Lots of debates are revolving around big data being the “new oil”. Some might argue that it is slowly becoming the resource for which every country will fight in the future. Some might conversely consider that it is nothing compared to oil. Whatever the stance, it seems that big data have become a strategic stake many actors are ready to fight for.
This idea has been reinforced by the declaration made in 2017 by Russian President Vladimir Putin. Talking about artificial intelligence, President Putin indeed stated loud and clear that “[w]hoever becomes the leader in this sphere will become the ruler of the world”. Though, “[to] build great AI, you need data”. Indeed, AI relies heavily on massive data, especially in its deep learning dimension. Thus, it seems clear that massive data will provide whoever gets them a great advantage. Consequently, whoever wants to lead the world should first make sure to access as much data as possible to feed AI.
The strategic importance of big data
The United States and China have already understood the strategic importance of massive data flow, especially since they are fighting each other to take or keep the lead in AI.
The fact is that AI is a very promising market that no countries want to let escape. AI impacts all aspects of our lives, and its influence will keep growing creating new opportunities in the fields of employment, research and development, education, health, transportation, defense, finance, communication, end even agriculture and food, to mention but a few. AI is already there using the incredible flows of data to learn and improve itself.
“The amount of data we produce doubles every year. (…) Every minute we produce hundreds of thousands of Google searches and Facebook posts. These contain information that reveals how we think and feel. (…).”
That is a reality we have to accept and to adjust to. Here China is definitely favored. First, because with its massive population of 1.4 billion, and its 730 million Internet users, the country has access to a plethora of information. Second, given that China is not really into users’ privacy concerns, data are way easier to collect than in countries with legislation that protect citizens from intrusive personal data collection.
China’s “deep pool of data” will undoubtedly help the country to beat the U.S. and reach its goals, as stated in its 2017 Policy paper, to make AI the major driver for its industry by 2025, and to “occupy the commanding heights of artificial intelligence technology” by 2030. A quick glance at AI related figures makes it easy to understand why China is so aggressive and willing to lead in the field. According to a report by PwC, “The greatest gains from AI are likely to be in China (boost of up to 26% GDP in 2030) and North America (potential 14% boost)”. The whole world would be impacted with AI potentially contributing “up to $15.7 trillion to the global economy in 2030”. In order to fully benefit form AI, “the supply of data and how it’s used are set to become the primary asset”.
It is thus clear that data are the next generation of resource countries cannot allow themselves to ignore. More than that, they will certainly have to struggle for data.
Public actors are not alone in the big data arena, and many companies and private actors are eager to get more and more data, may it be to increase their sales by improving their marketing strategies, to be more specific in who they may target, or to offer new products precisely adjusted to their consumers’ needs. With big data goes along big money. This makes data a very valuable and profitable resource.
“[A]rtificial-intelligence (AI) techniques such as machine learning extract more value from data. Algorithms can predict when a customer is ready to buy, a jet-engine needs servicing or a person is at risk of a disease. Industrial giants such as GE and Siemens now sell themselves as data firms.”
Thus data are exceeding oil as a strategic value in some sectors, and they are not only an asset companies want to take over, they have also become a highly money-making product to sell.
As an illustration, the Czech Republic-based antivirus company Avast, of which software is used by 400 million people worldwide, has been selling its users’ data since 2013 to customers such as investors. The question is to know how much data are worth, and how their price will evolve along with the growing need for AI fuel. We have already entered a circle, may it be vicious or virtuous, for “[b]y collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on”.
Whatever, we think about it, data are here, and so is the competition to access them. Obviously this battle for data goes hand in hand with worries about their final use and users’ privacy. Yet, there are also many promising uses that counterbalance concerns.
Concerning or promising resource?
Public actors are just as much aware of the benefits of big data as private actors are. Obviously, their interest is to support economic activities of their industries and trade, may it be by fostering the use of data and AI by private companies. Money made by these companies leads to employment, consumption, taxes, and new investments, that in turn will benefit the society, and eventually governments. In that sense, supporting big data collection sounds positive and promising.
Big data also offer some other advantages to governments that want to keep a tight control over their population and its activities. The use of data, collected through facial recognition, by the Chinese government, is the perfect illustration of it. Yet, the use of personal data by states is not the privilege of China or any other country considered in the West as authoritarian and disreputable. Data collection is also at work in Europe and Northern America. Even when the practice is framed by legal norms, these data are nonetheless collected and might be used in ways, good or bad, we do not imagine.
In some places like Japan, data collection through networked cameras and sensors is even seen as a way to “improve quality of life”.
“Aside from making residents feel more secure about their loved ones, the crime rate in Kakogawa fell below the Hyogo Prefecture average for the first time in November 2018.”
It can also be an asset for countries experiencing shortage of manpower due to ageing population. Still in Japan, robots fitted with IA, will certainly fill the lack of employees in retirement homes, or even be used in fully automated stores that cannot be staffed with humans.
AI already has a huge importance in military operations such as in urban warfare where data collection allows ground troops or strategists to make smarter and quicker decisions. Robots sent on the field are able to provide essential data through surveillance, tracking, exploration and mapping of urban areas, environment modeling. Facial recognition would thus allow to discriminate between combatants and non-combatants, and consequently to avoid killing innocents.
The promises of AI are undoubtedly numerous. It can be used to teach machines how to perform dangerous or even boring tasks in place of humans; to be more efficient in our food consumption or production, and therefore to limit waste and trash released into the wild; to improve security by monitoring dangerous behavior and even predicting terrorism; to anticipate natural disasters; to help elders by offering them companions with which they will interact and escape loneliness; to increase logistic efficiency such as in so-called “smart-ports”; or even “cut collateral damages” at war.
Obviously, if we can be idealists, we must not be naive. The war for data will also lead to many concerning uses. Think about the Cambridge Analytica scandal. There private and public interests intersected and overlapped, and obviously data were used in a way voters could not foresee, namely “to manipulate elections by smearing candidates with fabricated news stories in order to swing elections to the candidates it favors”. That did not happen in China, neither in Russia, or any other country applying disputable politics.
The giant tech companies, the so-called GAFAM (Google, Apple, Facebooks, Amazon, Microsoft), as well as their Chinese counterparts, the BATX (Baidu, Alibaba, Tencent, Xiaomi), are collecting, generating, storing and processing a gigantic quantity of data for better or for worth.
Countries such as China and the U.S. that affirm a strong will to be leaders in the artificial intelligence sector, will undoubtedly do whatever it needs to reach their goals. There is no way, given all that is at stake, that they will constrain themselves. Beijing and Washington do want to keep the lion’s share of this humongous cake. Other pretenders, such as France, the United Kingdom, Canada or Germany, are eagerly awaiting to seize some pieces of it. The struggle will be as tough as the struggle for oil has been for decades.
Data are the fuel of AI. They are a strategic asset for companies. As Mick Lévy puts it, “making this asset more productive, is the key issue” for the coming years. Data might not be the “new oil” strictly speaking. Nonetheless, it has become a strategic resource that will shape the future of humanity. Our reliance on technology and AI will make data even more strategic and subject to a lucrative trade. In that sense, the comparison with oil remains relevant. We need oil as much as we will, if not already, need data. So now, “there’s a serious question of how much some of this data is worth”. The answer to this question will shape the battle for data.
We need to accept that big data are some kind of “new oil”. The point here is not the label, but its significance. Data are already a strategic resource, as oil is. They will become more and more strategic as AI will evolve and will need to be fed with an ever-growing amount of data. Large parts of human activities will rely on AI, which in turn will rely on still bigger flows of data.
We must free ourselves form the Manichean assessment of the potentialities of big data. As with oil, there will be good consequences as well as bad ones. As for oil, there will be morally acceptable uses of them, and morally unacceptable ones. As for oil there will be leaders that will set the rules, and followers that will apply them. As for oil, our dependence toward data will be such that whatever the risks we will still use them. Call it progress or decline, AI is shaping the world and data are its fuel. Whoever wants to rule the world in the coming years will need to use AI and, consequently, access massive amounts of data. That will be the moral compass for many actors on the international scene for the years to come.
If there are legitimate concerns about the way data are to be used both by private and public actors, it is yet worth stressing that “there are myriad ways in which all this data can (and does) improve the world”. Even President Putin statement highlighted the fact that AI “is the future, not only for Russia, but for all humankind, and that “[i]t comes with colossal opportunities”. AI being fueled by big data, one can easily infer that data is the door toward these opportunities. “Oil causes pollution, yet it was also responsible for lifting a large majority of the population of the world out of dire poverty.” The perspectives open by big data are of the same kind: concerning and promising at the same time.
If oil has been years ago labeled the “black gold”, it seems definitely fair to label data as “digital oil”. And yes, data are the new strategic resource everyone will fight for. They are the new oil.
 Vladimir Putin, “Speech by the President of the Russian Federation to students for the start of the school year. Opening lesson”, Yaroslavi, Russian Federation, Sept 1, 2017.
 James Vincent, “China and the US are battling to become the world’s first AI superpower”, The Verge, August 3, 2017.
 Dirk Helbing et al., “Will democracy survive big data and artificial intelligence?”, Towards digital enlightenment. Springer, Cham, 2019, pp. 73-98.
 “China may match or beat America in AI”, The Economist, July 15, 2017.
 Chinese State Council, Notice of the State Council Issuing the New Generation of Artificial Intelligence Development Plan, State Council Document , No. 35, July 8, 2017.
 “Sizing the prize What’s the real value of AI for your business and how can you capitalise?”, PwC Report, 2017, p. 1.
 Idem, p. 5.
 Idem, p. 23.
 “The world’s most valuable resource is no longer oil, but data”, The Economist, New York, NY, May 6, 2017.
 Thomas Brewster, “Are You One Of Avast’s 400 Million Users? This Is Why It Collects And Sells Your Web Habits”, Forbes, December 9, 2019.
 “The world’s most valuable resource is no longer oil, but data”, Op. cit..
 “Data Governance And Smart Cities Are Helping Improve Quality Of Life In Japan”, January 21, 2020.
 Jean-Simon Gagné, « Japon: les robots à la rescousse d’une société vieillissante », Le Soleil, 3 novembre 2019.
 Taiki Asakawa, “Fukuoka firm to open Japan’s first store fully automated at night”, The Mainichi, December 11, 2018.
 Chris Baraniuk, “Exclusive: UK police wants AI to stop violent crime before it happens”, New Scientist, 26 November 2018; Julian Ryall, “Japan developing ‘pre-crime’ artificial intelligence to predict money laundering and terror attacks”, South CHna Morning Post, 31 August 2018.
 Kayla Stoner, “Predicting terror activity before it happens. New model utilizes data science to predict terror groups’ lifetime lethality after first 10 attacks”, Northwestern Now, October 7, 2019.
 Luka Riester, “How is the Port of Antwerp optimising logistics with data science?”, The Blog of Business & Decision, 6 December 2019.
 Larry Lewis, “Killer robots reconsidered: Could AI weapons actually cut collateral damage?”, Bulletin of the Atomic Scientists, January 10, 2020.
 Court Stroud, “Cambridge Analytica: the turning point in the crisis about big data”, Forbes, April 30, 2018.
 Juan-Carlos Miguel de Bustos, “GAFAM, Media and Entertainment groups and big data”, Les enjeux de l’information et de la communication, 27 décembre 2017.
 Garcia Martinez, “No, Data Is Not the New Oil”, Op. cit..
 Kiran Bhageshpur, “Data Is The New Oil – And That’s A Good Thing”, Forbes Technology Council, November 15, 2019.
 Putin, “Opening lesson”, Op. cit..
 Antonio Garcia Martinez, “No, Data Is Not the New Oil”, Wired, February 26, 2019.
Emmanuel R. Goffi est Directeur de l’Observatoire Ethique & Intelligence Artificielle de l’Institut Sapiens. Il est spécialiste en sciences politiques et éthiques. Il a servi durant 25 ans dans l’armée de l’Air française. Titulaire d’un doctorat en sciences politiques de Science Po Paris, Emmanuel est également professeur en éthique des relations internationales à l’ILERI et chercheur associé au Centre for Defence and Security Studies à la University of Manitoba, à Winnipeg, Canada.
Emmanuel a enseigné et conduit des travaux de recherche dans de nombreux établissements universitaires en France et aux Canada. Il intervient régulièrement dans des colloques et dans les médias. Il a publié de nombreux articles et chapitres d’ouvrages et est l’auteur de Les armées françaises face à la morale : une réflexion au cœur des conflits modernes(Paris : L’Harmattan, 2011) et a coordonné un ouvrage de référence sur les drones, Les drones aériens : passé, présent et avenir. Approche globale(Paris: La Documentation française, coll. Stratégie aérospatiale, 2013).
Ses recherches portent essentiellement sur l’éthique appliquée à la robotique et à l’intelligence artificielle, notamment dans le domaine de la défense.