It didn’t take long for artificial intelligence (AI) to be invited to support the fight against the viral pandemic affecting the world since the beginning of 2020. The press and bloggers echo the high hopes of data science and AI to confront coronavirus(D. Yakobovitch, How to fight the Coronavirus with AI and Data Science, Medium, February 15, 2020)and “fill the voids” still left by science(G. Ratnam, Can AI Fill in the Blanks About Coronavirus? Experts Think So, Government Technology, March 17, 2020).).
It is surprising, however, that China, the first epicentre of this disease and renowned for its technological advance in this field, does not seem to have been able to gain a decisive advantage. Its most effective uses appear to be more about population control and predictions of disease outbreaks than research for vaccine or treatment. There have, of course, been applications of AI to accelerate genome sequencing, perform faster diagnostics, scan or more occasionally use maintenance and delivery robots(A. Chun, In a time of coronavirus, China’s investment in AI is paying off in a big way, South China Morning post),but we are far from pre-crisis rhetoric where some techno-evangelists thought this technology would protect us from such global events.
The way AI is currently used is therefore quite revealing of its strengths and limitations: effective because of the power of its computational capabilities with very large datasets, it does not yet seem to be able to replace expertise to design a vaccine or treatment. Its contributions also remain undeniable to organize knowledge and assist in population control, or even support doctors for a diagnosis, but the events seem to lead to a certain modesty and reveal above all that health infrastructure in some countries is not scalable in times of crisis… and that it is not computer technology alone (including AI) that is able to provide a solution.
The contribution of artificial intelligence to the search for a cure
The first application of AI expected in the face of this crisis is certainly the assistance to researchers to design a vaccine, able to protect caregivers and contain the pandemic. Let us immediately move away from the idea of a central AI to the creation of such a medical treatment, since this activity is a matter of biomedicine and research is based on numerous techniques including the various applications of computer science. and statistics have long since been available.
Predictions of the structure of the virus generated by AI, however, could save scientists months of experimentation. Indeed, AI already seems to have provided significant support, even if it is limited by so-called “continuous” rules and infinite combination, for the study of protein folding (see O. Ezratty, The Practical Consequences of AlphaGo Zero, Free Opinions, November 9, 2017).). The American startup Moderna, behind one of the first vaccine trials, has distinguished itself by its mastery of a biotechnology based on messenger ribonucleic acid (mRNA), which would have significantly reduced the time to develop a prototype vaccine testable on humans and probably deployed this type of technological support.
Similarly, Chinese technology giant Baidu, in Partnership with Oregon State University and the University of Rochester, published its Linearfold prediction algorithm in February 2020 to study protein folding. This algorithm is much faster than traditional ribonucleic acid (RNA) folding algorithms to predict the secondary RNA structure of a virus. It is this type of analysis of secondary structural changes between homologous RNA virus sequences (such as bats and humans) that can provide scientists with additional information on how viruses spread. The secondary structure of the Covid-19 RNA sequence would have been revealed by Linearfold in 27 seconds, instead of 55 minutes(Baidu, How Baidu is bringing AI to the fight against coronavirus, MIT Technology Review, March 11, 2020). DeepMind, a subsidiary of Google’s parent company, Alphabet, also shared its predictions about coronavirus protein structure with its AlphaFold AI system(J. Jumper, K. Tunyasuvunakool, P. Kohli, D. Hassabis et al. , Computational predictions of protein structures associated with COVID-19, DeepMind, March 5, 2020).).
Artificial intelligence, the engine of knowledge sharing
In full awareness of the potentially catastrophic consequences for the United States, the Officeof Science and Technology Policymet with technologycompanies and major research groups on March 11, 2020 to determine how AI tools could be used to, among other things, sift through the thousands of research papers published around the world on the pandemic(A. ) Boyle, White House seeks the help of tech titans to combat coronavirus and misinformation, GeekWire, March 11, 2020).
In the weeks following the emergence of the new coronavirus in Wuhan, China in December 2019, nearly 2,000 research papers have been published on the effects of this new virus, on possible treatments, and on the dynamics of the pandemic. . This influx of scientific literature is a natural testament to the eagerness of researchers to deal with this major health crisis, but it also represents a real challenge for anyone hoping to exploit its substance.
Microsoft Research, the National Library of Medicine and the Allen Institute for AI (AI2) presented their work on March 16, 2020, which involved collecting and preparing more than 29,000 documents related to the new virus and the broader coronavirus family, 13,000 of which were processed so that computers could read the underlying data, as well as information about the authors and their affiliations. Kaggle, a Google subsidiary and platform that usually organizesdata sciencecompetitions, has created challenges around 10 key coronavirus-related questions. These questions range from risk factors and non-drug treatments to the genetic properties of the virus to vaccine development efforts. The project also involves the Chan Zuckerberg Initiative (named after Facebook founder Mark Zuckerberg and his wife Priscilla Chan) and Georgetown University’s Center for Security and Emerging Technologies(W. Knight, Researchers Will Deploy AI to Better Understanding Coronavirus, Wired, March 17, 2020).).
Artificial intelligence, observatory and predictor of the evolution of the pandemic
Canadian company BlueDot is touted as having detected the virus early through AI, which conducts ongoing review of more than 100 datasets,such as news, airfare sales, demographics, climate data and animal populations. BlueDot detected an outbreak of pneumonia in Wuhan, China, on December 31, 2019 and identified the cities most at risk of the virus(C. Stieg, How this Canadian start-up spotted coronavirus before everyone else knew about it, CNBC, March 3, 2020).).
A team of researchers working with Boston Children’s Hospital has also developed an AI to monitor the spread of coronavirus. Called HealthMap, the system integrates data from Google searches, social media and blogs, as well as discussion forums: sources of information that epidemiologists generally do not use, but that are useful in identifying the first signs of an epidemic and assessing public reaction(A. Johnson, How Artificial Intelligence is Aiding the fight Against Coronavirus, Datainnovation, March 13, 2020).).
The UNESCO-sponsored International Artificial Intelligence Research Centre (IRCAI) in Slovenia has launched a “smart” coronavirus media watch called Corona Virus Media Watch, which provides updates on global and national news based on a selection of media with open online information. The tool, also developed with oecd support and Event Registryinformation extractiontechnology, is presented as a useful source of information for policy makers, the media and the public to observe emerging trends related to Covid-19 in their countries and around the world.
Artificial intelligence, in assistance to health care workers
Two Chinese companies have developed an AI-based coronavirus diagnostic software. Beijing-based startup Infervision has trained its software to detect lung problems by CT scan. Originally used to diagnose lung cancer, it can also detect pneumonia associated with respiratory diseases such as coronavirus. At least 34 Chinese hospitals are reported to have used this technology to help them examine 32,000 suspected cases(T. Simonite, Chinese Hospitals Deploy AI to Help Diagnose Covid-19, Wired, February 26, 2020).).
Alibaba DAMO Academy, a research arm of China’s Alibaba, has also formed an AI system to recognize coronaviruses with an alleged accuracy of up to 96%. According to the company, the system could treat the 300 to 400 scanners needed to diagnose a coronavirus in 20 to 30 seconds, whereas the same operation would usually take between 10 and 15 minutes for an experienced physician. This system would have helped at least 26 Chinese hospitals to examine more than 30,000cases (C. Li, How DAMO Academy’s AI System Detects Coronavirus Cases, Alizila, March 10, 2020).).
In South Korea, AI would have helped reduce the design of testing kits based on the genetic makeup of the virus to a few weeks, when it would usually have taken two to three months. Biotechnology company Seegene used its automated test development system to develop the screening kit and distribute it widely. Large-scale testing is indeed crucial to exit containment measures and this testing policy appears to have contributed to the relative control of the pandemic in this country, which equipped with this device 118 medical facilities and tested more than 230,000 people(I.Watson, S.Jeong, J.Hollingsworth, T.Booth, How this South Korean company created coronavirus test kits in three weeks, CNN World, March 13, 2020).).
Artificial intelligence, a tool for population control
Singapore’s example of controlling epidemic risks is certainly unique and difficult to export: issuing a containment order for at-risk populations, checking compliance with mobile phone and geolocation measures, random home checks. And this same model, based on a cultural and social acceptance of control, also has its limits which raise fears of an increase in cases and make it necessary to adopt other measures(K. Vaswani, Coronavirus: The detectives racing to contain the virus in Singapore, BBC News, 19 March 2020).
More generally, AI has been fairly widely used in support of this type of mass surveillance policies. Thus, devices could be used to measure temperature and recognize individuals in China(M. Si, AI used in the battle against the novel coronavirus outbreak, China Daily, February 6, 2020)or equip law enforcement with “smart” helmets in Sichuan province, helmets able to report individuals with high body temperature (High-techhelmets tackle temperature tasks, China Daily, March 19, 2019). Facial recognition devices, however, have had difficulties with the wearing of surgical masks, which has led a Chinese company to try to circumvent this difficulty since many services in China now rely on this technology, including state services for surveillance measures. Hanvon claims to have created a device to increase the recognition rate of surgical mask wearers to 95% (MrPollard, Even mask-wearers can be ID’d, China facial recognition firm says, Reuters, 9 March 2020). The pandemic has succeeded in removing this technology from its limits in a much more effective way than the discourse on fundamental rights… In Israel, the first steps in a plan to use individual telephone tracking to warn users not to rub shoulders with people potentially carrying the virus are being developed. In Italy, a company has also developed a smartphone appsmartphoneto reconstruct the route of an individual with the virus and to warn people who have had contactwith them. According to the designer, privacy would be guaranteed, as the application would not reveal phone numbers or personal data(E. Tebano, Coronavirus, pronta the app italiana per tracciare i contagi: ‘Coss’ possiamo fermare epidemia’, Corriere della Sera, 18 March 2020). It remains to be seen whether, in these times justifying measures that are extremely derogatory to fundamental rights and freedoms, intentions will be translated into effect.
In the United States, there is this tension between the protection of individual and collective interests. Thus, GAFAM has likely found an opportunity with this health crisis to improve their image by providing, with the support of AI, the means to process a considerable mass of scientific articles(see above). At the same time, however, they have even more valuable information that every public decision-maker dreams of in this period of health crisis: a wealth of data on the American population. Larry Brilliant, an epidemiologist and executive director of the Google.org, says he can “change the face of public health” and believes that “little in life is more important than whether big technologies are too powerful, but a pandemic is definitely part of it”(N. Scola, Big Tech faces a ‘Big Brother trap’ on coronavirus, POLITICO, March 18, 2020).).
However, after both the Cambridge Analytica and Snowden cases, these major technology companies have shown, for the time being, a certain inability to compartmentalize the use (or reuse) of the data they have with clear purposes. Since the U.S. government has asked these companies to have access to aggregated and anonymous data, including on mobile phones, in order to combat the spread of the virus, it is understandable that their current caution in view of the legal risk and potential image harm(S. Overly, White seek Houses Silicon Valley help battling coronavirus, POLITICO, March 11, 2020). It should also be noted that the companies that would be most able to provide meaningful information, such as Google, Facebook or Amazon, are the same companies that have opposed the federal government in all aspects in recent years, whether it is privacy, competition or content rules. Data regulation would likely have helped to frame the dialogue between the public and private sector, and to determine what types of emergencies should put the collective interest over the protection of individual rights (and the conditions and guarantees of such a scheme), but Congress has still not made progress in the last two years on such a law. The current urgency may lead to more significant progress, as major crises sometimes have the distinction of referring us to our condition and to the essentials.
Artificial intelligence: one way among others should not lead to avoiding the structural difficulties of health care facilities
The possibilities offered by digital technology, including computer science and AI, are therefore proving to be relevant instruments for building a coordinated response to this pandemic. The multiple uses also illustrate the limits of the promises and possibilities of these same technologies, which we cannot expect to compensate for structural difficulties, such as those experienced by many care around the world. These have been tailored to a logic of operation based on efficiency and cost, not on their mission, which should remain essential: universal access to care.
Article 11 of the European Social Charter (ratified by 34 of the 47 Member States of the Council of Europe) enacts a right to health protection that commits signatories “to take, either directly or in cooperation with public and private organisations, appropriate measures aimed, in particular, at: (1) in order to eliminate, as far as possible, the causes of poor health; (2) provide consultation and education services for improving health and developing a sense of individual responsibility for health; (3) to prevent, as far as possible, epidemic, endemic and other diseases, as well as accidents. »
The emergency measures taken, which are essentially restrictive of freedoms or support for businesses, should therefore be able to be followed in the after-the-crisis by new public policies that stop placing digital and AI as the instrument cost reductions and efficiency improvements. These same technologies, on the other hand, can prove to be valuable allies in systemic and global policies, placing the mission of public services at the heart of a social project truly focused on human progress, whose indisputable pillars are human rights, democracy and the rule of law.