Photo: Andy Kelly / Unsplash
AI East West is an applied, interdisciplinary initiative dedicated to AI ethics in practice – mapping where AI systems misalign with the real-world, cross-cultural contexts they operate in, and carrying human and community insights onto the technical and policy radar of AI.
AI East West works in the in-between space: where systems meet social contexts, where research meets practice. Rather than treating AI risks as purely technical or regulatory problems, we focus on the human layer, using a cross-context lens to map where AI can serve our diverse societies better.
Photo: Andy Kelly / Unsplash
One cube, many sides: we support responsible AI as an integrated system, where each side informs the others.
For organisations, we identify where their AI deployment breaks in the real-world contexts it actually operates in, before risks and harm scale.
Beyond tool-based literacy, we nurture science-backed and socially-aware judgment for everyday users to know when to trust, question, and push back.
Where human experience becomes insight that shapes responsible AI practice: our interview-based, trilingual book project with The University of Tokyo.
A stories-meets-research digital book about what people discover about being human as AI enters their lives. As AI's ethical questions are debated ever more intensely in technical and policy circles, this book turns to the people already living them. What emerges, curated across cultural contexts, is sometimes a human question the AI field has not yet thought to ask.
The book is designed both as public reading and as an accessible educational resource for classrooms exploring AI ethics in pluralistic societies. It is developed jointly with AIR/E at the Interfaculty Initiative in Information Studies, The University of Tokyo.
Periodic memos translating frontier AI ethics research into plain, multilingual briefings for the people AI actually affects. The first memo collection is in preparation.
Photo: Unsplash
AI systems are developed within specific technical, linguistic, and cultural frames. A model built for chat is increasingly expected to make consequential decisions; benchmarks designed for one language are applied as if they measure universal capability; training data reflecting a few societies' norms is deployed across many.
The human layer is wherever AI outputs are used to score, rank, include, exclude, predict, or prioritize: in hiring, law, education, care, creative work, information, and public services. Across these domains, people interpret and act on AI through the lens of their roles, cultures, and lived experience.
AI governance frameworks are globally uneven and often classify risk by domain rather than by how harm actually propagates, through decisions, interpretations, and cultural contexts. The EU builds trust through rights-based legal design; China regulates for societal stability; the US defaults to market self-governance, and these are only three of many diverging approaches worldwide.⁵
In English, a civilizational axis often used as a shorthand for cultural difference itself. We use it not as a binary, not as an exhaustive map, but as a starting point for comparative inquiry into how AI is built, governed, and understood across different societies, stakes, and assumptions.
In Japanese,「東西」can name an East–West transport line connecting two points, or reference two civilizations in relation across history, conveying how we situate ourselves in both physical machines and human knowledge.
Beyond geographical directions,「東西」in Chinese also means "things" and "matters": the tangible and the abstract, the object and the knowledge, even an action and a thought.
These multiple meanings spotlight the pluralism of human experience and the challenge in realizing human-centered AI, where the same technology lands different opportunities and risks for people across cultures, industry, and governance.
'East–West' represents a comparative inquiry lens, not a geographical binary. Responsible AI must be built on pluralistic understanding, not narrow assumptions.
AI East West works project by project across research, dialogue, and publication, choosing each cycle the topics and methods best able to carry community insights onto AI's technical and policy radar. Its inaugural flagship project, a trilingual interview-based book, is developed jointly with AIR/E at The University of Tokyo.
AIEW is founder-led and in its early phase, collaborating with project-based affiliates across Europe and Asia. Its founding team is currently taking shape — if this work resonates with yours, we would like to hear from you.
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