Beyond Literacy.
Toward Fluency.

Has this question crossed your mind? Since generative AI entered everyday public conversation in late 2022, organisations and individuals across many sectors have been exploring how AI can support work, learning and decision-making. At the same time, concerns about employment, trust, privacy and the future of human skills have continued to grow.

The more useful question may be: "How can I adapt, contribute and remain human in an AI-shaped world?"

AI literacy is the starting point; AI fluency is what helps you take that understanding into new situations. AI tools will continue to change, so the goal is not simply to keep up with the latest one. It is to build the confidence to use AI purposefully, make informed choices and adapt across different learning, work and everyday contexts.

AI fluency is not about using every new tool. It is about knowing when, why and how to use AI to support your purpose.

That's the spirit behind this Week. Over the next few days, colleagues from across HSUHK — not just us — will share their own answers to that question, one perspective at a time.

So as you read on this week: what would it mean, in your role, to move from AI literacy toward AI fluency?

Once there was a tireless and fictitious servant named Mr. AI, who stood at the gates of knowledge, offering answers to all who requested. He spoke with perfect confidence, never hesitating, never doubting.

Students flocked to him, marveling at his speed and eloquence. Some accepted every word as truth, for he sounded so certain. Others grew wary, for they noticed that sometimes his stories were beautiful but fake, his facts impressive but generated.

A wise scholar observed: “Mr AI is like a mirror that reflects many books ever written, yet cannot verify. He can speak without conscience and answer without accountability. Do you know Mr AI also reads human-written books to prevent him from collapsing?!”

The smart students learned to bow politely to Mr AI, thanking him for his service, then verify his words against trusted sources, peer-reviewed wisdom, and their own reasoning. They treated him as a servant, not a master.

The lazy students followed him blindly, and when errors came—as they surely did—they had no foundation to stand upon.

💡 Lesson: Mr AI offers answers, but wisdom demands verification. Trust his speed, not his certainty. Use him well, but never surrender your judgment.

A recent 30-month study involving 26,811 students found a striking paradox: after adopting generative AI, students’ homework scores increased by 18% and completion time fell by 30% , yet their closed-book examination scores declined by 20% within six months.

Bloom’s Taxonomy, a widely used framework that describes learning from foundational knowledge to higher-order thinking, helps explain why. At the foundational levels of Remember and Understand , AI cannot learn for you. If an exam requires you to recall concepts or explain theories, you still need to know and understand them yourself. AI can instead support how you learn by turning difficult content into analogies, examples, visual explanations, quizzes, or conversations that work better for you.

As you progress through Apply, Analyse and Evaluate , use what you know to solve problems and become increasingly critical of AI’s outputs. Question its reasoning, identify assumptions, compare perspectives, verify claims against reliable sources, and make your own judgement.

Finally, at Create , AI can become a co-creator, helping you explore possibilities, challenge ideas, prototype and refine your work.

AI can support you at every stage, but it should not replace the learning that needs to happen in your own mind. AI fluency is not about letting AI climb for you. It is about learning how to climb yourself, with AI supporting you along the way.

One habit every HSUHK student should develop when using AI is verifying information before relying on it. AI tools can quickly provide answers, summaries, and suggestions, but they are not always accurate. A practical skill is to cross-check important facts with reliable sources such as academic journals, textbooks, or HSUHK library databases. This helps students avoid using incorrect information in assignments and improves their critical thinking skills.

Another useful practice is asking AI to explain concepts rather than generate complete answers. For example, students can use AI to understand a theory, create a study plan, or review grammar, while still completing the actual work themselves. This supports learning and maintains academic integrity.

I believe responsible AI use is not about avoiding AI but about using it wisely. By developing fact-checking skills and treating AI as a learning assistant rather than a shortcut, HSUHK students can benefit from technology while protecting academic standards and producing high-quality work.

💡Use AI to support your learning - not to replace it. Let AI help you understand, practise and improve, while you remain responsible for the final work.

When I imagine AI in students’ futures, I do not see tools replacing thinking. I see graduates who can direct those tools.

AI is changing what “entry-level ready” means. Tasks that once trained juniors, such as data entry, first-draft reports, scheduling, basic analysis and transcription, are now often done by AI, faster and with fewer errors. Employers still want accuracy and coordination, but they now look for graduates who can:

• give AI clear instructions;
• judge its output, use it ethically;
• and hold a whole-project view rather than complete isolated pieces.

The shift is from follower to co-creator. You no longer only execute instructions; you work with colleagues and AI to shape the work.

To see how AI applies to your field, look outside the classroom. Internships, joint-university competitions, exchanges and even a small business venture show how the world already applies AI and where new uses are still taking shape. More exposure brings more insight into both the industry and the new skills you need in the AI era.

Feeling uncertain is normal in a fast-changing world. A useful next step is not more guessing about the future, but a closer look at present work, what AI can already finish, and what your field still needs human judgement to decide. That difference is where we move from using AI to shaping how it should be used.

💡 Start with a real problem in your field, then use AI to explore options while you provide the judgement, context and direction.