Technology does not exist in a vacuum — computing systems affect individuals and society in profound ways. Ethical issues arise when the use of technology conflicts with moral values such as fairness, privacy, autonomy, and equity. Computer scientists must consider not just "can we build this?" but "should we, and what are the consequences?"
The AQA spec focuses on four main ethical areas: AI ethics, surveillance, data privacy, and the digital divide.
Algorithmic bias, autonomous decision-making in high-stakes contexts (medicine, criminal justice, employment), accountability gaps, deepfakes.
CCTV, facial recognition, workplace monitoring, mass data collection by governments and corporations.
Right to be forgotten, data harvesting by tech companies, consent, personal data traded for free services.
Unequal access to technology by geography, socioeconomic status, age, or disability — creating inequality.
E-waste (toxic materials in landfill), energy consumption of data centres, carbon footprint of streaming and AI models.
Automation displacing jobs, algorithmic management, gig economy platforms exploiting workers.
Algorithmic bias occurs when an AI system produces systematically unfair outcomes for certain groups. This can happen when training data reflects historical prejudices — for example, a facial recognition system trained mostly on white faces may be less accurate for people of colour.
Autonomous decision-making raises accountability questions. When an AI makes a mistake in sentencing, hiring, or medical diagnosis, who is responsible — the developer, the organisation using it, or the algorithm itself? There is currently no clear legal or ethical consensus.
Deepfakes use AI to generate convincing fake video and audio. They can be used to spread disinformation, create non-consensual images, or undermine trust in genuine evidence.
Mass surveillance involves monitoring populations at scale — CCTV in public spaces, facial recognition technology, interception of communications. Proponents argue this makes society safer and helps detect crime. Critics argue it erodes civil liberties, enables oppression, and creates a "chilling effect" where people self-censor knowing they are watched.
Workplace monitoring includes keyloggers, screen recording, email scanning, and tracking remote workers' activity. Again, employers argue this ensures productivity; employees argue it violates dignity and privacy.
The digital divide is the gap between those who have access to technology and those who do not. It exists at multiple levels:
| Type | Example | Consequence |
|---|---|---|
| Geographic | Rural areas with no broadband | Excluded from online services, remote work, education |
| Economic | Families who cannot afford devices or data | Children disadvantaged in school; adults excluded from job market |
| Age-related | Elderly people who lack digital skills | Cannot access banking, healthcare, government services online |
| Disability | Visual/motor impairments with inaccessible software | Excluded if assistive technology not supported |
| Global | Developing nations with limited infrastructure | Fall further behind economically as more services go digital |
Many "free" digital services monetise user data — search queries, location, purchase history, health data. This raises ethical questions about informed consent, data security, and the power imbalance between tech giants and individual users.
The right to be forgotten (established in EU GDPR) allows individuals to request that their data be erased from search results and databases. It conflicts with freedom of information and the public interest.
Surveillance capitalism refers to business models built on harvesting and selling user behavioural data to advertisers — critics argue users are the product, not the customer, and this fundamentally undermines privacy.
8 questions · 24 marks
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Timed exam conditions.