Title: The Societal Integration and Transformative Potential of Generative Artificial Intelligence
Prof. Suji Moon (Major in Convergence Contents)
Department of Literature and Arts Content Creation, College of Humanities and Arts, Daejin University, Korea.
Biography. Prof. Suji Moon is a professor in the Department of Literature and Arts Content Creation at Daejin University in Korea. She is currently engaged in pioneering research on the innovative advancement of content ecosystems driven by emerging technologies such as artificial intelligence and generative AI, the metaverse, blockchain, augmented reality, virtual reality, and NFTs. Her work encompasses the development of immersive content, as well as user-centered models based on advanced technologies. Through addressing technical challenges and enhancing user experience, she aims to strengthen the technological foundations of the content industry via interdisciplinary research that generates both academic and industrial value. Furthermore, she is committed to expanding the scope of convergence research—traditionally conducted between science and engineering or between the humanities and social sciences—to foster new synergies that integrate the humanities, social sciences, arts, and engineering.
Abstract. With the rapid advancement and proliferation of generative artificial intelligence (AI) technologies, their applications have become increasingly integrated into daily life, such as in smart homes and autonomous vehicles. Moreover, generative AI is actively being developed and applied across various sectors of society, including education, medicine, and business. Accordingly, the expectation that generative AI will bring about unprecedented changes in the way we live and work is highly persuasive. In fact, over the past few years, as awareness of AI’s potential has spread and the availability of AI technologies has increased, the use of AI among the general public has expanded significantly. This trend signifies the normalization of AI usage and suggests that interacting with AI is evolving into an essential competency.
Artificial intelligence is a field of computer science that seeks to understand human cognitive processes and replicate their effects through information systems. AI encompasses intelligent systems capable of learning, reasoning, problem-solving, perception and generation, as well as action. AI can be categorized into weak AI and strong AI. Weak AI(narrow AI) does not possess the full range of human abilities but can solve problems or perform specific tasks—such as playing Go or chess—through algorithms. In contrast, strong AI is characterized by a broad spectrum of human-like capabilities, including communication, reasoning, and emotional responses, enabling it to perform a wide variety of tasks. Currently, commercially available generative AI applications are considered to fall within the domain of weak AI. Nevertheless, they are being utilized in diverse areas, including gaming, entertainment, and various creative activities, and are expected to bring significant social and economic benefits. As a result, the societal expansion of AI is anticipated to accelerate even further.
Title: Toward Realizing Systems Supporting Cognitive Fluctuations in Dementia from a First-Person Perspective
Biography.
Dear Colleagues and Fellow Researchers,
It is with great honor and excitement that I have been invited to participate as a speaker at the 8th International Conference on Next Generation Convergence Technology, organized by the Korea Institute of Electronic Communication Science. The theme “Generative AI and Convergence” represents one of the most significant technological frontiers of our time. As we witness the rapid integration of artificial intelligence with various convergence technologies into our daily lives, this conference provides an invaluable platform for exploring the transformative potential and practical applications of these innovations.
I am particularly excited about the opportunity to engage with all participants, as the topics of this conference have fascinating crossovers with my primary research field of natural computing. I very much look forward to the discussions and exchanges of ideas that will emerge from these interdisciplinary connections.
Thank you to the organizing committee for creating this exceptional opportunity for global collaboration and knowledge exchange.
Abstract.
While numerous IT devices have been proposed to support the care of dementia patients, most are designed for physicians and caregivers to obtain information about patients, with few devices premised on utilization by the patients themselves. Even in Kant’s era, who is believed to have had dementia with Lewy bodies, memoranda were used to cope with memory decline. What is needed is addressing cognitive fluctuations and the forgetting of episodic memories, yet essentially the same memoranda continue to be used even today.
For designing devices that support the independence of dementia patients, engineers need to adopt a “first-person perspective.” This means designing systems from the viewpoint of being able to continue system design even if one were to develop early-onset dementia. It is necessary to prepare what could be called a “thinking cane” – a system that supports “one’s own” thinking processes – and prepare for impending dementia. The essential problem can be summarized in one point: “There may come a time when, in the process of using the ‘cane’ that one prepared for oneself, one forgets who prepared that cane and for what purpose after developing dementia.” Systems must be designed to function beyond that point.
Disorientation in dementia patients often worsens with changes of residence, but from our perspective, this can be reframed as preparing what could be called a “Knowledge Home” – a kind of lifelog – before the onset of dementia, and continuing to remain in one’s own Knowledge Home without “moving” beyond the aforementioned point, which becomes a strategy for avoiding disorientation. This research presents a prototype of a Knowledge Home and raises implementation-based issues, including how to prepare for the arrival of the aforementioned point and social problems related to system realization.