1“Artificial intelligence is the future... Whoever becomes the leader in this sphere will become the ruler of the world,” declared Vladimir Putin, speaking before a group of Russian students and journalists in September 2017. Three days later, Elon Musk, founder of SpaceX and Tesla, went even further in a tweet: “Competition for AI superiority at national level most likely cause of WW3 imo [in my opinion].”

2The rapid progress of AI makes it a powerful tool from the economic, political, and military standpoints. Embedded in the digital revolution, AI will help determine the international order for decades to come, accentuating and accelerating the dynamics of an old cycle in which technology and power reinforce one another. It will transform certain axioms of geopolitics through new relations between territories, space-time dimensions, and immateriality.

3The American and Chinese digital empires will probably dominate international geopolitics in the years to come. If Europe wants to rebuild its digital sovereignty, it will have to redouble its efforts and investments. Otherwise, Europe will have to be satisfied with strategic alliances that entail its “cyber-vassalization.” As for Africa, it already presents a vast battleground, clearly threatened with “cyber-colonization.”

What is artificial intelligence?

4AI does not have a universally accepted definition. Although it is firmly rooted in the field of computing and was consubstantial with its emergence in the 1940s, today it refers to a broad range of disciplines, technologies, and methods. The co-author of the textbook Artificial Intelligence: A Modern Approach, Stuart Russell, a professor at the University of California, Berkeley, defines AI as “the study of methods for making computers behave intelligently.” For him, AI includes tasks such as learning, reasoning, planning, perception, language understanding, and robotics. [1]

5AI is thus a more generic term than it seems: in fact, it is a collective imaginary onto which we project our hopes and our fears. The technologies of AI include, among others, machine learning, computer vision, intelligent robotics, biometrics, swarm intelligence, virtual agents, natural language processing, and semantic technology. These technologies are of course not mutually exclusive.

AI and the return of empires

6Can we, at present, analyze the rise to power of what could be called “digital empires?” These are the result of an association between multinationals, supported or controlled to varying degrees by the states that financed the development of the technoscientific bases on which these companies could innovate and thrive.

7Historically, empires have been characterized by three principal features: 1) the exercise of power over a wide territory; 2) a relative inequality between the central power and the administered “regions,” often associated with a will to expand; 3) the implementation of a political project through various forms of influence (economic, institutional, and ideological). [2]

8Contrary to the common notion according to which the digital revolution necessarily involves economic decentralization, it is actually possible that AI may cause, or reinforce, an overall trend toward the centralization of power in the hands of a few actors. These digital empires would benefit from economies of scale and the acceleration of their concentration of power in the economic, military, and political fields thanks to AI. They would become the major poles governing the totality of international affairs, returning to a “logic of blocs.” These new public-private digital empires would extend to the continental scale, especially in the case of the American and Chinese empires, while other actors, such as Europe, would adopt strategies of non-alignment.

The convergence of big data, computing power, and machine learning

9AI is propelled by the convergence and industrial maturity of three main techno-scientific tendencies: big data (the power to process enormous quantities of data, produced by the human internet and the Internet of Things), machine learning (the ability of computers to learn), and high-performance cloud computing. Although AI has been a field of study for more than half a century, the acceleration of the increase in computing power and the recent availability of massive stores and flows of digital data has made possible the deployment of very powerful solutions based on machine learning.

10It would be tempting to think that AI is a neutral tool, but it is not situated in a vacuum devoid of human interests. Big data, computing power, and machine learning in fact form a complex socio-technical system in which human beings have played and will continue to play a central part. Thus, it is not really a matter of “artificial” intelligence but rather of “collective” intelligence, involving increasingly massive, interdependent, and open communities of actors with power dynamics of their own.

11Teams of engineers construct vast sets of data (produced by each and all: consumers, salesmen, workers, users, citizens, etc.), design, test, and parameter algorithms, interpret the results, and determine how they are implemented in our societies. Equipped with telephones and ever more interconnected “intelligent” objects, billions of people use AI every day, thus participating in the training and development of its cognitive capacities.

The platform, data, media triad

12Specific and mature business models at the industrial level underlie the convergence between big data, computing power, and machine learning. What sets apart the giants in this sector—whether American (GAFAMI [3]) or Chinese (BHATX [4])—is more their innovative economic model, where the customer (and not the product) holds a central place, than the technological solutions they offer.

13For the majority of these companies, the product is free or inexpensive (for example, the use of a search engine or a social network). As in the media economy, the essential thing for these platforms is to invent solutions that mobilize the “available human brain time” of the users, by optimizing their experience, in order to transform attention into engagement, and engagement into direct or indirect incomes. [5] In addition to concentrating on the attention of the users, the big platforms use their data as raw material. These data are analyzed to profile and better understand users in order to present them with personalized products, services, and experiences at the right time.

14We will first distinguish the groups that initially propose the sale of products and services (Apple, Alibaba, Amazon, Huawei, Microsoft, Xiaomi, IBM) or recommend products and services for sale online. For the others, it is a matter of exploiting users’ data in order to sell them various commercial services (Baidu, Tencent, Facebook, Google). The economic model of these companies also relies on the close interweaving of their highly variegated activities into a coherent unity. For example, the instant messaging and payment service, WeChat, the primary application of Tencent, is used by 500 million Chinese. It interferes with the functionalities of Facebook, Twitter, Instagram, Paypal, WhatsApp, and even of the dating app, Tinder…

15The research of Tristan Harris, former Google engineer and creator of the Center for Humane Technology, has denounced certain excesses of the big platforms. [6] Even if their products have unquestionably benefited users worldwide, these companies are also engaged in a zero-sum contest to capture our attention, which they need to monetize their products. Constantly forced to surpass their competitors, the various platforms depend on the latest advances in the neurosciences to deploy increasingly persuasive and addictive techniques, all in order to keep users glued to their screens. By doing this, they influence our perception of reality, our choices and behaviors, in a powerful and as yet completely unregulated form of soft power.

16The development of AI and its worldwide use are thus constitutive of a type of power making it possible, by non-coercive means, to influence actors’ behavior or even their definition of their own interests. [7] In this sense, one can thus speak of a “political project” on the part of the digital empires, commingled with the mere quest for profit.

Convergence of network effects, economies of scale, and winner-takes-most

17Along with critical masses of data and the processing capacities necessary for machine learning, AI’s rise to power almost necessarily sets in motion a market dynamic that is monopolistic within a given economic area, and oligopolistic on the global level. We thus witness a centralization of digital power in the hands of these digital empires.

18The development of AI corresponds to the dynamics of economies of scale and scope, as well as to the effects of direct and indirect networks: the digital mega-platforms are in a position to collect and structure more data on consumers, and to attract and finance the rare talents capable of mastering the most advanced functions of AI. [8] These platforms can also give these talents access to processing power and user bases of a size sufficient to develop their AI capacities even further.

19The machine learning algorithms used in certain applications are also transferable to others within the framework of a discipline called “transfer learning,” which favors the established actors even more. In fact, AlphaZero, developed by Google DeepMind on the basis of the AlphaGo program, learned the game of Go only by playing against itself, without human experts training it; then it succeeded in beating the best computers at chess and shogi thanks to the dynamics of transfer learning.

20The current domination of the world market by GAFAMI and BHATX arises—naturally, to a certain extent—from the components necessary to the development of AI within the framework of the digital economy. [9] This logic will necessarily be accentuated by the continuing process of convergence between hardware and software, which pushes operators to turn to the development of their own solutions and critical components. This centralization of digital power around a few actors characterizes a new form of digital empire.

Can we speak of a cyber-colonialism?

21After the example of past empires, these platforms concentrate resources and seek to extend their sphere of influence. Cédric Villani, mathematician and parliamentarian, was charged by Prime Minister Edouard Philippe with a fact-finding mission on artificial intelligence. His report, submitted in March 2018, explains: “There is a danger of a capture of value and competency by foreign institutions. To some extent, this has already taken place in France: the big platforms are the French government’s number one candidates for the development of artificial intelligence.” Cédric Villani also declared, in connection with the investments of the big platforms in Africa—such as Google, Facebook or Alibaba: “These big platforms capture all the added value: the value of the brains they recruit, and that of the applications and services, by the data that they absorb. The word is very brutal, but technically it is a colonial kind of procedure: you exploit a local resource by setting up a system that attracts the value added to your economy. That is what is called cyber-colonization.” [10]

22Laurent Alexandre, entrepreneur and specialist in matters of artificial intelligence, stresses that French and European companies are lagging behind at the global level, recalling that they “barely reach $1 billion of capitalization, while GAFA will soon be worth $1000 billion each.” [11] In August 2018, the stock market capitalization of Apple exceeded $1,000 billion, the equivalent of the capitalization of the first ten companies on the CAC40.

A clear question of sovereignty for governments

23National actors are increasingly aware of the strategic, economic, and military stakes of the development of AI. They also anticipate its impact on elections, as demonstrated by interference in the United States’ presidential election of 2016, and in the referendum on Brexit.

24In the past 15 months, France, Canada, China, Denmark, the European Commission, Finland, India, Italy, Japan, Mexico, the Scandinavian and Baltic region, Singapore, South Korea, Sweden, Taiwan, the United Arab Emirates, and the United Kingdom have all unveiled strategies for promoting the use and development of AI. These strategies variously address education, research and development, digital infrastructures, public services, and ethics. Not all countries can aspire to leadership in this sphere. Rather, it is a matter of identifying and constructing comparative advantages, and of meeting the nation’s specific needs. Some states concentrate on scientific research, others on the cultivation of talent and education, still others on the adoption of AI in administration, or on ethics and inclusion. [12]

25Among the actors who are characterized by their aspiration to global leadership are the United States and China, but also the European Union. Smaller actors such as France, the United Kingdom, and Canada also have an ambitious strategy and are making significant investments in AI. Other countries are specializing in particular aspects of AI, following a niche strategy. India, for example, wants to become an “AI garage” by specializing in applications specific to developing countries. [13] Poland is exploring aspects related to cybersecurity and military uses. The government of the United Arab Emirates launched its AI strategy in October 2017, creating the world’s first artificial intelligence ministry, with the use of AI to improve its performance and efficiency as its principal objective. [14]

An American-Chinese duopoly

26Today, the United States and China form a kind of AI duopoly based on the critical dimensions of their markets and their laissez-faire policies regarding personal data protection. [15] Their competition is illustrated in particular in a trade war that began with the imposition by the Trump administration of a 25% tariff on Chinese goods (including some concerning AI), [16] representing a total value of $34 billion, in response to what Donald Trump calls the “theft” of intellectual property and technologies. [17] China retaliated by imposing 25% tariffs on 540 American products. Additionally, in August 2017, the United States launched an investigation against China, accusing it of unfair commercial practices regarding intellectual property, particularly in the area of technology. [18]

27China’s “Sputnik moment” arrived in March 2016, when South Korean Go champion Lee Sedol was defeated by DeepMind’s artificial intelligence program, AlphaGo. In July 2017, Beijing publicized an especially ambitious national strategy aiming to reach a market estimated at $15,700 billion in 2030. [19] It intends to “become the ‘primary’ center for AI innovation by 2030.” [20]

28In line with this policy, closely directed at the highest levels of the state, the Chinese technological ecosystem will pursue an offensive strategy of investments in and reinforcement of AI capabilities. Alibaba, for example, invested $15 billion in research and development (R&D) [21]—a figure comparable with those of the American giants: Amazon invested $16.1 billion in R&D in 2017. [22] AI is advancing rapidly; Chinese teams, for example, won the ImageNet visual recognition competition two years in a row, in 2016 and 2017.

29China has also integrated the digital and AI into its geopolitical strategy. Since 2016, its “Belt & Road” initiative for the construction of infrastructures connecting Asia, Africa, and Europe has included a digital component under the “Digital Belt and Road” program. The program’s latest advance was the creation of a new international center of excellence for “Digital Silk Roads” in Thailand, in February 2018. [23]

30Following the voluntarist approach of the Obama administration, that of President Trump seems to be one of laissez-faire. In May 2018, the White House stated four objectives: 1) maintaining American leadership in AI, 2) supporting American workers, 3) supporting national R&D efforts, and 4) eliminating obstacles to innovation. [24] Although China profits from a comparative advantage in the mass of available data—it projects possessing 30% of the world’s data until 2030—and from more permissive regulations on its use, it lags behind the United States in regard to talent. In spite of a greater number of graduates in the sciences, technology, engineering, and mathematics, China has only approximately 39,000 researchers in AI, that is to say, half the American pool of more than 78,000 researchers. [25] In addition, in spite of considerable efforts over several decades, China has remained dependent on the United States for the development of processors and chips, in particular the Graphics Processing Units, critical to machine learning. [26]

Europe: The champion of ethics?

31Europe has fallen far behind China and the United States in techno-industrial terms. In 2013, a report issued by the French Senate expressed concern, witnessing the Old Continent becoming a “digital colony.” [27] The situation has not improved over the last five years. The European approach seems to consist in taking advantage of its market of 500 million consumers to provide the foundations of an ethical industrial model of AI, while renegotiating a de facto strategic partnership with the United States. Thus, in April 2018, when the European Commission published its AI strategy, the Swedish Minister for Digital Development declared: “We can’t expect China to do that [to establish ethical norms]. We have to do that. With a democracy and a legal system that works, Europe has to take that as the most important thing. The competition with China, the competition with the US, is of course important. But if we don’t create the legal and ethical framework, we will lose anyway.” [28]

32Europe lags behind in private investment in AI, which ran at approximately €2.4 – €3.2 billion in 2016, as compared to €6.5 – €9.7 billion in Asia and €12.1 – €18.6 billion in North America. [29] In spite of the size of its market—which has yet to be digitally integrated—with its recognized scientific excellence and entrepreneurial and creative vigor, there are few European “unicorns.” Their growth is retarded by the European market’s lack of a digital and capitalistic industrial surface. It is difficult, under these conditions, to prevent the purchase of European gems by the American and Chinese giants, as was the case for the British company DeepMind, a pioneer in the field of AI, bought by Google in 2014 for $500 million, or the purchase of Kuka, the prize gem of German robotics, by the Chinese electric household appliance giant Midea in 2016 for $4.5 billion.

33As Darty’s cofounder indicated in a recent opinion piece, [30] the AI revolution is perceived in Europe—more technophobic than China or the United States—as a wave coming from abroad that threatens its socio-economic model, to be protected against. Driven by dominant industrial actors that have not succeeded in carrying out their own digital transformation, Europeans seek to regulate the revolution of AI (to restrain it) instead of seeking to govern it (to guide it).

34A universalistic ambition is indeed present here, but it is more conservative than progressive. It results in the search for a European model of AI that ties together the reclamation of sovereignty and the quest for power with respect for human dignity. Balancing these three desiderata will not be easy: by regulating from a position of extreme weakness and industrial dependency in relation to the Americans or the Chinese, Europe is likely to block its own rise to power. This is the risk that the General Data Protection Regulation (GDPR) could pose to French and European ambitions for power.

35Sounding a possible but very relative alarm, the European Commission announced an increase in its investments in research and innovation in AI of €1.5 billion over the period 2018-2020, within the framework of the program Horizon 2020. The EU also approached Canada, a “non-bloc” power in the field of AI, to establish cooperation in scientific and technological research. [31]

Africa: The great battlefield?

36The African continent is practically virginal in terms of digital infrastructures oriented towards AI. The Kenyan government is to date the only one to develop a strategy in this respect. [32] However, Africa has enormous potential for exploring the applications of AI and inventing new business and service models. Chinese investments in Africa have intensified over the last decade, and China is currently the primary trade partner of the African nations, followed by India, France, the United States, and Germany. Africa is probably the continent where cyber-imperialisms are most evident.

37Examples of the Chinese industrial presence are numerous there: Transsion Holdings became the first smartphone company in Africa in 2017. [33] ZTE, the Chinese telecommunications giant, provides infrastructure to the Ethiopian government. CloudWalk Technology, a start-up based in Guangzhou, signed an agreement with the Zimbabwean government and will work in particular on facial recognition.

38A powerful cyber-colonialist phenomenon is at work here. Still traumatized by the liability of European colonization, Africa, confronted with the combined urgencies of development, demography, and the explosion of social inequalities (with which China is quite familiar), is embarking on a logical but very unequal techno-industrial partnership with China. As the Americans did to Europe after the war, China massively exports its solutions, its technologies, its standards, and the model of company that goes with these to Africa (while also providing massive financing).

39Enjoying a free field with respect to the Europeans, the American digital giants are mounting a counterattack. Google, for example, recently opened its first AI research center on the continent in Accra. [34] Moreover, the GAFAMI companies are multiplying startup incubators and support programs for the development of African talent.

40* * *

41AI is an instrument of power right now, and it will be increasingly so as its applications develop, particularly in the military field. However, focusing exclusively on hard power would be a mistake, insofar as AI exercises indirect cultural, commercial, and political influence over its users around the world. This soft power, which especially benefits the American and Chinese digital empires, poses major problems of ethics and governance.

42Henry Kissinger expressed his concerns about AI in The Atlantic in June 2018. In an article titled “How the Enlightenment Ends,” [35] he explains why human societies were not prepared for the rise of AI. Without naming it as such, he denounces the impact of AI on the American election campaign, speaking of the power to target micro-groups, particularly through social networks, and of the possibility of disrupting the shared sense of priorities. If AI makes it possible to influence voters in democratic countries, in authoritarian states, it can also reinforce the control of the populace.

43The big platforms must integrate these ethical and political concerns into their strategy. AI, like any technological revolution, offers great opportunities, but also presents—inextricably overlapping with these—many risks.