IT in society
Learn the core concepts and decision-making in Cambridge 9626 Topic 12, then practise recall, application and transfer with fictional scenarios.
Exam scope and assessment notes
This is original StudyForA teaching and fictional practice based on Cambridge syllabus outcomes, not copied syllabus text, an official question, a required software brand or a Cambridge mark scheme. Practical software tasks here are planning and reasoning exercises; StudyForA does not inspect files created in spreadsheet, database, graphics, audio/video or animation software, simulate the practical exam environment, award official marks or predict a grade. Follow the software and file-format requirements issued by your centre for your exam year.
Before you begin
- Check whether your route is AS Level (Topics 1–11) or full A Level (Topics 1–21).
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
Before Topic 12: it in society
What you will learn
- Compare electronic, virtual, cryptocurrency, central-bank digital, stored-value, centralised and decentralised currencies and blockchain ledgers
- Explain data-mining stages from business understanding through deployment and evaluate uses/risks
- Analyse social-networking, data-protection, computer-misuse and technology-enhanced learning issues
- Balance organisational and individual benefits against privacy, reliability, safety and access
IT changes how organisations and people interact
Digital currency spans centralised payment systems, stored-value cards, virtual currencies and decentralised cryptocurrencies. A blockchain is a distributed ledger used by some cryptocurrencies; it is not a synonym for all digital money. Data mining follows business understanding, data understanding, preparation, modelling, evaluation and deployment. Its uses range from science and healthcare to business analysis and surveillance.
Evaluate impact, rights and responsibility
Social networking includes forums, blogs, messaging, email and social media. Consider data collection, privacy, misuse, identity, computer-misuse laws and the effects of technology-enhanced learning. Online learning can increase flexibility and autonomy but depends on access, motivation and suitable design. Analyse benefits and costs for affected individuals and organisations; avoid assuming an innovation benefits everyone equally.
Sources for this lesson
Pause and explain
Which approach best demonstrates secure, reliable IT practice in it in society?
Worked example
A retailer mines purchase histories to recommend products. Describe two stages and analyse one benefit and one risk.
Show the worked solution
- Define a business goal, such as improving useful recommendations.
- Prepare relevant, lawful data and build a model; evaluate it before deployment.
- Compare relevance benefits with privacy, bias and security risks.
Answer The retailer should define the purpose, understand and prepare suitable data, build and evaluate a recommendation model, then monitor it after deployment. Recommendations may help customers find relevant items and improve stock decisions. However, sensitive profiling, inaccurate inferences or data breaches can harm people; use data minimisation, transparency, access controls and ongoing evaluation.
Try a topic test
Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.
Test this topic →From guided practice to a new situation
Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
A central bank is considering a digital form of its currency. Give two issues it should analyse before launch.
Give me a hint
Compare system design, access and trust as well as payment speed.
Compare my reasoning
- Clarify whether the system is centralised and who operates it.
- Assess privacy, security, resilience and inclusion.
- Consider effects on banks, consumers, businesses and government.
It should assess privacy and what transaction data the operator can see, alongside security and resilience if the central system fails. It should also consider access for people without smartphones or bank accounts, the effect on commercial banks, offline payments and fraud controls. The design and safeguards determine the trade-offs; the label 'digital currency' alone does not.
Look for these in your work
- Names system-level issues
- Considers multiple stakeholders
- Avoids assuming one design
A data-mining project has a high-accuracy model but was trained on incomplete data. What must happen before deployment?
Give me a hint
Evaluation includes fit to purpose and data limitations, not just one metric.
Compare my reasoning
- Review missingness and representativeness.
- Test against suitable, separate data and relevant groups.
- Correct, limit or delay deployment and monitor outcomes.
The team should investigate why data are missing and which groups are under-represented, then evaluate the model against an appropriate hold-out dataset and task-specific measures. High overall accuracy can hide poor results for a subgroup. It may need better data, revised scope or no deployment, followed by monitoring and a route to correct harmful outcomes.
Look for these in your work
- Challenges the single metric
- Checks group performance
- Makes deployment conditional
An online course is available at any time but many learners stop attending. Explain one benefit, two possible causes and a useful response.
Give me a hint
Availability does not guarantee motivation, access or achievement.
Compare my reasoning
- Identify flexibility as a potential benefit.
- Investigate access and motivation/feedback factors.
- Use learner evidence to adjust support and delivery.
Self-paced delivery can give learners flexibility and autonomy. Drop-off may reflect poor connectivity or device access, low motivation, limited feedback or a course that is difficult to navigate. Compare attendance and feedback across groups, then add accessible low-bandwidth materials, progress cues and timely support. Measure completion and achievement rather than assuming video views equal learning.
Look for these in your work
- Balances benefit and causes
- Uses evidence
- Proposes measurable improvement
Common mistakes
- Calling every digital payment a cryptocurrency
- Treating data mining as only algorithm building
- Discussing benefits without identifying affected groups or risks
What can you explain now?
A central bank is considering a digital form of its currency. Give two issues it should analyse before launch.
Compare with the explanation
It should assess privacy and what transaction data the operator can see, alongside security and resilience if the central system fails. It should also consider access for people without smartphones or bank accounts, the effect on commercial banks, offline payments and fraud controls. The design and safeguards determine the trade-offs; the label 'digital currency' alone does not.
Compare system design, access and trust as well as payment speed.
After trying it yourself, choose your next review. This is your self-assessment.
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Make it stick
Which six stages should a data-mining project pass through?
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.