Notes · Computer ScienceUK · A-Levels

Consequences of uses of computing

Every computing system has consequences beyond the technical, and this chapter develops the ability to analyse and evaluate them. It covers the individual, social, ethical, cultural and environmental impacts and risks of digital technology, the tension between data collection and privacy, and the main UK legislation that governs computing. The marks here are earned by balanced, well-reasoned extended-response judgements rather than by recall alone.

3 sections~11 min reading time3 competenciesLevel Standard 3

T·121212 / 14

Exam profile

AO1 · Know the categories of consequence of computing and the relevant UK legislationAO2 · Apply ethical, legal and social frameworks to a described use of computingAO3 · Analyse and evaluate the impacts and risks of a computing system and reach a reasoned, balanced judgement

Operators:discussanalyseevaluateexplainjustifyassess

basic level

AS-Level expects awareness of the ethical, legal, cultural and environmental issues and the main legislation.

higher level

The full A-Level expects balanced, evidenced extended-response evaluation that weighs benefits against risks and reaches a justified conclusion.

Depth

Text

Contents · 3 sections

Consequences of uses of computing

Ethical, cultural and environmental issues#

StandardAQA 7517 4.8.1DfE GCE Computer Science - consequences

Categories of consequence of a computing system

Fig. 1A use of computing should be evaluated across several overlapping dimensions - individual, social, legal, ethical, cultural and environmental - rather than judged on its technical merits alone. A strong answer draws on more than one category.

The consequences of a computing system are usually analysed under a set of overlapping categories (shown opposite): individual (effects on a person's work, health, relationships), social (effects on communities and society - inclusion, the digital divide, the nature of work), legal (what the law permits and requires), ethical (what is right, beyond what is merely legal), cultural (effects on shared values, language and identity), and environmental (effects on energy, resources and waste). A strong analysis considers several of these categories rather than only the obvious technical or economic one.

The crucial distinction is between legal and ethical: the law sets a minimum standard, but something can be perfectly legal and still ethically questionable (selling users' browsing habits within the terms of a consent form), or illegal in one country and accepted in another. Professional bodies such as the BCS publish codes of conduct that ask computing professionals to act with integrity, competence and regard for the public interest - to consider not just can this be built, but should it be, and who might be harmed.

Cultural and social effects are far-reaching. Computing has transformed how people work (automation removing some jobs while creating others, remote and gig working), communicate (social media reshaping public discourse, enabling both connection and misinformation), and access services and information - but unevenly, creating a digital divide between those with reliable access and skills and those without, along lines of income, age, geography and disability. Weighing these benefits and harms, rather than declaring technology simply 'good' or 'bad', is the mark of a top answer.

The environmental impact is significant and often overlooked. Manufacturing devices consumes energy and scarce raw materials; data centres and networks draw enormous amounts of electricity for computation and cooling; and short device lifespans generate mountains of electronic waste (e-waste), often containing toxic materials and exported to countries ill-equipped to process it safely. Against this, computing also enables environmental gains - smart energy grids, reduced travel, optimised logistics, dematerialisation of media. A balanced evaluation acknowledges both sides and reaches a supported conclusion.

Worked example

Evaluating the environmental impact of streaming

Evaluate the environmental impact of the shift from physical media (DVDs) to online video streaming. Reach a reasoned conclusion.

Argument for streaming
Streaming avoids manufacturing, packaging and transporting discs, and removes the e-waste of obsolete physical media - a clear dematerialisation benefit.
Argument against
Streaming shifts the cost to data centres and networks, which consume large amounts of electricity for delivery and cooling; heavy, repeated streaming of the same content can exceed the footprint of a single disc.
Weigh the evidence
The net impact depends on how the electricity is generated (renewable vs fossil), how often content is re-watched, and streaming quality. Neither option is unconditionally 'greener'.

Result: A justified conclusion: streaming is generally lower-impact for occasional, varied viewing on efficient, renewably-powered infrastructure, but the environmental case weakens for repeated high-definition streaming on fossil-fuelled grids - the answer is conditional, not absolute.

Typical mistakes

Treating 'legal' and 'ethical' as the same thing - an action can be legal but unethical, or vice versa.
Writing a one-sided answer (all benefits or all harms) when evaluative questions reward a balanced argument with a reasoned conclusion.

Active revision

Discuss the impact of widespread automation of routine jobs by software and robotics. Consider social, individual and economic consequences, and reach a reasoned conclusion about whether the benefits outweigh the harms.

Active recall

Recall the key points — then reveal.

Sources: GCE AS and A level subject content for computer science (Department for Education) · AQA A-level Computer Science 7517 specification (AQA)

Privacy, data and surveillance#

StandardAQA 7517 4.8.1DfE GCE Computer Science - privacy

Modern systems collect personal data on an unprecedented scale - location, browsing, purchases, health, social connections - and the central tension of this section is between the value of that data (personalised services, medical research, security, convenience) and the individual's right to privacy. Data that is genuinely useful is also data that can be misused, lost in a breach, or repurposed beyond what the individual expected, so the debate is rarely 'collect or not' but 'collect what, for what purpose, with what safeguards and consent'.

Surveillance by governments and companies raises acute concerns. State surveillance of communications may help prevent crime and terrorism but can chill free expression and be abused; corporate surveillance - the tracking that funds much of the 'free' web - builds detailed profiles used to target advertising and influence behaviour, often with only nominal consent buried in lengthy terms. Technologies such as facial recognition sharpen the dilemma: powerful for finding missing people or suspects, but capable of pervasive, non-consensual tracking and prone to bias against some groups.

Two related risks are profiling and algorithmic bias. When decisions about credit, insurance, policing or hiring are made or informed by algorithms trained on historical data, they can entrench existing biases while appearing objective, and they can be hard to challenge because the reasoning is opaque. The concentration of data in a few large companies also creates power imbalances and single points of failure. Good analysis names the specific harm (bias, breach, loss of autonomy) rather than a vague 'privacy is bad'.

Mitigations exist and should feature in a balanced answer: data minimisation (collect only what is needed), anonymisation and pseudonymisation, strong encryption, meaningful and informed consent, transparency about how data is used, and the legal rights (below) that let individuals see, correct and delete their data. The mark of a mature response is to recognise that privacy is not absolute - it is traded off against genuine benefits - and to argue where the line should sit and why, with reference to specific safeguards.

Worked example

Weighing a data-driven recommendation system

A streaming service tracks everything a user watches to recommend content and to sell aggregated insights to advertisers. Analyse the privacy trade-off and reach a judgement.

Benefits
The user gets more relevant recommendations and a free or cheaper service funded by advertising; the company gains commercially valuable insight.
Risks
A detailed behavioural profile is built, possibly beyond what the user realises; the data could be breached, sold on, or used to manipulate choices, and consent is often not meaningfully informed.
Safeguards
Data minimisation, clear opt-in consent, anonymisation before any sale, and a right to view and delete the profile would reduce the harm while keeping most of the benefit.

Result: Justified conclusion: the personalisation benefit can be legitimate provided consent is genuinely informed and the data is minimised, anonymised and controllable by the user; without those safeguards the same system becomes an unacceptable intrusion. The judgement turns on the safeguards, not the tracking alone.

Typical mistakes

Arguing that any data collection is simply 'an invasion of privacy' without weighing the genuine benefits and possible safeguards.
Ignoring algorithmic bias and profiling, treating a system as neutral just because it is automated.

Active revision

A city proposes live facial-recognition cameras in public spaces to help police identify suspects. Discuss the benefits and the privacy and ethical risks, name two safeguards that could be required, and give a reasoned conclusion.

Active recall

Recall the key points — then reveal.

Sources: AQA A-level Computer Science 7517 specification (AQA)

The legal framework: computing legislation#

StandardAQA 7517 4.8.1DfE GCE Computer Science - legislation

Key UK computing legislation

Fig. 2The four Acts most relevant to A-Level Computer Science, and what each governs. In a scenario question, match the situation to the Act and state the specific offence, right or obligation.

Several pieces of UK legislation govern computing, and you should know the purpose of each and be able to apply it to a scenario (summarised opposite). The Data Protection Act 2018, which enacts the UK GDPR, regulates how personal data is processed: data must be collected and used fairly, lawfully and for a specified purpose, kept accurate, secure and no longer than necessary, and individuals have rights to access, correct and erase their data. Organisations that fail to protect personal data can be heavily fined - the law that a company breaches when it leaks its customers' details.

The Computer Misuse Act 1990 is the anti-hacking law. It creates three offences: unauthorised access to computer material (accessing a system you have no right to, such as guessing a password); unauthorised access with intent to commit a further crime (accessing in order to defraud); and unauthorised modification of computer material (altering or deleting data, or creating and spreading malware). It is the law that criminalises hacking, virus-writing and denial-of-service attacks regardless of whether damage results.

The Copyright, Designs and Patents Act 1988 protects intellectual property - including software, music, film, images and text - giving the creator exclusive rights to copy, distribute and adapt their work. It makes unauthorised copying, sharing (piracy) or use of protected works unlawful, and underlies software licensing and the terms of open-source and proprietary distribution. It is the law engaged when someone pirates software or uses copyrighted media without permission.

The Regulation of Investigatory Powers Act 2000 (RIPA) governs how public authorities may lawfully intercept communications and conduct surveillance, setting out who may do so, under what authorisation, and with what oversight - balancing investigative powers against civil liberties. In an exam scenario the skill is to identify which Act applies and state the relevant obligation or offence: a data breach engages the Data Protection Act, hacking engages the Computer Misuse Act, piracy engages the Copyright Act, and lawful interception engages RIPA.

Worked example

Matching scenarios to legislation

Identify the relevant UK Act and the specific issue for each: (a) a company's customer database is stolen because it was left unencrypted; (b) a person writes a virus and releases it; (c) a website hosts pirated films.

Scenario (a)
Personal data has not been kept secure, breaching the Data Protection Act 2018 / UK GDPR obligation to protect personal data - the company may be fined.
Scenario (b)
Writing and releasing a virus is unauthorised modification of computer material under the Computer Misuse Act 1990 (its third offence).
Scenario (c)
Distributing films without the rights-holder's permission infringes the Copyright, Designs and Patents Act 1988.

Result: (a) Data Protection Act, (b) Computer Misuse Act, (c) Copyright, Designs and Patents Act. The exam skill is matching the scenario to the correct Act and naming the specific offence or obligation.

Typical mistakes

Confusing the Acts - a data leak is the Data Protection Act, hacking is the Computer Misuse Act, and copying software is the Copyright Act.
Stating an Act's name without applying it - the marks come from linking the specific scenario to the specific offence or obligation.

Active revision

For each scenario, name the UK Act that applies and the specific offence or obligation: (a) an employee guesses a colleague's password to read their emails; (b) a firm loses a laptop of unencrypted customer records; (c) a student shares a paid-for game online for free.

Active recall

Recall the key points — then reveal.

Sources: AQA A-level Computer Science 7517 specification (AQA)

References & sources

Sources

Department for Education

GCE AS and A level subject content for computer science

AQA

AQA A-level Computer Science 7517 specification

Consequences of uses of computing

3 sections~11 min reading time3 competenciesLevel Standard 3

Consequences of uses of computing

Key points

Evaluating the environmental impact of streaming

Key points

Weighing a data-driven recommendation system

Key points

Matching scenarios to legislation

Sources

Consequences of uses of computing

Key points

Evaluating the environmental impact of streaming

Key points

Weighing a data-driven recommendation system

Key points

Matching scenarios to legislation

Sources