7.1 Ethics and Ownership
Objective
Show understanding of the different types of software licensing and justify the use of a licence for a given situation.
Key concepts (linked to the Cambridge AS & A‑Level CS syllabus)
- AO1 – Knowledge and understanding: Define ethical principles, copyright, related rights and the main families of software licences (proprietary, freeware, shareware, copyleft, permissive).
- AO2 – Application: Use a systematic checklist to select an appropriate licence for a real‑world scenario and justify the choice.
- AO3 – Analysis and evaluation: Evaluate the ethical implications of different licensing strategies and of AI‑driven systems, referencing professional codes of conduct.
1. Why licences matter
- Licences set the legal rights and responsibilities of creators and users.
- They protect intellectual property, dictate how software may be used, modified and redistributed, and help developers meet ethical and commercial goals.
2. Professional ethics in computing
Professional bodies provide codes of conduct that guide responsible practice. The most widely referenced are:
- BCS (British Computer Society) – public interest, competence, integrity, responsibility.
- IEEE (Institute of Electrical and Electronics Engineers) – emphasis on safety, privacy and the broader impact of technology.
- ACM (Association for Computing Machinery) – focuses on honesty, fairness and respect for intellectual property.
These codes reinforce the same core duties, for example:
- Public interest: software must be safe, reliable and respect privacy.
- Competence: only undertake work you are qualified for.
- Integrity: be honest about capabilities and limitations.
- Responsibility: accept accountability for the impact of your work.
Illustrative scenario: A developer ships an update that disables a security feature to increase advertising revenue. This breaches the public‑interest duty, erodes user trust and may lead to legal action.
3. Impact of ethical and unethical behaviour
| Behaviour | Real‑world example | Consequences |
|---|
| Unethical – unauthorised data sharing | Cambridge Analytica scandal (2018) | Massive privacy breach, £500 m fine for Facebook, loss of public confidence. |
| Unethical – distributing ransomware | WannaCry attack (2017) | £4 bn estimated global losses, disruption of health services, criminal prosecution. |
| Ethical – open‑source security tool released for free | Wireshark, maintained by volunteers | Improved network diagnostics worldwide, enhanced community reputation. |
4. Copyright, related rights and other legislation
- Copyright: gives the creator exclusive rights to reproduce, adapt, distribute and publicly perform the work.
- Related rights: moral rights (right of attribution, integrity) and database rights (EU).
- Data ownership: the creator of a dataset (or the organisation that commissions it) holds rights to the data, subject to GDPR and any contractual terms. This is crucial when training AI models.
- Fair dealing / fair use: limited exceptions for teaching, research, criticism, etc.
- DMCA (USA) & EU‑GDPR: protect against unauthorised copying and ensure personal data is handled lawfully – both affect how software may be distributed and used.
5. Types of software licences
| Licence type | Permission to use | Permission to modify | Distribution rights | Typical cost | Key restriction / distinctive clause | Typical use‑cases |
|---|
| Proprietary (Commercial) | Yes, under a signed agreement | No (source code hidden) | Only the licensor may redistribute | Paid licence fee | Warranty & liability clauses; no copying without permission | Enterprise applications, commercial games |
| Freeware | Yes, free of charge | No | Usually prohibited; may allow sharing of the binary only | Free | Source code not provided; no modification rights | Utilities, demo versions |
| Shareware | Yes, trial period (often 30 days) | No (unless a paid licence is obtained) | Limited – redistribution often prohibited until purchase | Free trial → paid licence | Full functionality unlocked after payment | Games, specialised tools |
| GNU GPL v3 (Copyleft) | Yes, free | Yes | Derived works must be distributed under the same GPL licence and source code must be provided | Free | Strong “share‑alike” requirement; patent‑grant clause | Community libraries where openness is mandatory |
| MIT / BSD (Permissive) | Yes, free | Yes | Can re‑license, even for commercial products; only attribution required | Free | Very minimal restrictions – ideal for start‑ups | Frameworks, APIs, rapid‑prototype projects |
| Apache 2.0 | Yes, free | Yes | Allows commercial use and redistribution; includes explicit patent‑grant | Free | Patent‑termination clause protects contributors and users | Server software, large‑scale open‑source platforms |
Common misconceptions
- GPL forbids commercial use. It allows commercial distribution; it only requires that the source of any derivative remains open.
- Freeware = open source. Freeware is free to use, but the source code is typically unavailable.
- Permissive licences prevent patents. Licences such as Apache 2.0 actually grant a royalty‑free patent licence to users.
6. Choosing an appropriate licence – a systematic checklist
- Intended audience – commercial customers, schools, hobbyists?
- Desired level of openness – do you want others to modify and share?
- Commercial intent – will you sell the software or charge for support?
- Compatibility with other components – does the licence need to work with libraries under a different licence?
- Legal protection required – warranty disclaimer, attribution, patent clauses?
- Philosophical stance – copyleft (ensure openness) vs permissive (maximise adoption).
7. Case study – licensing an educational mathematics app
Situation: A group of A‑Level students have built a mobile app that lets learners practise mathematics. The app will be offered free to schools, and the developers want teachers to be able to adapt it for their own curricula.
Analysis using the checklist
- Audience: Primarily schools and teachers (non‑commercial), but the app could later be incorporated into commercial learning platforms.
- Openness: Modification and redistribution are essential to allow curriculum‑specific customisation.
- Commercial intent: No immediate sales, but future commercial use should be permitted.
- Compatibility: The app uses a few third‑party libraries under the Apache 2.0 licence – the chosen licence must be compatible.
- Legal protection: The team wants a simple warranty disclaimer and clear attribution.
Justified licence recommendation
| Licence option | How it meets the checklist | Potential drawback |
|---|
| MIT Licence | - Free use and modification – satisfies openness.
- Allows commercial reuse – future revenue possibilities.
- Only requires attribution – meets legal‑protection need.
- Compatible with Apache 2.0 libraries.
| Derivatives can be relicensed as closed source, so improvements may not be shared back. |
| GNU GPL v3 | - Ensures any derivative remains open – aligns with a community‑building ethos.
- GPL v3 includes an explicit compatibility exception for Apache 2.0.
| May deter schools that wish to embed the app in proprietary learning‑management systems. |
| Apache 2.0 | - Provides the same freedoms as MIT plus an explicit patent‑grant – useful if the app later incorporates patented algorithms.
| Longer licence text; still permissive, so derivatives can become closed‑source. |
Conclusion: For the stated goals, the MIT Licence offers the best balance of openness, commercial flexibility and simplicity. If the team later decides that all derivatives must stay open, they can re‑release the source under the GPL v3.
8. AI ethics – extended guidance (required by the syllabus)
Key AI‑related ethical issues
- Bias: Training data that under‑represents certain groups can lead to discriminatory outcomes (e.g., facial‑recognition systems mis‑identifying people of colour).
- Transparency: “Black‑box” models make it hard to explain decisions, which is problematic in health or criminal‑justice contexts.
- Accountability: Determining who is responsible when an autonomous system makes a harmful decision.
- Data privacy: AI often requires large datasets; misuse can breach GDPR.
- Guidelines to follow: IEEE’s Ethically Aligned Design and the ACM Code of Ethics provide concrete recommendations for responsible AI development.
Question for students: A school wants to use an AI‑driven grading assistant that automatically awards marks. Identify two ethical risks and suggest how the developers could mitigate them.
9. Glossary of key terms
- Copyleft
- A licensing principle (used by the GPL) that requires derivative works to be distributed under the same licence, preserving openness.
- Permissive licence
- A licence (e.g., MIT, BSD) that allows code to be used, modified and re‑licensed with few restrictions, typically only requiring attribution.
- Attribution
- The requirement to give credit to the original author(s) when the software is redistributed.
- Patent‑grant clause
- A provision (found in Apache 2.0) that gives users a royalty‑free licence to any patents held by the contributors that cover the code.
- Fair dealing / fair use
- Limited legal exceptions that permit copying of copyrighted material for purposes such as teaching, research or criticism.
- Data ownership
- The rights held by the creator or commissioner of a dataset, subject to privacy legislation (e.g., GDPR) and any contractual terms.
10. Summary
- Software licences are legal tools that express ethical and commercial intentions.
- Understanding the differences between proprietary, freeware, shareware and the major open‑source licences (GPL, MIT, BSD, Apache) is essential for AO1.
- Applying the licence‑selection checklist enables students to justify a licence choice – fulfilling AO2.
- Professional codes of conduct (BCS, IEEE, ACM) and AI‑ethics frameworks extend the discussion beyond legal compliance, linking the topic to real‑world responsibilities (AO3).
11. Self‑check questions
- Explain the main difference between a copyleft licence (e.g., GPL) and a permissive licence (e.g., MIT).
- Give an example of a situation where a proprietary licence would be the most appropriate choice.
- Why might a developer choose a shareware model instead of freeware?
- In the educational‑app case study, list two ethical advantages of releasing the software under an open‑source licence.
- Identify one ethical risk associated with AI‑driven grading software and propose a mitigation strategy.