Digitalization and the development of artificial intelligence (AI) bring up many philosophical and ethical questions about the role of man and robot in the nascent social and economic order. How real is the threat of an AI dictatorship? Why do we need to tackle AI ethics today? Does AI provide breakthrough solutions? We ask these and other questions in our interview with Maxim Fedorov, Vice-President for Artificial Intelligence and Mathematical Modelling at Skoltech.
On 1–3 July, Maxim Fedorov chaired the inaugural Trustworthy AI online conference on AI transparency, robustness and sustainability hosted by Skoltech.
Maxim, do you think humanity already needs to start working out a new philosophical model for existing in a digital world whose development is determined by artificial intelligence (AI) technologies?
The fundamental difference between today’s technologies and those of the past is that they hold up a “mirror” of sorts to society. Looking into this mirror, we need to answer a number of philosophical questions. In times of industrialization and production automation, the human being was a productive force. Today, people are no longer needed in the production of the technologies they use. For example, innovative Japanese automobile assembly plants barely have any people at the floors, with all the work done by robots. The manufacturing process looks something like this: a driverless robot train carrying component parts enters the assembly floor, and a finished car comes out. This is called discrete manufacturing – the assembly of a finite set of elements in a sequence, a task which robots manage quite efficiently. The human being is gradually being ousted from the traditional economic structure, as automated manufacturing facilities generally need only a limited number of human specialists. So why do we need people in manufacturing at all? In the past, we could justify our existence by the need to earn money or consume, or to create jobs for others, but now this is no longer necessary. Digitalization has made technologies a global force, and everyone faces philosophical questions about their personal significance and role in the modern world – questions we should be answering today, and not in ten years when it will be too late.
At the last World Economic Forum in Davos, there was a lot of discussion about the threat of the digital dictatorship of AI. How real is that threat in the foreseeable future?
There is no evil inherent in AI. Technologies themselves are ethically neutral. It is people who decide whether to use them for good or evil.
Speaking of an AI dictatorship is misleading. In reality, technologies have no subjectivity, no “I.” Artificial intelligence is basically a structured piece of code and hardware. Digital technologies are just a tool. There is nothing “mystical” about them either.
My view as a specialist in the field is that AI is currently a branch of information and communications technology (ICT). Moreover, AI does not even “live” in an individual computer. For a person from the industry, AI is a whole stack of technologies that are combined to form what is called “weak” AI.
We inflate the bubble of AI’s importance and erroneously impart this technology stack with subjectivity. In large part, this is done by journalists, people without a technical education. They discuss an entity that does not actually exist, giving rise to the popular meme of an AI that is alternately the Terminator or a benevolent super-being. This is all fairy tales. In reality, we have a set of technological solutions for building effective systems that allow decisions to be made quickly based on big data.
Various high-level committees are discussing “strong” AI, which will not appear for another 50 to 100 years (if at all). The problem is that when we talk about threats that do not exist and will not exist in the near future, we are missing some real threats. We need to understand what AI is and develop a clear code of ethical norms and rules to secure value while avoiding harm.
Sensationalizing threats is a trend in modern society. We take a problem that feeds people’s imaginations and start blowing it up. For example, we are currently destroying the economy around the world under the pretext of fighting the coronavirus. What we are forgetting is that the economy has a direct influence on life expectancy, which means that we are robbing many people of years of life. Making decisions based on emotion leads to dangerous excesses.
As the philosopher Yuval Noah Harari has said, millions of people today trust the algorithms of Google, Netflix, Amazon and Alibaba to dictate to them what they should read, watch and buy. People are losing control over their lives, and that is scary.
Yes, there is the danger that human consciousness may be “robotized” and lose its creativity. Many of the things we do today are influenced by algorithms. For example, drivers listen to their sat navs rather than relying on their own judgment, even if the route suggested is not the best one. When we receive a message, we feel compelled to respond. We have become more algorithmic. But it is ultimately the creator of the algorithm, not the algorithm itself, that dictates our rules and desires.
There is still no global document to regulate behaviour in cyberspace. Should humanity perhaps agree on universal rules and norms for cyberspace first before taking on ethical issues in the field of AI?
I would say that the issue of ethical norms is primary. After we have these norms, we can translate them into appropriate behaviour in cyberspace. With the spread of the internet, digital technologies (of which AI is part) are entering every sphere of life, and that has led us to the need to create a global document regulating the ethics of AI.
But AI is a component part of information and communications technologies (ICT). Maybe we should not create a separate track for AI ethics but join it with the international information security (IIS) track? Especially since IIS issues are being actively discussed at the United Nations, where Russia is a key player.
There is some justification for making AI ethics a separate track, because, although information security and AI are overlapping concepts, they are not embedded in one another. However, I agree that we can have a separate track for information technology and then break it down into sub-tracks where AI would stand alongside other technologies. It is a largely ontological problem and, as with most problems of this kind, finding the optimal solution is no trivial matter.
You are a member of the international expert group under UNESCO that is drafting the first global recommendation on the ethics of AI. Are there any discrepancies in how AI ethics are understood internationally?
The group has its share of heated discussions, and members often promote opposing views. For example, one of the topics is the subjectivity and objectivity of AI. During the discussion, a group of states clearly emerged that promotes the idea of subjectivity and is trying to introduce the concept of AI as a “quasi-member of society.” In other words, attempts are being made to imbue robots with rights. This is a dangerous trend that may lead to a sort of technofascism, inhumanity of such a scale that all previous atrocities in the history of our civilization would pale in comparison.
Could it be that, by promoting the concept of robot subjectivity, the parties involved are trying to avoid responsibility?
Absolutely. A number of issues arise here. First, there is an obvious asymmetry of responsibility. “Let us give the computer with rights, and if its errors lead to damage, we will punish it by pulling the plug or formatting the hard drive.” In other words, the responsibility is placed on the machine and not its creator. The creator gets the profit, and any damage caused is someone else’s problem. Second, as soon as we give AI rights, the issues we are facing today with regard to minorities will seem trivial. It will lead to the thought that we should not hurt AI but rather educate it (I am not joking: such statements are already being made at high-level conferences). We will see a sort of juvenile justice for AI. Only it will be far more terrifying. Robots will defend robot rights. For example, a drone may come and burn your apartment down to protect another drone. We will have a techno-racist regime, but one that is controlled by a group of people. This way, humanity will drive itself into a losing position without having the smallest idea of how to escape it.
Thankfully, we have managed to remove any inserts relating to “quasi-members of society” from the group’s agenda.
We chose the right time to create the Committee for Artificial Intelligence under the Commission of the Russian Federation for UNESCO, as it helped to define the main focus areas for our working group. We are happy that not all countries support the notion of the subjectivity of AI – in fact, most oppose it.
What other controversial issues have arisen in the working group’s discussions?
We have discussed the blurred border between AI and people. I think this border should be defined very clearly. Then we came to the topic of human-AI relationships, a term which implies the whole range of relationships possible between people. We suggested that “relationships” be changed to “interactions,” which met opposition from some of our foreign colleagues, but in the end, we managed to sort it out.
Seeing how advanced sex dolls have become, the next step for some countries would be to legalize marriage with them, and then it would not be long before people starting asking for church weddings. If we do not prohibit all of this at an early stage, these ideas may spread uncontrollably. This approach is backed by big money, the interests of corporations and a different system of values and culture. The proponents of such ideas include a number of Asian countries with a tradition of humanizing inanimate objects. Japan, for example, has a tradition of worshipping mountain, tree and home spirits. On the one hand, this instills respect for the environment, and I agree that, being a part of the planet, part of nature, humans need to live in harmony with it. But still, a person is a person, and a tree is a tree, and they have different rights.
Is the Russian approach to AI ethics special in any way?
We were the only country to state clearly that decisions on AI ethics should be based on a scientific approach. Unfortunately, most representatives of other countries rely not on research, but on their own (often subjective) opinion, so discussions in the working group often devolve to the lay level, despite the fact that the members are highly qualified individuals.
I think these issues need to be thoroughly researched. Decisions on this level should be based on strict logic, models and experiments. We have tremendous computing power, an abundance of software for scenario modelling, and we can model millions of scenarios at a low cost. Only after that should we draw conclusions and make decisions.
How realistic is the fight against the subjectification of AI if big money is at stake? Does Russia have any allies?
Everyone is responsible for their own part. Our task right now is to engage in discussions systematically. Russia has allies with matching views on different aspects of the problem. And common sense still prevails. The egocentric approach we see in a number of countries that is currently being promoted, this kind of self-absorption, actually plays into our hands here. Most states are afraid that humans will cease to be the centre of the universe, ceding our crown to a robot or a computer. This has allowed the human-centred approach to prevail so far.
If the expert group succeeds at drafting recommendations, should we expect some sort of international regulation on AI in the near future?
If we are talking about technical standards, they are already being actively developed at the International Organization for Standardization (ISO), where we have been involved with Technical Committee 164 “Artificial Intelligence” (TC 164) in the development of a number of standards on various aspects of AI. So, in terms of technical regulation, we have the ISO and a whole range of documents. We should also mention the Institute of Electrical and Electronics Engineers (IEEE) and its report on Ethically Aligned Design. I believe this document is the first full-fledged technical guide on the ethics of autonomous and intelligent systems, which includes AI. The corresponding technical standards are currently being developed.
As for the United Nations, I should note the Beijing Consensus on Artificial Intelligence and Education that was adopted by UNESCO last year. I believe that work on developing the relevant standards will start next year.
So the recommendations will become the basis for regulatory standards?
Exactly. This is the correct way to do it. I should also say that it is important to get involved at an early stage. This way, for instance, we can refer to the Beijing agreements in the future. It is important to make sure that AI subjectivity does not appear in the UNESCO document, so that it does not become a reference point for this approach.
Let us move from ethics to technological achievements. What recent developments in the field can be called breakthroughs?
We haven’t seen any qualitative breakthroughs in the field yet. Image recognition, orientation, navigation, transport, better sensors (which are essentially the sensory organs for robots) – these are the achievements that we have so far. In order to make a qualitative leap, we need a different approach.
Take the “chemical universe,” for example. We have researched approximately 100 million chemical compounds. Perhaps tens of thousands of these have been studied in great depth. And the total number of possible compounds is 1060, which is more than the number of atoms in the Universe. This “chemical universe” could hold cures for every disease known to humankind or some radically new, super-strong or super-light materials. There is a multitude of organisms on our planet (such as the sea urchin) with substances in their bodies that could, in theory, cure many human diseases or boost immunity. But we do not have the technology to synthesize many of them. And, of course, we cannot harvest all the sea urchins in the sea, dry them and make an extract for our pills. But big data and modelling can bring about a breakthrough in this field. Artificial intelligence can be our navigator in this “chemical universe.” Any reasonable breakthrough in this area will multiply our income exponentially. Imagine an AIDS or cancer medicine without any side effects, or new materials for the energy industry, new types of solar panels, etc. These are the kind of things that can change our world.
How is Russia positioned on the AI technology market? Is there any chance of competing with the United States or China?
We see people from Russia working in the developer teams of most big Asian, American and European companies. A famous example is Sergey Brin, co-founder and developer of Google. Russia continues to be a “donor” of human resources in this respect. It is both reassuring and disappointing because we want our talented guys to develop technology at home. Given the right circumstances, Yandex could have dominated Google.
As regards domestic achievements, the situation is somewhat controversial. Moscow today is comparable to San Francisco in terms of the number, quality and density of AI development projects. This is why many specialists choose to stay in Moscow. You can find a rewarding job, interesting challenges and a well-developed expert community.
In the regions, however, there is a concerning lack of funds, education and infrastructure for technological and scientific development. All three of our largest supercomputers are in Moscow. Our leaders in this area are the Russian Academy of Sciences, Moscow State University and Moscow Institute of Physics and Technology – organizations with a long history in the sciences, rich traditions, a sizeable staff and ample funding. There are also some pioneers who have got off the ground quickly, such as Skoltech, and surpassed their global competitors in many respects. We recently compared Skoltech with a leading AI research centre in the United Kingdom and discovered that our institution actually leads in terms of publications and grants. This means that we can and should do world-class science in Russia, but we need to overcome regional development disparities.
Russia has the opportunity to take its rightful place in the world of high technology, but our strategy should be to “overtake without catching up.” If you look at our history, you will see that whenever we have tried to catch up with the West or the East, we have lost. Our imitations turned out wrong, were laughable and led to all sorts of mishaps. On the other hand, whenever we have taken a step back and synthesized different approaches, Asian or Western, without blindly copying them, we have achieved tremendous success.
We need to make a sober assessment of what is happening in the East and in the West and what corresponds to our needs. Russia has many unique challenges of its own: managing its territory, developing the resource industries and continuous production. If we are able to solve these tasks, then later we can scale up our technological solutions to the rest of the world, and Russian technology will be bought at a good price. We need to go down our own track, not one that is laid down according to someone else’s standards, and go on our way while being aware of what is going on around us. Not pushing back, not isolating, but synthesizing.
From our partner RIAC
At Last A Malaria Vaccine and How It All Began
This week marked a signal achievement. A group from Oxford University announced the first acceptable vaccine ever against malaria. One might be forgiven for wondering why it has taken so long when the covid-19 vaccines have taken just over a year … even whether it is a kind of economic apartheid given that malaria victims reside in the poorest countries of the world.
It turns out that the difficulties of making a malaria vaccine have been due to the complexity of the pathogen itself. The malarial parasite has thousands of genes; by way of comparison, the coronavirus has about a dozen. It means malaria requires a very high immune response to fight it off.
A trial of the vaccine in Burkina Faso has yielded an efficacy of 77 percent for subjects given a high dose and 71 percent for the low-dose recipients. The World Health Organization (WHO) had specified a goal of 75 percent for effective deployment in the population. A previous vaccine demonstrated only 55 percent effectiveness. The seriousness of the disease can be ascertained from the statistics. In 2019, 229 million new malaria infections were recorded and 409 thousand people died. Moreover, many who recover can be severely debilitated by recurring bouts of the disease.
Vaccination has an interesting history. The story begins with Edward Jenner. A country doctor with a keen and questioning mind, he had observed smallpox as a deadly and ravaging disease. He also noticed that milkmaids never seemed to get it. However, they had all had cowpox, a mild variant which at some time or another they would have caught from the cows they milked.
It was 1796 and Jenner desperate for a smallpox cure followed up his theory, of which he was now quite certain, with an experiment. On May14, 1796 Jenner inoculated James Phipps, the eight-year-old son of Jenner’s gardener. He used scraped pus from cowpox blisters on the hands of Sarah Nelmes, a milkmaid who had caught cowpox from a cow named Blossom. Blossom’s hide now hangs in the library of St. George’s Hospital, Jenner’s alma mater.
Phipps was inoculated on both arms with the cowpox material. The result was a mild fever but nothing serious. Next he inoculated Phipps with variolous material, a weakened form of smallpox bacteria often dried from powdered scabs. No disease followed, even on repetition. He followed this experiment with 23 additional subjects (for a round two dozen) with the same result. They were all immune to smallpox. Then he wrote about it.
Not new to science, Edward Jenner had earlier published a careful study of the cuckoo and its habit of laying its eggs in others’ nests. He observed how the newly hatched cuckoo pushed hatchlings and other eggs out of the nest. The study was published resulting in his election as a Fellow of the Royal Society. He was therefore well-suited to spread the word about immunization against smallpox through vaccination with cowpox.
Truth be told, inoculation was not new. People who had traveled to Constantinople reported on its use by Ottoman physicians. And around Jenner’s time, there was a certain Johnny Notions, a self-taught healer, who used it in the Shetland Isles then being devastated by a smallpox epidemic. Others had even used cowpox earlier. But Jenner was able to rationally formalize and explain the procedure and to continue his efforts even though The Royal Society did not accept his initial paper. Persistence pays and finally even Napoleon, with whom Britain was at war, awarded him a medal and had his own troops vaccinated.
The Dark Ghosts of Technology
Last many decades, if accidently, we missed the boat on understanding equality, diversity and tolerance, nevertheless, how obediently and intentionally we worshiped the technology no matter how dark or destructive a shape it morphed into; slaved to ‘dark-technology’ our faith remained untarnished and faith fortified that it will lead us as a smarter and successful nation.
How wrong can we get, how long in the spell, will we ever find ourselves again?
The dumb and dumber state of affairs; extreme and out of control technology has taken human-performances on ‘real-value-creation’ as hostage, crypto-corruption has overtaken economies, shiny chandeliers now only cast giant shadows, tribalism nurturing populism and socio-economic-gibberish on social media narratives now as new intellectualism.
Only the mind is where critical thinking resides, not in some app.
The most obvious missing link, is theabandonment of own deeper thinking. By ignoring critical thinking, and comfortably accepting our own programming, labeled as ‘artificial intelligence’ forgetting in AI there is nothing artificial just our own ‘ignorance’ repackaged and branded. AI is not some runaway train; there is always a human-driver in the engine room, go check. When ‘mechanized-programming, sensationalized by Hollywood as ‘celestially-gifted-artificial-intelligence’ now corrupting global populace in assuming somehow we are in safe hands of some bionic era of robotized smartness. All designed and suited to sell undefined glittering crypto-economies under complex jargon with illusions of great progress. The shiny towers of glittering cities are already drowning in their own tent-cities.
A century ago, knowing how to use a pencil sharpener, stapler or a filing cabinet got us a job, today with 100+ miscellaneous, business or technology related items, little or nothing considered as big value-added gainers. Nevertheless, Covidians, the survivors of the covid-19 cruelties now like regimented disciples all lining up at the gates. There never ever was such a universal gateway to a common frontier or such massive assembly of the largest mindshare in human history.
Some of the harsh lessons acquired while gasping during the pandemic were to isolate techno-logy with brain-ology. Humankind needs humankind solutions, where progress is measured based on common goods. Humans will never be bulldozers but will move mountains. Without mind, we become just broken bodies, in desperate search for viagra-sunrises, cannabis-high-afternoons and opioid-sunsets dreaming of helicopter-monies.
Needed more is the mental-infrastructuring to cope with platform economies of global-age and not necessarily cemented-infrastructuring to manage railway crossings. The new world already left the station a while ago. Chase the brain, not the train. How will all this new thinking affect the global populace and upcoming of 100 new National Elections, scheduled over the next 500 days? The world of Covidians is in one boat; the commonality of problems bringing them closer on key issues.
Newspapers across the world dying; finally, world-maps becoming mandatory readings of the day
Smart leadership must develop smart economies to create the real ‘need’ of the human mind and not just jobs, later rejected only as obsolete against robotization. Across the world, damaged economies are visible. Lack of pragmatic support to small medium businesses, micro-mega exports, mini-micro-manufacturing, upskilling, and reskilling of national citizenry are all clear measurements pointing as national failures. Unlimited rainfall of money will not save us, but the respectable national occupationalism will. Study ‘population-rich-nations’ and new entrapments of ‘knowledge-rich-nations’ on Google and also join Expothon Worldwide on ‘global debate series’ on such topics.
Emergency meetings required; before relief funding expires, get ready with the fastest methodologies to create national occupationalism, at any costs, or prepare for fast waves of populism surrounded by almost broken systems. Bold nations need smart play; national debates and discussions on common sense ideas to create local grassroots prosperity and national mobilization of hidden talents of the citizenry to stand up to the global standard of competitive productivity of national goods and services.
The rest is easy
China and AI needs in the security field
On the afternoon of December 11, 2020, the Political Bureau of the Central Committee of the Communist Party of China (CPC) held the 26th Collective Study Session devoted to national security. On that occasion, the General Secretary of the CPC Central Committee, Xi Jinping, stressed that the national security work was very important in the Party’s management of State affairs, as well as in ensuring that the country was prosperous and people lived in peace.
In view of strengthening national security, China needs to adhere to the general concept of national security; to seize and make good use of an important and propitious period at strategic level for the country’s development; to integrate national security into all aspects of the CPC and State’s activity and consider it in planning economic and social development. In other words, it needs to builda security model in view of promoting international security and world peace and offering strong guarantees for the construction of a modern socialist country.
In this regard, a new cycle of AI-driven technological revolution and industrial transformation is on the rise in the Middle Empire. Driven by new theories and technologies such as the Internet, mobile phone services, big data, supercomputing, sensor networks and brain science, AI offers new capabilities and functionalities such as cross-sectoral integration, human-machine collaboration, open intelligence and autonomous control. Economic development, social progress, global governance and other aspects have a major and far-reaching impact.
In recent years, China has deepened the AI significance and development prospects in many important fields. Accelerating the development of a new AI generation is an important strategic starting point for rising up to the challenge of global technological competition.
What is the current state of AI development in China? How are the current development trends? How will the safe, orderly and healthy development of the industry be oriented and led in the future?
The current gap between AI development and the international advanced level is not very wide, but the quality of enterprises must be “matched” with their quantity. For this reason, efforts are being made to expand application scenarios, by enhancing data and algorithm security.
The concept of third-generation AI is already advancing and progressing and there are hopes of solving the security problem through technical means other than policies and regulations-i.e. other than mere talk.
AI is a driving force for the new stages of technological revolution and industrial transformation. Accelerating the development of a new AI generation is a strategic issue for China to seize new opportunities in the organisation of industrial transformation.
It is commonly argued that AI has gone through two generations so far. AI1 is based on knowledge, also known as “symbolism”, while AI2 is based on data, big data, and their “deep learning”.
AI began to be developed in the 1950s with the famous Test of Alan Turing (1912-54), and in 1978 the first studies on AI started in China. In AI1, however, its progress was relatively small. The real progress has mainly been made over the last 20 years – hence AI2.
AI is known for the traditional information industry, typically Internet companies. This has acquired and accumulated a large number of users in the development process, and has then established corresponding patterns or profiles based on these acquisitions, i.e. the so-called “knowledge graph of user preferences”. Taking the delivery of some products as an example, tens or even hundreds of millions of data consisting of users’ and dealers’ positions, as well as information about the location of potential buyers, are incorporated into a database and then matched and optimised through AI algorithms: all this obviously enhances the efficacy of trade and the speed of delivery.
By upgrading traditional industries in this way, great benefits have been achieved. China is leading the way and is in the forefront in this respect: facial recognition, smart speakers, intelligent customer service, etc. In recent years, not only has an increasing number of companies started to apply AI, but AI itself has also become one of the professional directions about which candidates in university entrance exams are worried.
According to statistics, there are 40 AI companies in the world with a turnover of over one billion dollars, 20 of them in the United States and as many as 15 in China. In quantitative terms, China is firmly ranking second. It should be noted, however, that although these companies have high ratings, their profitability is still limited and most of them may even be loss-making.
The core AI sector should be independent of the information industry, but should increasingly open up to transport, medicine, urban fabric and industries led independently by AI technology. These sectors are already being developed in China.
China accounts for over a third of the world’s AI start-ups. And although the quantity is high, the quality still needs to be improved. First of all, the application scenarios are limited. Besides facial recognition, security, etc., other fields are not easy to use and are exposed to risks such as 1) data insecurity and 2) algorithm insecurity. These two aspects are currently the main factors limiting the development of the AI industry, which is in danger of being prey to hackers of known origin.
With regard to data insecurity, we know that the effect of AI applications depends to a large extent on data quality, which entails security problems such as the loss of privacy (i.e. State security). If the problem of privacy protection is not solved, the AI industry cannot develop in a healthy way, as it would be working for ‘unknown’ third parties.
When we log into a webpage and we are told that the most important thing for them is the surfers’ privacy, this is a lie as even teenage hackers know programs to violate it: at least China tells us about the laughableness of such politically correct statements.
The second important issue is the algorithm insecurity. The so-called insecure algorithm is a model that is used under specific conditions and will not work if the conditions are different. This is also called unrobustness, i.e. the algorithm vulnerability to the test environment.
Taking autonomous driving as an example, it is impossible to consider all scenarios during AI training and to deal with new emergencies when unexpected events occur. At the same time, this vulnerability also makes AI systems permeable to attacks, deception and frauds.
The problem of security in AI does not lie in politicians’ empty speeches and words, but needs to be solved from a technical viewpoint. This distinction is at the basis of AI3.
It has a development path that combines the first generation knowledge-based AI and the second generation data-driven AI. It uses the four elements – knowledge, data, algorithms and computing power – to establish a new theory and interpretable and robust methods for a safe, credible and reliable technology.
At the moment, the AI2 characterised by deep learning is still in a phase of growth and hence the question arises whether the industry can accept the concept of AI3 development.
As seen above, AI has been developing for over 70 years and now it seems to be a “prologue’.
Currently most people are not able to accept the concept of AI3 because everybody was hoping for further advances and steps forward in AI2. Everybody felt that AI could continue to develop by relying on learning and not on processing. The first steps of AI3 in China took place in early 2015 and in 2018.
The AI3 has to solve security problems from a technical viewpoint. Specifically, the approach consists in combining knowledge and data. Some related research has been carried out in China over the past four or five years and the results have also been applied at industrial level. The RealSecure data security platform and the RealSafe algorithm security platform are direct evidence of these successes.
What needs to be emphasised is that these activities can only solve particular security problems in specific circumstances. In other words, the problem of AI security has not yet found a fundamental solution, and it is likely to become a long-lasting topic without a definitive solution since – just to use a metaphor – once the lock is found, there is always an expert burglar. In the future, the field of AI security will be in a state of ongoing confrontation between external offence and internal defence – hence algorithms must be updated constantly and continuously.
The progression of AI3 will be a natural long-term process. Fortunately, however, there is an important AI characteristic – i.e. that every result put on the table always has great application value. This is also one of the important reasons why all countries attach great importance to AI development, as their national interest and real independence are at stake.
With changes taking place around the world and a global economy in deep recession due to Covid-19, the upcoming 14th Five-Year Plan (2021-25) of the People’s Republic of China will be the roadmap for achieving the country’s development goals in the midst of global turmoil.
As AI is included in the aforementioned plan, its development shall also tackle many “security bottlenecks”. Firstly, there is a wide gap in the innovation and application of AI in the field of network security, and many scenarios are still at the stage of academic exploration and research.
Secondly, AI itself lacks a systematic security assessment and there are severe risks in all software and hardware aspects. Furthermore, the research and innovation environment on AI security is not yet at its peak and the relevant Chinese domestic industry not yet at the top position, seeking more experience.
Since 2017, in response to the AI3 Development Plan issued by the State Council, 15 Ministries and Commissions including the Ministry of Science and Technology, the Development and Reform Commission, etc. have jointly established an innovation platform. This platform is made up of leading companies in the industry, focusing on open innovation in the AI segment.
At present, thanks to this platform, many achievements have been made in the field of security. As first team in the world to conduct research on AI infrastructure from a system implementation perspective, over 100 vulnerabilities have been found in the main machine learning frameworks and dependent components in China.
The number of vulnerabilities make Chinese researchers rank first in the world. At the same time, a future innovation plan -developed and released to open tens of billions of security big data – is being studied to promote the solution to those problems that need continuous updates.
The government’s working report promotes academic cooperation and pushes industry and universities to conduct innovative research into three aspects: a) AI algorithm security comparison; 2) AI infrastructure security detection; 3) AI applications in key cyberspace security scenarios.
By means of state-of-the-art theoretical and basic research, we also need to provide technical reserves for the construction of basic AI hardware and open source software platforms (i.e. programmes that are not protected by copyright and can be freely modified by users) and AI security detection platforms, so as to reduce the risks inherent in AI security technology and ensure the healthy development of AI itself.
With specific reference to security, on March 23 it was announced that the Chinese and Russian Foreign Ministers had signed a joint statement on various current global governance issues.
The statement stresses that the continued spread of the Covid-19 pandemic has accelerated the evolution of the international scene, has caused a further imbalance in the global governance system and has affected the process of economic development while new global threats and challenges have emerged one after another and the world has entered a period of turbulent changes. The statement appeals to the international community to put aside differences, build consensus, strengthen coordination, preserve world peace and geostrategic stability, as well as promote the building of a more equitable, democratic and rational multipolar international order.
In view of ensuring all this, the independence enshrined by international law is obviously not enough, nor is the possession of nuclear deterrent. What is needed, instead, is the country’s absolute control of information security, which in turn orients and directs the weapon systems, the remote control of which is the greedy prey to the usual suspects.
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The Chairperson of the Commission, H.E. Moussa Faki Mahamat, has announced the appointment of H.E John Dramani Mahama, former President...
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