| Date / Time | 2026-07-21 17:00 -- 18:30 |
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| Room | Mercure Hotel - We Move |
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| Synopsis | This session examines the strategic business implications of AI for industries and technology development. As AI technologies move from laboratory research to large scale deployment, competitive advantage increasingly depends not only on technical excellence but also on how AI solutions generate market value, shape user adoption, and scale within complex organizational systems.
For scientists and technology engineers, this session provides insight into how AI innovations translate into real world impact. Advanced algorithms, robotics, and intelligent systems achieve commercial success only when they are aligned with customer needs, behavioral responses, and strategic positioning. Understanding market intelligence, demand forecasting, and customer relationship management enables technical experts to design AI systems that are both technically robust and economically viable.
From a marketing perspective, AI transforms personalization, consumer analytics, and performance optimization. Firms rely on predictive models to interpret behavioral data and refine communication strategies. For engineers, this creates opportunities to collaborate with business researchers to enhance model explainability, transparency, and trustworthiness in human facing systems.
From a strategy perspective, AI reshapes competitive dynamics, innovation processes, and resource allocation. Organizations must determine how to integrate AI into core technological capabilities, whether to build proprietary systems or partner across ecosystems, and how to sustain advantage in rapidly evolving digital markets. These strategic considerations directly influence research priorities, system architecture decisions, and long term technology roadmaps.
This session aims to foster interdisciplinary dialogue that strengthens the link between AI innovation and market implementation. It also invites research on decision making under AI augmentation, human AI collaboration, and the ethical governance of intelligent systems. Such discussions provide a broader understanding of how cognitive, behavioral, and regulatory factors influence AI adoption and societal acceptance.
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| Date / Time | 2026-07-22 09:00 -- 10:30 |
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| Room | Mercure Hotel - We Move |
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| Synopsis | The rapid advancement of artificial intelligence (AI), machine learning, and large-scale data infrastructures is fundamentally reshaping the way science and technology engage with society. Social systems - ranging from urban mobility and public health to climate adaptation, misinformation, inequality, and governance - are increasingly mediated by digital platforms and data-generating technologies. At the same time, these systems produce vast streams of behavioral, economic, environmental, and network data. This convergence presents a transformative opportunity: to integrate computational methods with social science theory in order to better understand, predict, and address complex societal challenges.
This session, Data Analytics for Societal Challenges: Bridging Computational and Social Sciences, aims to foster interdisciplinary dialogue at the intersection of AI, data analytics, and social inquiry. Computational social science has emerged as a powerful field that combines statistical modeling, network analysis, natural language processing, simulation, and AI-driven approaches with substantive knowledge from sociology, economics, political science, psychology, and related disciplines. However, meaningful progress requires deeper integration between methodological innovation and contextual understanding of social phenomena.
Aligned with the EKC2026 theme, AI-Driven Future of Science and Technology, this session highlights how AI is not only a technological advancement but also a scientific paradigm shift. AI enables the analysis of high-dimensional, dynamic, and heterogeneous data that were previously inaccessible, opening new frontiers in modeling social complexity. From predictive models for public policy to agent-based simulations of collective behavior and AI-assisted decision systems, data analytics is transforming how societal problems are conceptualized and addressed.
The purpose of this session is threefold:
1. Advance methodological innovation by showcasing cutting-edge AI and data-driven techniques applied to societal challenges.
2. Strengthen interdisciplinary collaboration by connecting computational researchers with social scientists and policy-oriented scholars.
3. Promote responsible and ethical AI applications that consider bias, fairness, transparency, and societal impact.
The significance of this session lies in its forward-looking perspective. As AI systems increasingly shape economic systems, information ecosystems, and governance structures, understanding their societal implications becomes essential for sustainable and inclusive technological development. By bridging computational and social sciences, this session contributes to shaping an AI-driven future that is not only technologically advanced but also socially informed, ethically grounded, and responsive to real-world challenges.
Ultimately, the session aims to position data analytics as a central pillar in the future of science and technology - one that enables deeper insight into human behavior, supports evidence-based policy, and strengthens the societal relevance of AI innovation.
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| Date / Time | 2026-07-22 13:30 -- 15:00 |
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| Room | Mercure Hotel - We Move |
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DR. PARK, Hanla
International Agency for Research on Cancer (IARC)
DR. HWANG, Ji Hyun
International Vaccine Institute |
| Synopsis | Background
In an era of rapid technological advancements and digital transformation, the interaction between science, technology, and society has never been more critical. The ways in which technology is governed, the policies shaping its development, and the philosophical underpinnings of scientific progress significantly impact societal well-being and sustainable development. Socio-technical systems play a crucial role in determining the inclusivity, accessibility, and fairness of technological innovations, necessitating a deeper understanding of how technological advancements align with human values and socio-ecological needs.
Historically, technological development has not always been inclusive, often exacerbating social disparities. The governance of artificial intelligence, biotechnology, and emerging digital ecosystems presents ethical and policy challenges that demand multidisciplinary discourse. Likewise, the philosophy of science questions the very foundations of knowledge production, urging scientists and engineers to reflect on the broader socio-political and ecological implications of their work.
As the world confronts issues of climate change, AI/digital ethics, escalating geo-political tensions, and social equity, it is imperative to explore how science and technology can be harnessed or governed to create a more just, peaceful and sustainable future. This session provides a platform to critically examine how innovation can be steered to serve human and societal interests for all.
Purpose
This session aims to bring together researchers from diverse fields, including (but not limited to) science and technology studies, philosophy of science, technology policy and governance, and business studies to explore the intersection of technological advancement (including AI) and socio-economic, political, ecological needs and human values. By facilitating interdisciplinary discussions, the session will encourage participants to reflect on their roles as scientists, engineers, and policymakers in shaping a just and inclusive future particularly in the age of artificial intelligence.
● Presentations and Discussions: The first segment will feature presentations that address fundamental questions. The session welcomes presentations that address any of the following keywords or questions (our scope is not limited to AI):
○ Keywords: AI for social good (AI4SG); AI act and ethics; Global AI regulatory compliance; Socio-ecological perspectives; twin transition (AI & sustainability); technology policy; technology governance; philosophy of science; political economy of science and technology; AI and work; AI and human agency
○ How do socio-technical systems (including AI) influence social and sustainable development?
○ What roles do technology policy and governance play in shaping scientific progress?
○ How can the philosophy of science inform ethical decision-making in technological innovation or shape the ways we understand development and progress?
○ What are the tensions around science and technology and how can tech governance address such tensions?
○ What distinctive forms of value can humans create relative to increasingly capable AI systems?
○ Which skills and capabilities should individuals develop as AI performs tasks traditionally undertaken by professionals such as economists, lawyers, scientists,
analysts, and engineers?
○ Case studies of science and technology fostering inclusivity and social impact |
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