The relationship between minds and machine is at the heart of innovation. Its history has been marked by critical moments that changed the nature of the bond forever —, many of which brought fundamental disruptions in our global economy as well. One need only think of the changes brought about by the use of tools for agriculture or the Internet to appreciate the scale of the impact, for example.
Today, we stand at the verge of another Schumpeterian wave, characterised by the digitisation of our economies, our knowledge and our lives. The transformative potential of such a transition could be just as game changing as the previous waves of innovation, if not more so. This transition will also bring about a new evolution in the links between minds and machines. We are in the early stages of this transformation. On the industrial side, for example, we are just now building the infrastructure that will enable the Industrial Internet to reach its full potential — cloud platforms like Predix being a recent example of that trend.
A smooth transition will also require us to address the concerns associated with the new phase of the minds-machines relationship. Our minds now rely much more on machines for productivity at the same time that machines are developing a mind of their own. We are also getting to a point where our minds can influence not just mechanical machines but biological machines as well (eg DNA, cells). Some concerns associated with these tensions are old and often exaggerated (eg “automation will take our jobs”); others are new and relate to tipping-point dynamics, such as Stephen Hawking’s and Elon Musk’s arguments about artificial intelligence or how far we should go with human enhancement. These are complex issues for which there are no easy answers; they will require careful consideration if we are to make a successful transition.
With that in mind — pun intended — Look ahead is dedicating the next two weeks to a series of pieces exploring the relationship between minds and machines and what this might mean for the future of our global economy.
Starting this series is an in-depth discussion with Dr Marco Annunziata, chief economist and executive director of Global Market Insights at General Electric, one of the few companies that managed to go through and build on multiple waves of disruptive innovation. Since joining GE, Dr Annunzianta has devoted particular attention to innovation and technology and their economic impact, co-authoring two papers on the Industrial Internet.
In this two-part interview, he shares with Look ahead his views on the history and future of minds and machines and how we can best prepare for the next wave of innovation.
Looking at the history of the relationship between minds and machines, what would you say have been the milestones and where do we stand in that evolution process today?
The relationship between minds and machines is probably one of the most defining characteristics of human evolution — certainly one of the most powerful in terms of the evolution of the speed and form of economic growth.
In my view, the evolution process has had three key stages — the third one of which is unfolding today.
The first stage came when we started to introduce more powerful tools to help us with agricultural work. Agriculture had until then been the pillar of economic growth for mankind; the introduction of tools marked a fundamental shift in the relationship between minds and machine. Technology could be used to reduce workload. And to a large extent, it was not seen as something to be concerned about.
The second stage was the Industrial Revolution and the beginning of the introduction of more powerful machines into industry, with successive waves of automation. That phase was similar to the first in that we were again using machines to unburden us from some of the hardest and most tedious tasks that humans were performing. But while the introduction of machines in agriculture was important, it was the Industrial Revolution that really kicked off the process of productivity growth and with it exponential improvements in economic growth and standards of living.
I believe we are now at the third stage of this evolutionary process, where we are learning to use machines to help us also in the areas of intelligence and information. It’s no longer just about using machines to unburden ourselves from physical tasks that are either very hard or very tedious. It’s about using machines to help us on the intellectual side and on the control side, taking advantage of the fact that they can now perform a larger number of tasks with greater precision and at faster speeds.
I think that this phase will prove to be similarly disruptive in the sense that it’s opening a completely new dimension in the relationship between minds and machines and therefore will engender another substantial burst of accelerated economic growth.
The relationship between minds and machines is probably one of the most defining characteristics of human evolution…
Compared with previous phases, what would you say is new about today’s relationship between minds and machines? Are we seeing any important differences in terms of how these transitions are happening?
I think what is interesting is the way in which the relationship between minds and machines is fraught with contradictions. There’s always an element of hope mixed with fear. We love to use the machines and we love to use them to do things that we don’t like doing, but at the same time we have this instinctive fear that machines might somehow replace us, replace workers and not work in our interest.
These concerns were probably less important during the first wave of this evolution — agriculture — but you see it very clearly in the case of the Industrial Revolution. In both cases, however, no comparison was being made between the mind and the machine. The demarcation line between the two was very clear.
What is happening now with this current wave of evolution is that this line becomes to some extent blurred. With the development of big data mining, computing and eventually artificial intelligence — and to some extent robotics — we’re also looking at the possibility of machines taking over a number of intellectual tasks.
Take my case. I’m an economist, I look at global economic data, and now you can have a super computer, machines that can sift through tons of economic data and come up with economic forecasts for any number of variables.
So, all of a sudden you have machines expanding into a different realm of activity. And what’s distinctive and interesting about this phase of evolution is that it’s leading us to ask ourselves more insightful and complicated questions about what it is that makes humans special.
This is not just a philosophical question, it’s an economic one. It amounts to asking, “What is the best division of labour between minds and machines in this third phase of revolution where machines can take over more and more intelligent and intellectual activities?”
The Luddites never had to worry about the AI singularity. We do.
The Luddites never had to worry about the AI singularity. We do.
If we look over the short term for cycles of this kind, say 2030 or 2050, what kind of realistic industrial economic opportunities does this new type of relationship offer?
This is a very good question. I think the economic potential of this new phase has been underestimated, in part because we are just at the beginning of this process and because we’re coming out of the healing process after a long global financial crisis and global recession. There’s this sense of pessimism in the market, with people thinking that growth is still too weak and that there isn’t much industrial economic opportunity coming from this new relationship of minds and machines.
I see it completely differently. I think once you start making industrial machines and supply chains more intelligent through data and sensors, what you get is a more efficient and productive economy, leading to more economic growth and more jobs. These productivity gains, in a sense, are not dissimilar to the previous wave [Industrial Revolution] but the difference is that now we will have software helping us predict when and what will go wrong with any piece of equipment, where to intervene before an outage occurs, how to plan around it and thus eliminate outages or stoppages in production.
The most powerful characteristic of this new wave of relationships, however, is the global brain. This is probably where you have the closest interaction and cooperation between minds and machines. And this is because on top of having humans leverage the computing power of machines, we are also now leveraging the ability that machines have to put humans in contact with each other.
In terms of software development this has been going on for a while. But when you look at industry, we’ve been dipping our feet into it so far. Yet it is equally powerful. I think we will see a big acceleration in this over the next 20-30 years, with business and governments exploring how to create the right incentive structures for people to cooperate in a way that rewards open innovation and that safeguards intellectual property.
Last but not least is progress in advanced manufacturing techniques. This is another form of the evolution of this new phase of mind and machine interaction, and it has a different kind of power. These techniques allow you — and by you I mean the engineer, the scientist, the thinking brain of the machine — to start figuring out completely new products that are smart by design rather than smartened by having sensors added on top of them. I think this is another area where we will see enormous progress over the next 20 years.
…once you start making industrial machines and supply chains more intelligent through data and sensors, what you get is a more efficient and productive economy,
In many ways we are just at beginning of this new innovation wave. How long do you expect the transition will take to complete? And what do we need to get there?
It took a period of 100-150 years for the Industrial Revolution to unfold. Getting to the top of the current wave of innovation is going to take longer, because it is a much more complex an evolution than the Industrial Revolution.
We started decades ago with creation of computers, but I think it’s going to take probably another 50-100 years before we reach the top of this wave. That is not to say that the next 5, 10 years will not see anything meaningful — they will — but some of the innovations we have discussed, including 3D printing and 4D printing, are really at the beginning in terms of interesting applications. This is going to be a long and productive ride.
In terms of what needs to happen to get there, there are different things. An obvious one is infrastructure investments — both in physical and digital infrastructure. In my opinion, however, it will be much more important to invest in education.
Prior to the crisis, there was a widespread feeling — especially in advanced economies — that it didn’t matter what you studied, you would get a great job and be employed in a high‑paying job for the rest of your life. As machines become more powerful on the information data intelligence front, however, it is becoming clearer that we need to better understand what skills humans need to have the best possible compatibility with the machines.
This means raising the bar on STEM (science, technology, engineering and mathematics) qualifications, but it also means focusing education systems on creativity, flexibility and adaptability. In other words, to engage in this new phase of innovation, minds need to come first, then machines.
Part two of this interview with Dr Marco Annunziata will be available on Friday, September 25th and will focus on the next wave of innovation, how US and China are are handling the technological shift, and how we can best prepare for the next wave of innovation. Follow @GELookahead on Twitter to join the conversation.
This article first appeared on GE LookAhead. Publication does not imply endorsement of views by the World Economic Forum.
To keep up with the Agenda subscribe to our weekly newsletter.
Author: Dr. Elie Chachoua is an expert in strategic and multidisciplinary research.
Image: A visitor tests an exoskeleton from CEA during the Innorobo 2014 fair. REUTERS/Robert Pratta.