● AI Learning · Youth Leadership · Real-World Practice
Learn what
matters
in a changing
world.
A learning community connecting young people, AI-future and the real world.
MOSI works with schools, universities and educators to create project-based AI learning experiences for students aged 14–22.
Scroll to travel the route: land, cross the information field, then pull back to see the whole system
01 / WHY MOSI BEGAN
AI makes creation more accessible. Human connection makes it meaningful.
Students do not begin with a tool or a predetermined answer. They begin with a person, a place or a question that matters.
02 / OUR TEAM
Different expertise, one shared educational purpose.
Alex Xi 席陆晨
Based in the UK — Learning Innovation and Curriculum Design
Leads learning innovation, technical curriculum development and project-based pedagogy.
Completing the joint MA/MSc in Innovation Design Engineering at the Royal College of Art and Imperial College London. ACM MobileHCI 2026 Best Demo Award; a second EEG-based installation accepted into the ACM Multimedia 2026 Interactive Art Track. Founded the digital arts education platform Jade, whose courses have reached learners in 56 countries and more than 3,500 paid students.
Tiffany Tin 田咏琴
Geneva · the UK · Hong Kong — Strategy and Programme Development
Leads strategy, educational direction, learning experience and international communication.
MDes in Design Futures, Royal College of Art; works in public communication in the United Nations human rights context, with more than 100 social media and digital outputs translating complex policy into public narratives. Research on gendered deepfake harm, visual trust and AI governance; co-founder of Guikesong, a youth innovation event in Guizhou with about 300 participants in 2026.
Susie Zou 邹桢
Shenzhen · Hong Kong — International Partnerships & Talent and Teams Operations
Develops partnerships with schools, universities, mentors and industry organisations, and coordinates collaborative delivery.
Graduate of the School of Foreign Studies, Nanjing University. Experience across international communication, policy research, education and programme management, connected with the UNESCO International Centre for Engineering Education, sustainability reporting and clean-energy communication. Represented Chinese youth at the fourth Global Peace Summit; co-founder of Nankathon and Guikesong, which together have connected more than 1,200 participants.
Yifan Zheng
AI Applications and IT Support
Supports AI applications, website development, digital infrastructure and student prototyping.
Seventeen, a first-year undergraduate at East China Jiaotong University. Contributed to an AI project addressing a practical challenge in the bearing industry during the 72-hour Guikesong AI Challenge in Guizhou, and has supported AI education content, small digital products and projects for overseas clients. The youngest member of the team, with a direct understanding of how young people encounter, interpret and learn with AI.
03 / WHAT WE BELIEVE
- Human understanding Begin with people, experiences and contexts.
- Interdisciplinary thinking Connect technology with design, science, communication, business and the humanities.
- Early experimentation Make ideas tangible enough to examine and improve.
- Real-world feedback Test assumptions beyond the classroom.
- Responsible reflection Consider limitations, consequences and who may be affected.
04 / WHAT YOUNG PEOPLE LEARN
More than how to use a tool
- Understand Recognise what AI can do, where it can fail and how its outputs should be evaluated.
- Question Identify problems worth exploring and examine the assumptions behind an answer.
- Imagine Develop original possibilities rather than accepting the first available solution.
- Collaborate Listen to different perspectives, communicate clearly and contribute to shared decisions.
- Make and Test Turn an idea into a tangible prototype, gather feedback and improve it through evidence.
- Lead and Reflect Take initiative, support others and consider the wider consequences of a project.
05 / THE LEARNING CYCLE
Design, technology and people belong in the same conversation.
MOSI uses project-based and experiential learning. Students work in small, interdisciplinary teams to investigate a question, make decisions, build a prototype, test their assumptions and reflect on the results.
- 01
Explore
Observe a place, community or experience.
- 02
Question
Turn a broad concern into a focused challenge.
- 03
Imagine
Generate possibilities and compare perspectives.
- 04
Make
Use AI and other tools to build a prototype.
- 05
Test
Gather feedback from peers, mentors or potential users.
- 06
Reflect and Improve
Evaluate evidence, limitations and next steps.
Mentors do not provide every answer. They create the conditions in which students can experiment safely, learn from setbacks and take ownership of their work.
06 / STUDENTS AND OUTCOMES
What students carry out of a MOSI project.
- They finish something real. Every project ends in a working artefact, not a slide deck: a tool, a prototype, a published study.
- They can explain the trade-offs. Students learn to say what their system does not do, where the data came from and who it affects.
- They work with people outside the classroom. Mentors from our team's own hackathon experience — more than 1200 participants have been through that format — review progress and push back.
07 / REAL-WORLD QUESTIONS
- Learning How could AI support curiosity without replacing independent thought?
- Well-being How might technology provide support without replacing human care?
- Inclusion How could a school or community become more accessible?
- Trust How can young people recognise unreliable information and synthetic media?
- Sustainability How might environmental information become more relevant to everyday decisions?
- Future work How is AI changing the roles, skills and opportunities available to young people?
Think widely. Begin locally. Learn by making.
08 / PROGRAMMES AND PILOTS
Start with a single 240-minute pilot.
A pilot runs with 20–40 students and one teaching team. It is short enough to fit inside a term and structured enough to show whether project-based AI learning works in your setting.
- 240 minutes, run as one intensive day or six short sessions
- 20–40 students per cohort, with their teachers in the room
- 1 working project per team, presented to a real audience
09 / THE NAME
Learn by making.
One idea, held together by everything the students do: explore, question, imagine, make, test, improve.
10 / BUILD WITH PURPOSE
A shared space for education, research and experimentation.
A partnership with MOSI can help a school or university introduce AI through structured, purposeful and responsible learning.
Explore the partnership