Presentation Materials

Mr. Kang highlighted that as AI rapidly advances from the AlphaGo era into language processing and Transformer model-based generative AI, society is transitioning into an era where users should focus on how to apply technology rather than studying its technical inner workings. He emphasized that the enhanced capabilities and cost-efficiency of AI are transforming diverse industries—including entertainment, media, architecture, marketing, and healthcare—and proposed fostering mutual growth by building a mobility data ecosystem combining AI and creativity across the ASEAN region.

Collaboration between humans and AI in the contemporary continuation of Thai traditional dance was explored through projects such as Remapping Traditions and No. 60, which extract key elements of Thai classical dance and use them to create new movements and techniques. Rather than simply preserving traditional movements and knowledge, this practice has developed into experiments in which AI learns traditional dance movements and generates new movements based on them. This research has moved beyond a one-way relationship in which dancers provide movements to AI toward a two-way form of “co-dancing,” where AI generates movements in real time and dancers respond to them. The practice also considers how traditional dances across Southeast Asia can be connected through new technologies and knowledge, exploring ways of carrying tradition into the future through collaboration with AI.

Working as a digital artist in the age of AI, the speaker reflected on the changing relationship between technology and creative practice. While the emergence of image-generating AI initially created a sense of threat and concern that visual artists’ work could be replaced, AI also opened possibilities for collaboration by assisting with repetitive tasks and the development of ideas. Particular emphasis was placed on maintaining an artist’s distinctive aesthetic identity, cultural heritage, personal experiences, and stories, which form an artistic identity that AI cannot easily replace. Rather than simply using AI-generated results, AI can be used as a source of inspiration to develop one’s own ideas, combining human creativity with the efficiency of technology.

AI was examined as a language-based model and a system through which cultural meanings are produced, with examples of its use in Indonesia’s cultural and artistic fields. These included reinterpreting histories of colonial resource extraction and political violence, digitally recreating historical figures and artworks, and combining traditional drawing practices with gaming culture, demonstrating how AI can connect the past and future while bringing marginalized narratives to light. Viewing AI as a language system also drew attention to how data and algorithms shape cultural signs and meanings, highlighting ethical concerns including transparency, data bias, privacy, and copyright. The discussion ultimately called for policymakers, technology developers, and the cultural and arts sectors to work together in establishing fair and inclusive policy and ethical frameworks so that AI can expand creative possibilities and provide broader access to cultural production.

Brunei’s creative industry landscape revealed both opportunities and structural limitations for the adoption of generative AI, particularly in relation to local cultural, technological, and infrastructural conditions. Despite high levels of internet and mobile connectivity, Brunei’s creative industry remains limited by gaps in relevant data, policy and regulatory frameworks, and physical infrastructure, while traditional cultural practices also lack systematically digitized datasets. Examples of public-sector efforts to preserve traditional textiles and crafts, alongside private-sector initiatives using generative AI, illustrated the potential of AI to support cultural heritage preservation and the development of new designs. At the same time, AI was positioned not as an abstract technology accessed simply through the internet, but as a system dependent on data, networks, and physical infrastructure. Building stronger datasets documenting local everyday life and cultural practices was therefore identified as an important foundation for enabling AI systems to better reflect Brunei’s cultural context.

Approaching AI from the perspectives of publishing, universities, and cultural institutions, the presentation examined the emerging concept of sovereign AI and the creation of locally controlled foundation models aligned with local values and languages. The discussion emphasized that AI depends on a broader supply chain involving human-created data, curation, model training, and deployment, raising questions about who creates, selects, and controls the data used to build AI systems. A case from Norway illustrated collaboration among copyright holders, publishers, the national library, and researchers to examine the value of local content in a national AI model. The presentation also stressed the importance of human and community access to digitized cultural content, particularly when working with minority communities, and highlighted questions of consent, choice, ownership, and control over cultural materials used in AI systems.

Approaching AI from the perspectives of architecture, education, and cultural institutions, the presentation examined how educational institutions can respond to the growing use of AI while maintaining appropriate guidance and governance. The AI Tool Usage Policy at De La Salle-College of Saint Benilde was presented as an example of an institutional approach that welcomes AI while establishing guidelines for its use. Examples from architecture and multimedia arts demonstrated how AI can support visual production, idea development, and communication. Its use in exhibition and curatorial work was also discussed, particularly for writing, editing, proofreading, and processing interview transcripts. Overall, AI was framed as a developing tool whose value depends on how it is integrated into professional and educational practices.

Focusing on the role of Thailand’s Creative Economy Agency, the presentation examined how public policy, infrastructure, and skills development can support creators and the creative economy in the age of AI. The agency’s creative-sector programs, regional incubation centers, resource centers, and Virtual Media Lab were introduced as infrastructure for strengthening the creative ecosystem. Looking toward the next decade, AI in content creation, blockchain, and interactive content were highlighted as areas requiring further development. A Music Exchange project also demonstrated efforts to connect Thai musicians with international markets. The presentation emphasized that AI can support creative industries when accompanied by appropriate data strategies, infrastructure, skills development, and policy frameworks.

Drawing on her dual experience as a media artist working with data and AI and as a public institution practitioner, the speaker examined how data visualization and AI can represent and reshape perceptions of reality. Her practice in data visualization was presented as a way of making social realities visible through digital datasets, while her exploration of AI focused on how machine-learning systems learn from human behavior and transform data into new forms of content. Particular attention was given to the underrepresentation of Korean and other minority cultures in major AI datasets, highlighting how culturally specific subjects can be reproduced through inaccurate or blended representations. The discussion emphasized the need for public institutions to develop and provide culturally relevant datasets so that local and minority cultures are not lost within dominant AI models.

The relationship between humans and machines was explored through the concept of cybernetics and the artistic practice Human Learning. Rather than treating humans and machines as opposing entities, the discussion considered them as participants in a process of mutual learning and influence within interconnected systems. Human Learning explores this relationship through the imitation and reinterpretation of machine movements by the human body, creating a cybernetic loop between human and machine. Posthumanism and the concept of technological singularity were also considered in relation to the possibility of machines reaching or surpassing human intellectual capacities. Art was positioned as a space for speculation and critical engagement with machines, with the possibility of regarding machines as equals to humans serving as a starting point for future collaboration and co-living with AI.

Focusing on the visual arts, major ethical issues surrounding the use of AI were addressed, beginning with the controversy over an AI-generated work that won an art competition in 2022. Key concerns included job displacement, copyright and ownership, the imitation of artistic styles, the use of artworks as training data without consent, and bias and insufficient representation within AI systems. Particular attention was given to Southeast Asia through the example of Filipino artist Patrick Cabral, whose use of AI and machine learning sought to imagine what pre-colonial Philippine architecture and fashion might have looked like without colonization. The limitations of AI-generated imagery were highlighted through the insufficient availability of authentic Southeast Asian historical data, which can lead AI systems to reproduce statistically common visual patterns rather than historically specific regional contexts. Copyright lawsuits and broader questions surrounding the ownership and value of AI-generated works were also discussed, along with whether AI should be regarded simply as another creative tool and how it can be used without reproducing existing ethical problems.

Discussions of machine ethics and principles for ethical AI were introduced, while their limitations, including their non-binding nature and broad scope for interpretation, were also considered. Humanism was ultimately emphasized as a central consideration, with the importance of keeping humans at the center of AI use while maintaining integrity, ethical responsibility, and acknowledgment of the artworks and data that serve as sources for AI systems.

Tracing the historical and philosophical genealogy of artificial intelligence, the discussion examined how the concept of AI developed beyond its association with computers and contemporary technologies. It explored how the distinction between humans and machines has been shaped by technological and philosophical imaginaries, proposing that machines should be understood neither as inferior nor superior to humans, but as entities that are different from us. AI was also approached as an assemblage rather than simply an instrument or tool, with attention given to the development from symbolic AI to connectionist AI and neural networks. Drawing on the histories of cybernetics, neuroscience, and machine learning, questions were raised about whether AI can actually reproduce human thought and consciousness. Contemporary AI was characterized not necessarily as a thinking machine, but as something that thinks for us. In this context, the concept of “weak technology” was introduced, emphasizing the need to open up the weaknesses of technology for creative and aesthetic uses rather than focusing only on ethical applications. The discussion also highlighted the role of hardware development, the internet, big data, and data-labeling labor in the resurgence of AI after the period known as the “AI winter.”

Beginning with an encounter with Google’s machine-learning-based Portrait Matcher in 2016, questions of historical representation, AI, and systems of intelligence were examined through artistic research. The encounter with an artwork from a Malaysian collection raised questions about what happens when images move from national and local contexts into multinational datasets and neural networks. This contemporary technology was connected to the history of colonial information systems and intelligence operations in Malaya, particularly systems developed to collect, process, and act upon information during counter-insurgency campaigns. Connections were also drawn between these systems, later models of information management, and the concept of the “global village,” highlighting the colonial histories underlying contemporary technological systems. Turning to generative AI, the discussion emphasized that AI identifies patterns and statistical regularities within large bodies of data rather than understanding images and the world in the same way as humans. The transformation of history into information and fragmented data was therefore considered in relation to the loss of historical context and understanding, raising broader questions about the relationship between intelligence and understanding.

Drawing on historical examples of technologies that have transformed artistic practices—including photography, film and television, electronic music, and graphic design—the presentation explored how generative AI may reshape creative work. Just as photography challenged painting while giving rise to new forms such as Impressionism and Cubism, generative AI was presented as a technology that can expand creative possibilities rather than simply replace existing practices. However, overreliance on AI may constrain creativity due to biases and limitations in training data, standardized outputs, limitations in composition and expression, and AI errors and hallucinations.

Future creators were therefore described as “T-shaped creatives” with expertise in a specific field and a broad understanding of media and technologies such as film, games, the web, and AI. This could enable individuals and small teams to undertake work once requiring large-scale studios. Ultimately, the presentation emphasized using AI not merely as a content-production tool, but as part of a creative process grounded in human experience, inspiration, and individuality, alongside ethical standards for data transparency, fair compensation and ownership, bias prevention, and disclosure of AI use.

AI was viewed not as an independent creative entity that threatens human creativity, but as a collaborative technology that participates in the human creative process. The presentation emphasized that using AI requires more than simply utilizing generated images; understanding new media and the language and mechanisms of AI is also essential. A collaborative structure involving technology experts, creators, and critical interpreters was introduced, highlighting the artist’s role in questioning what data to collect and how to transform it into meaningful information.

The speaker’s own work transforms everyday emotions and memories into sound and spatial experiences through camera sensors, algorithms, and AI, creating a collaborative process in which humans compose and AI reinterprets. Future possibilities for human-AI artistic collaboration were also discussed, including multimodal AI, brain-computer interaction, VR, immersive spaces, and future opera.

AI was viewed not as an independent creative entity that threatens human creativity, but rather, at present, as a collaborative technology that participates in the human creative process. It was emphasized that using AI requires more than simply using generated images; understanding new media and the language and mechanisms of AI is also important. A collaborative structure in the speaker’s laboratory, where technology experts, creators, and critical interpreters work together, was also introduced. In the convergence of art, science, and technology, artists were described as having a role not only in utilizing data, but also in questioning what data should be collected and how it can be transformed into meaningful information. In the speaker’s own work, everyday emotions and memories are turned into data and transformed into sound and spatial experiences using camera sensors, algorithms, and AI, allowing machines to reinterpret human experiences and creating a collaborative relationship in which humans compose and AI reinterprets. Looking ahead, artistic collaboration between humans and AI was expected to expand further through multimodal AI, brainwave and brain-computer interaction, VR, immersive spaces, and future opera.

Drawing on the artist’s Malaysian Chinese family history, the presentation explored how AI can reconstruct personal and collective memories fragmented or lost through colonialism, migration, and war. Using family photographs, oral histories, and colonial archives, the artist examined the disappearance of a grandfather and the historical gaps left behind, developing possible narratives and images between historical facts and archival gaps through a methodology called “machine fictioning.” Early works used facial recognition and machine learning to address colonial surveillance and the disappearance of people from historical records, while later works used generative AI to reconstruct family memories and colonial history. The artist also discussed AI’s limitations, including its inability to reproduce certain forms of historical violence and its tendency to produce overly polished images, and described using metaphors from oral histories to negotiate with AI and develop narratives. Rather than simply restoring the past, AI serves as a medium for revealing erased memories and absences and rethinking history and memory, while raising questions about what remains beyond AI’s reach and what should be preserved in human memory.

MyCreative Ventures, a government-linked investment institution under Malaysia’s Ministry of Finance, has supported creators who face difficulties accessing traditional financial services and played a role in promoting the creative economy, or “Orange Economy.” It operates various funding programs for the creative industries, including private equity investments, revolving loans, and bridge funds, while contributing to job creation and regional economic development through its support programs and the RIO platform. The institution has supported a broad range of creative industries, including visual arts, performing arts, and animation, achieving notable results. It also outlined the allocation of the 2025 government budget and expressed its commitment to building a sustainable ecosystem in which Malaysian talent can grow over the long term in collaboration with global partners, including Korea.

AI technology should be understood not simply as an automation tool for webtoon creation, but as a partner that helps creators realize their creative plans. The subject of creation and the core creative direction should remain with humans, while creators’ experience and wisdom are essential to avoid being misled by AI hallucinations and inaccurate information. The need to establish clear standards and guidelines for copyright management in training data, the creative process, and secondary and tertiary distribution was also emphasized. The presentation also proposed creating new possibilities for the webtoon industry through the complementary combination of technology and creators, as well as through cooperation between Korea and Malaysia.