Show understanding of the need for and purpose of ethics as a computing professional

7.1 Ethics and Ownership

Learning Objective

Demonstrate why ethics is essential for computing professionals and how ethical practice supports individuals, organisations, and society.

1. Why Professional Ethics Matter

• Computing systems affect everyday life – from personal data to critical infrastructure.
• Decisions made by developers, analysts or managers can lead to:
  • Privacy breaches
  • Safety hazards (e.g., medical devices, autonomous vehicles)
  • Environmental impact (e.g., energy‑intensive data‑centres)
• Public trust and professional credibility are built on ethical behaviour.
• Ethical standards help balance commercial goals with the wider public good.

2. Legal vs Ethical Considerations

Legal compliance is the minimum requirement; ethical practice often goes beyond the law.

3. Professional Codes of Conduct

All major computing bodies provide a written code that guides ethical practice.

1. British Computer Society (BCS) Code of Conduct – public interest, competence, integrity, and professional development.
2. Institute of Electrical and Electronics Engineers (IEEE) Code of Ethics – safety, privacy, avoidance of conflicts of interest, and honest reporting.
3. Association for Computing Machinery (ACM) Code of Ethics and Professional Conduct – responsibilities to society, clients, colleagues, and the profession.

4. Intellectual Property (IP) and Ownership

4.1 Types of IP Relevant to Computing

• Copyright – protects original source code, documentation, graphics, multimedia and the expression of ideas.
• Patents – protect a novel, non‑obvious invention (e.g., a new encryption algorithm, a specialised processor architecture).
• Trade secrets – confidential business information such as proprietary algorithms, test data, or source‑code repositories.
• Design rights – protect the visual appearance of a user interface or hardware enclosure.

4.2 Software Licensing

Licences define how software may be used, modified and redistributed. Choose a licence that matches the intended commercial or collaborative model.

Justify the licence – For a commercial web‑application sold to multiple clients, a proprietary licence (or a dual‑licence model) is usually appropriate because the developer needs to protect revenue while restricting unauthorised redistribution.

4.3 Data Ownership and Privacy

• Who owns data generated by users, sensors, or automated processes? (e.g., IoT telemetry, biometric logs.)
• Legal frameworks (GDPR, CCPA, UK Data Protection Act) grant data subjects rights to access, correct, restrict, and delete personal data.
• Ethical practice adds:
  • Transparent data‑handling policies.
  • Informed, freely‑given consent.
  • Respect for users’ reasonable expectations of privacy.

4.4 Digital Rights Management (DRM)

DRM uses technical controls to enforce IP rights. Ethical questions include:

• Does DRM unduly limit legitimate user activities (e.g., making a personal backup)?
• Are accessibility needs (e.g., for disabled users) considered?
• Is the balance between creator rights and user freedom proportionate?

5. AI Ethics

Artificial Intelligence introduces new ethical challenges that computing professionals must address.

• Bias and fairness – training data may encode societal prejudices; algorithms can produce discriminatory outcomes.
• Transparency and explainability – users should understand how a decision was reached, especially in high‑risk domains (medical diagnosis, hiring, credit scoring).
• Accountability – clear responsibility for autonomous system actions (e.g., self‑driving cars, automated trading bots).
• Privacy – AI often requires large data sets; ethical handling of personal data is mandatory.
• Societal impact – consider job displacement, environmental cost of training large models, and influence on public discourse.

6. Ethical Decision‑Making Models

1. Consequentialist (Utilitarian) approach – Choose the action that produces the greatest overall benefit.
2. Deontological (Duty‑based) approach – Follow moral rules or professional duties regardless of outcomes.
3. Virtue ethics – Act in a way that reflects good character traits such as honesty, fairness, and responsibility.
4. Professional‑code reference – Align decisions with the relevant code of conduct (BCS, IEEE, ACM).

7. Illustrative Case Studies

7.1 Social‑Media Data Mining

A company analyses user activity to deliver targeted ads without explicit consent.

• Legal aspect: May breach GDPR/CCPA requirements for lawful basis and consent.
• Ethical aspect: Violates user autonomy, privacy expectations, and the principle of “do no harm”.
• Recommended action: Implement an opt‑in mechanism, publish a clear data‑use policy, and provide an easy way for users to withdraw consent.

7.2 Open‑Source Security Flaw

A developer discovers a critical vulnerability in a widely used open‑source library.

• Legal aspect: No contractual duty to disclose, but may be covered by the library’s contribution guidelines.
• Ethical aspect: Duty to protect users from harm and maintain community trust.
• Recommended action: Report the flaw responsibly to the maintainers, provide a patch, and coordinate a public advisory once a fix is available.

7.3 AI‑Driven Recruitment Tool

An organisation uses a machine‑learning system to screen job applicants.

• Legal aspect: Must comply with anti‑discrimination legislation (e.g., Equality Act 2010).
• Ethical aspect: Risk of bias against protected groups; lack of transparency for candidates.
• Recommended action: Conduct regular bias audits, make the scoring criteria explainable, and retain human oversight for final hiring decisions.

8. Summary Checklist for Ethical Practice

1. Identify all stakeholders (users, clients, employers, wider society) and their interests.
2. Determine applicable laws, regulations and professional codes.
3. Analyse possible actions using an ethical decision‑making model.
4. Select the action that balances legal compliance, professional standards and the public good.
5. Document the reasoning, keep records for accountability, and schedule a review after implementation.