances in technology that are happening. And the premise is that the more human-like the technology becomes, the more radical the leap in human capability and human productivity of people that we could drive. And we wrote the book really for two reasons. One is for individuals, because a lot of people sometimes are suspicious of or concerned about the new technologies. And the message is that embracing these technologies is really the path to success. And for businesses, the real message is that you need to think differently about the application of these technologies to drive the benefits, because it's not just about the technology, it's not just about the people, but it's powering them up with technology and new capabilities and matching with the human strengths that amazing human skills people have to really drive improvements in your business. That's the underlying premise. And it's not just an idea. We did a lot of research around this very large research project over a number of years with 10,000 companies. I think it's the largest ever study that was done of the use of enterprise technology or use of technology in companies. And it highlighted some really interesting results that led us down this path. And one of the results was that pre-pandemic we did a survey which showed that companies that were leaders in applying technology, that were applying technology in a more in a better way, in a more radical way, as we suggest were outperforming others by a factor of two X, of two times, which is really stunning. That was before the pandemic. Then when we did the research after the pandemic and the period of growth following that, as companies really doubled down on technology, it was really amazing to see what the results were and it surprised us. And that two X outperformance by those that were leaders in applying technology increased to five X and it was about how they were adapting these new technologies, how they were pairing them with the workforce, with the talent, and with the way customers use technology to drive different outcomes. That's really the upshot of Radically Human.

Kate Whiting: That's incredible. Am I right in thinking you call them, those companies, high achievers?

Paul Daugherty: Yeah, AI achievers. That is a big part of it. Cloud, AI and the metaverse are three technologies that we really talk about a lot and that I believe are really foundational and the megatrends for companies over the next decade, you know, between now and 2030. Cloud is the underlying... I think about as the operating system of business. It's how you how do you make the business work more efficiently, take advantage of innovation more effectively and more quickly. And companies are on that journey. Artificial intelligence then becoming a real differentiator, driving the insights of processes, the way the companies work and the way that people work. And that's where the AI achievers come in. Those that are adapting AI more effectively, driving superior results. Then the metaverse just coming on the scene to some extent, we're already seeing how that becomes kind of a new layer of experience of products for companies. Also with some hype and questions around the metaverse that are that are natural at the early stage of a technology.

Kate Whiting: That's incredible. Later, we'll get to some best practice examples of how that works. But your earlier book was Human + Machine which looked at AI and how humans and technology are more powerful when they work together. What does it mean when you say AI is radically human and how are companies benefiting from that?

Paul Daugherty: Human + Machine as you said, the premise there, we wrote that book to set the story straight on. That was about six or seven years ago we started the research, published the book roughly five years ago, and we wrote that book because we thought the narrative on AI was wrong. Companies were... it was being interpreted as it's going to eliminate all the jobs, that is going to lead to this dystopian future. We didn't believe that was right, and that's why we wrote Human + Machine and did the research around that. And then what we saw after Human + Machine is that our view was really born out, that AI was really about blending the human and the AI or machine capability together. Then Radically Human, takes that a step further. And I'd say we believe we're moving into kind of a new era. If you think about technology, think about how you've used technologies yourself over the last, say, five, 10, 20 years. We've had to adapt to how technology works. So we use our thumbs on these tiny little keyboards, QWERTY keyboards that were designed the way they were to slow typing, down because mechanical typewriters would get jammed up. That's the state of the art in terms of how humans and machines have worked together. What we're talking about in Human + Machine is kind of moving from an era where humans were forced to use machines on their own terms. Human + Machine was how do we pair humans together? How do you use voice and other forms of interaction so we can communicate on our own terms? How do we pair the incredible analytic capability of AI to enhance the investigative and curiosity and other powers that humans have? With Radically Human we believe we're moving a step beyond that, where we could actually use this more human-like technology now to enter a new era where we actually designed everything around the humans, that it's about how do we accentuate radically human capability by applying technology in support of humans. And that's just a radical shift from where we were five, 10 years ago, where it was all about how do we spend, as a company, if you're deploying technology, spend immense amounts of money in the change management, which was bending the will of people to use the technology. We think moving to this new era has profound benefits for individuals and businesses as well.

Kate Whiting: If we can get systems of examples of how companies are using AI to grow. Now, you said that there's five times growth since the pandemic. Those companies that are using these technologies actually are now seeing such a great return on their investment in these technologies. So what kind of things are they doing?

Paul Daugherty: Lots of great examples. I think one of the things that really exploded during the pandemic and that's now really taking off is basic areas, things like call center AI, artificial intelligence applied in how you interact with companies. I alluded to this a bit earlier and it was needed during the pandemic because in many cases you couldn't staff the call centers, you couldn't get people in and companies have shifted to allowing remote operations and such. And there were new queries that were coming in that you didn't have before. So how do you answer entirely new lines of questioning that were coming in because of new concerns or opportunities raised by the pandemic? So that's an area that really took off. And in fact, with during the pandemic, we saw 63% first-time adoption of AI. So if a company had not used AI before the pandemic, they were 63% more likely to use it during the pandemic. So just rapid uptake in using AI. Another area where we're seeing is companies using AI and supply chains. With supply chain disruption, everything that's happened and still happening around the world are using AI to get better visibility into both the demand and the supply around their products and where it's going. Something we've been working on for years is areas around regulatory compliance. For example, on money laundering. Compliance and things like that in financial services is really good at sorting through these transaction logs, these voluminous sets of data to find patterns that might be fraudulent and then surface to human investigators who can do the further work and verify what's happening. But then what we're talking about in Radically Human is how do you go to the next step in applying artificial intelligence? And that's why we talk in the book about this ideas framework. And it's a clever acronym that my co-author came up with to give credit where credit is due to Jim Wilson, because we had these five core areas: Intelligence, which is about making less artificial, more human; Data, where we talk about not just big data, but looking at minimum amounts of data as well as maximum big data; Expertise, which is using human expertise, not just machine learning in which people talk about how to use human expertise; Architecture and new ways of building living systems. And then Strategy, which is I think one of the real key parts of book where we talk about how do you develop strategy in this new environment. That's called Ideas I-D-E-A-S, that's the acronym my coauthor Jim came up with. He's very clever. I think about one great example of how that framework applies, to your question of new ways of applying technology, and expertise is how do you use human expertise to make the technology more effective and blend the two together. A great example is Etsy, the platform you may have used Etsy to buy things like these bracelets and such a kind of different offbeat, quirky products. The way you find them is by searching in different ways, and Etsy has a way of categorizing based on design and esthetics and such, which is very difficult to do through algorithms. But blending the design capabilities of their human designers who understand those concepts with the way the algorithms work, they're able to embed ideas like design esthetics into the technology to help customers find their products more effectively, to help merchants classify their technologies better and be a real example of the kind of radically human shift we're talking about that wouldn't could it be done without taking this different approach.

Kate Whiting: It's really fascinating - it's actually how humans and machine are kind of collaborating together, but the human is very much at the center of that and is kind of directing it rather than it being, as you say, previously seen as a battle between the two to some sort of extent.

Paul Daugherty: Yeah, that's exactly right. And you nailed it. In our first book, we talk about this idea of the missing middle, which were the new jobs that we believe would be created, which are about humans, machines working together. And that's what we're seeing bearing out like this, this idea that algorithmic design esthetic specialist, you know, who would have thought you'd have a job category like that? But that's the kind of thing that you see forming. And I think going forward, as you look about the roles, you know, the way we design work and the roles that people play, it'll be about how do we adjust the skills that people have to use the technology to do their jobs in different ways. And that's something we talked a lot about the book, as well as new ways of talent development to accentuate the capabilities that people have.

Kate Whiting: That's really interesting because the forum does a lot of work around the future of work, and we see the jobs that we're talking about now didn't exist, possibly some of them pre-pandemic. You know, last week I was writing about the Chief Remote Officer, which obviously didn't exist before we all started working hybrid. So these are jobs, aren't they, now that we're seeing that are being developed because of how we're working with AI, which is really exciting.

Paul Daugherty: And that's why the some of the work that the Forum does, which I'm familiar with too, and great work in this area, it's about how companies become learning organizations as well, because the jobs are changing so fast. You can't just go hire people with these new job categories because they're merging so fast. They won't be there. So increasingly, companies need to be talent creators, which is something we talk about in the book. We have a whole chapter on talent. We talk about this idea of becoming a talent creator. You need to take ownership as a company for developing this talent because they're unique skills to your company that might not exist. An example we've talked about before is in the energy space. Work we're doing with energy companies that do drilling and such to do it more effectively. Rather than the old way of technicians, which could only types of valves and things, they're operating machinery with artificial intelligence and sensors of visualization through game engines and such as a digitally enabled physical field services technician. That's a job that if you didn't bring your workforce along and train them, that kind of job, that kind of skill doesn't exist unless you take the proactive steps to build it. So I think, again, the work the Forum is doing on this front is very important and puts the way to these learning platforms and companies becoming talent creators as we go to the future.

Kate Whiting: We touched a little bit on the second part of the book, which really focuses on how technologies will drive these four key areas for companies to be successful in future, which is talent, trust, experiences and sustainability. And what I love about that is that they're so solutions focused as well.

Paul Daugherty: I think sustainability is one of the areas where there's very interesting things happening. It's really important to factor in to this kind of radically human journey because there's there's two reasons. One is the technology itself can be a bad contributor in a bad way to sustainability challenges. We talk about that as Red IT, we use this term Red IT in the book because all these technologies consume more resources and more energy, but there's ways to do it more effectively and efficiently. So we talk about how do you change Red IT to Green IT and it requires a new mindset in terms of the way you apply technology. We've been part of a founding something called the Green Software Foundation, which is an open source foundation dedicated to green practices. That's one really important thing to build in. The other reason is, getting to solutions, is that IT is often the solution to sustainability challenges. One example is work we're doing with a energy company on using sensing technology, imaging technology and artificial intelligence and cloud technology to track methane emissions more effectively. Methane is a very high-impact form of emissions that causes a lot of the atmospheric issues and it comes about through leaks in different ways that are very difficult to detect and then remediate. But with using technology, you can find it much more effectively. So that's an example. Virtual Singapore is an example where they're looking at how do you develop a digital twin of a city to operate it much more effectively. And those are some great examples of applying the technology on a larger scale. And many of the problems that we face are these large-scale, planet-scale problems that really can only be applied if you if you tackle them in this way. And it requires multiple companies, a lot of cases come together to do so, applying the technologies.

Kate Whiting: Thank you. I appreciate you touching on the red to green technology because that, as you say, is part of the problem. So it's sort of trying to decarbonize like the hard-to-abate sectors are having to think about how they decarbonize across the entire value chain, like the IT sector in itself has to think about decarbonizing itself, doesn't it?

Paul Daugherty: Yes, the IT sector has to think about it. Every company applying technology has to think about it because every company is becoming a technology company, because technology is pervading every part of the value chain, every part of what they do. So companies need to think about it. It becomes really important in the metaverse kind of context. When you think about blockchain and new types of applications that companies are developing, they can be very resource intensive. You use proof of work, the mining people talk about with blockchain that can be very environmentally impacting. You know, you talk about your bitcoin using the energy of something like Argentina, it doesn't have to be that way. And Ethereum, the blockchain platform moving to proof of stake based verification to dramatically reduce their energy intensity by a factor of over 99%. So companies have these decisions they can make and how to apply technology to be much more energy efficient.

Kate Whiting: Yeah, brilliant. I want to ask because I know you're an advocate for gender equality as well, particularly in STEM fields. How can AI, which sometimes is criticized for being coded with gender bias, help to overcome it?

Paul Daugherty: Yeah, I think it's a great question. I'll just start by saying every technology is neutral. It's the people applying it who inject biases or in AI's case, it's the historical data that we're training AI on that reflects human bias, that has risk of creating bias in it. You know, the famous example from one of the large tech companies, they applied AI in the recruiting process. It unfortunately screened out a lot of women and optimized towards men because that's what they had historically hired. So it was an unforeseen consequence that probably should have been foreseen in that case. And that points to what the solution is from a gender equality perspective in applying these technologies is we believe that every company needs to have principles and policies around responsible AI, which is about accountability. It's about fairness and screening out bias. It's about trust, it's security and other things we need to look out. We talked about this a lot in our book and at Accenture, we've actually codified responsible AI into a set of processes and principles that we monitor and are driving across our organization. So if you're designing a recruiting algorithm or if you're designing a loan approval processor or something, any of these algorithms could get bias injected into them depending how you develop and train them. But it's unacceptable for that to happen. And the onus is on us as the engineers that as the designers and as the testers of these systems to understand how to use tools, to understand bias and correlation of these types of things and make sure we're developing systems that's fair. There's no reason we cannot do that and it's very possible. It's just a matter of going about it the right way, which is what we're trying to bring about to education. The other part of it that is making sure we celebrate a lot of the great role models, diverse voices are developing and leading in the technology. That's why I'm very proud to be on the board of Girls Who Code, where it's about investing in girls and women in technology. And there's so many great examples of role models in the technology field that we often don't celebrate a lot, say Fei-Fei Li, pioneer from Stanford and Google and one of the pioneers in artificial intelligence. I could go on and list a whole bunch more, and we need to increasingly celebrate the role models we have so that we encourage more girls, more women, more diverse voices across every dimension to enter into technology and into the emerging technology areas.

Kate Whiting: If they can see it, they can be it. So I guess I want to come on to let's call it the metaverse part of our conversation. The word itself is one of Oxford Dictionaries words of the year I just discovered. You refer to in the book as one of the next wave of frontier technologies. What's radically human in your view about the metaverse?

Paul Daugherty: When we talk about the metaverse, we're not just talking about putting the headsets in and going to headsets all day long, like Ready Player One. We're talking about a metaverse that is not just about 3D, but it's how do you enable two dimensional experiences that you can get on your mobile phone or your or your laptop? That's critical to think about the metaverse. It's about how you create shared experiences, which is what people typically think about with the metaverse, how they come together in whether it be Microsoft Altspace or Mesh on their platform, or using Epic and Unreal on their platforms or Meta's Horizon Worlds, whatever it might be. The Internet of Place is what I'd call that. The Internet of Ownership is the other key part of the metaverse, which is new technologies, Web3 types of technologies, blockchain that I already referred to a little bit that are creating the opportunity to have really unique, verifiable digital identity for people and products and currency. That's revolutionizing how we can really go to the next stage of digital in how we build our companies and products. And that's why it's a little bit controversial when we say this but I believe it's very true that over the next decade, as we look at I talk about cloud, AI and metaverse earlier, I don't think many doubt cloud and AI at this point, but a lot of people doubt the metaverse. But I think you got it at your own peril because the Web3 technologies, the evolution of the internet and the adaptation of how we create experience for people is going to lead to the adoption of all of the of these technologies. And it's going to enable radically new capabilities. And those that lead in this move to it, I think, will have a dramatic advantage.

Kate Whiting: And I understand that Accenture has its own enterprise metaverse, the Nth Floor. Can you talk me through that a bit, please?

Paul Daugherty: Just to put that in context, I think there's three ways to categorize the use cases, the metaverse. There's the consumer metaverse, which is Nike or Gucci, JPMorgan Chase, many that are pioneering ways to interact with customers, consumers in the metaverse. There's the enterprise metaverse, which is how you use it in your business. I'll talk about what we're doing there with Nth Floor minute. Then there's industrial metaverse, which is augmented reality, digital twins. And how do you bring the metaverse to outside of the operations of your business? We believe those are really the three areas to focus on. What we talked about, the enterprise metaverse is was our onboarding process. It was partly by necessity. We have some research going on to use virtual reality to onboard our employees. Pre-pandemic, we had a very small scale research project. The pandemic happened. We were still... we're a large company. We have now 750,000 employees, roughly. We were hiring over 100,000 a year through the pandemic and onboarding that number of employees. There was a challenge to do that virtually. So we said, let's scale up this work we're doing around the Nth Floor and we tried it in our onboarding process and we successfully increased the scale to where in this 12 month period, we'll onboard 150,000 employees using our Nth Floor metaverse. Employees get a headset when they join the company. They go in for some guided experiences, some orientation, some training. Then they have some unguided activities that they can do of learning, etc. And the engagement of the employees is better to this process than the previous way of doing it. The learning retention is better. We have neuroscientists and learning specialists studying this, and so it's really adding value. It's a better way of doing the process, but we believe it's the largest metaverse example at scale. We have lots of client meetings there. We do internal meetings there with our management committee. We've taken our board of directors there, lots of things that we do. And we've scanned our environments. So we have 3D scans of our labs and offices around the world. So I can and I have taken clients on a tour of our labs in France, our labs in Silicon Valley that they can do with this rather than traveling, which back to our prior discussion is efficient. It's a new way of creating the experience. It's offloading a lot of climate impact from people flying around the old way of doing things. So it's an example of the experiences you can create.

Kate Whiting: Wow. So you can actually say, see you in the metaverse and you mean it?

Paul Daugherty: Yeah. Yeah. The title of our vision last year was Meet Me in the Metaverse, and that's exactly what we see happening now. Today, you can wear these headsets forever. The headset technology will improve, but I think you run a risk of pointing out why it doesn't work today rather looking at where the technology is going, I think that was a problem with the internet. I still remember talking to companies in the late 1990s that were telling me, that's OK, I don't need a web page or all I need is my corporate directory on the web. That's all I'm going to ever need. And they missed the inflection point. They fell behind and others captured the opportunity. I think with the metaverse now is the time to look ahead and understand what and how this might change what you do and be leading into that rather than getting stuck behind.

Kate Whiting: That's fascinating. I read Brad Smith the President Microsoft's book Tools & Weapons and he talks about the promise and peril. We've talked a lot about the positive side of AI and the metaverse. But what are the challenges that are facing us and what are the imperatives to your mind that we need for a responsible metaverse, for example?

Paul Daugherty: Yeah, it's a great question. Tools & Weapons is a brilliant book, and Brad and I work together on some of these issues that we're talking about. I think the thing to keep in mind, there is always a bright side and a dark side of any new technology. If you go back to the the Stone Age when fire was invented, you probably have a group of people saying, this is great, we can cook our meat, we can stay warm. We have another group of people say, this is terrible, it's going to burn us and hurt us. So with any technology, there's positives and negatives. It's about us and how we influence it. So with the metaverse, what's particularly important is following the path that I talked about earlier with artificial intelligence, we need to take accountability to create the principles and the mechanisms to make sure it is creating the metaverse we want to. We're creating the worlds and experiences that we want for ourselves, for our employees, for our customers, for our children, for our communities. And to me, it comes down to three areas that we're working on. And we're working with many companies, many organizations are this. The first is trust. So creating the trust in the environment. So I know that my identity is safe. I know that if I buy products I really own it and it's not going to taken away from me. I know the security is there, so trust is one key thing. Safety is another key concern. How do I know that appropriate safety will be enforced? I don't want to be bullied or I don't want non-inclusive behavior or toxic behavior, which is an issue in some environments today. So content moderation, behavior moderation is critical. Along with safety is a focus on inclusion and we have the right representation of the right groups, the right people, the way we're building the world. And then finally, the third area is sustainability, which we've talked a lot about, designing this in a sustainable way so that we're utilizing resources appropriately and not taking to going down the Red IT path that I talked about earlier, which is a challenge that we're going to need to work on this as an industry and as companies deploy the technology because the headsets, the metaverse, rendering these environments does consume more competing resources, but there's solutions to do it in a more effective manner.

Kate Whiting: Yeah, brilliant. So earlier in the year with the World Economic Forum, you and Microsoft collaborated on the Global Collaboration Village in the metaverse. Can you tell me a little bit about that?

Paul Daugherty: Yeah, the Global Collaboration Village, I think, is a real kind of shining light of what the metaverse can be. I think it's a fantastic use case and a great vision, creating new levels of collaboration and opening up the World Economic Forum to more stakeholders. So it's an amazing vision, and I think it shows the real power of applying the metaverse in the right way. So we were so pleased to partner with Microsoft on this with the World Economic Forum and bring it to life. So it's creating a virtual forum, so to speak, a global collaboration village with leading places where stakeholders can come together on issues. So there's a focus on climate and how we can preserve climate and natural resources and such an amazing experience that we take people off to see forests with biodiversity and show why they're at risk and how you protect them and then create the dialog around that among the stakeholders. It's really illustrating the power of bringing people together much easier, and not just occasionally throughout the year through curated events, but continuously using the power of the metaverse to do that. I think it really is a brilliant vision. And an early, a very powerful example of how to use the metaverse for a lot of good.

Kate Whiting: Are there any books around the metaverse or AI, obviously we're talking for the Book Club, that you recommend to your listeners?

Paul Daugherty: I've got some on my some of my bookshelf right here. One is by Matthew Ball, it's called The Metaverse. He's one of the leading thinkers, commentators and followers of what's happened in the metaverse. I highly recommend his book, where he goes into all the issues that we've talked about and more and talked about a lot of examples of how to bring it to life. Another book that's really stretching the future of what you might think about the metaverse is a book called Reality Plus, I believe the author is David Chalmers, and he's a philosopher who's looking at the metaverse in a different way in terms of how should and how might we use the metaverse as humans that it really, it talks about a lot of the concepts in the metaverse from a different perspective. It is very thought provoking. So those are two books that I'd recommend.

Beatrice Di Caro: That was author Paul Daugherty from Accenture speaking to my colleague Kate Whiting. Big thanks for joining us on the World Economic Forum Book Club podcast. Please subscribe to this podcast, listen to our sister podcast, Radio Davos and Meet the Leader and leave us a review. Don't forget to join our two clubs on Facebook for the Book Club and for podcasts from the World Economic Forum. This episode of the Book Club Podcast was presented by my colleague Kate Whiting and myself, Beatrice Di Caro. Production was with Gareth Nolan and thanks to our podcast editor Robin Pomeroy. We'll be back soon. But for now, thanks for listening and goodbye.