7.1 Ethics and Ownership
Ethics as a Computing Professional
What is Ethics?
Definition: Ethics are moral principles that govern a person’s behaviour or the conducting of an activity. In computing, ethics refers to the professional standards and moral choices that guide how technology is developed, deployed, and used.
Key ethical principles in computing:
- Honesty: Being truthful about capabilities, limitations, and practices
- Integrity: Acting consistently with moral principles
- Transparency: Being open about methods, data use, and decision-making
- Accountability: Taking responsibility for outcomes
- Fairness: Treating all users and stakeholders equitably
- Privacy: Respecting personal information
- Professional competence: Maintaining and updating skills
Why Ethics Matters in Computing
Computing professionals have unique ethical responsibilities because:
- Technology affects everyone: Software touches nearly every aspect of modern life
- Power imbalance: Developers have technical knowledge users lack
- Long-term consequences: Decisions today affect future generations
- Global reach: Code written locally can affect people worldwide
- Invisible decisions: Users often don’t know how systems make choices
- Data collection: Computers can collect and process data at massive scale
Examples of Ethical Issues in Computing
| Area | Ethical Questions |
|---|---|
| Privacy | How much user data should be collected? Who has access? |
| AI/Machine Learning | Are algorithms biased? Should AI make life-or-death decisions? |
| Social media | Should platforms moderate content? What is “harmful”? |
| Autonomous vehicles | How should cars choose in accident situations? |
| Surveillance | Where is the line between security and privacy? |
| Employment | Will automation replace jobs? What about displaced workers? |
| Environmental | How much energy should data centres consume? |
| Accessibility | Is software designed for all users, including disabled? |
Professional Ethical Bodies
Purpose of Professional Bodies
Why join a professional body?
- Provides ethical framework and guidance
- Demonstrates commitment to professional standards
- Offers continuing professional development (CPD)
- Creates network of peers for support and advice
- Gives voice to profession in public debate
- Can provide certification and recognition
- Disciplinary procedures for unethical behaviour
British Computer Society (BCS)
Overview:
- Chartered Institute for IT in the UK
- Established 1957
- Royal Charter status
BCS Code of Conduct:
- Public Interest: Have regard for public health, privacy, security, and wellbeing
- Professional Competence: Work within professional competence; maintain knowledge
- Duty to Relevant Authority: Honour contracts; respect confidentiality
- Professional Integrity: Avoid conflicts of interest; reject bribery
BCS Membership Grades:
- Student member
- Associate member (AMBCS)
- Professional member (MBCS)
- Fellow (FBCS)
- Chartered IT Professional (CITP)
Benefits of BCS membership:
- Professional recognition
- Access to resources and publications
- Networking events
- Career development
- Ethical guidance
- Influence on policy
Institute of Electrical and Electronic Engineers (IEEE)
Overview:
- World’s largest technical professional organisation
- Founded 1963
- Over 400,000 members in 160+ countries
IEEE Computer Society:
- Specialises in computing
- Publishes numerous journals and conferences
- Develops standards (including Wi-Fi – 802.11)
IEEE Code of Ethics:
- Accept responsibility in making decisions consistent with safety, health, and welfare of public
- Avoid real or perceived conflicts of interest
- Be honest and realistic in stating claims or estimates
- Reject bribery in all forms
- Improve understanding of technology and its consequences
- Maintain and improve technical competence
- Treat all persons fairly regardless of race, religion, gender, etc.
- Avoid injuring others (property, reputation, employment)
- Protect privacy of others
- Assist colleagues in professional development
Other Professional Bodies
| Organisation | Region | Focus |
|---|---|---|
| ACM (Association for Computing Machinery) | International | Academic computing |
| IET (Institution of Engineering and Technology) | UK | Engineering and technology |
| ACS (Australian Computer Society) | Australia | Computing profession |
| IPSJ (Information Processing Society of Japan) | Japan | Information processing |
| IFIP (International Federation for Information Processing) | Global | International cooperation |
Acting Ethically vs Unethically
The Impact of Ethical Behaviour
Positive impacts of acting ethically:
| Stakeholder | Benefits |
|---|---|
| Users | Trust in technology; privacy respected; fair treatment |
| Society | Technology serves public good; reduced harm |
| Profession | Public trust in computing professionals |
| Organisation | Reputation; customer loyalty; legal compliance |
| Individual | Personal integrity; pride in work; career success |
Example of ethical behaviour:
- A developer discovers a security flaw in their software
- Reports it immediately to management and users
- Works to fix it before it can be exploited
- Result: Users protected, company reputation enhanced
The Impact of Unethical Behaviour
Negative impacts of acting unethically:
| Stakeholder | Consequences |
|---|---|
| Users | Privacy violated; financial loss; psychological harm |
| Society | Erosion of trust; widening inequality; social harm |
| Profession | Loss of public confidence; increased regulation |
| Organisation | Legal penalties; reputation damage; loss of business |
| Individual | Career damage; legal liability; personal guilt |
Examples of unethical behaviour and consequences:
Example 1: Volkswagen Emissions Scandal
- What happened: Software detected when car was being tested and reduced emissions; on road, emissions far exceeded limits
- Impact: $30 billion+ in fines and settlements; criminal charges; environmental damage; loss of trust
Example 2: Cambridge Analytica
- What happened: Facebook user data harvested without consent for political targeting
- Impact: Facebook fined $5 billion; erosion of trust; regulatory changes (GDPR)
Example 3: Theranos
- What happened: Fake blood testing technology; lied about capabilities
- Impact: Company dissolved; founder convicted of fraud; patients potentially harmed
Ethical Decision-Making Framework
When facing an ethical dilemma, consider:
- Identify the facts: What do you know? What don’t you know?
- Identify stakeholders: Who will be affected? How?
- Consider options: What are possible courses of action?
- Evaluate consequences: What are the likely outcomes of each option?
- Consult guidelines: What do professional codes say?
- Make decision: Choose most ethical option
- Take responsibility: Be prepared to justify decision
Copyright Legislation
What is Copyright?
Definition: Legal right that grants the creator of an original work exclusive rights to its use and distribution.
Key principles:
- Automatic protection (no registration required in most countries)
- Protects expression, not ideas
- Limited duration (life of author + 50-70 years typically)
- Exclusive rights to copy, distribute, adapt, perform
What Can Be Copyrighted in Computing?
| Category | Examples |
|---|---|
| Source code | Program code, scripts, app code |
| Object code | Compiled machine code |
| Documentation | User manuals, API docs, comments |
| Databases | Structured collections of data |
| User interfaces | Screen layouts, GUI design (in some jurisdictions) |
| Multimedia | Images, sounds, videos in software |
| Websites | Content, layout, code |
What Cannot Be Copyrighted?
- Ideas and concepts (only their expression)
- Algorithms (though implementations can be)
- Facts and data (though compilations may have protection)
- Programming languages (though compilers/interpreters can be)
- Functional requirements
Why Copyright is Needed in Computing
1. Protect investment
- Software development costs millions
- Without protection, others could copy instantly
2. Incentivise creation
- Developers need to earn from their work
- Encourages innovation
3. Prevent plagiarism
- Ensures credit where due
- Maintains academic/professional integrity
4. Enable licensing
- Copyright allows legal distribution models
- Open source licenses rely on copyright
5. International protection
- Berne Convention ensures protection across borders
- Important for global software industry
Copyright Infringement in Computing
Examples of infringement:
- Making unauthorised copies of software (piracy)
- Downloading from pirate sites
- Using unlicensed software in business
- Copying code without permission
- Plagiarising documentation
- Circumventing copy protection
Penalties:
- Civil lawsuits (damages, injunctions)
- Criminal prosecution (fines, imprisonment)
- Professional consequences (reputation damage)
Fair Use / Fair Dealing
Limited exceptions to copyright:
Fair use (US) considers:
- Purpose of use (commercial vs educational)
- Nature of copyrighted work
- Amount used
- Effect on potential market
Fair dealing (UK) includes:
- Research and private study
- Criticism and review
- News reporting
- Education (limited)
Software Licensing
Why Software Licenses Are Needed
Purpose:
- Legal agreement between copyright holder and user
- Specifies how software can be used
- Grants permissions beyond default copyright
- Protects developer rights
- Informs users of their rights and obligations
Types of Software Licenses
1. Commercial Software
Definition: Software sold for profit, with restrictions on copying, modification, and redistribution.
Characteristics:
- Must purchase license to use
- Source code usually hidden (closed source)
- No modification allowed
- Limited to specific number of installations
- Support typically provided
Examples:
- Microsoft Windows
- Adobe Photoshop
- Microsoft Office
- Apple macOS
When to use:
- When you need professional support
- For business-critical applications
- When you trust vendor’s reputation
- When budget allows
Advantages:
- Professional development and testing
- Technical support available
- Regular updates
- Guaranteed functionality
- Vendor accountable
Disadvantages:
- Cost (often expensive)
- Cannot modify or fix yourself
- Vendor lock-in
- May include unwanted features
2. Shareware
Definition: Software distributed free on trial basis, with payment expected for continued use.
Characteristics:
- “Try before you buy”
- Often limited time (e.g., 30 days)
- May have limited features (crippleware)
- May show reminders to register (nagware)
- Payment unlocks full version
Types of shareware:
- Trialware: Time-limited full version
- Feature-limited: Basic features free, advanced paid
- Nagware: Reminders to register
- Donationware: Request donations
Examples:
- WinRAR (nagware after trial)
- Many mobile apps (freemium model)
- IDM (Internet Download Manager)
When to use:
- When you want to evaluate before buying
- For occasional use where full version not needed
- When budget limited but need professional software
Advantages:
- Try before committing
- Often lower cost than commercial
- Good for occasional users
Disadvantages:
- Feature limitations
- Time limits
- Nag screens
- May expire unexpectedly
3. Open Source Initiative (OSI) Approved Licenses
Definition: Software with source code freely available, allowing modification and redistribution.
OSI Definition requires:
- Free redistribution
- Source code available
- Derived works allowed
- Integrity of author’s source code (may require modified versions to be differently named)
- No discrimination against persons or groups
- No discrimination against fields of endeavour
- Rights apply to all redistributions
- License not specific to a product
- License must not restrict other software
- License must be technology-neutral
Common OSI licenses:
| License | Type | Key Features |
|---|---|---|
| GPL (GNU General Public License) | Copyleft | Derived works must also be GPL |
| MIT License | Permissive | Very few restrictions |
| Apache License | Permissive | Patent protection included |
| BSD License | Permissive | Similar to MIT |
| LGPL (Lesser GPL) | Weak copyleft | Can link from non-GPL code |
Examples:
- Linux kernel (GPL)
- Python (PSF license – similar to MIT)
- Mozilla Firefox (MPL)
- WordPress (GPL)
- Android (Apache 2.0 + GPL for kernel)
When to use:
- When you want to modify software
- For learning and education
- To avoid vendor lock-in
- When building upon existing open source
- For cost-sensitive projects
Advantages:
- Free to use
- Source code available
- Can modify to suit needs
- Community support
- Transparent (no hidden features)
- Long-term availability (can’t be discontinued)
Disadvantages:
- May lack professional support
- Documentation variable
- Compatibility issues with proprietary software
- Copyleft licenses may restrict commercial use
4. Free Software Foundation (FSF) / Free Software
Definition: Software that respects users’ freedom and community. “Free as in freedom, not free as in beer.”
Four Essential Freedoms:
| Freedom | Description |
|---|---|
| 0 | Run the program for any purpose |
| 1 | Study and modify the program (requires source) |
| 2 | Redistribute copies |
| 3 | Distribute modified versions |
Free Software vs Open Source:
- Free Software: Philosophical/ethical position (freedom)
- Open Source: Practical/development methodology
Examples:
- GNU Project tools
- Linux (though often called open source)
- GIMP
- LibreOffice
Free Software licenses:
- GPL (most common)
- AGPL (for network services)
- LGPL (for libraries)
License Comparison
| Feature | Commercial | Shareware | Open Source | Free Software |
|---|---|---|---|---|
| Cost | Paid | Free trial, then pay | Free | Free |
| Source code | Closed | Usually closed | Available | Available |
| Modify | No | No | Yes | Yes |
| Redistribute | No | No | Yes | Yes |
| Support | Vendor | Vendor/None | Community | Community |
| Examples | Windows | WinRAR | Linux kernel | GNU tools |
Justifying License Choice
Choose Commercial when:
- Professional support required
- Mission-critical applications
- Users non-technical
- Budget available
- Specific functionality needed
- Liability/accountability important
Choose Shareware when:
- Evaluating before purchase
- Occasional use only
- Budget limited but need professional features
- Testing software for potential purchase
Choose Open Source when:
- Development/modification planned
- Learning/education
- Budget very limited
- Want to avoid vendor lock-in
- Community contributions desired
- Transparency important
Choose Free Software when:
- Freedom is philosophical priority
- Want to ensure software remains free
- Building upon existing code
- Contributing to community
Artificial Intelligence (AI)
What is Artificial Intelligence?
Definition: The theory and development of computer systems able to perform tasks that normally require human intelligence.
Key capabilities:
- Learning from experience
- Reasoning and problem-solving
- Understanding language
- Recognising patterns
- Making decisions
- Perceiving environment
Applications of AI
Healthcare
| Application | Description | Example |
|---|---|---|
| Diagnosis | AI analyses medical images, symptoms | Detecting tumours in X-rays |
| Drug discovery | Identifies potential new medicines | DeepMind’s AlphaFold |
| Personalised medicine | Tailors treatment to individual | Genetic analysis |
| Robot surgery | Assists or performs surgery | da Vinci system |
| Patient monitoring | Tracks vital signs, predicts deterioration | ICU alert systems |
Transportation
| Application | Description | Example |
|---|---|---|
| Autonomous vehicles | Self-driving cars, trucks | Waymo, Tesla Autopilot |
| Traffic management | Optimises traffic flow | Smart traffic lights |
| Route planning | Finds optimal routes | Google Maps, Waze |
| Predictive maintenance | Predicts vehicle failures | Fleet management |
Finance
| Application | Description | Example |
|---|---|---|
| Fraud detection | Identifies suspicious transactions | Credit card monitoring |
| Algorithmic trading | Automated high-speed trading | Stock market algorithms |
| Credit scoring | Assesses creditworthiness | Loan applications |
| Risk management | Evaluates financial risks | Insurance pricing |
| Customer service | Chatbots for banking | Bank virtual assistants |
Education
| Application | Description | Example |
|---|---|---|
| Personalised learning | Adapts to student’s pace | Adaptive learning platforms |
| Tutoring systems | Provides individual instruction | Intelligent tutoring |
| Grading | Automated essay scoring | Assessment tools |
| Content recommendation | Suggests learning materials | Course recommendations |
Entertainment
| Application | Description | Example |
|---|---|---|
| Content recommendation | Suggests movies, music | Netflix, Spotify |
| Game AI | Computer opponents | Chess engines, NPCs |
| Content creation | Generates art, music, text | DALL-E, ChatGPT |
| Personalisation | Tailors user experience | Social media feeds |
Business
| Application | Description | Example |
|---|---|---|
| Customer service | Chatbots, virtual assistants | Customer support bots |
| Recruitment | Screens job applications | CV analysis |
| Marketing | Targeted advertising | Ad personalisation |
| Supply chain | Optimises logistics | Demand forecasting |
| Business intelligence | Data analysis insights | Sales predictions |
Other Applications
- Agriculture: Crop monitoring, yield prediction
- Manufacturing: Quality control, predictive maintenance
- Security: Facial recognition, threat detection
- Environmental: Climate modelling, conservation
- Legal: Document review, case prediction
- Creative: Art, music, writing assistance
Impact of AI
Social Impacts
Positive Social Impacts:
| Area | Benefits |
|---|---|
| Healthcare | Better diagnosis, personalised treatment, increased life expectancy |
| Education | Personalised learning, accessible education |
| Accessibility | Assistive technologies for disabled |
| Safety | Crime prevention, accident reduction |
| Convenience | Automated tasks, personal assistants |
| Communication | Language translation, accessibility |
Negative Social Impacts:
| Issue | Description | Example |
|---|---|---|
| Job displacement | Automation replaces workers | Manufacturing, customer service |
| Bias and discrimination | AI perpetuates or amplifies bias | Facial recognition less accurate for minorities |
| Privacy concerns | Mass surveillance, data collection | Facial recognition in public |
| Social isolation | Reduced human interaction | Over-reliance on devices |
| Misinformation | AI-generated fake content | Deepfakes, fake news |
| Addiction | Designed to be engaging | Social media algorithms |
| Digital divide | Unequal access to AI benefits | Rich/poor gap widens |
Economic Impacts
Positive Economic Impacts:
| Impact | Description |
|---|---|
| Productivity | Automation increases efficiency |
| Innovation | New products, services, industries |
| Economic growth | GDP increases from AI adoption |
| Cost reduction | Lower operational costs |
| New jobs | AI creates new roles (AI engineers, data scientists) |
| Global competitiveness | Nations with AI leadership benefit |
Negative Economic Impacts:
| Impact | Description |
|---|---|
| Job losses | Certain roles become obsolete |
| Inequality | Wealth concentrates among AI owners |
| Market disruption | Traditional industries decline |
| Monopoly power | Tech giants dominate |
| Skills gap | Workers lack required skills |
| Transition costs | Retraining, social safety nets needed |
Jobs at high risk of automation:
- Routine manual work (factory, warehousing)
- Data processing (bookkeeping, data entry)
- Customer service (call centres)
- Translation (basic)
- Driving (truck, taxi)
Jobs at lower risk:
- Creative professions (artists, writers)
- Complex social interaction (therapists, teachers)
- Unpredictable physical work (plumbers, electricians)
- High-level decision making (executives)
- Care professions (nurses, carers)
New jobs created:
- AI engineers and researchers
- Data scientists
- Ethics specialists
- AI trainers
- Robot maintainers
- Human-AI collaboration specialists
Environmental Impacts
Positive Environmental Impacts:
| Impact | Description | Example |
|---|---|---|
| Energy efficiency | AI optimises energy use | Smart grids, buildings |
| Climate modelling | Better predictions | Climate change research |
| Conservation | Wildlife monitoring | Camera trap analysis |
| Agriculture | Reduced resource use | Precision farming |
| Transport optimisation | Reduced emissions | Route optimisation |
| Material discovery | New sustainable materials | Battery technology |
Negative Environmental Impacts:
| Impact | Description | Concern |
|---|---|---|
| Energy consumption | Training AI models uses huge energy | One model = 5 cars’ lifetime emissions |
| Hardware production | Manufacturing requires rare minerals | Mining impacts |
| E-waste | Rapid hardware obsolescence | Growing waste stream |
| Data centre footprint | Cooling, land use | Water consumption |
| Rebound effect | Efficiency gains increase consumption | Jevons paradox |
Example: Training an AI model
- Training large language model (like GPT-3) estimated 1,300 MWh
- Equivalent to 130 homes’ annual electricity
- Produces ~550 tonnes CO₂ (like 5 cars’ lifetime)
Mitigation efforts:
- Green data centres (renewable energy)
- Efficient algorithms (less compute)
- Hardware improvements (specialised AI chips)
- Carbon offsetting
- Research into low-energy AI
Ethical Issues in AI
Key ethical concerns:
| Issue | Description | Example |
|---|---|---|
| Bias | AI systems discriminate | Facial recognition fails for dark skin |
| Transparency | “Black box” decisions | Unknown why loan refused |
| Accountability | Who is responsible when AI fails? | Autonomous car accident |
| Privacy | Mass surveillance | Facial recognition in public |
| Autonomy | Machines making decisions | Military drones |
| Control | AI exceeding human control | Superintelligence concerns |
| Employment | Mass job displacement | Driverless vehicles |
| Weaponisation | Autonomous weapons | Lethal autonomous weapons |
Addressing AI Impacts
Individual level:
- Stay informed about AI developments
- Develop skills less likely to be automated
- Use AI responsibly
- Consider ethical implications of work
Organisational level:
- Ethical AI guidelines
- Diverse development teams
- Impact assessments
- Transparency in AI use
- Human oversight of AI decisions
Government/Societal level:
- AI regulation and legislation
- Investment in education and retraining
- Research into AI safety
- International cooperation
- Social safety nets
- Digital inclusion initiatives
Professional level:
- Codes of ethics for AI development
- Professional standards
- Public education
- Ethical review boards
Summary Checklist for Assessment Objectives
AO1 (Knowledge) – You should be able to:
- ✓ Explain need for ethics in computing
- ✓ Describe professional bodies (BCS, IEEE) and their purpose
- ✓ Define ethical and unethical behaviour impacts
- ✓ Explain copyright legislation purpose
- ✓ Describe software licence types (commercial, shareware, open source, free software)
- ✓ Define AI and list applications
- ✓ Describe social, economic, environmental impacts of AI
AO2 (Application) – You should be able to:
- ✓ Apply ethical principles to given scenarios
- ✓ Recommend professional body membership benefits
- ✓ Analyse ethical/unethical impacts in situations
- ✓ Justify software licence choice for given scenarios
- ✓ Identify AI applications for specific problems
- ✓ Analyse AI impacts in different contexts
AO3 (Design/Evaluation) – You should be able to:
- ✓ Evaluate ethical implications of computing solutions
- ✓ Compare different software licences and judge appropriateness
- ✓ Assess AI impacts and recommend mitigations
- ✓ Develop ethical frameworks for decision-making
- ✓ Critically evaluate AI applications and their consequences
- ✓ Form reasoned judgements about ethical dilemmas