Ethical, Legal and Environmental Issues in Computing
Computing: Ethics, Law and Environment
This GCSE computing lesson explores Ethical, Legal and Environmental Issues in Computing. Students evaluate how computing affects privacy, employment, access, sustainability and society, and connect decisions to relevant legal and ethical principles. It supports KS4 classroom teaching, independent study and exam revision using clear, subject-specific vocabulary.
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Computing: Ethics, Law and Environment
This GCSE computing lesson explores Ethical, Legal and Environmental Issues in Computing. Students evaluate how computing affects privacy, employment, access, sustainability and society, and connect decisions to relevant legal and ethical principles. It supports KS4 classroom teaching, independent study and exam revision using clear, subject-specific vocabulary.
Ethics in Computing, KS4 Computer Science, GCSE Computer Science, Ethical Issues, Environmental Impact, E-waste, Digital Divide, Artificial Intelligence, Privacy, Surveillance, Technological Impact on Society, Cyberbullying, MCQs, Open Questions, Polls, Emoji Polls, Exit Tickets
Learning goal
I can understand and explain the main ethical, legal and environmental issues in computing, and apply them to real-world examples.
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What issues come to mind when computing starts to seriously affect people’s lives?
Use this to surface prior ideas such as privacy, hacking, fairness, safety, jobs, waste or energy use. Briefly sort responses into ethical, legal and environmental themes.
Ethical issues in computing
Ethics asks what is fair, safe and responsible
A system can be legal but still unethical
In computing, choices about data and algorithms affect real people
Useful contrast: following the law is a minimum standard, while ethics asks whether a decision should be made in the first place.
Privacy and surveillance
Privacy means people should have control over personal information about them. Surveillance means monitoring people’s actions, locations or communications. Computing makes surveillance easier through phones, cameras, apps and online tracking, so ethical questions arise about consent, necessity and who holds the power.
Link to everyday experience: location tracking, cookies, smart doorbells and app permissions. Students often assume 'I agreed' means fully informed consent; note that long terms and conditions can weaken meaningful choice.
Example: social media data collection
Platforms collect clicks, likes, searches and location data
This data can be used for advertising and recommendations
Ethical concerns include weak consent, profiling and loss of privacy
Keep the example broad and well-known rather than tied to a single company unless the class already knows one. Emphasise that personal data can reveal habits, beliefs and relationships.
Algorithmic bias and discrimination
Algorithms learn from data and rules
If the data is unbalanced, the outputs may also be unfair
Bias can lead to discrimination in areas such as recruitment, policing or facial recognition
Students may think computers are automatically neutral. Stress that bias usually enters through training data, design choices, labels, testing or the way a system is used.
Example: facial recognition bias
Some facial recognition systems have been less accurate for certain groups
A higher error rate can lead to unfair treatment
Ethical computing needs testing across diverse users
Avoid over-technical detail. The core point is that unequal accuracy matters because mistakes can cause harm when systems are used in security or policing.
Online safety, the digital divide and jobs
Risks include bullying, scams and harmful content
Good design should protect users and report abuse
The digital divide means unequal access to devices, internet and skills
Automation and AI
Online safety and access
Automation can replace some routine tasks
It can also create new roles and change existing jobs
Ethical debate: efficiency versus fairness for workers
Make clear that the digital divide is not only about owning a device; it also includes reliable internet access and digital literacy. For jobs, avoid extreme claims that AI will replace all work.
Why can a system be legal but still unethical?
It follows old code
It uses too much data
It may still be unfair
It works too slowly
Checks the ethics-law distinction from slides 2-6. Students may confuse technical quality or efficiency with ethics; the key idea is fairness, safety and responsibility.
Ethical issues check
People should have control over personal information, which links to privacy. When systems monitor actions or communications, this is called surveillance. If training data is unbalanced, an algorithm may show bias. Unequal access to devices, internet and skills is the digital divide.
All four blanks are key terms explicitly taught across slides 3-7.
Why is facial recognition bias harmful?
Expected points: students might argue that facial recognition should not be used if some groups face higher error rates; reasons may include unfair treatment, discrimination, lack of trust, and possible harm in policing or security. Accept balanced answers that mention testing, safeguards or limited use.
Legal issues in computing
Laws set rules for how computing is used
They protect people, organisations and creative work
In the UK, important areas include data protection, cybercrime and copyright
Frame law as enforceable rules, unlike ethics which concerns what is right or responsible. Students should see both as connected but not identical.
Data Protection Act and UK GDPR
These rules cover how personal data is collected and used
Organisations must have a lawful reason for processing data
Data should be accurate, secure and not kept longer than needed
People have rights over their personal data
You do not need to list every principle. Focus on the idea of lawful processing, security, minimisation and user rights such as access or correction.
Computer misuse and cybercrime
Illegal acts include unauthorised access to computer systems
Malware, fraud and data theft are forms of cybercrime
The law aims to deter attacks and protect systems and users
Students sometimes confuse curiosity with permission. Emphasise that accessing systems without authorisation is unlawful even if no damage was intended.
Copyright and software licensing
Copyright protects software, music, images and text
A licence explains how software may be used, copied or shared
Using cracked software or unlicensed media breaks legal rules
You may mention that free software is not always permission-free; the licence still sets conditions. Keep the distinction between ownership and permission to use.
Intellectual property in digital content
Intellectual property protects creations of the mind such as code, designs, videos and written content. In digital form, copying and sharing are easy, so creators need legal protection while users need clear rules about reuse, remixing and attribution.
A good teaching point is that digital copying can be instant and perfect, which increases both convenience and the risk of infringement.
Which action would break computer misuse law?
Fixing your own file
Sharing licensed software
Accessing a system without permission
Correcting stored data
Targets slide 10. Distractors connect to legal terms from nearby slides but are not misuse offences in themselves.
Legal issues check
Under UK GDPR, organisations need a lawful reason to use personal data. Copyright protects creative work such as software and images. A software licence sets the rules for use, copying or sharing. Digital creators are also protected by intellectual property law.
Echoes slides 9-12 and reinforces the difference between data protection, copyright, licensing and intellectual property.
Which legal issue seems most important in everyday computing?
Data protection
Cybercrime
Copyright
Software licences
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Environmental issues in computing
Computing depends on electricity, materials and global supply chains
Its impact comes from making devices, using them and disposing of them
Technology can both increase and reduce environmental harm
Students often think 'digital' means environmentally harmless. This subtopic corrects that by covering the full life cycle of computing products and services.
Energy use of data centres and devices
Data centres need power for servers, storage and cooling
Everyday devices also use electricity during charging and use
Streaming, cloud storage and AI processing can increase demand
The key idea is that online services run on physical infrastructure. 'Cloud' sounds invisible, but it depends on buildings full of hardware using large amounts of energy.
Example: the cost of cloud computing
Saving data online uses remote servers, not empty space
More storage and processing mean more electricity use
Environmental impact depends on efficiency and energy sources
Useful nuance: cloud systems can sometimes be more efficient than many separate local systems, but they still carry a real environmental cost.
E-waste and resource extraction
E-waste
Hardware needs metals and rare materials
Mining and processing use energy and damage habitats
Environmental impact begins before a device is switched on
Old devices may contain toxic materials
Poor disposal can damage land and water
Short upgrade cycles increase waste
Resource extraction
This is a good place to reinforce life-cycle thinking: extraction, manufacture, transport, use and disposal all matter.
How computing can reduce impact
Energy-efficient hardware uses less electricity
Repair, reuse and recycling can cut waste
Smart systems can reduce travel, monitor energy use and improve efficiency
Balance the previous slides by showing that computing is not only a problem source; it can also support greener choices when designed and used carefully.
Applying the three perspectives
A real-world computing system can raise ethical, legal and environmental issues at the same time. For example, social media data collection raises ethical concerns about privacy, legal issues about data protection, and environmental issues because large platforms depend on energy-hungry data centres.
This slide ties the lesson together. Encourage students to see that one technology often needs more than one lens to judge it properly.
Why does cloud computing have an environmental cost?
It uses remote servers
It avoids all hardware
It deletes old devices
It stops energy use
Checks the misconception from slides 14-15 that the cloud is somehow weightless or impact-free.
Environmental issues check
Data centres need electricity for servers and cooling. Discarded electronics become e-waste, which can harm land and water if poorly managed. Before devices are even used, resource extraction for metals and rare materials can damage habitats. Repair, reuse and recycling can reduce waste.
Uses life-cycle terms from slides 14-17 and a solution term from slide 17.
How could one system raise all three issues?
Expected elements: one valid example is social media data collection. Ethical: privacy, consent, profiling. Legal: data protection, lawful processing, user rights. Environmental: data centres, storage, energy use. Accept other real-world systems if all three lenses are applied clearly.
How much more do you understand the wide range of issues associated with computing?
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Glossary
privacy - the right to control personal information about yourself
surveillance - monitoring people’s activities or communications
personal data - information that can identify a person
algorithmic bias - unfair patterns in algorithm decisions or outputs
digital divide - unequal access to devices, internet or digital skills
automation - using technology to perform tasks with less human input
UK GDPR - UK rules for how personal data must be handled
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Glossary
cybercrime - crime carried out using computers or networks
copyright - legal protection for original creative work
software licence - rules that state how software may be used
intellectual property - legal rights over creations such as code or media
e-waste - discarded electronic devices and components
data centre - a facility that stores and processes digital data
resource extraction - taking raw materials from the Earth for manufacturing
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