This large-scale section provides a comprehensive analysis of the geopolitical and economic transformation of the 21st century, with a particular focus on structural changes accelerated by artificial intelligence. Its central themes are the emergence of a multipolar world order, the redefinition of the role of traditional multilateral institutions, and the strengthening of regional cooperation. The panel analyzes the deepening US-China rivalry, the growing geostrategic importance of India, the Middle East, and Southeast Asia, and the new geopolitical role of critical technologies such as semiconductors, data centers, and cloud infrastructures.
The section focuses on the transformation of the concept of sovereignty: control over data assets, algorithmic decision-making, and digital infrastructures are becoming new dimensions of national self-determination. It will present the functioning of the digital state, models of e-governance and AI-supported public administration, and compare European, Chinese, Indian, and Southeast Asian digital sovereignty frameworks.
The transformation of the global economy will receive special attention: new patterns of globalization, the restructuring of supply chains, the strengthening of regional economic blocs, the energy transition, and the impact of digitalization are all key topics. The panel will analyze in detail the growth dynamics of Asian economies and the new role of Central Asia and Southeast Asia in the global economic architecture. The section aims to explore how geopolitical, technological, and economic megatrends are interlinked and how modern statehood, the global economy, and international cooperation are transforming in the age of AI.
This section provides a comprehensive overview of the educational, scientific, financial, and technological integration taking place in the Eurasian region, which is one of the most important drivers of strategic development in the 21st century. It focuses on strengthening scientific connectivity: new transport and data infrastructures, digital silk road projects, digital education ecosystems, AI-based networks, and cross-border scientific platforms. The panel will show how joint training programs, dual degrees, research consortia, and virtual campuses are transforming the flow of knowledge between continents. It will also address the geopolitical, cultural, and sustainability challenges associated with Eurasian academic cooperation. The panel aims to outline a long-term, shared vision for Eurasia based on the strategic interconnection of education, innovation, and research.
The panel examines the decisive role of physical, digital, and financial connectivity in Eurasia's rise in the 21st century. A key topic is the role of new transport corridors, data infrastructures, digital silk road projects, and regional energy networks in deepening economic integration. The section analyzes the rise of Eurasian financial centers that are now key players in the global financial architecture. It presents the impact of fintech innovations, blockchain-based systems, digital currency experiments, and AI-driven financial processes on economic cooperation. Special emphasis will be placed on how AI-based connectivity solutions are transforming trade, supply chains, and regional economic ecosystems. The panel aims to explore how connectivity is becoming key to Eurasia's sustained economic growth and scientific and infrastructural stability.
This section takes a comprehensive look at how artificial intelligence is reshaping geopolitical power relations, national security strategies, and the concept of technological sovereignty. Its central theme is how AI is becoming one of the most important factors in great power competition: from autonomous weapons systems and predictive security algorithms to the new logic of information warfare and disinformation campaigns. The panel will analyze in detail the geopolitical significance of the semiconductor industry, cloud technologies, 5G/6G networks, and global AI platforms, which now form the basis of digital power and strategic autonomy.
The section presents the different approaches of European, American, and Asian security models, as well as new forms of power derived from control over digital infrastructures. It also addresses the challenges of cybersecurity, critical infrastructure protection, and international AI regulation. Its goal is to explore how 21st-century security policy is transforming in a world where data, algorithms, and the technological ecosystem itself are becoming geopolitical factors.
This section examines the intersections between life-centered sustainability thinking and artificial intelligence, showing how AI is transforming the functioning of economic, social, and ecological systems. Its central theme is how sustainable economics prioritizes human well-being, the protection of natural resources, and ecological integrity over traditional growth indicators. The panel will analyze in detail how AI-based models help measure social and environmental impacts, develop sustainability indicators, and make long-term forecasts.
The section presents AI solutions applied in the fields of energy management, water management, waste management, and agricultural and biodiversity monitoring, which enable a new level of responsible resource use. The energy and resource requirements of artificial intelligence itself will also be critically analyzed, highlighting the need to develop "green AI." The section discusses the possible synthesis of Asian and European sustainability and economic traditions, as well as how AI can become not only a technological tool, but also a strategic partner in the transition to a sustainable society and economy.
This section presents the new generation of circular economy, made more efficient and transparent by digitalization, IoT, and AI. It analyzes methods for tracking material flow chains and optimizing collection and recycling systems. Special attention is given to industrial systems, product life cycle analyses, and "design for reuse" approaches. The panel presents best practices from European and Asian cities, regions, and corporate ecosystems. Its goal is to map out how AI can accelerate the transition from a linear economic model to circular structures.
The panel will discuss the latest scientific findings and methodological challenges in global climate change. It will present the complexity of climate modeling and the importance of research collaborations across multiple scientific disciplines. It addresses the increasing frequency of extreme weather events, growing social vulnerability, and the issue of a just transition. The section reviews how AI can contribute to the refinement of climate models, while also highlighting the difficulties of dealing with uncertainties. Its aim is to provide a solid scientific basis for sustainability policies.
The panel will present in detail how AI-based methods—machine learning, big data analysis, high-resolution simulations—can contribute to improving the accuracy of climate projections. The section also addresses the uncertainties and limitations of AI-based forecasting systems, particularly in the area of regional and local modeling. It analyzes the key role of open data platforms, international scientific collaborations, and supercomputing capacities in the advancement of climate research. It highlights the need for interdisciplinary collaboration between climate science, data analysis, and AI research, with the aim of providing a reliable scientific basis for sustainability and adaptation policies.
This section examines the comprehensive transformation of 21st-century urban development, in which artificial intelligence, digitalization, and sustainability are shaping the future of urbanization in a mutually reinforcing way. Its central theme is how AI-based systems—urban data platforms, sensor networks, smart transportation solutions—contribute to optimizing resource use, creating more resilient infrastructure, and building more livable urban environments. The panel will analyze in detail new models for energy-efficient buildings, green and blue infrastructure, and climate-resilient urban planning.
The section also addresses the role of social innovation: rethinking community spaces, inclusive housing solutions, and the transformation of transportation systems. Special attention is given to comparing European and Asian urbanization patterns and to the question of how technological developments can be reconciled with social well-being and environmental sustainability. Its aim is to show that the sustainable city of the future is the result of technical innovation, ecological adaptation and social cooperation, and to steer smart city concepts in a people-centered, sustainable direction.
This section examines the relationship between energy transition and digitalization. It analyzes the integration of renewable energy sources, energy storage solutions, and smart grids. It addresses the issues of green data centers, energy-efficient AI systems, and digital infrastructures. The panel reviews how energy systems can be developed that ensure both security of supply and decarbonization. Its goal is to connect the technological, economic, and regulatory dimensions.
This section examines how the use of artificial intelligence can be made more hardware- and energy-efficient without hindering innovation. It points out that more environmentally friendly AI is not only a technical issue, but also a regulatory and business model issue. It deals with more efficient algorithms, energy-optimized data centers, new hardware architectures, and the "priority" principles of AI use (which problems are worth using large models for). The panel raises a normative question: what principles should we use to regulate AI's energy consumption in order to maximize social benefits?
This section attempts to quantify the environmental impact of the entire life cycle of artificial intelligence—hardware manufacturing, operation, and waste management. It discusses energy consumption, resource requirements, and e-waste in detail. It highlights that while AI can help achieve climate and sustainability goals, its own ecological footprint also creates new types of negative externalities. The panel addresses the need to develop measurement methodologies, standards, and data systems so that decision-makers can weigh the benefits and costs based on real data.
This section discusses how artificial intelligence is transforming the processes of learning and teaching. It presents adaptive learning systems, intelligent tutors, learning analytics, and virtual learning environments. It addresses the transformation of the role of teachers, the development of new competencies, and the system of lifelong learning. The panel analyzes the benefits and risks of educational solutions using AI. Its goal is to present education as a strategic investment in the digital age.
This section examines the transformation of creative industries and artistic practices in the light of AI. It presents tools and platforms that use AI to create music, images, literature, or multimedia works. It addresses new questions of authorship, originality, and value creation. The panel will discuss the relationship between human creativity and machine generativity. Its goal is to explore how AI can become an inspiring co-author rather than a mere tool.
This section examines modern theories of knowledge management and their applicability in the AI era. It presents systems that support the integration of organizational learning, innovation management, and tacit and explicit knowledge. It addresses new models of data-driven decision-making in the corporate and public sectors. The panel highlights the role of AI in knowledge mapping, competency management, and institutional performance evaluation. Its goal is to position doctoral research as a driver of the knowledge-based society.
This section examines the areas of application of marketing and management science that have been transformed by artificial intelligence. It presents new opportunities in predictive analytics, personalized content generation, brand communication automation, and customer experience management. It deals with AI-based management decisions, corporate risk analysis, and strategic planning tools. The panel analyzes deep learning-supported analysis of consumer behavior, new market segmentation models, and the development of omnichannel systems. It also touches on marketing ethics, transparency, and the social impact of artificially generated content. Its goal is to show how AI is becoming a central strategic resource in corporate operations.
This section examines the impact of AI on the tourism sector, from personalization of services to sustainable destination management. It deals with smart device-supported travel planning, demand forecasting, and real-time visitor management. It analyzes the role of artificial intelligence in tourism marketing automation, big data-based segmentation, and experience design. The panel will discuss new models of sustainable tourism that aim to manage resource capacity, seasonal fluctuations, and reduce environmental footprints. Its goal is to show how the tourism industry can become more flexible, resilient, and experience-oriented with the help of AI.
This section provides a comprehensive overview of how artificial intelligence is transforming the future of agriculture, horticulture and rural areas. Its central theme is how AI increases food security through advanced methods of precision farming, remote sensing, soil monitoring, and crop forecasting, as well as how it supports supply chain transparency and waste reduction. The panel will present in detail the digitization of horticultural production—the use of sensor networks, drones, image processing technologies, and robotic solutions—which enable real-time analysis of plant condition and precise optimization of irrigation, nutrient supply, and plant protection.
The section also addresses the transformation of rural areas, where AI-based services—smart villages, digital public services, e-health platforms—contribute to the modernization of the local economy, increase the competitiveness of businesses, and strengthen community innovation. It analyzes the entire value chain of sustainable food production, including quality control, disease prediction, automated classification, loss minimization, and digital support for short supply chains. Special emphasis is placed on the horticultural research of John Von Neumann University and its applicability in Eurasia.
The aim of the section is to show that AI is not only a technological innovation in agriculture, but also a strategic tool for addressing the challenges of climate change, sustainable production, and the socio-economic renewal of rural areas.
This section examines the historical and theoretical significance of John Von Neumann's work in the light of today's computing and AI. It presents the timelessness of Neumann architecture, the concept of programmable machines, and the mathematical approach to complex systems. It deals with how Neumann's ideas are further developed in modern processor architectures, network systems, and AI frameworks. The aim of the panel is to build a bridge between Neumann's legacy and the technological revolution of the 21st century.
This section discusses the economic and environmental challenges of computing infrastructures that serve artificial intelligence, such as server farms, data centers, and high-performance hardware. It points out that the computing capacity required by AI applications is based on resources that are expensive to build and operate. It analyzes the tensions between investment costs, energy consumption, and sustainability considerations. The panel examines how a balance can be struck between the socio-economic benefits generated by AI and the visible and hidden costs of its operation. It raises the question of what ethical, philosophical, and accountability considerations should play a role in decision-making alongside financial rationality.
This section provides a comprehensive analysis of the mutually reinforcing developments in artificial intelligence, robotics, quantum computing, and digital security, showing how these technologies are shaping economic and social innovation in the 21st century. A key topic is the rapid development of multimodal large language models and autonomous systems, which are taking autonomous learning, problem solving, and adaptation capabilities to a new level. It presents the breakthrough potential inherent in the intersection of quantum computing and AI, with a particular focus on the acceleration possibilities of quantum algorithms, the development of quantum hardware, and critical issues of error correction.
It discusses in detail the new generation of robotics: the sensing, navigation, and coordination technologies of industrial robots, service robots, drones, and autonomous vehicles, as well as the related safety and ethical challenges.
Special emphasis is placed on the human-centered approach of Industry 5.0, which combines human creativity and machine intelligence through collaborative robots and intelligent manufacturing systems. The section also addresses workplace well-being, skills development, and the future of human-machine partnership. Through the topics of digital sovereignty and cyber defense, the panel will highlight the importance of critical infrastructure protection, data security, and cyber warfare, as well as the application of AI-based cybersecurity systems.
The aim of this section is to provide a comprehensive overview of the ecosystem of intelligent technologies and explore how they are fundamentally transforming industry, society, and global security.
This section examines the comprehensive transformation of transport and logistics systems in light of the rise of artificial intelligence and autonomous technologies. It provides a detailed overview of the functioning of self-driving vehicles, intelligent public transport systems and automated logistics networks, with a particular focus on perception, navigation, decision-making and control algorithms. It analyses how these systems can be made safer, more efficient and more environmentally friendly through the integration of AI components.
The panel will cover the digitization of global supply chains and AI-based decision support tools, including predictive inventory management, route optimization, warehouse automation, and real-time network monitoring. It will examine ways to increase the resilience of supply chains amid geopolitical instability, climate change, and market volatility. The section also addresses the coordination and challenges of maritime, air, and land logistics infrastructures. The panel aims to explore how AI can become a key innovation and strategic pillar of mobility and global trade in the 21st century.
This section examines the development of autonomous mobility solutions – self-driving vehicles, smart public transport, logistics systems. It presents AI technologies for perception, decision-making and control. It addresses issues of transport safety, responsibility and regulation. The panel will discuss the transformation of urban and regional mobility models. Its goal is to explore how transportation can be made safer, more efficient, and more environmentally friendly at the same time.
This section discusses the impact of AI on the labor market. It analyzes sectors sensitive to automation, the emergence of new occupations, and the transformation of skill structures. It addresses issues such as working time organization, teleworking, the platform economy, and the digital work environment. The panel examines the role of social inequalities, safety nets, and retraining systems. Its goal is to interpret AI not as the end of work, but as a force that heralds a new quality of work.
This section focuses on the human factor: how to prepare societies for an AI-based world. It addresses the role of education systems, adult education, retraining programs, and labor market policies. It analyzes what digital and "meta" competencies are needed for people to be active shapers, rather than victims, of the changes brought about by AI. The panel places particular emphasis on a fair transition, support for vulnerable groups, and responsible regulation of AI use in the workplace.
This section examines the short- and long-term effects of artificial intelligence on the labor market. It discusses in detail which sectors are likely to see automation, where new occupations will emerge, and which skills will become key. It analyzes the links between productivity growth and changes in the structure of employment, with a particular focus on middle-class jobs. The panel addresses the issue of a just transition, the role of retraining systems, adult education, career correction, and social safety nets. Its central dilemma is how to introduce AI in a way that serves to create a new quality of work rather than mass displacement.
This section discusses how artificial intelligence helps to integrate renewable energy sources—solar, wind, geothermal, and biomass—into modern energy systems. It addresses the prediction of production fluctuations, the management of smart grids, the optimization of energy storage systems, and the prediction of consumer demand. The panel will analyze real-world industrial examples from Asia and Europe, demonstrating the role of digitalization in the transition to carbon neutrality. Its goal is to show that AI is one of the most important strategic drivers of green energy infrastructure.
This section analyzes the technological, economic, and regulatory issues of the hydrogen-based energy economy. It shows how AI can be used to optimize the production, storage, and transport of green hydrogen. It addresses the efficiency improvement of electrolysis systems, the safety of the hydrogen chain, and industrial applications (steel industry, transport, energy). The panel also discusses the potential for Eurasian hydrogen corridors and cooperation. Its aim is to highlight the role of hydrogen in AI-supported, carbon-free future energy systems.
This section examines how AI is transforming the vehicle manufacturing ecosystem in the name of sustainability and climate-neutral mobility. It presents new manufacturing processes for electric and hydrogen-powered vehicles, robotized assembly, and energy efficiency optimizations. It addresses green battery technologies, recycling solutions, and supply chain transparency. It analyzes AI-based design and simulation methods that significantly reduce development time and environmental impact. The panel also reviews a comparison of European and Asian automotive innovations.
This section presents the latest trends in automotive research in line with the profile of the GAMF faculty. It focuses on the perception, control, and navigation systems of autonomous vehicles, as well as testing methods used in real-world environments and simulation spaces. It addresses issues related to automotive software development, cyber-physical systems, and functional safety. The panel will review AI-based solutions for electromobility, energy management, and vehicle diagnostics. Its goal is to show how the NJE GAMF faculty contributes to the research and industrial integration of future mobility technologies.
This section presents research directions in modern mechatronic systems, sensor technologies, and intelligent industrial equipment. It deals with smart manufacturing cells, new methods of robotic assembly, and AI-based solutions for predictive maintenance. It presents software and hardware integration techniques that organize mechanical, electronic, and IT components into a unified system. The panel analyzes the applications of digital twin technology in prototype development and production planning. Its goal is to place the research results of the GAMF faculty in an international context, with a special focus on Eurasian industrial cooperation.
This section presents revolutionary trends in AI-supported materials research. It deals with the role of generative materials science, machine learning-based molecular design, and large-scale simulations. It highlights the development of new battery materials, lightweight industrial materials, biomimetic structures, and extreme-strength alloys. The panel examines how AI accelerates laboratory cycles, reduces costs, and increases the success rate of developments. Its goal is to show that materials science is one of the areas where AI is expected to make the greatest breakthroughs.
This section provides a comprehensive overview of how artificial intelligence is transforming the entire ecosystem of life sciences, medicine, and the healthcare industry. Its main focus is on the rapid development of genomics and precision medicine, where AI-based pattern recognition and predictive models are taking diagnostics, patient pathway planning, and personalized therapies to a new level. The panel will present in detail generative AI solutions for drug discovery, protein structure modeling, and the role of clinical decision support systems and automated triage platforms in modern healthcare.
Special emphasis will be placed on university AI laboratories and innovation centers, which play a key role in scientific breakthroughs, training the next generation of researchers, and strengthening industry-university collaborations. The section reviews the importance of supercomputing infrastructures, open scientific platforms, and interdisciplinary research networks as drivers of healthcare innovation.
The panel will also address ethical, data protection, and liability issues, which are particularly important in the rapidly evolving field of AI-driven healthcare. Its goal is to explore how AI can become one of the most important strategic pillars of preventive medicine, telemedicine, sustainable healthcare, and Eurasian scientific cooperation.
This section examines regional knowledge creation ecosystems, with a particular focus on university-business-government cooperation structures. It presents the development trajectories of regional innovation systems (RIS), the mechanisms of knowledge flows, and collaborative platforms that promote the digitalization of industry and services. It addresses the role of universities in catalyzing corporate research and development. The aim of the panel is to explore how doctoral research can be positioned in the local and Eurasian innovation space.
This section examines how doctoral research contributes to understanding and supporting the digital transformation of companies. It addresses issues of process optimization, automation, AI-based decision support, and performance management. It presents the links between technological innovation and sustainability in corporate strategy. The panel analyzes challenges such as supply chain flexibility, data asset utilization, workforce digitization, and the green transition. Its goal is to make doctoral students' research a key part of the Industry 4.0–5.0 transformation.
This section presents the links between social innovation and digitalization from an interdisciplinary perspective. It deals with the development of digital competencies, community platforms, social participation, and digitally supported services. It analyzes the social embeddedness of AI, the reduction of digital inequalities, and the factors influencing technological acceptance. The panel will also address innovation in the public sphere, the resilience of local societies, and the role of community solutions. Its aim is to show how doctoral research in the social sciences can become a strategic resource in the digital age.
This section examines issues related to the application and further development of international principles on artificial intelligence, in particular the OECD's AI principles adopted in 2019 and updated in 2024. It presents the essence of the value-based approach: reliability, respect for human rights, democratic values, transparency, and accountability. It analyzes how these principles can be translated into specific rules and operating standards for practitioners—companies, public institutions, doctors, teachers, and students. The panel will also discuss whether there is a need to expand and refine these principles in a rapidly changing technological environment.
This section focuses on one of the often missing elements of national and corporate AI strategies: the conscious planning of computing capacities. It points out that the previous cloud-based model obscured the geographical and ownership concentration of physical infrastructure, such as data centers and server farms. It analyzes how AI hardware can become a scarce, strategic resource and how this affects economic sovereignty. The panel seeks metrics and indicators for conscious planning in the three dimensions of capacity (availability), efficiency (human resources, innovation, access), and resilience (security, sovereignty, sustainability).
This section focuses on the use of value-based artificial intelligence. According to the analogy, the AI era also needs a "traffic code" that provides clear, understandable, and binding frameworks for all actors—developers, users, and institutions. The panel will explore the principles of inclusive growth, sustainability, human rights, privacy, transparency, robustness, and accountability. It will examine how these principles can be taught, institutionalized, and monitored in practice in a way that maintains and even strengthens social trust.
This section analyzes the pressure that artificial intelligence puts on political, economic, and social decision-makers. It addresses the differences between various models of capitalism, legal systems, cultural norms, and linguistic environments that influence AI regulation and application. It presents the challenges of investments, governance systems, and collaborations necessary for trustworthy AI. The panel highlights that sound AI policy requires technological, legal, ethical, and intercultural competence, as well as a new type of international coordination.
This section examines how artificial intelligence can contribute to greater prosperity, equal opportunities and sustainability – and when it can lead to the opposite. It highlights that AI has the potential to boost economic growth and productivity, but that GDP growth alone does not guarantee social well-being or environmental protection. The panel discusses how to consciously involve underrepresented groups, how to reduce inequalities, and how to make AI a tool for supporting global sustainability goals.
This section focuses on the financing and strategic issues of AI research and development. It shows why it is important that public and private investments address not only technical challenges, but also social, legal, and ethical ones. It addresses the support of open science, open source, and open data sets, which can promote transparent and less biased AI development. The panel discusses the role of interoperability of standards and the creation of a research ecosystem that helps to create an environment free from harmful biases.
This section presents the complexity of the AI ecosystem: data, computing capacity, network infrastructures, knowledge-sharing platforms, and the regulatory environment together shape the path of development. It analyzes how accessible, sustainable digital environments can be created. It deals with tools such as data trusts and secure data sharing mechanisms. The panel aims to show that the social benefits of AI use depend not only on algorithms, but also on the quality of the entire ecosystem.
This section examines new institutions and forums for global and regional AI governance. It points out that the effects of AI are cross-border, so standards, guidelines, best practices, and metrics are also being developed at the international level. It presents the role of multilateral organizations, professional networks, and intergovernmental cooperation in developing trustworthy AI. The central question of the panel is how to create a consensus-based, interoperable, and culturally sensitive global framework.
This section analyzes the physical presence, or "geography," of artificial intelligence: where data centers are built, how computing capacity is distributed spatially, and what political and economic interests shape the space. It points out that although cloud services are seemingly "location-independent," physical location is strategically important in terms of latency, security, job creation, and jurisdiction. The panel examines how spatial distribution can be shaped to support regional development and regulatory goals.
This section views artificial intelligence as a horizontal, networked technology, like telecommunications or air transport. It points out that the environmental impacts of such basic innovations cannot be easily localized by country, yet must be addressed within a global climate policy framework. The panel discusses how AI, as a global, rapidly growing industry, can be integrated into climate accounting systems. It considers it necessary to develop standards and indicators for measuring AI-related emissions that can be incorporated into national and international climate policy.
This section examines the dual role of AI in agriculture and food chains. It highlights the enormous potential of precision farming, disease monitoring, supply chain tracking, and quality assurance in strengthening food security and sustainability. At the same time, it points out that all this requires huge databases, computing capacity, and energy consumption, creating new risks for small farms, peripheral regions, and the environment. The panel asks: how can agricultural AI be shaped so that it does not deepen inequalities, marginalize small farmers, and truly serve the fair and sustainable transformation of the global food system?
This section focuses on the ethical dimensions of artificial intelligence. It addresses issues of algorithmic bias, discrimination, transparency, privacy protection, and human dignity. It analyzes who bears responsibility for the decisions made by AI systems—developers, operators, institutions, or legal regulators. The panel raises the practical feasibility of the "human in the loop" principle and examines the limits of autonomous systems. Special attention is given to the role of education, codes of ethics, and professional standards in ensuring that AI is truly human-centered, fair, and operates within the rule of law.
This section explores new possibilities for the convergence of augmented reality (AR), virtual reality (VR), and artificial intelligence. It shows how adaptive, real-time, multimodal virtual environments are being created that are transforming education, the world of work, culture, and tourism. The panel will address new forms of human-machine interaction, digital avatars, and mixed reality experience-based applications. It will also address the social and psychological impacts of AR/VR systems, including issues of the attention economy, cognitive load, and digital identity. Its goal is to show how virtual space is becoming one of the strategic knowledge and innovation platforms of the 21st century.
This section presents the convergence of the space industry and artificial intelligence, focusing on AI-based solutions for satellite observation, space infrastructure, planetary research, and space logistics systems. It analyzes the role of autonomous space devices, robotic systems, and spacecraft in the development of scientific research and the commercial space industry. The panel will address the global significance of space-based data platforms—climate monitoring, disaster management, agricultural and urban planning applications—as well as new issues in space security, space sovereignty, and international law. Its aim is to explore how AI is becoming a key strategic component of terrestrial and extraterrestrial infrastructures
This section examines the transformation of social lifestyles, community structures, and cultural patterns in the era shaped by artificial intelligence, with a particular focus on the transition to ecological civilization. It analyzes how AI affects everyday life in practical terms—work, learning, family and community relationships—and how new digital communities, platform-based societies, and online identities are emerging. The panel will address sustainable lifestyle models and conscious consumption patterns in which AI supports the strengthening of environmental responsibility and a culture of well-being.
Special attention will be given to the concept of turquoise zones, which presents organizational and social models based on high awareness, cooperation, and systems thinking. The section also touches on the knowledge and ecological wisdom of indigenous communities, which offer timeless models for harmonious connection with nature, community responsibility, and the development of regenerative lifestyles. The panel aims to explore how new life strategies, community models, and cultural patterns are taking shape in an AI-driven world and how AI can contribute to the creation of an ecological civilization.
Building on the idea of the "Planetary Sutra," this section examines how the development and use of artificial intelligence can be made climate-positive. It shows how AI can be designed to at least minimize environmental harm and, ideally, promote climate goals. It addresses the quantification of AI energy demands, their representation in global inventory assessments, and their incorporation into projections. The panel points out that the "greening" of AI is currently largely based on voluntary, often unaudited commitments, and therefore there is a need to develop more binding and transparent frameworks.