Disrupting the world order

Talking Heads Podcast with Professor Athanasios Platias

Sophie Dimopoulou: Hello, and welcome to the BNP Paribas Asset Management Talking Heads podcast. Every week, Talking Heads will bring you in-depth insights and analysis on the topics that really matter to investors. In this episode, we will be discussing disruption from geopolitics, technology and AI (artificial intelligence).

I’m Sophie Dimopoulou, Head of External Distribution for Luxembourg, and I’m joined by Professor Athanasios Platias, Professor Emeritus of Strategy at the University of Piraeus in Greece, and President of the Council of International Relations Greece, an Athens-based think tank.

And of course, I’m joined by Daniel Morris, our Chief Market Strategist. Welcome, gentlemen, and thanks for joining me.

Professor Platias: Hi, Sophie. Thank you for the invitation.

Daniel Morris: Likewise.

SD: So, I will start with you, Professor Platias. The international system we’ve seen that has been disrupted. Is this a bargaining trick? Is it a ‘Trump thing’, or is it more structural?

Prof. P: Well, as [Canadian Prime Minister, Mark] Carney said in Davos, it’s disruption. I mean, the post-world order, the so-called rule-based order, is over. We are entering a period of strategic competition, geopolitical competition, with changes in the power distribution and power transition.

I mean, now we have the rise of China that is challenging the United States, and at the same time, we have power diffusion in several important mid-powers that play [a] tremendous role in the region. So, the system is undergoing – at the same time – power transition and power diffusion, and this creates instability.

The old rules don’t apply. Everything that, during globalisation, connected East and West, now it’s weaponised. We are in a period of weaponisation of technology, of trade, of supply chains, of energy. All these create a very competitive, fragmented and disruptive international system.

SD: Thank you very much for that. Now, Daniel, a question for you. If globalisation is giving way to fragmentation and strategic autonomy, which regions and sectors are likely to emerge as the long-term winners of this new investment regime?

DM: Well, I have to perhaps acknowledge an American bias before, before I give my response.

But we on [the] one hand see where the source of the disruption has been – clearly from the United States – and to the degree that this has been instigated by the US, you might argue that that gives it some advantage. If we think about how Europe has responded to the challenges from a macroeconomic and from a market point of view, which is where my area of expertise is, I think we probably would see that response so far as being somewhat lacking.

The conclusion has been that Europe needs to be more autonomous. That’s been pretty clear now for a while. And it has been taking steps. There’s a big initiative now to increase defence spending within Europe to increase autonomy across a whole host of sectors.

So, the words are there, the efforts are there. I think the biggest challenge ultimately is going to be the source of the money to pay for all of this. There are a lot of parallels with the need globally, but certainly within Europe also to finance a green transition, which is also going to  require significant sums of money.

So, clear objectives for Europe, a question about having the means to achieve those ends. The US, with its very flexible economy, flexible labour force, is well positioned to adjust to the changes we see coming.

And then of course, we always wonder about and try to predict how China is going to be able to take advantage of this environment. It’s often noted that [the] Chinese tend to have a much longer time horizon than the West, and I would imagine that’s true to some degree.

At the same time, flexibility does seem quite critical in all of this. Whether or not the current economic system in China can show that flexibility is going to be a fundamental question.

SD: Thank you, Daniel. Professor Platias, we have geopolitical disruption. What are the internal effects? How can we compare that, for example, with effects that nuclear weapons had in the past?

Prof. P: You mean the disruption that came from technology, mostly from artificial intelligence?

SD: Yes.

Prof. P: Well, you cannot really compare it with nuclear weapons because nuclear weapons [was] a revolution in strategic affairs. It created destruction huge and placed it in a very small device. This created preconditions for deterrence and mutual assured destruction, and therefore it produced stability.

Artificial intelligence, is something else. [It] does not touch only one element, for example, military power. It touch[es] economic competitiveness. It touch[es] geopolitical power. Actually, it touch[es] whole state power. The historical analogy in my mind is the Industrial Revolution – the technology that was generated there and the economic prosperity, but also the military power [that] propelled the West in[to] dominance in the international system for centuries.

So that’s what we are observing right now, and this has geopolitical but also internal effects. Before I get into the internal effect, let me say that in the US-China competition, the technological competition in artificial intelligence is central. To be competitive in artificial intelligence, you need several layers.

You need energy, hardware, software, the algorithms. You need talent, of course, to power all these things. And at the same time, you need capital. Mr. Morris referred to capital before on clean energy, but the demands of capital for artificial intelligence are bigger. I mean, I estimate that this year American firms will invest at least four hundred billion [dollars] in artificial intelligence.

And also State policies, from regulation to incentives or disincentives. Along this area, the United States has some advantages. China has other advantages. So, the competition there is taking place. We don’t have a clear winner, but definitely the US is in front in this competition in term of energy, in terms of talent, in terms of financial resources. You have all Silicon Valley throwing money into this operation.

Now, coming to the destructive domestic effects, I think they are going to be huge. All technological disruption before –agricultural disruption, industrial disruption – created displacement of labour. And until this labour was utilised again, we had huge time lags, and these time lags created instability.

In this case, the losers will not be labour. It’s not going to be workers. It’s going to be [the] middle class – lawyers, consultants – and this middle class is the basis of democracy. So, you will have disruption at this level and at the same time, huge inequality of wealth.

The ones that take advantage of this will concentrate tremendous power. The rest – most of the middle class – will be losers. So, for example, the rise of communism and fascism was to some extent a response to this disruption or the 1848 revolutions in Europe.

So you see these kinds of transitions and disruptions create domestic political effects, and I expect them to come in this case.

SD: Thank you very much. A question for you, Daniel, on the same subject. Do you believe that AI will ultimately prove deflationary through productivity gains or inflationary because of the enormous investment required in computing power energy infrastructure?

DM: Well, the simplest answer is to say both, and [it’s] probably more a question of timing than anything else. I think we appreciate that it’s primarily inflationary in the short term. [We] could say it’s inflationary for semiconductor prices and the stock prices of companies that produce the semiconductors.

Inflationary to a degree, then, for the equity market because of the significant demand that we’re seeing. The professor mentioned the $400 billion that’s going to be spent just this year. Clearly, this has an effect not only on semiconductor production, but on energy demand and so on.

So clearly inflationary in the short term, but it really should prove to be disinflationary to the degree you see an increase in productivity. From a macroeconomic point of view, that’s a good thing. Normally, increased productivity is one of the things that we want the most. We look back to the internet revolution and believe that ultimately that did increase the rate of productivity growth globally, but certainly in the US, and all for the good.

I think the questions in terms of worries about the future are two-fold. Number one, how quickly it happens. If we talk about creative destruction, clearly this isn’t the first time you’ve had a new technology but will the disruption from AI be so rapid that society really doesn’t have time to adjust to it – provide employment for the people that will lose their jobs?

So, a very critical question and even more so when we appreciate everything just seems to be happening so much more quickly now than it did in the past. And then finally, if things do go too quickly, you have a large number of people that lose their jobs. That’s going to have a big impact on consumer demand.

Does economic growth fall simply because if people aren’t employed, they don’t have wages [and] they’re not going to be consuming so much? You could have all the productivity gains that you want, but you’d have a collapse in consumer demand. So, a lot of uncertainties. One comforting thing is that this isn’t the first time this has happened historically, but at the same time it really does seem to be different this time.

Prof. P: If I can add one dimension: inequality. Inequality not only internally, but at the international system [level], because very few states have the capacity to invest so heavily in artificial intelligence, for example, [the] United States, China. The Europeans are lagging, but look [at] the rest. So actually, one of the trends we are going to see is that inequality among states will increase rather than decrease. The usual analysis is that we are going in[to] a multipolar international system.

But certainly, this technology is actually driving mostly the two superpowers that have the resources to invest on it. Let me give you one example. One, just one company, NVIDIA, has capitalisation of about $5.5 trillion. The GDP of Japan, of India, of Germany [is] around $4 trillion. So, you could see how wealth is generated and how it’s distributed unequally among states, but also within states. And this is a huge disruption.

SD: Well, gentlemen, thank you very much for joining me.

Prof. P: Thank you for the questions.

DM: It was a pleasure.

SD: That’s it for this week’s episode of Talking Heads. If you would like to receive more of our thought leadership, please reach out to your asset management contact or check out Viewpoint, our website for investment insights at viewpoint.bnpparibas-am.com.

You’ve been listening to the BNP Paribas Asset Management Talking Heads podcast with me – Sophie Dimopoulou, Head of External Distribution for Luxembourg, Professor Athanasios Platias from University of Pireus, and Daniel Morris, Chief Market Strategist.

Please do join us next week. Until then, take care.