1.5.2 Moral and Ethical Issues
Computing technology raises profound questions about how we should use it responsibly. These issues affect individuals, organisations, and society as a whole.
Definition
Ethics refers to the values and moral principles held by a society or community that guide behaviour and decision-making.
Morals are an individual's personal beliefs about what is right and wrong.
Morals are an individual's personal beliefs about what is right and wrong.
1.5.2(a) Computers in the Workforce
Technology is transforming the workplace, creating both opportunities and challenges.
Automation and Employment
Key Point
| Workforce impact | Examples |
|---|---|
| Jobs at risk from automation | Manufacturing, data entry, customer service chatbots, transportation, retail checkouts/warehouses |
| New jobs created | AI/ML specialists, data scientists, robotics engineers, cybersecurity experts, UX designers |
Worked Example
Worked Example: Analysing Automation Impact
Scenario: A supermarket introduces self-checkout machines
Benefits:
• Reduced waiting times for customers
• Lower operational costs
• Consistent service 24/7
• Staff can focus on customer service
Drawbacks:
• Cashiers may lose their jobs
• Some customers prefer human interaction
• Technical issues require staff anyway
• Theft may increase
Ethical Consideration:
Does the company have responsibility to:
• Retrain displaced workers?
• Provide redundancy support?
• Consider community impact?
Scenario: A supermarket introduces self-checkout machines
Benefits:
• Reduced waiting times for customers
• Lower operational costs
• Consistent service 24/7
• Staff can focus on customer service
Drawbacks:
• Cashiers may lose their jobs
• Some customers prefer human interaction
• Technical issues require staff anyway
• Theft may increase
Ethical Consideration:
Does the company have responsibility to:
• Retrain displaced workers?
• Provide redundancy support?
• Consider community impact?
1.5.2(b) Automated Decision Making
Algorithms increasingly make decisions that affect people's lives, often without human oversight.
Definition
Automated decision making is when algorithms or AI systems make decisions without human intervention, based on data and programmed rules.
Key Point
| Area | Example uses | Main concern |
|---|---|---|
| Recruitment | CV filtering, interview shortlisting | Bias against protected groups |
| Finance | Loan approval, credit scoring, fraud checks | Unfair rejection / opacity |
| Healthcare | Diagnostic support, treatment recommendations | Accountability for errors |
| Justice | Bail/sentencing risk scoring | Fairness and explainability |
| Social media | Content curation/moderation | Transparency and appeal rights |
Example
Algorithmic Bias Example:
A recruitment AI trained on historical hiring data may learn to favour male candidates because historically more men were hired - perpetuating past discrimination rather than identifying the best candidates.
A recruitment AI trained on historical hiring data may learn to favour male candidates because historically more men were hired - perpetuating past discrimination rather than identifying the best candidates.
1.5.2(c) Artificial Intelligence
AI presents some of the most significant ethical challenges in computing.
Key Point
| AI issue | Typical concern | Example |
|---|---|---|
| Job displacement | Skills disruption and unemployment risk | Professional and administrative roles automated |
| Privacy/surveillance | Continuous tracking and profiling | Facial recognition, always-on assistants |
| Autonomous systems | Responsibility for harmful outcomes | Self-driving crashes, autonomous weapons |
| Bias/fairness | Discrimination from biased training data | Hiring, lending, policing outcomes |
Worked Example
Worked Example: AI in Healthcare
Scenario: An AI system can diagnose skin cancer more accurately than dermatologists.
Arguments FOR deployment:
• More accurate diagnoses save lives
• Can reach underserved areas without specialists
• Faster screening allows earlier treatment
• Reduces healthcare costs
Arguments AGAINST deployment:
• Who's liable for misdiagnosis?
• Patients may prefer human doctors
• AI may not explain reasoning
• Could widen health inequality if only some can access
• May deskill human doctors over time
Ethical Framework:
The benefits must be weighed against risks, with safeguards:
• Human oversight for final decisions
• Clear liability framework
• Transparent about AI involvement
• Equal access regardless of wealth
Scenario: An AI system can diagnose skin cancer more accurately than dermatologists.
Arguments FOR deployment:
• More accurate diagnoses save lives
• Can reach underserved areas without specialists
• Faster screening allows earlier treatment
• Reduces healthcare costs
Arguments AGAINST deployment:
• Who's liable for misdiagnosis?
• Patients may prefer human doctors
• AI may not explain reasoning
• Could widen health inequality if only some can access
• May deskill human doctors over time
Ethical Framework:
The benefits must be weighed against risks, with safeguards:
• Human oversight for final decisions
• Clear liability framework
• Transparent about AI involvement
• Equal access regardless of wealth
1.5.2(d) Environmental Effects
Technology has significant environmental impacts that must be considered.
Key Point
| Negative impact area | Key issues |
|---|---|
| E-waste | Planned obsolescence, toxic materials, low recycling rates, export to developing countries |
| Energy consumption | Data centre demand, crypto mining, always-on infrastructure, manufacturing energy costs |
| Resource extraction | Rare earth use, conflict minerals, high water use in chip fabrication |
Key Point
| Positive impact area | Benefit |
|---|---|
| Smart grids | More efficient energy distribution |
| Remote working | Reduced commuting emissions |
| Digital documents | Less paper use |
| AI optimisation | Better logistics/heating efficiency |
| Environmental monitoring | Sensor-based pollution tracking |
| Renewable integration | Improved solar/wind management |
1.5.2(e) Privacy and Surveillance
The balance between security and privacy is one of the most contested ethical issues.
Monitoring and Surveillance
Key Point
| Context | Typical monitoring methods |
|---|---|
| Workplace monitoring | Email/web logs, keystroke logging, screen capture, GPS vehicle tracking, office CCTV |
| Public surveillance | CCTV, facial recognition, ANPR, mobile location tracking |
Worked Example
Worked Example: Workplace Email Monitoring
Scenario: A company monitors all employee emails
Arguments FOR:
• Prevent data leaks and theft
• Ensure professional communication
• Comply with legal requirements
• Protect company reputation
Arguments AGAINST:
• Invasion of employee privacy
• Creates atmosphere of distrust
• Chilling effect on honest communication
• May be disproportionate response
Ethical Approach:
• Clear policy communicated to employees
• Monitoring proportionate to risk
• Reasonable expectation of privacy respected
• Legal compliance (Data Protection, RIPA)
Scenario: A company monitors all employee emails
Arguments FOR:
• Prevent data leaks and theft
• Ensure professional communication
• Comply with legal requirements
• Protect company reputation
Arguments AGAINST:
• Invasion of employee privacy
• Creates atmosphere of distrust
• Chilling effect on honest communication
• May be disproportionate response
Ethical Approach:
• Clear policy communicated to employees
• Monitoring proportionate to risk
• Reasonable expectation of privacy respected
• Legal compliance (Data Protection, RIPA)
1.5.2(f) Censorship and the Internet
Who decides what content is acceptable online?
Key Point
| Position | Main arguments |
|---|---|
| FOR internet censorship | Protect children, reduce illegal material, limit hate/radicalisation, support national security, reduce cyberbullying |
| AGAINST internet censorship | Free speech concerns, subjective harm definitions, abuse-of-power risk, weak enforceability, circumvention via VPNs |
1.5.2(g) Piracy and Digital Rights
Key Point
| Perspective | Key points |
|---|---|
| Against piracy | Creators lose income, future creation discouraged, malware risk, illegal under Copyright law |
| Arguments sometimes made for piracy | Cost/access issues, DRM restrictions, culture-sharing argument, mixed evidence on legal purchasing behaviour |
| Balanced exam conclusion | Piracy is illegal and harmful, but pricing/accessibility concerns should still be addressed by industry |
1.5.2(h) Cultural and Global Considerations
Technology must work for diverse global users.
Key Point
| Design area | Key considerations |
|---|---|
| Language/character support | Unicode, right-to-left scripts, translation/localisation |
| Cultural differences | Colour meaning, date/number formats, icon interpretation |
| Accessibility/inclusion | Disability support, digital literacy range, bandwidth/device constraints |
Ethical Discussion Framework
Exam Tip
For Ethics Questions, Consider:
1. Stakeholders - Who is affected?
2. Benefits - What are the advantages?
3. Harms - What are the risks/downsides?
4. Rights - Whose rights are involved?
5. Fairness - Is the impact distributed fairly?
6. Alternatives - Are there better approaches?
7. Laws - What legislation applies?
8. Balance - How do we weigh competing interests?
Always present BOTH sides of the argument and come to a reasoned conclusion.
1. Stakeholders - Who is affected?
2. Benefits - What are the advantages?
3. Harms - What are the risks/downsides?
4. Rights - Whose rights are involved?
5. Fairness - Is the impact distributed fairly?
6. Alternatives - Are there better approaches?
7. Laws - What legislation applies?
8. Balance - How do we weigh competing interests?
Always present BOTH sides of the argument and come to a reasoned conclusion.