About AI for All
Abstract
Artificial intelligence (AI) is advancing faster than the collaborative frameworks needed to critically shape it, resulting in innovation that remains siloed and insufficiently grounded in cultural and humanistic knowledge. This gap is especially evident in Asia, where complex histories, geopolitical tensions, and vast linguistic diversity remain poorly represented in dominant AI models. AI for ALL/ ALL for AI is a multi-year, cross-disciplinary partnership across six Asian regions and University of California (UC) campuses that brings these issues into sustained, collective inquiry. Initiated and coordinated by the Asia Theories Network (ATN), the project convenes artists, designers, humanists, and AI engineers to work together, emphasizing co-production as a method for generating shared knowledge, building mutual understanding, and fostering discourse across fields. Launched in 2024, the project has established an international research network and completed its initial phase of collaborative groundwork. Building on this foundation, a structured program of research and dissemination is planned through 2029, including an active student research group. The project operates through two complementary components: one focused on ongoing research development through research clusters, theme-based virtual exchanges and presentations, and AI literacy tutorials for all participants; and another focused on dissemination, sharing scholarly and creative outcomes through a multi-year sequence of exhibitions, symposia, public forums, and publications across Asia and the UC system.
Keywords
Artificial Intelligence, Asia, Cultural and Linguistic Representation, Knowledge Co-creation, Arts Research, Critical Humanities, AI Engineering, Cross-disciplinary, AI Literacy
OVERVIEW
The rapid expansion of artificial intelligence has outpaced the development of collaborative frameworks capable of critically engaging and shaping it. [1][2] Current AI innovation remains overwhelmingly siloed—engineers build systems with limited engagement from humanistic, creative, or cultural perspectives, while critical humanists and arts professionals critique AI from the outside, often without meaningful opportunities to influence its design. [3][4] This disciplinary fragmentation produces technologies that are culturally narrow, ethically incomplete, and insufficiently grounded in the lived realities of the global communities they affect. [5][6] This disparity is especially pronounced in Asia, which is home to over one-third of the world’s languages, yet remains severely underrepresented in the datasets, benchmarks, and ethical frameworks that shape dominant AI systems. [7][8]
With its co-founders, and building on and expanding the Asia Theories Network’s substantial international consortium, the University of California, Davis (UC Davis) and National Taiwan University (NTU) received the 2024 Global Affairs UC Davis–Taiwan Collaborative Research Fund in Memory of Larry Vanderhoef and, in February 2025, launched the cross-disciplinary critical AI project titled AI for ALL / ALL for AI. [9] The project is grounded in three principles: 1) developing shared literacy in how AI systems work (“knowing the beast”), 2) integrating humanistic frameworks and regionally grounded cultural and linguistic knowledge into AI criticism and development, and 3) cultivating imaginative, experimental practices that catalyze new ways of thinking on AI. A defining feature of this partnership is through a triadic disciplinary structure—artists, critical humanists, and AI engineers—working together to examine how AI both shapes and is shaped by people, language, and culture across diverse Asian contexts.
With the Vanderhoef Fund and multiple matching grants from NTU, we have now completed three workshops in Taiwan (April, July, and November 2025). In April, regional leaders convened at NTU and co-produced the project’s five core project themes: Sensational Failure: Obsolescence and Cognition, Radical GeneAIologies: Thresholds and Counterhistories, Planetary Co(m)motions: Care and Affect, Situated Systems: Locality and Language, and Unpredictable Machines: Embodiment and Institutions. In July, the project convened Taiwan-based participants for an intensive collaborative workshop at Taipei National University of the Arts (TNUA), marking a significant milestone. Students from partner institutions played an essential role in the workshop. Shortly thereafter, the project launched a binational Student Group, which has since organized reading circles and an online AI literacy training series. The first tutorial, "Embark on a Deep Exploration Journey with Gemini and NotebookLM," was held in September 2025 and featured Dr. Chao Chun Chuang (莊朝均), a Research Fellow at the National Center for High-Performance Computing (NCHC), National Applied Research Laboratories, Taiwan. Six research clusters have emerged to explore topics ranging from the semiotic and representational challenges of Taiwan’s Bua-Puei (搏杯) divination practice in large language models, to research on Cyborg Frontlines: Slow Violence and Grassroots Resistance in Taiwan’s Posthuman Warfare.
Parallel to developments anchored in Taiwan, AI for ALL / ALL for AI has expanded across five additional Asian regions—India, Japan, the Philippines, Singapore, and South Korea—engaging participants from the Centre for the Study of Developing Societies (India); the University of Tokyo and Tokyo University of the Arts (Japan); Ateneo de Manila University (Philippines); the National Gallery Singapore; Kyung Hee University (South Korea); and a broad consortium of Taiwanese institutions, including National Taiwan University (NTU), National Tsing Hua University (NTHU), Soochow University, Taipei National University of the Arts (TNUA), Academia Sinica, the Digital Art Foundation, and the National Center for High-Performance Computing (NCHC). Two University of California campuses—Davis and Irvine—serve as the project’s primary U.S. partners. This partnership is uniquely positioned to advance new discourse and collaborative experimentation on AI rooted in local cultural, linguistic, and political contexts, while contributing outward-facing perspectives to global AI futures.
In November 2025, regional leaders convened at NTU once again, this time, to map out the project structure and multi-year timeline (2026-2029). At this meeting, we also expanded the student group to include 24 graduate and undergraduate students from 7 universities across Asia and the U.S. The student-led workshop that followed explored the conditions necessary for initiating and sustaining collective inquiry and production, and helped establish initial methods for continued cross-cultural collaboration.
PROJECT IMPLEMENTATION PLAN AND TIMELINE
The project is organized around a dual structure: one that supports ongoing research development—through research clusters, theme-based virtual exchanges, monthly virtual presentations, and AI literacy tutorials for students—and another that supports the dissemination of scholarship and creative work through a multi-year sequence of exhibitions, symposia, public forums, and publications across Asia and the UC system.
At the core of the research structure are the research clusters, which operate either regionally or cross-institutionally across Asia and UC campuses. Each cluster will respond to one of the five foundational themes developed in April 2025, using it as a framework to formulate research questions, generate initial writing and conceptual development, produce prototypes, and create scholarly or creative outputs. This model supports locally grounded inquiry while keeping clusters connected to a shared international research framework.
To sustain intellectual momentum, clusters will participate in a monthly theme-based virtual research exchange, a one-hour session led by the regional leaders who authored the thematic frameworks. These exchanges are open to all clusters and function as collective knowledge-building environments. Sessions will feature short provocations with moderated discussion. Example topics include: AI Genealogies; Situated Systems of locality and geopolitics; Embodiment and Interfaces; and Failure and Obsolescence. This structure provides continuity, theoretical depth, and methodological cross-pollination. A second research-support mechanism is the monthly virtual presentation series, featuring artists, humanists, engineers, and invited external scholars to present new ideas and creative or technical developments in AI in their respective fields and regions. Example topics include: Machine Learning as Cultural Technique; Ethical and High-Performance Computing Practices; AI and Bodily Knowledge; AI and the City; and Temporal Capital and Semiconductor Infrastructures. These sessions broaden participants’ exposure and directly feed into cluster research.
The third component supporting research is the virtual AI literacy tutorial series, taught by engineering faculty and AI specialists. These tutorials build foundational technical understanding. Example topics include: Transformer Models and Generative AI Architecture; Bias Identification and Dataset Governance; Prompt Engineering and Model Steering; and Ethical Evaluation of AI Systems.
Complementing the research activities is the project's dissemination structure, which spans exhibitions, public programs, symposia, virtual forums, and publications across multiple regions. These events drive intellectual momentum and generate scholarly and creative outputs that keep pace with AI’s unfolding role in society. The timeline we are working with includes:
CHRONOLOGY
April 2025 — Co-Production Workshop
The project’s five themes were collectively drafted through a co-production workshop, establishing an initial framework for cross-disciplinary and cross-cultural inquiry into artificial intelligence.
2025–2026 — Research and Development
Regional research clusters and collaborators developed projects across art, design, humanities, philosophy, engineering, and other fields. The five themes continued to evolve through dialogue, making, teaching, research, and experimentation.
October 2026 — Taipei Festival
AI for All convenes in Taipei for exhibitions, presentations, workshops, student exchanges, and public conversations. The festival brings together participants and regional collaborators while opening the project in Taipei with an emphasis on Taiwan-specific topics and to broader public dialogue.
December 2026 — Tokyo Exhibition & Forum
The project continues in Tokyo with a forum and exhibition at the University of Tokyo and Tokyo University of the Arts, focusing on Japan and also including a platform that provides exposure to artwork and intellectual development from other project regions.
An Addition: An Open Call for Manifestos
As AI for All continues to evolve, we invite others to enter the conversation by contributing manifestos. Rather than asking for conventional academic papers, the open call invites propositions, provocations, declarations, reflections, refusals, questions, images, sounds, performances, and other forms through which alternative relations with AI might be imagined.
>> Link to Instructions
References
[1] Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (New Haven and London: Yale University Press, 2021), 1–15.
[2] Ruha Benjamin, Race After Technology: Abolitionist Tools for the New Jim Code (Cambridge: Polity Press, 2019), 1–10.
[3] Lilly Irani, Janet Vertesi, Paul Dourish, Kavita Philip, and Rebecca E. Grinter, “Postcolonial Computing: A Lens on Design and Development,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New York: ACM, 2010), 1311–1320.
[4] Catherine D’Ignazio and Lauren F. Klein, Data Feminism (Cambridge and London: MIT Press, 2020), 15–32.
[5] Abeba Birhane, “Algorithmic Colonization of Africa,” Scripted 18, no. 2 (2021): 389–409.
[6] Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: New York University Press, 2018), 1–23.
[7] David M. Eberhard, Gary F. Simons, and Charles D. Fennig (eds.), Ethnologue: Languages of the World, 26th ed. (Dallas: SIL International, 2023).
[8] UNESCO, Recommendation on the Ethics of Artificial Intelligence (Paris: UNESCO, 2021).
[9] AI for All / All for AI. Accessed December 18, 2025. https://sites.google.com/ucdavis.edu/aiforall