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Future-proofing and ethical issues, worked in full

Part (d) rewards a genuinely two-sided answer — name a real tension or a real adaptive strategy, not a one-sided description.

What each answer type needs to include

  • FUTURE-PROOFING: name what SPECIFICALLY will change (computing power, threat sophistication, standards being deprecated), and a measure that ADAPTS rather than just fixes a current problem.
  • ETHICAL ISSUES: name a SPECIFIC, real tension — a genuine benefit on one side and a genuine harm or risk on the other — not just a list of possible bad outcomes with no counterbalancing benefit named.
Worked example Future-proofing AES against quantum computing Explain, giving examples, what can be done to future-proof AES. WHAT WILL CHANGE: sufficiently powerful quantum computers running Shor's algorithm would eventually threaten current key sizes and some underlying mathematical assumptions. ADAPTIVE MEASURE 1: increase key sizes over time (e.g. AES-256 over AES-128) as available computing power grows, buying more time before brute-force attacks become feasible. ADAPTIVE MEASURE 2: begin staged migration toward post-quantum-resistant algorithms alongside AES, so systems are not caught unprepared when quantum threats become practical. WHY THIS COUNTS AS FUTURE-PROOFING (not just a fix): the measures respond to an ANTICIPATED future threat, not a current known flaw — the definition of "future-proof" specifically. ✓ Future-proofing answers must be forward-looking (anticipating a change that has not fully arrived yet) — describing a fix for a CURRENT vulnerability is a security patch, not future-proofing. Worked example Ethical issues in AI-generated content on social media Explain, giving examples, known ethical issues from AI-generated content in social media. THE BENEFIT SIDE: AI-generated content can lower the barrier to creative expression and content creation for people without professional design or writing skills. THE HARM SIDE: deepfakes and AI-generated misinformation can be created and spread convincingly at scale, and undisclosed AI authorship can manipulate audiences who believe they are viewing genuine human-created content. THE SPECIFIC TENSION: platforms benefit from increased content volume and engagement, but users are exposed to manipulation they cannot easily detect — a genuine harm that is not simply solved by removing the technology, since it has real creative value too. CONCLUSION: naming both the benefit (creative access) and the harm (undisclosed manipulation) is what makes this a genuine ETHICAL tension, not a one-sided complaint. ✓ A one-sided "AI content is bad because of deepfakes" answer misses the ethical TENSION the question is testing — always name a real benefit being weighed against the named harm.

A fast check on a future-proofing or ethics answer

  • Future-proofing: is the measure responding to an ANTICIPATED future threat, not fixing a current known flaw?
  • Ethics: have I named a genuine benefit AND a genuine harm, not just a one-sided list of risks?

Practice for this standard covers the whole topic — flashcards and quiz.