What’s Your Power, Strong AI? – Modern Diplomacy

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The outgoing year has demonstrated, on the one hand, continued growth in the power and capabilities of Artificial Intelligence (AI) relying on so-called “foundation models”, based on deep neural networks such “astransformers”. On the other hand, we were witnessing an entrenchment of certain trends of AI’s development that have to do with overcoming of well-known limitations of AI systems. This is happening against the backdrop of tectonic shifts in the political arena, potentially leading to the breakdown of unipolarity not only in the global economic space but also in the domain of technological infrastructure.
As we mentioned in last year’s review, “foundattioon models” still display their growing “human-level” capabilities to the unsophisticated user. A month ago, almost simultaneously, Facebook [1] and Google announced their “transformer” models, which are capable of generating semi-realistic videos based on textual entries. Somewhat little earlier, the Midjourney neural network enabled an American artist to win the first prize in a fine art competition held in the United States. This summer, it came to a point when a specialist from Google, who takes lead in this field, discovered signs of consciousness in AI and went public with his concerns about it, which led to him being fired for disclosing confidential information.
However, experts are well aware that almost all of the above-mentioned achievements would be impossible without a human specialist working as a “prompt engineering” and “cherry-picking” advisor. On the one hand, a human operator of an AI system manually picks words, phrases, word combinations and their sequences, aimed at obtaining the expected result, and, on the other hand, the same operator subjectively evaluates the quality and adequacy of the result, selecting only one of hundreds of proposed outcomes in the end. This is roughly how you do an Internet search, picking and combining words in a query until you find the desired information in the results. In a similar manner, fortune-tellers read coffee grounds, stirring them up until the resulting configuration of the grounds could be interpreted in a way that would be convincing to the client.
In the meantime, the combination of deep neural network technology based on the “transformer” architecture with an “attention” mechanism is securing more and more applications in areas other than text processing, for which it was originally designed. A wide range of such applications was presented earlier this year at the annual Russian OpenTalks.AI conference. Virtually all such applications either involve severe limits on the range of tasks solved (e.g., face or traffic sign recognition) with large amounts of manually prepared training data or imply uses where errors do not appear to be critical—such as the generation of images and video sequences or creating conversational chat bots in entertainment and leisure industries.
Problems of “explicability and interpretability” of AI based on deep neural network models, while raised in one of the previous reviews, have not been adequately addressed so far, meaning that reliable automation of critical infrastructure with the help of modern AI is not feasible as of yet. In turn, full-scale implementation of “foundation models” requires computational resources that are beyond the reach of even large corporations, except for major IT companies and banks.
Alongside the progress outlined above, more and more “opinion shapers” in today’s scientific community are focusing both on the “inherent problems” of the classical deep neural network-based approach and on the possible ways of overcoming those problems. For example, Yann LeCun, the “thought leader” from one of the world’s leading IT companies, describes in his recent seminal paper the current situation in AI as “a cul-de-sac”, analyzing ways out of this “blind alley” in great detail. He sees the need for “structural thinking” based on the hierarchical neuro-symbolic representations discussed in our previous review as one of development vistas. Another important thrust is the construction of energy-efficient models, roughly in the same vein as Pei Wang, one of the authors of the Artificial General Intelligence (AGI) term, proposed over 20 years ago in his Non-Axiomatic Reasoning System NARS, operating in a resource-constrained environment.
We should remind that the generalized canonical definition of general (strong) artificial intelligence, based on the private definitions of Ben Goertzel, Pei Wang, Shane Legg and Marcus Hutter, is “the ability to achieve complex goals in complex environments using limited resources”.
The need for “structural reasoning” also stems from the recent work done by a team involving Jürgen Schmidhuber, another “authority” on neural networks, the “inventor of LSTM”, where the effectiveness of machine learning was experimentally demonstrated by identifying relatively high-level behavioral primitives (invariants) based on relatively low-level spatiotemporal data obtained during unsupervised learning. Similar results were obtained at the NSU and presented at the AGI-2021 conference last year. In the latter work, it was shown—both experimentally and quantitatively—that successful learning of the same reinforcement learning task under identical conditions, when parameterized at the object level or at the level of individual pixels, occurs in the same number of learning environment cycles, but computational costs in the former case are abysmally lower than in the latter instance. Moreover, the time input in the second case is unacceptably high for physical implementation, indicating the practical need, in terms of efficiency, to build complex—at least, two-level—learning schemes, where the system learns primitives of the environment at the first level, while it learns more complex behavioral programs based on these primitives at the second level. Here we arrive at the fundamental role of cost-effectiveness, whose critical importance has long been touted by Pei Wang to be presently highlighted by Yann LeCun.
An even more fundamental basis for the strong AI in terms of theoretical physics is provided by a team of authors led by Karl Friston in this year’s book, where he justifies intelligent behavior of living beings, including humans, by the fundamental principle of minimizing the so-called “free energy”. Without going into philosophy, physics or mathematics, this principle, very roughly, predetermines the tendency of an “intelligent or reasonable system” to reduce the energy it incurs, or to mitigate uncertainty or reduce unpredictability it experiences. Interestingly enough, despite an apparent semantic similarity of such parameters as probability and predictability, we demonstrated in our recent work, on the example of unsupervised learning for segmenting of natural language texts, significant differences in the accuracy of models based on probability and uncertainty metrics, with uncertainty-based models being much more efficient in terms of text segmentation quality. At the same time, the vast majority of current machine learning models are based on maximizing the prediction probability, so these works pave the way for new fundamental and applied research.
At the Annual AGI-2022 Conference on strong AI, held in August, Ben Goertzel, in his opening address, quite accurately described the current moment in its development. This moment can be seen as reaching the frontiers laid back 25 years ago, when the above-mentioned principles, including “structural reasoning”, “neuro-symbolic integration”, “cost-effectiveness”, “interpretability”, along with several others, under slightly different names and definitions, formed the basis of the first strong AI Webmind project (1997-2001). It was a starting point in professional careers of many prominent contemporary researchers and developers in the field. Today, however, a return to these principles is taking place at a totally different level of computing resource availability and power as well as the development of neural network methods based on “deep” neural networks and understanding of their fundamental strengths and weaknesses.
The trend of creating the so-called “cognitive architectures” that implies a combination of modules performing various cognitive functions for the purpose of solving a more or less wide range of tasks, is still relevant. The most famous example of such architecture is the Alpha Go from DeepMind. In Russia, the most advanced robotics solutions in this field are created at AIRI research institute. The original neuro-symbolic cognitive architecture for decision-making systems pivoted on the fundamental principles of brain activity, implemented in formal mathematical methods has been presented this year by a joint team of the Neurosciences Laboratory of Sberbank and NSU at two international conferences – Biologically Inspired Cognitive Architectures (BICA-2022) and General/Strong AI (AGI-2022). The latter conference also introduced an innovative cognitive architecture that reproduces the functional structure and architecture of the human brain with the purpose of creating an operating system for robots based on the artificial psyche of МIPT developers.
A separate trend worthy of note and related both to the problem of strong AI and to the problem of cost-effectiveness is the so-called neuromorphic computing architectures—specifically, pulsed neural networks. The fact is that any modern solutions based on up-to-date classical computing architectures, including artificial neural networks implemented on “central processors”, multi-core multiprocessor systems and even on graphic cards, have both extremely high energy consumption and an extremely low degree of parallel processing, as compared to the computational properties of animal central nervous systems. The most advanced computing systems which are not yet even comparable with mammals in terms of intellectual capabilities, already exceed the energy consumption of the human biological brain by many orders of magnitude. Pulsed neural networks implemented in neuromorphic chips could hypothetically help bridge this gap.
One crucial factor is that the complex cognitive tasks performed by animals and humans are extremely sophisticated and usually require sorting out a large number of options to select the optimal one. Within traditional architectures, this calls for some form of enumeration, and it may happen that an acceptable option can be either the first or the last in the list of those to be analyzed, which is not known in advance, so we have to run through all variants, and in case of classical neural networks, to figure out activations of all neurons in all layers of a deep neural network. In case of massive parallel processing of cognitive tasks both in the cerebral cortex, and in impulse neural networks, all variants are searched simultaneously (in an asynchronous manner) in all layers, with the “winning” variant starting to suppress “alternatives” at some point, whereas “the enumeration of all possibilities” is not required in most cases. Furthermore, representation of information at the level of single pulses instead of transmitting multibit machine words is another factor potentially reducing power consumption by several orders of magnitude. Those interested in this subject may read Mikhail Kiselev’s last-month report.
The last report, as well as other works in the field of strong and general AI (AGI), mentioned above, have been discussed weekly for the past few years at the online seminars of the Russian-speaking community of developers of strong AI — AGIRussia and its groups in Telegram; the discussion materials are available on the community’s YouTube channel.
Unfortunately, this year’s political situation has not only hampered international scientific communications, destroying a large number of industrial and economic ties in AI research and development, but it has also aggravated the disastrous situation with Russia’s strategic technological lag in this field as compared to the United States and China. The Artificial Intelligence Almanac 2021 ranks Russia 17-22 in the world in terms of scientific publications and patents, tens and hundreds of times behind the leaders—China and the United States. Unfortunately, the resources used in our country for the development of relevant areas and implementation of the above-mentioned projects are negligible as compared to the allocations of Western IT giants and the Chinese government. Under the pressure of sanctions and the destruction of global economic ties, this technological backwardness of Russia can be irreversible unless extraordinary measures are taken.
In humanitarian terms, the problem of AI security, as regards the the unacceptability of Lethal Autonomous Weapons Systems (LAWS), stated in our previous review, has taken on a whole new dimension. The Armenian-Azerbaijani conflict, which broke out in 2020, turned out to be a “war of drones” (unmanned aerial vehicles or UAVs), with the victory going to the side that had the advantage. The conflict in Ukraine has been described as a “drone war” by Elon Musk, and that of a very different scale, as we can tell from the news reports. A search on the Internet for “drone war, Ukraine” gives us an opportunity to assess the drama of the situation in its entirety, both in terms of the areas of application and in terms of providing the troops with these technical capabilities. In this case, the presence or absence of even imperfect modern UAVs with fully manual control or simply guided by GPS proves decisive for the outcome of military-technical operations of various classes. The same can be said about UAV counter-systems, so we can expect that the development of the technological arms race in the foreseeable future will be on the edge of UAV development—surface, underwater and ground “drones”, including LAWS, as well as UAV counter-systems.
In the latter case, the ability to operate autonomously against jamming or heavy clutter in a changeable operational environment may be among the decisive “competitive advantages” in this race. With that said, cost-effectiveness of UAVs will be crucial in their practical applicability due to the direct relationship between power consumption, range, take-off weight, and payload. Given that even existing international arms control agreements are denounced, it is still difficult to expect progress in LAWS control, including loitering munitions, kamikaze drones, and their forthcoming autonomous versions with independent target selection and strike decision-making.
Further complicating the situation is the explosive growth in demand for UAVs and the dramatic increase in profits of the companies producing them. As a result, banning the development and use of LAWS seems almost impossible—at least, until the current conflict is over and the entire global international security system is radically revised. In the meantime, states with greater UAV and LAWS capabilities will have significant military and technical advantages, and those that produce them will have an economic edge.
In conclusion, it can be stated that the further development of AI, undergoing rapid growth, on the one hand, requires new solutions and new thrusts. On the other hand, the aggravation of political, economic and military confrontation between the leading players on the world stage makes them even more dependent on the technological edge, or they might quickly lag behind. Finally, the prospective AI humanization is possible only following a radical stabilization of the international situation.
[1] Meta, a company that owns Facebook, has been recognized as extremist and banned in Russia.
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Since the Covid19 outbreak and the onset of the Russia-Ukraine war, many industrialised and developing nations have understood the significance of supply chains and the risks they provide. This has been seen in the situations of numerous items, such as food and oil, whose supply was affected by the Russia-Ukraine war; it is now especially evident in the case of semiconductors.
Every nation, whether developed or developing, requires semiconductors since they are utilised in every electronic device and in a range of areas, including medical, healthcare, defence, renewable energy initiatives, and a number of upcoming projects, such as quantum computing. The leaders in the semiconductors race on the worldwide market are the United States, whose 2020 market share was valued at over $200 billion. The United States has been a pioneer in the export of semiconductors, commanding about 50 percent of the worldwide market. Semiconductors are one of the top export goods of the United States. Additionally, the United States invests more than one-fifth of their sales on research and development, placing them second only to the pharmaceutical business. China is another nation that is emerging as a major participant in the semiconductor race, since it has been making rapid progress in this arena. China’s semiconductor industry has been growing since 2015, when it accounted for only 3.8% of the global supply race. However, in the last 5 years, China’s semiconductor industry has grown from a mere $!3billion in 2015 to an annual growth rate of $40 billion market industry, and China now stands 1% behind Europe and Japan in the semiconductor race, as China’s semiconductor industry accounts for 9% today and the Europe’s and Japan’s annual percentage growth rates are 2% and 3%, respectively. China has already eclipsed Taiwan in the semiconductor business during the previous two years. If China’s semiconductor industry continues to develop at the same rate, its annual sales might reach $114 billion by 2024, placing it just behind the United States and South Korea.
India’s future with Semiconductors
India’s current semiconductor facilities are the Gallium Arsenide Enabling Technology Centre (GAETEC) and the Semiconductor Laboratory (SCL), but all this could change as India’s Prime Minister Narendra Modi has addressed at the Indian Mobile Congress, which helped in highlighting India’s scope and ambitions with the future technology which India t is developing. The government has begun to recognise the importance of semiconductors and how a domestic semiconductor industry could enable India to reduce its dependence on the giants of the Semiconductor industry and increase the ‘Atmanhirbar Plan’ of India. The Prime Minister of India aspires to make India a leader in cutting-edge technology, and semiconductors are a key component in achieving this objective. The United States has long sought to isolate its essential technology supply chains from China; India can provide an assist in this endeavour. In this cooperation, India is projected to contribute a total of $20 billion, which may help India become a superpower and compete with nations like China and European markets in the chip race. Many countries, not just the United States, are adopting a “China Plus One” strategy to reduce their reliance on China and shift their markets to “like-minded countries” such as India. Many private companies, such as Tata and Adana, have also pledged multi-million dollar investments in this project, which can help India’s semiconductor industry grow at a projected rate of $64 billion by 2026, representing a 19% annual growth rate. As India has been relatively weak in this sector, as India’s imports of semiconductors inputs reached $21 billion in 2019 and that figure has been rising rapidly each year, the recent semiconductor manufacturing incentives offered by the government of India will also help the Indian economy as many American companies will expand their capacities in India and this will help in building the right supply chains worldwide and this will also help industries in India. This will also contribute to the growth of the Indian economy.
Conclusion
While all of this is true and will help India in the long run and increase its presence on the global market, India must not forget that the United States has always been focused on increasing its profits and developing its own industry. India must also keep in mind that chip manufacturing requires a great deal of raw materials and that the United States has always been focused on increasing its profits and developing its own industry. The India-United States cooperation cannot be viewed as restrictive to any particular field, and with the rapidly changing geopolitical situation, it is important to remember that China, which is a producer of electronics, is also a consumer, and that one must observe how the semiconductor and high-end chip industries continue and how demand develops.
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In December 2022, the International Center for Social and Political Studies and Consulting published the second report “Experts on the Malicious Use of Artificial Intelligence and Challenges to International Psychological Security”, penned by this author. This report stems from the research project titled “Malicious Use of Artificial Intelligence and Challenges to Psychological Security in Northeast Asia” (21-514-92001) and jointly funded by the Russian Foundation for Basic Research (RFBR) and the Vietnam Academy of Social Sciences (VASS). The responses garnered from a targeted survey of twenty-five experts from twelve countries and the subsequent analysis of their feedback aim to bring to light the most serious threats to international information-psychological security (IPS) through malicious use of artificial intelligence (MUAI), determining how dangerous these threats are, which measures should be used to neutralize them, and identifying the prospects for international cooperation in this area.
This publication attempts to define the current level of MUAI threat to the IPS as well as its possible level by 2030. The report pays special attention to the situation in Northeast Asia (NEA), where MUAI practices are based on a combination of a high level of AI technologies in leading countries and a complex of acute contradictions in the region. The results of the second survey allow us to trace the continuity and changes in expert assessments compared to the first survey conducted a year earlier, in which nineteen experts from ten countries took part.
In the year since the first expert survey, the world has become even more unstable and dangerous. NATO’s aggressive advance to the East provoked a massive military conflict in Ukraine, one that risks escalating into a world war. Gross domestic product in Ukraine is expected to decline 35 to 40 percent in 2022; Russia also expects a decline of 2,5 percent for the same period. There are clear signs of a recession in the U.S. and the EU, with this economic slowdown reaching even China. Unprecedented inflation, rising borrowing costs, and increasingly intimidating levels of indebtedness are all contributing to fears of economic collapse in many Western and non-Western countries. However, even amid COVID-19, the ultra-rich have little to worry about. In 2022, Forbes identified more than 1,000 billionaires around the world who were richer than they were a year prior (Dolan and Peterson-Withorn, 2022). This deepening polarization in living standards inevitably intensifies the world’s most acute political, racial, and national conflicts across both developing and rich countries—including the United States, long thought immune to such turmoil. In a sick society, threats to psychological security through the malicious use of AI are much higher than in a socially healthy environment. Especially if social regression is observed against the background of the ongoing progress of high technologies.
The transition to advanced forms of AI is already happening. In 2022, DeepMind, a subsidiary of Alphabet specializing in AI, announced the creation of an intelligent agent called “Gato” that can single-handedly perform more than 600 of different tasks (MSN, 2022). The same network, with the same weights, can play Atari video games, capture images, chat, stack blocks with a real robot arm and much more. Gato decides whether to produce text, torque joints, press buttons or take other actions based on context (DeepMind, 2022). The agent could outperform human experts in 450 tasks. Gato learns several different tasks at the same time, easily switching from one skill to another without forgetting what it has learned. Previous AI models have started to combine different skills but when starting a new task, these models had to forget what was previously learned in order to move on to the next one. However, Gato does make some mistakes that a human would not make. While Gato is still far from being an AGI creation, progress is still evident. In terms of malicious use, an agent similar to Gato repeatedly, if not by orders of magnitude, reduces the cost of preparing and implementing various actions by one agent. This makes it easier to carry out psychological operations with a combined effect on the senses—an intelligent agent like Gato can simultaneously send text messages, conduct a conversation and so on.
Modern AI capabilities already enable one to influence public consciousness. The president-elect of South Korea, Yoon Suk-yeol, used an unusual strategy during his 2022 election campaign. His campaign team used deepfakes to make an “AI avatar” that helped him win the election. This technology is helpful for appealing to younger voters and to get them more involved (Vastmindz 2022). AI Yoon’s creators believe he is the world’s first official deepfake candidate—a concept that is gaining traction in South Korea, which has the world’s fastest average internet speeds (AFP 2022). AI technology transformed Yoon Suk-yeol into a more modern candidate than his competitors from the perspective of younger voters. With neatly combed, black hair and a smart suit, the avatar looks nearly identical to the real candidate but instead, used salty language and meme-ready quips in a bid to engage younger voters who get their news online (AFPRelaxnews 2022). Some alarms were raised when the avatar politician used humor to try and deflect attention from Yoon’s past scandals (The Times of India 2022). AI Yoon’s pronouncements made headlines in the South Korean media, and seven million people visited the “Wiki Yoon” website to question the avatar (AFP 2022). At first glance, AI Yoon could pass for an actual candidate—an apt demonstration of how far artificially generated videos have come in the last few years. “Words that are often spoken by Yoon are better reflected in AI Yoon,” said Baik Kyeong-hoon, director of the AI Yoon team (AFP 2022). However, there is a question about what should be done if the avatar of a statesman, politician or business person is a false representation, reinforcing in the public’s conscious and subconscious mind inflated qualities, creating the illusion of attributes that the real person does not possess. The experience of South Korea’s last presidential campaign may have shown, in part, the initial form of a new method of rather dangerous political manipulation. An increasingly adaptive avatar that does not need rest creates an image that a real person will be able to compete with less and less in the public space. This prompts the question of whether “televised presidents” will soon be replaced by “deepfake presidents”?
The world’s first AI TV news anchor was unveiled in China in 2018 (Kuo, 2018), and they were immediately noticeable as the result of an algorithm. However, in December 2021, AI company Xiaoice introduced N Xiaohei and N Xiaobai—virtual replicas of two real-life news anchors—on “AI Business Daily.” According to the Chinese state-run Xinhua News Agency, Xiaoice, in collaboration with National Business Daily, has demonstrated a strong ability to develop virtual replicas that are effectively indistinguishable from real humans through advanced machine learning (ML) and rendering technologies (Lin, 2022). Unfortunately, these extraordinary achievements have the potential to be used for malicious purposes by anti-social actors aiming to destabilize the public consciousness, provoke anti-social actions, and/or deceive individuals.
Notably, this risk is not purely theoretical, with deepfakes having been used on several occasions to trick companies into sending money by them (Statt, 2019; Stupp, 2019; Veldkamp, 2022). Of course, this practice is not yet common, meaning that the risk is fairly minor—for now. In June 2022, the FBI warned that scammers are beginning to use deepfakes to apple for sensitive jobs; this type of fraud could be used to gain access to company networks and obtain company data (Ferraro and Chipman, 2022).
AI technologies are being tested in military conflicts, including psychological warfare. The use of Western-produced AI technologies in the ongoing military conflict in Ukraine is significant. US facial recognition startup Clearview AI has provided technical support to Ukraine. Clearview AI’s tools can identify faces in videos, comparing them to a company database of 20 billion images from public networks, identifying potential spies and people who have been killed. AI tools also play an important role in Ukraine’s propaganda war and in processing critical conflict information. A program from the US company Primer can perform speech recognition, transcription and translation that captures and analyzes Russian information, including conversations between Russian soldiers in Ukraine. The Swiss encrypted chat service called Threema allows Ukrainian users to send this data to the military without revealing their identities. According to former Google chief executive officer Eric Schmidt, now an AI adviser to the US government, the Ukrainian military receives thousands of such reports every day, which are then filtered by an AI program (Global Times, 2022). Russia has not been slow to respond. The Russian Federation’s Ministry of Defense Office for the Development of Artificial Intelligence conducted an examination of the innovative projects to be presented at the Army 2022 Forum for AI technology use (IMTF “Army–2022,” 2022). Vasily Elistratov, head of the Russian Defense Ministry’s Department for the Development of AI Technologies, said that special military operation experience in Ukraine is used to improve weapons systems (Ixbt.com, 2022). Unfortunately, the arms race that is growing in terms of both size and participation, not least in the field of AI, is making international security, including its psychological component, less and less durable.
The potential for MUAI today is astounding. Noting this, researchers from Collaborations Pharmaceuticals in cooperation with European scientific institutions conducted a conceptual experiment. Instead of synthesizing new drugs, they asked the opposite of the MegaSyn AI neural network: to identify substances that are the most toxic to the human body. The neural network correctly understood the task and, in under six hours, generated a list of 40,000 substances that are optimal components of chemical and biological weapons. The AI independently designed not only many known chemical warfare agents, but also many new ones that are more toxic. This simple inversion of the ML model turned a harmless generative model from a useful tool into an enabler of mass murder (Urbina et al., 2022). It is reasonable to suspect that this inversion approach could be applied to other areas, such as finding optimal ways to have negative psychological impacts on the public consciousness.
The most worrisome aspect of these mounting concerns is simple: legislative responses are lagging behind. The sluggish speed of the legislative process (especially relative to that of the MUAI-development process) is clear in the fact that, for example, the EU Artificial Intelligence Act, at the time of writing this text, has not yet passed the first reading in the European Parliament (EUR-Lex, 2022).
In analyzing the current international situation, most studies focus on economic, military, and geopolitical changes without sufficiently linking them to the growing impact of qualitative technological changes on international dynamics, including those in the sphere of psychological security. This underestimation is clear in the near-complete lack in the literature of a systemic analysis of the possible risks of MUAI to psychological security at individual, group, national, and international levels. The absence of such an analysis is unacceptable for numerous reasons.
First, the penetration of modern AI into countless spheres of life makes it a critical component of continued development and progress. Investment in AI may consist of trillions of dollars within the next two decades. According to a PricewaterhouseCoopers Middle East (PwC) report released at the World Government Summit in Dubai, 14 per cent (U.S. $15.7 trillion) of global economic growth will stem from the use of AI by 2030. PwC believes that the greatest gains in 2030 will be in China, where AI will be responsible for up to 26 percent of economic growth (Rao and Verweij, 2018, p. 3). However, as already established, alongside AI’s development will come tremendous risks, including in the field of psychological security.
Second, there is already some research into international practices of MUAI in the psychological field. It is short-sighted not to continue existing research on a systemic interdisciplinary basis, taking into account the counter progress of AI technologies and the regression of existing public structures, national and international institutions, and simply wait until the consequences of AI become an even greater threat to international security. At the same time, strong support from state and non-state actors is required for such research that goes beyond such areas as cybersecurity and information security, as well as psychological security before the introduction of AI technologies, because we are talking about qualitatively different possibilities of causing irreparable damage to the development of human civilization than simply quantitative expansion of propaganda capabilities.
Third, the international situation is continually worsening in several respects. This is not because of particular politicians being in power but because of the severity of the problems faced during the transition to a qualitatively new stage in human development. This transition has been accompanied by an increase in economic problems, socio-political tensions, and geopolitical competition. AI can become both the technological foundation of a new, more socially oriented world order, and the tool of high-tech undemocratic dictatorships, actively used for antisocial purposes by various non-state actors.
The conducted expert survey and the subsequent analysis of its results are precisely intended to fill the gap in the awareness of the nature and scope of threats to society associated with modern and future MUAI practices in the context of the global crisis, as well as an assessment of possible risks in this area in the near future. Further research in this direction obviously follows from the nature and dynamics of the changes taking place in the world.
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By Sofia Strodt
As the year draws to a close, we take a look back at the 33rd annual European Union Contest for Young Scientists (EUCYS) that took place in the Dutch city of Leiden in September. Four projects emerged from a group of 85 to claim the top prizes.
The 2022 edition marked a return to a physical event following the Covid-19 pandemic and was one of many initiatives held under the European Year of Youth. In total, 132 scientists who ranged in age from 14 to 20, came from 33 countries and had gained recognition in national competitions participated in this year’s EUCYS, with the winning projects claiming 7 000 euros each.
EUCYS 2023 will take place in Brussels in September. Following are profiles of this year’s top-prize recipients.
Aditya Joshi and Aditya Kumar, Ireland
Aditya Joshi and Aditya Kumar almost missed the announcement that they were among this year’s EUCYS winners.
During the lunch break in Leiden on the day of the ceremony, they ordered hamburgers that ended up taking longer than expected. As a result, the two 15-year-old boys had to sneak into the back of the concert hall to join the proceedings.
Neither was prepared for the news: they had won the top prize for their new method of solving a triangle-geometry question known as the “Bernoulli quadrisection problem”. More than three centuries after Swiss mathematician Jacob Bernoulli offered a construction for dividing any triangle into four equal parts with two perpendicular lines, Joshi and Kumar produced a method based on computer science and mathematical optimisation.
‘We were just there in silence,’ Joshi said. ‘It took a minute to comprehend.’
Kumar, a longtime friend of Joshi, said: ‘I was in shock. It was like a dream.’
Joshi came up with the project idea after seeing a mathematics book lying around his home in Dublin. He also drew inspiration from his brother, who had competed in earlier math competitions in Ireland.
‘I wanted to do better than him,’ Joshi said with a laugh.
Asking Kumar to help was a no-brainer. The two met in primary school and work well together. For a full year, they devoted virtually every free minute to their project.
‘I must have spent about five to six hours each day working on our project,’ said Kumar. ‘Even when you’re not working on it, you’re thinking about it.’
When Kumar isn’t tackling math riddles, in his free time he likes to play basketball and listen to music. Joshi also plays basketball and enjoys using his 3D printer to design things like customised phone stands.
As they look ahead to university, Joshi and Kumar signalled that they could end up at the same place while having different fields of focus.
‘I want to study something in the area of tech for sure,’ Joshi said. ‘Maybe I’ll go for Computer Science at Dublin City University or Trinity College.’
Kumar is keen to study medicine at either of those institutions – or at the Royal College of Surgeons in Ireland.
Konrad Basse Fisker, Denmark
Konrad Basse Fisker described winning the top EUCYS prize this year as a ‘one-way ticket into the universe of science.’
‘Hearing about all these other extremely cool projects, it hit me how similar all of us are even though we all live in different countries,’ said the 20-year-old from the Danish city of Roskilde.
Fisker was recognised for a project on integrating a protein known as Dsup into algae. Dsup holds out hope of making food more tolerant against radiation and of helping feed astronauts on any successful manned mission to Mars.
Besides receiving the top prize, a personal highlight for Fisker was getting to carry the Danish flag at the opening ceremony in Leiden.
His scientific goal is to help change the ways in which people eat including by growing crops on Mars. That requires new methods to address radiation levels on the Red Planet that are about 50 times as high as on Earth.
‘Earth can’t sustain so many animals for food consumption, so we have to find another way of producing enough food,’ Fisker said.
For the next year or two, he plans to hold off moving on to the university classroom and instead focus on real-life lessons. With his project in mind, Fisker aims to save money for a trip to South-East Asia.
‘It’s going to be a journey to learn about the world – about how people are living in poorer countries – and to get a perspective on how people elsewhere are impacted by the ways in which we eat,’ he said.
Meda Surdokaite, Lithuania
Meda Surdokaite went to art school for 10 years before switching to chemistry and becoming a EUCYS winner.
‘I’m mostly interested in the “why” of my research,’ the 19-year-old student of applied chemistry said during a break from laboratory work at Kaunas University in Lithuania. ‘Either it’s something new or it should help someone.’
Her reason for joining the EUCYS contest had nothing to do with the prospect of a top prize, so Surdokaite could hardly believe her eyes when her name appeared on the projector as a winner.
‘I remember reading it and thought I was dreaming,’ she said.
Her project determined a way to optimise the production of a dye – “Nile Red” – used to identify microplastics. To maximise the impact, Surdokaite decided to share her findings with other scientists for their own research.
‘People tend to get scared about implementing sustainable practices because it can be costly, but we should think about the long-term,’ she said. ‘More money should be spent to implement sustainable practices.’
Surdokaite also believes more companies and universities should give students an opportunity for chemistry training to drive innovation in the EU.
She plans to earn a master’s degree in either organic chemistry or analytical chromatography and then apply for a post-doctoral position.
Michael Lukas Strudler and Andreas Strommer, Austria
Michael Lukas Strudler and his friend Andreas Strommer are aeronautical engineers whose winning EUCYS project is meant to help Europe wean itself off fossil fuels by using more wind energy – a key EU goal as climate change intensifies. 
‘We have to fix the problems the older generation created,’ Strudler said.
Strudler and Strommer, both 19 years old, developed a wind turbine with integrated centrifugal flaps. The vertical axis turbine works at low speeds by using the resistance principle and at higher speeds by using the buoyancy principle.
In their leisure time, Strommer loves sailing in summer and Strudler is fond of playing guitar, drums and harmonica. From different parts of Austria, the duo met in school and consider themselves to be a harmonious team.
‘It took us about 10 seconds to agree on the idea for our project for the competition,’ said Strudler.
He and Strommer are now seeking to turn it into a start-up business. Both are developing the turbine prototype, talking to potential partners and reinvesting the 7 000 euros in EUCYS prize money.
While the EU-contest recognition has further fuelled their ambitions, Strudler and Strommer must complete mandatory military service in Austria before they can devote even more of their energy to the cause of wind power.
This article was originally published in Horizon, the EU Research and Innovation Magazine.   
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