Research Reports
《AI Adoption and Data Governance in Hong Kong Primary and Secondary Schools》
The research team visited more than 80 primary and secondary schools in Hong Kong and analysed over 200,000 de-identified pieces of student work produced with AI. It found that schools typically operate multiple AI platforms in parallel, and that the lack of common data formats and governance mechanisms has given rise to "data silos" that prevent teachers, parents, and schools from tracking students' learning journeys and assessing whether AI is actually improving learning. The study recommends building an AI data-governance regime on three levels — schools, school sponsoring bodies , and the wider education sector.
Latest Articles
Building an AI Learning Data Governance Framework Can Begin with a Single Contract
Abstract: For AI to support personalised learning effectively, Hong Kong needs to translate the principles of learning data portability, interoperability and ownership into practical governance arrangements. This article proposes three levels of action: a shared checklist to help schools assess suppliers; standard contracts developed by school sponsoring bodies to reduce duplicated work; and voluntary certification established by the education sector and professional bodies to support product evaluation. While preserving school autonomy and market choice, Hong Kong can begin building common rules through guidance, contracts and pilot schemes, supported by an education data dictionary and staff training in data literacy. Progress…
AI Is Already in Schools. Why Is Personalised Learning Still One Step Away?
Abstract: AI is already making its way into Hong Kong’s classrooms, but achieving personalised learning at scale depends on more than adopting increasingly advanced tools. What matters is whether learning data can be preserved, integrated and used over time. At present, schools and AI platforms often rely on different data formats and standards. When students change schools, advance to a new stage of education or move between platforms, their learning records may not follow them, creating “data silos”. This article argues that Hong Kong should establish three guiding principles—data portability, interoperability, and data ownership and control—so that AI can help…
The Vision for AI in Education: Personalised Education Need No Longer Be Out of Reach
Throughout the history of human education, people have pursued the ideal of teaching each student according to their individual aptitude. More than 2,000 years ago, Confucius advocated “education for all without distinction”: regardless of ability or family wealth, everyone should have an equal opportunity to receive an education and be nurtured. It remains one of education’s highest ideals today. Yet why, after 2,000 years, has it remained an ideal rather than become reality? The answer is simple. Personalised education has never been a problem of principle; it has been a problem of cost. Historically, very few people have truly enjoyed…
What Should Children Learn in the Age of AI?
Artificial intelligence is fundamentally reshaping the value of human skills. As execution becomes increasingly commoditised, judgment is becoming the most valuable capability. Hong Kong’s education system must therefore rethink not only what students learn, but also how their abilities are assessed.
More Than a Jobs Crisis — AI Is Severing Hong Kong's Talent Pipeline
AI is reshaping what the labour market demands of talent, yet Hong Kong's talent development system still runs on the old logic. As entry-level jobs vanish, the apprenticeship channels that turn graduates into seasoned professionals are quietly being lost — a hidden cost that will not show up for another decade.
