Recent years have seen breakthroughs in neural network technology: computers can now beat any living person at the most complex game invented by humankind, as well as imitate human voices and faces (both real and non-existent) in a deceptively realistic manner. Is this a victory for artificial intelligence over human intelligence? And if not, what else do researchers and developers need to achieve to make the winners in the AI race the “kings of the world?”
Over the last 60 years, artificial intelligence (AI) has been the subject of much discussion among researchers representing different approaches and schools of thought. One of the crucial reasons for this is that there is no unified definition of what constitutes AI, with differences persisting even now. This means that any objective assessment of the current state and prospects of AI, and its crucial areas of research, in particular, will be intricately linked with the subjective philosophical views of researchers and the practical experience of developers.
In recent years, the term “general intelligence,” meaning the ability to solve cognitive problems in general terms, adapting to the environment through learning, minimizing risks and optimizing the losses in achieving goals, has gained currency among researchers and developers. This led to the concept of artificial general intelligence (AGI), potentially vested not in a human, but a cybernetic system of sufficient computational power. Many refer to this kind of intelligence as “strong AI,” as opposed to “weak AI,” which has become a mundane topic in recent years.
As applied AI technology has developed over the last 60 years, we can see how many practical applications – knowledge bases, expert systems, image recognition systems, prediction systems, tracking and control systems for various technological processes – are no longer viewed as examples of AI and have become part of “ordinary technology.” The bar for what constitutes AI rises accordingly, and today it is the hypothetical “general intelligence,” human-level intelligence or “strong AI,” that is assumed to be the “real thing” in most discussions. Technologies that are already being used are broken down into knowledge engineering, data science or specific areas of “narrow AI” that combine elements of different AI approaches with specialized humanities or mathematical disciplines, such as stock market or weather forecasting, speech and text recognition and language processing.
Different schools of research, each working within their own paradigms, also have differing interpretations of the spheres of application, goals, definitions and prospects of AI, and are often dismissive of alternative approaches. However, there has been a kind of synergistic convergence of various approaches in recent years, and researchers and developers are increasingly turning to hybrid models and methodologies, coming up with different combinations.
Since the dawn of AI, two approaches to AI have been the most popular. The first, “symbolic” approach, assumes that the roots of AI lie in philosophy, logic and mathematics and operate according to logical rules, sign and symbolic systems, interpreted in terms of the conscious human cognitive process. The second approach (biological in nature), referred to as connectionist, neural-network, neuromorphic, associative or subsymbolic, is based on reproducing the physical structures and processes of the human brain identified through neurophysiological research. The two approaches have evolved over 60 years, steadily becoming closer to each other. For instance, logical inference systems based on Boolean algebra have transformed into fuzzy logic or probabilistic programming, reproducing network architectures akin to neural networks that evolved within the neuromorphic approach. On the other hand, methods based on “artificial neural networks” are very far from reproducing the functions of actual biological neural networks and rely more on mathematical methods from linear algebra and tensor calculus.
Are There “Holes” in Neural Networks?
In the last decade, it was the connectionist, or subsymbolic, approach that brought about explosive progress in applying machine learning methods to a wide range of tasks. Examples include both traditional statistical methodologies, like logistical regression, and more recent achievements in artificial neural network modelling, like deep learning and reinforcement learning. The most significant breakthrough of the last decade was brought about not so much by new ideas as by the accumulation of a critical mass of tagged datasets, the low cost of storing massive volumes of training samples and, most importantly, the sharp decline of computational costs, including the possibility of using specialized, relatively cheap hardware for neural network modelling. The breakthrough was brought about by a combination of these factors that made it possible to train and configure neural network algorithms to make a quantitative leap, as well as to provide a cost-effective solution to a broad range of applied problems relating to recognition, classification and prediction. The biggest successes here have been brought about by systems based on “deep learning” networks that build on the idea of the “perceptron” suggested 60 years ago by Frank Rosenblatt. However, achievements in the use of neural networks also uncovered a range of problems that cannot be solved using existing neural network methods.
First, any classic neural network model, whatever amount of data it is trained on and however precise it is in its predictions, is still a black box that does not provide any explanation of why a given decision was made, let alone disclose the structure and content of the knowledge it has acquired in the course of its training. This rules out the use of neural networks in contexts where explainability is required for legal or security reasons. For example, a decision to refuse a loan or to carry out a dangerous surgical procedure needs to be justified for legal purposes, and in the event that a neural network launches a missile at a civilian plane, the causes of this decision need to be identifiable if we want to correct it and prevent future occurrences.
Second, attempts to understand the nature of modern neural networks have demonstrated their weak ability to generalize. Neural networks remember isolated, often random, details of the samples they were exposed to during training and make decisions based on those details and not on a real general grasp of the object represented in the sample set. For instance, a neural network that was trained to recognize elephants and whales using sets of standard photos will see a stranded whale as an elephant and an elephant splashing around in the surf as a whale. Neural networks are good at remembering situations in similar contexts, but they lack the capacity to understand situations and cannot extrapolate the accumulated knowledge to situations in unusual settings.
Third, neural network models are random, fragmentary and opaque, which allows hackers to find ways of compromising applications based on these models by means of adversarial attacks. For example, a security system trained to identify people in a video stream can be confused when it sees a person in unusually colourful clothing. If this person is shoplifting, the system may not be able to distinguish them from shelves containing equally colourful items. While the brain structures underlying human vision are prone to so-called optical illusions, this problem acquires a more dramatic scale with modern neural networks: there are known cases where replacing an image with noise leads to the recognition of an object that is not there, or replacing one pixel in an image makes the network mistake the object for something else.
Fourth, the inadequacy of the information capacity and parameters of the neural network to the image of the world it is shown during training and operation can lead to the practical problem of catastrophic forgetting. This is seen when a system that had first been trained to identify situations in a set of contexts and then fine-tuned to recognize them in a new set of contexts may lose the ability to recognize them in the old set. For instance, a neural machine vision system initially trained to recognize pedestrians in an urban environment may be unable to identify dogs and cows in a rural setting, but additional training to recognize cows and dogs can make the model forget how to identify pedestrians, or start confusing them with small roadside trees.
The expert community sees a number of fundamental problems that need to be solved before a “general,” or “strong,” AI is possible. In particular, as demonstrated by the biggest annual AI conference held in Macao, “explainable AI” and “transfer learning” are simply necessary in some cases, such as defence, security, healthcare and finance. Many leading researchers also think that mastering these two areas will be the key to creating a “general,” or “strong,” AI.
Explainable AI allows for human beings (the user of the AI system) to understand the reasons why a system makes decisions and approve them if they are correct, or rework or fine-tune the system if they are not. This can be achieved by presenting data in an appropriate (explainable) manner or by using methods that allow this knowledge to be extracted with regard to specific precedents or the subject area as a whole. In a broader sense, explainable AI also refers to the capacity of a system to store, or at least present its knowledge in a human-understandable and human-verifiable form. The latter can be crucial when the cost of an error is too high for it only to be explainable post factum. And here we come to the possibility of extracting knowledge from the system, either to verify it or to feed it into another system.
Transfer learning is the possibility of transferring knowledge between different AI systems, as well as between man and machine so that the knowledge possessed by a human expert or accumulated by an individual system can be fed into a different system for use and fine-tuning. Theoretically speaking, this is necessary because the transfer of knowledge is only fundamentally possible when universal laws and rules can be abstracted from the system’s individual experience. Practically speaking, it is the prerequisite for making AI applications that will not learn by trial and error or through the use of a “training set,” but can be initialized with a base of expert-derived knowledge and rules – when the cost of an error is too high or when the training sample is too small.
How to Get the Best of Both Worlds?
There is currently no consensus on how to make an artificial general intelligence that is capable of solving the abovementioned problems or is based on technologies that could solve them.
One of the most promising approaches is probabilistic programming, which is a modern development of symbolic AI. In probabilistic programming, knowledge takes the form of algorithms and source, and target data is not represented by values of variables but by a probabilistic distribution of all possible values. Alexei Potapov, a leading Russian expert on artificial general intelligence, thinks that this area is now in a state that deep learning technology was in about ten years ago, so we can expect breakthroughs in the coming years.
Another promising “symbolic” area is Evgenii Vityaev’s semantic probabilistic modelling, which makes it possible to build explainable predictive models based on information represented as semantic networks with probabilistic inference based on Pyotr Anokhin’s theory of functional systems.
One of the most widely discussed ways to achieve this is through so-called neuro-symbolic integration – an attempt to get the best of both worlds by combining the learning capabilities of subsymbolic deep neural networks (which have already proven their worth) with the explainability of symbolic probabilistic modelling and programming (which hold significant promise). In addition to the technological considerations mentioned above, this area merits close attention from a cognitive psychology standpoint. As viewed by Daniel Kahneman, human thought can be construed as the interaction of two distinct but complementary systems: System 1 thinking is fast, unconscious, intuitive, unexplainable thinking, whereas System 2 thinking is slow, conscious, logical and explainable. System 1 provides for the effective performance of run-of-the-mill tasks and the recognition of familiar situations. In contrast, System 2 processes new information and makes sure we can adapt to new conditions by controlling and adapting the learning process of the first system. Systems of the first kind, as represented by neural networks, are already reaching Gartner’s so-called plateau of productivity in a variety of applications. But working applications based on systems of the second kind – not to mention hybrid neuro-symbolic systems which the most prominent industry players have only started to explore – have yet to be created.
This year, Russian researchers, entrepreneurs and government officials who are interested in developing artificial general intelligence have a unique opportunity to attend the first AGI-2020 international conference in St. Petersburg in late June 2020, where they can learn about all the latest developments in the field from the world’s leading experts.
From our partner RIAC
Implementation of virtual reality and the effects in cognitive warfare
With the increasing use of new technologies in warfare situations, virtual reality presents an opportunity for the domain of cognitive warfare. Nowadays, cognitive skills are treated equally as their physical counterparts, seeking to standardize new innovative techniques. Virtual reality (VR) can be used as a tool that can increase the cognitive capabilities of soldiers. As it is understandable in today’s terms, VR impacts the brain directly. That means that our visual organs (eyes) see one object or one surrounding area, but brain cells perceive and react to that differently. VR has been used extensively in new teaching methods because of the increased probability of improving the memory and learning capabilities of students.
Besides its theoretical teaching approach and improvement of learning, VR can be used systematically towards more practical skills. In medicine for example students can have a full medicine lesson on a virtual human being seeing the body projected in 3D, revolutionizing the whole field of medicine. If that can be used in the medical field, theoretically it will be possible to be used in combat situations, projecting a specific battlefield in VR, increasing the chances of successful engagement, and reducing the chance of casualties. Knowing your terrain is equally important as knowing your adversary.
The use of VR will also allow us to experience new domains relating to the physical health of a person. It is argued that VR might provide us with the ability to effectively control pain management. Since VR can stimulate visual senses, then it would be safe to say that this approach can have higher effectiveness in treating chronic pain, depression, or even PTSD. The idea behind this usage is that the brain itself is already powerful enough, yet sometimes when pain overwhelms us we tend to lose effectiveness on some of our senses, such as the visual sense. An agonizing pain can blurry our vision, something that we cannot control; unless of course theoretically, we use VR. The process can consist of different sounds and visual aids that can trick the mind into thinking that it is somewhere that might be the polar opposite of where it is. Technically speaking, the mind would be able to do that simply because it works as a powerful computer, where our pain receptors can override and actually make us think that we are not in such terrible pain.
Although the benefits of VR could be useful for our health we would still need to deal with problems that concern our health when we use a VR set. It is possible that the brain can get overloaded with new information and the new virtual environments. VR poses some problems to some people, regarding the loss of the real environment and creating feelings of nausea or extreme headaches. As a result, new techniques from cognitive psychologists have emerged to provide a solution to the problem. New technologies have appeared that can desaturate colors towards the edge of the headset in order to limit the probability of visual confusion. Besides that, research shows that even the implementation of a virtual nose when someone wears a VR headset can prevent motion sickness, something that our brain does already in reality.
However, when it comes to combatants and the implementation of VR in soldiers, one must think of maybe more effective and fast solutions to eliminate the problems that concern the confusion of the brain. Usage of specific pharmaceuticals might be the key. One example could be Modafinil which has been prescribed in the U.S. since 1998 to treat sleep-related conditions. Researchers believe it can produce the same effects as caffeine. With that being said, the University of Oxford analyzed 24 studies, where participants were asked to complete complex assignments after taking Modafinil and found out that those who took the drug were more accurate, which suggests that it may affect higher cognitive functions.
Although some of its long-term effects are yet to be studied, Modafinil is by far the safest drug that can be used in cognitive situations. Theoretically speaking, if a long exposure to VR can cause headaches and an inability to concentrate, then an appropriate dose of Modafinil can counter the effects of VR. It can be more suitable and useful to use on soldiers, whose cognitive skills are better than civilians, to test the full effect of a mix of virtual technology and pharmaceuticals. VR can be a significant military component and a simulation training program. It can provide new cognitive experiences based on foreign and unknown terrains that might be difficult to be approached in real life. New opportunities arise every day with the technologies, and if anyone wanted to take a significant advantage over adversaries in the cognitive warfare field, then VR would provide a useful tool for military decision-making.
Vaccine Equity and Beyond: Intellectual Property Rights Face a Crucial Test
The debate over intellectual property rights (IPRs), particularly patents, and access to medicine is not new. IPRs are considered to drive innovation by protecting the results of investment-intensive R&D, yet arguably also foster inequitable access to affordable medicines.
In a global public health emergency such as the COVID-19 pandemic, where countries face acute shortages of life-saving vaccines, should public health be prioritized over economic gain and the international trade rules designed to protect IPRs?
The Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPs), to which all 164 member states of the World Trade Organization (WTO) are a party, establish minimum standards for protecting different forms of IPRs.
In October 2020, India and South Africa – countries with strong generic drug manufacturing infrastructure – invoked WTO rules to seek a temporary waiver of IPRs (patents, copyrights, trade secrets, and industrial designs) on equipment, drugs, and vaccines related to the “prevention, containment or treatment of COVID-19.” A waiver would mean that countries could locally produce equipment and vaccines without permission from holders of IPRs. This step would serve to eliminate the monopolistic nature of IPRs that give exclusive rights to the holder of IPRs and enable them to impose procedural licensing constraints.
Brazil, Japan, the European Union (EU), and the United States (US) initially rejected the waiver proposal. That stance changed with the rise of new COVID-19 mutations and the associated increase in deaths, with several countries facing a public health crisis due to vaccine supply shortages. The position of many states began shifting in favor of the India-South Africa proposal, which now has the backing of 62 WTO members, with the US declaring support for the intent of the temporary waiver to secure “better access, more manufacturing capability, more shots in arms.” Several international bodies, the World Health Organization (WHO), and the UN Committee on Economic, Social and Cultural Rights have voiced support.
Some countries disagree about the specific IPRs to be waived or the mechanisms by which IPRs should be made available. The EU submitted a proposal to use TRIPS flexibilities such as compulsory licensing, while others advocate for voluntary licensing. The TRIPS Council is conducting meetings to prepare an amended proposal to the General Council (the WTO’s highest-level decision-making body in Geneva) by the end of July 2021.
The crisis in India illustrates the urgency of the situation. India produces and supplies Covishield, licensed by AstraZeneca; and Covaxin, which is yet to be included on the WHO’s Emergency Use Listing (EUL). Due to the devastating public health crisis, India halted its export of vaccines and caused a disruption in the global vaccine supply, even to the COVID-19 Vaccines Global Access (COVAX) program. In the meantime, the world’s poorest nations lack sufficient, critical vaccine supplies.
International law recognizes some flexibility in public health emergencies. An example would be the Doha Declaration on TRIPS and Public Health in 2001, which, while maintaining the commitments, stresses the need for TRIPS to be part of the wider national and international action to address public health problems. Consistent with that, the body of international human rights law, including the International Covenant on Economic, Social and Cultural Rights (ICESCR), protects the right to the highest attainable standard of health.
But as we race against time, the current IPR framework may not allow for the swift response required. It is the rigorous requirements before a vaccine is considered safe to use under Emergency Use Authorizations and procedural delays which illuminate why IPR waivers on already approved vaccines are needed. Capitalizing on the EUL’s approved vaccines that have proven efficacy to date and easing IPR restrictions will aid in the timely supply and access of vaccines.
A TRIPS waiver may not solve the global vaccine shortage. In fact, some argue that the shortages are not an inherent flaw in the IP regime, considering other supply chain disruptions that persist, such as the ones disrupting microchips, pipette tips, and furniture. However, given that patent licensing gives a company a monopoly on vaccine commercialization, other companies with manufacturing capacity cannot produce the vaccine to scale up production and meet supply demands.
Neither does a temporary waiver mean that pharmaceutical companies cannot monetize their work. States should work with pharmaceuticals in setting up compensation and insurance schemes to ensure adequate remuneration.
At the College of Law at Hamad Bin Khalifa University, our aim is to address today’s legal challenges with a future-oriented view. We see COVID-19 as a case study in how we respond to imminent and existential threats. As global warming alters the balance of our ecosystem, threats will cascade in a way that is hard to predict. When unpredictable health emergencies emerge, it will be human ingenuity that helps us overcome them. Even the global IP regime, as a legal system that regulates ideas, is being tested, and should be agile enough to respond in time, like the scientists who sprang into action and worked tirelessly to develop the vaccines that will soon bring back a semblance of normal life as we know it.
Sputnik V in the International Arena
Over a year since the World Health Organization (WHO) declared the COVID-19 outbreak a pandemic in March 2020, the disease is far from under control. Although global case rates on the whole have declined, 15 countries remain near or at the peak of their infection curve. Even countries well below their peak daily infection rates – such as the United Kingdom and Morocco – recently have witnessed an uptick in cases. Just this summer, the virus’ global death toll surpassed 4 million. Fortunately, scientists’ efforts to develop vaccines against COVID-19 have been fruitful: 16 vaccines have been either authorized for emergency use or fully approved. Russia’s Sputnik V is one of the most effective of them, yet one of the most controversial as well.
An important tool in humankind’s fight against the pandemic, Sputnik V is being overlooked by western powers on political grounds.
Sputnik V: controversy and advantages
Much of the controversy surrounding the Gamaleya Institute’s vaccine in western media and political discourse stems from the details surrounding Sputnik V’s approval. Russia’s Ministry of Health issued a registration certificate for the vaccine on August 11, 2020, thus making Sputnik V the world’s first vaccine to be granted regulatory approval for use against COVID-19. Instead of igniting international celebration, this development was met largely with skepticism as many considered the move premature. Typically, vaccines undergo extensive Phase 3 trials before government authorization for use. Sputnik V’s Phase 3 trials, however, did not begin until September 2020, after the vaccine had been registered. Since then, the Russian Ministry of Health’s unorthodox approach to approving the vaccine has been weaponized against Sputnik V.
Western media has also repeatedly called into question Sputnik V’s efficacy and safety. A study in the respected, peer-reviewed medical journal the Lancet, however, found that Sputnik V has an efficacy rate of 91.6% and is low-risk. Although a group of scientists raised concerns about the study’s integrity citing lack of transparency, no major scientific studies demonstrating that Sputnik V’s efficacy is significantly lower than reported have been published to date. Respected western media sources, such as the New York Times and the BBC, cite the Lancet’s figure when reporting on Sputnik V’s efficacy. Meanwhile, a report by the Argentinian Ministry of Health found that Sputnik V is one of the safest vaccines widely used in Argentina. As summarized in the Lancet: “the development of the Sputnik V vaccine has been criticised for unseemly haste, corner cutting, and an absence of transparency. But the outcome reported here is clear and the scientific principle of vaccination is demonstrated, which means another vaccine can now join the fight to reduce the incidence of COVID-19.”
Regardless of such controversy, the vaccine has several key advantages – namely its efficacy, affordability, and transportability. Sputnik V is one of only three vaccines globally with an efficacy of over 90% – the other two being Pfizer-BioNTech and Moderna. Running at less than $10 per dose on international markets, Sputnik V is the cheapest vaccine in this efficacy range. For comparison, the Pfizer-BioNTech vaccine runs between $14.50 and $20.00 on international markets, while Moderna’s vaccine sells for between $18.00 and $33.00 a dose. Sputnik V is also much easier to transport than its U.S./German counterparts. The Pfizer-BioNTech and Moderna vaccines must be stored at -70.0°C and -20.0°C respectively, whereas Sputnik V must be kept at a temperature range from 2 to 8°C, meaning that it can be stored in conventional refrigerators. This makes delivering the vaccine notably easier, especially to remote areas. Thus, Sputnik V is poised to make an important contribution to the global inoculation campaign.
Hurdles and victories in the international arena
Russia’s frontrunner vaccine has experienced a mix of hurdles and victories in the international arena. The biggest hurdles are regulatory in nature. For example, one major obstacle preventing the vaccine’s distribution is that the European Medicines Agency (EMA) – the EU agency responsible for authorizing and evaluating medicines – has not yet approved Sputnik V. The EMA is still undergoing its rolling revue of the vaccine, and it appears that approval is unlikely to be granted until September at the earliest. Italian Prime Minister Mario Draghi recently raised the possibility that Sputnik may never get the EMA’s approval, casting further doubt on the vaccine’s future in Europe. The EMA’s regulatory hesitancy towards Sputnik V has prevented major EU players, such as Germany and France, from buying millions of doses of the vaccine.
Sputnik V similarly has not yet been cleared for Emergency Use Listing by the WHO. The UN agency found production violations at the Sputnik V manufacturing site in Ufa during a June examination. Although the WHO’s concerns have since been addressed according to Russian Press Secretary Dmitry Peskov, the incident has further put on hold the Russian Direct Investment Fund’s (RDIF) commitment to supply the United Nations International Children’s Emergency Fund with 220 million doses of Sputnik V. In a similar vein, the RDIF applied for Sputnik V to participate in COVID-19 vaccine access program COVAX earlier this year. Discussions with the Vaccine Alliance Gavi regarding Sputnik V’s inclusion in the COVAX Facility’s Portfolio of COVID-19 vaccines, however, are still ongoing.
Although Sputnik V’s lack of EMA and WHO approval has hampered its international rollout, the ongoing authorization process has not eliminated the vaccine’s global relevance. In fact, the Russian vaccine is currently authorized for emergency use in nearly 70 countries and being used in 45. Two EU member states, Hungary and Slovakia, even have begun inoculating their citizens with Sputnik V without a greenlight from the EMA. Meanwhile, India and Turkey have ordered 250 million and 50 million doses of the vaccine, respectively. One thing is clear: Sputnik V is in high demand internationally despite the regulatory hurdles and controversies it faces. Trust in the Russian vaccine also remains markedly high notwithstanding these challenges. A poll conducted by British market research firm YouGov during February and March of this year found that, of participants who had a preference, 54.0% trusted Russia to produce a vaccine and 33.2% preferred to be vaccinated with Sputnik V. According to the survey, Russia and the United States are tied for the most trusted vaccine producing country, and Sputnik V is the second most preferred vaccine after Pfizer-BioNTech, which 36.6% of respondents favored. The survey featured respondents from the following 9 countries, collectively accounting for 25% of the global population: India; Brazil; Mexico; the Philippines; Vietnam; Argentina; Algeria; the UAE; and Serbia.
Sputnik V has been particularly successful in Latin America, a core region of the United States’ sphere of influence. Repeated polling has shown that Sputnik V enjoys high levels of confidence in Latin American countries, especially Argentina and Peru. The Russian vaccine got an early start in the region when on December 29, 2020, Argentina became the first Latin American country to administer the Sputnik V vaccine to its citizens. Mexico followed suit on February 24 and Nicaragua on March 2, 2021. To the surprise of many observers, on June 4 Brazil joined the list of countries that have approved Sputnik V.
Unfortunately, alongside the success Sputnik V has experienced in Latin America, the vaccine has also encountered a substantial challenge: supply shortages. Both Mexico and Argentina are currently facing shortages of Sputnik V’s second dose – and the problem is not confined to the region. Luckily, Russia’s strategy for eliminating supply shortages not only promises to see more people vaccinated, but also provides an opportunity for Russia to collaborate with its international partners: the country will manufacture vaccines abroad. Starting in July, 5 to 6 million doses of Sputnik V are set to be produced outside of Russia per month. Manufacturing countries include India, South Korea, and Brazil. The Argentine laboratory Richmond produced its first half million doses on June 18. The data sharing and collaboration necessary to manufacture Sputnik V abroad have the potential to increase Russia’s soft power in partner countries.
The other major players
It is crucial to note that Russia’s Sputnik V is only one piece in the puzzle of fighting COVID-19. Although an in-depth review of every country’s current approach to vaccine policy is beyond the scope of this article, a brief overview of the major vaccine providers’ – the United States, the United Kingdom, and China – global vaccine distribution is in store.
Unlike Russia, whose approach to vaccine distribution has been global facing since Sputnik V’s development, the United States initially favored domestic distribution and stockpiling of American vaccines. The Biden Administration has since turned course. The U.S. recently pledged to share 80 million U.S. vaccine doses by the end of June and to purchase 500 million additional doses of the Pfizer-BioNTech vaccine for lower-income countries over the next year. Pfizer-BioNTech is currently being distributed in 105 countries, Moderna in 55, and Johnson&Johnson in 27.
The United Kingdom’s Oxford-AstraZeneca vaccine is currently being used in 178 countries, making it the most widely-used COVID-19 vaccine to date. Although evidence that the vaccine is linked to blood clots put a rut in its distribution, the vaccine is performing well internationally. Meanwhile, China’s Sinopharm-Beijing and Sinovac vaccines are being used in 40 and 32 countries, respectively. China has favored international distribution of its vaccines since the beginning of the pandemic and has shipped more vaccines abroad than any other country. The vaccines referenced in this article – among others – have collectively led to 22.2% of the world’s population having received at least one dose of a COVID-19 vaccine.
Western, especially American, media has portrayed Sputnik V in an overwhelmingly negative light. The Russian vaccine is represented more as a political tool than a health solution. Hiccups in the road to Sputnik V distribution are cited as evidence that the vaccine is not to be trusted. This approach to Sputnik V is fundamentally flawed. Regulation and safety inspections are crucial to safe vaccination efforts; finger-pointing and name-calling are not. Ultimately, vaccination should take precedence over politics. Alongside other vaccines, Sputnik V will propel us into a post-pandemic world.
Above all else, Sputnik V is a highly efficacious vaccine against COVID-19. When Sputnik V successfully performs its function – safely preventing vaccinated people from contracting and dying from the virus – a growth in vaccinated individuals’ trust of Russia will organically follow. This happy side effect undoubtedly has the potential to promote Russia’s image abroad and increase the country’s soft power. But even if Russia’s political gains from Sputnik V turn out to be small, humankind’s gains in lives saved will be immeasurable.
From our partner RIAC
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