An interview with Manuel Muñiz, Dean of the School of Global and Public Affairs at IE University
Alexander Görlach: The disruption through technology is ubiquitous. I would argue it is always the prerogative of any societal change. Is there a difference today compared to previous disruptive eras?
Manuel Muñiz: I would argue that the difference is the velocity of change. We have seen an increase in the rate of change in a number of dimensions. For example, on data generation. We produced more data as a civilization in the last two years than in the last 20,000.
We are also seeing fundamental shifts in the economic model and in production processes. We’ve seen very deep changes in the life sciences space; from genetic engineering to organ printing to the development of brain-machine interfaces. So I think that the big difference with instances of the past is that today what we have is a very, very rapid process of transformation. This is posing an enormous governance challenge. It is a challenge at the individual level; it’s hard for individuals to govern that change personally, to imagine their future and navigate it. This is also creating enormous societal challenges.
Alexander Görlach: Alvin Toffler wrote half a century ago in his book Future Shock that in times when technological progress is advancing exponentially, it also shocks the elites in society so much that they retreat from the job of being the explainer of the future and become doomsday prophets. It that what we see right now – or would you say the leadership crisis in managing the new disruptive technological wave has different reasons?
Manuel Muñiz: I believe that the key framework to understand what is happening is that of “rigidity” or “flexibility”. Rigid systems are ones that need to accrue very large amounts of pressure before they adapt and become sustainable again. So a rigid political system would require very high levels of social and economic pain to accumulate in particular points before it moves to a new equilibrium.
What I see when I look at current elites is a high dosage of rigidity. Political elites find it hard to grapple with the notion of exponential transformation and it’s difficult for them to understand the full extent of the negative externalities of rapid technological transformation. Therefore, it is hard for these elites to craft a policy of solutions to some of these challenges.
You will also find a great deal of rigidity in economic elites. This is manifested in their inability to bridge the gap between the clearly noticeable social fracture and what they can do as business leaders, big employers, and others. It is in this latter capacity that they are pushed for greater margins, for profitability, and efficiency. So they are the ones that are automating jobs. Yet these firms and their management are assessed on the basis of profits they generate. That’s the criteria that determine their access to financial markets. That’s also their corporate culture. It is also how investors assess their investments, on the basis of profitability. There’s an entire incentive structure within the private sector by which these elites both abide and also reinforce that contributes to the overall rigidity of the system.
On academic or intellectual elites: there’s a great deal of rigidity in that field as well. One thing I find to be of particular concern is the notion that knowledge is acquired by looking backwards. This is right at the heart of how we have constructed our notions of truth and of academic inquiry. You get your doctorate by studying the past and extracting knowledge from it. You do not get a PhD or tenure by projecting into the future; that is almost intellectual sacrilege.
I think this is due to the fact that our academic institutions were founded at a time when looking at the past was extremely useful, because it not only provided us with answers about what happened decades ago but also because the present and the future looked very similar to the past. The world was not changing as quickly as it is today.
I believe that we need to develop a true science of anticipation. We need to be able to craft scenarios and depict trends to try to adjust and adapt in an anticipatory manner to the changes that are coming. That requires a very fundamental shift in the value we give to the exercise of foresight. People equate that to prediction and that is highly problematic in the academic environment. However, I am not speaking about prediction, I am speaking about scenario planning and crafting paths and worlds, assessing their implications and the challenges that they might bring.
To wrap up, I would rather look at the issue of elites through the lens of whether they are contributing flexibility or rigidity to the system. I fear at the current moment most of these elites are part of machinery that produces great doses of rigidity.
…our academic institutions were founded at a time when looking at the past was extremely useful, because it not only provided us with answers about what happened decades ago but also because the present and the future looked very similar to the past. The world was not changing as quickly as it is today.
Alexander Görlach: The turmoil regarding leadership and the uncertainty regarding the future of our societies and the workforce, in my opinion, stems from data that doesn’t give us a conclusive picture. Is there really a rise of inequality in democratic societies due to rising productivity and stagnating household income? I suppose the devil is in the detail.
Manuel Muñiz: We have a real avalanche of evidence that the middle class has stagnated in economic terms in most advanced economies for the last three decades. This is now being confirmed by the OECD and by numerous studies. In the US alone, seventy percent of households saw no real market increase over the last three decades. That stagnation of the middle has also produced not only the sense of the lack of economic intergenerational progress, which is toxic enough, but it has produced a spike in inequality.
In fact, in the aggregate, most of these countries have grown very markedly over the last 30 years. So if you have growth in the aggregate but you have a stagnating middle, then quite clearly a small group of people is capturing most of the economic growth. That’s what’s happened in the US and in most European economies.
For example, from 2009 to 2012, which was a period of economic recovery in the US after the financial crisis, ninety-five percent of all income gains went to the top 1% of income earners in the US, with the remaining 5% going to the 99%. In the aggregate, this is producing something which is quite astonishing, the decoupling of productivity and labor wages. We have seen this again in most advanced economies. We have found a way to increase productivity without increasing wages, without employing more people or paying people better. On the other side of that coin is a concentration of income in capital income earners and a decline of labor income share within the economy.
So the erosion of the redistributive capacity of wages is something that we witnessed across the board. There is something to the economic model that has really shifted. My explanation is that technological change and its impact on the labor market can explain these changes. It’s not just technology but technology is the major factor. If you take it out of the equation it is almost impossible to explain these trends and it is the impact of technology and production processes.
Alexander Görlach: If we look globally, Europe seems to be “sandwiched” between the US and China, both having different approaches to the new digital economy than the old world. Do you see any path that Europe could go that is different from its competitors yet still appealing to its own citizenry and investors from abroad?
Manuel Muñiz: You are absolutely right, we are quickly moving towards a G2 world in the space of technology. If you look at the top 20 largest technology Internet companies in the world, you won’t find a single European firm. If you look at the concentration of tech unicorns, startups with over a billion worth, they’re mostly in the US and China. Europe is missing from that map.
So we’re falling behind in terms of innovation; particularly in terms of digital technologies. We have to ask ourselves, why is that the case? The answer is complex and there are many factors that go into it, but I think we are still missing a truly well-structured and connected applied research fabric that can serve as a transfer platform towards the markets and societies. We’re not seeing a strong technological transfer from the research landscape to the market.
I think it also has something to do with the scale of our market in Europe; we do not have a single digital market. Entrepreneurs want to operate at a European level but they still need to operate in different languages and suffer different regulations, different tax burdens, etc. I think that’s a major issue because in the digital space, scale in everything. Simply put, if you don’t have a large market it puts you at a huge disadvantage.
When it comes to US and Chinese companies, they have enormous markets that they can operate in. So, I would argue that these are perhaps the two main constraints: the lack of transfer platforms and the scale of our market.
The other issue to raise is that I think there is a European model to innovation and regulation of these emerging technologies. I think GDPR is a very good example of how this can be manifested in the privacy space. So we do not think that it’s either the state as it would be in China that should be able to aggregate all this data and have access to it, and we do not think that it should be private corporations that have access either. We think that this data is the property of the people that produce it and that it needs to be protected and safeguarded. GDPR is the first step in that direction.
I would argue that we as Europeans have very strong views of other types of innovation, particularly in the health space where the ethical issues are so enormous. My hope is that the new EU Commission has this as a central objective and develops a European strategy for technology and innovation that positions us as the frontier of technological innovation. This will provide us not only with high-quality jobs and fiscal traction over some of the most profitable businesses in the world but it would also give us normative, regulatory power so that we can in fact shape how technology is regulated moving forward and to pin that regulation.
There is something to the economic model that has really shifted. My explanation is that technological change and its impact on the labor market can explain these changes. It’s not just technology but technology is the major factor. If you take it out of the equation it is almost impossible to explain these trends and it is the impact of technology and production processes.
Alexander Görlach: What are the most pressing ethical implications arising from the new possibilities that AI and big data provide?
Manuel Muñiz: I would point to developments in the health care space because I think those are the ones that are more ethically fraught. If you think, for example, about the implications of genetic selection, which is something that we are currently doing in many places. In the US, you will be allowed to do pre-implantation embryo selection on the basis of negative selection of pathologies. Both parents would have these genetic panels run for them by the hospital and these panels would provide information about over 90 pathologies that have a very clear genetic marking.
If both parents are carriers of one of these conditions, they will be allowed to go through IVF to produce a panel of embryos and select the embryo that is not a carrier of these conditions. Some of these pathologies are as severe as spina bifida or cystic fibrosis. These diseases are atrocious for both the patients and their families. This list of 90 pathologies used to be limited to just 25 five years ago, so our knowledge of genetic screening, in general, is leading to a great deal of sophistication in this space. In ten years it will be 200 pathologies or 2,000 pathologies rather than just 90.
What this is producing is a huge ethical iniquity question. The people that have the capacity to access these processes and technologies will have children that will not bear these diseases and will be better equipped to deal with life. That’s going to make a very big difference, right?
You’re going to start seeing in the US, for example, communities where the disease burden of some of these pathologies is much greater and others where it’s much less. I think the health care space is where the big ethical questions will arise.
Genetic selection and how it is done today is still a fairly simplistic way: through genetic panels and genetic selection of embryos pre-implantation. But you can imagine a future where this will be done through genetic engineering and it won’t just be negative selection. We won’t be just selecting against pathologies, but we will, in fact, be selecting in favor of certain traits. And again, people with sufficient resources will access this technology early on and this will produce a very segregated society, with some people having a very different set of talents compared to others.
This could mean the end of the equality of opportunity as we have known it and it could really ossify economic hierarchies from one generation to the next. People with resources would make sure that the following generation will be better equipped to deal with life and its challenges. So I think that’s the area where we should focus most of our attention.