2.4 · Ethics in ICT

Goal: present balanced ethical arguments — pros AND cons.

Common ethical themes in HKDSE essays

1. Privacy — should companies and governments collect / share user data?
2. Free speech vs misinformation — moderation, censorship.
3. Algorithmic bias — AI making unfair decisions.
4. Autonomous weapons and dual-use tech.
5. Job displacement by automation.
6. Environmental footprint of data centres and devices.
7. Surveillance and democratic freedoms.
8. Children's online safety — predators, addiction, mental health.

A balanced argument template

"Position A holds that X. They argue Y. However, position B holds that Z, citing W. On balance, the most workable approach is …"

Markers love seeing both sides plus a conclusion.

Example · "Should schools use facial-recognition attendance?"

Pro	Con
Eliminates impersonation	Treats every student as a suspect
Saves teacher time	Stores biometric data — privacy risk
Generates accurate records	Algorithm bias may misidentify minorities
Enables analytics	Could be misused for unrelated tracking

A measured conclusion: "Use only if data is minimised, parental consent is obtained, and a non-biometric alternative remains for students who opt out."

Code of conduct for ICT users

A simple personal code:

1. Use ICT legally — respect copyright, terms of service.
2. Use ICT honestly — no plagiarism, no impersonation.
3. Respect privacy — yours and others'.
4. Avoid harm — no cyberbullying, no hate speech.
5. Promote inclusion — accessible content, fair representation.
6. Be environmentally responsible — extend device life, recycle.

Exam-style question

Q (5 marks): Discuss the ethical considerations of using AI to grade students' essays. Present arguments on both sides and your conclusion.

Sample answer:

Pros: AI grading provides quick, consistent feedback to every student, reducing teacher workload and detecting subtle errors patiently. With large datasets, AI can identify common student weaknesses and tailor follow-up exercises.

Cons: AI models trained on previous essays may inherit bias against certain writing styles or non-native English speakers. Students may game the model by including keywords. The black-box nature of deep-learning systems makes it hard to explain a grade, undermining the educational purpose. Heavy reliance on AI also raises questions about teacher authority and academic integrity.

Conclusion: AI grading can be a useful assistant that flags issues for teachers, but it should not be the sole grader for important assessments. Transparency about model use, periodic audits for bias, and a teacher-final-say policy strike a reasonable balance.

Key takeaways

• Practice balanced arguments.
• Conclude clearly.
• Use specific HK examples whenever possible.

Chapter wrap-up

➡️ Next chapter: 3 · Intellectual Property