Show understanding of Artificial Intelligence (AI) and its ethical and ownership implications.
1. What is Artificial Intelligence?
Artificial Intelligence (AI) is the branch of computer science that aims to create systems capable of performing tasks that normally require human intelligence. These tasks include learning, reasoning, problem‑solving, perception, and language understanding.
Key AI techniques include:
Machine learning – algorithms that improve performance from data.
Neural networks – computational models inspired by the human brain.
Expert systems – rule‑based systems that emulate human expertise.
Natural language processing – enabling computers to understand and generate human language.
2. Ethical Issues in AI
AI raises a range of ethical concerns that must be considered by developers, users, and policymakers.
Bias and Discrimination – Algorithms trained on biased data can produce unfair outcomes. Example: facial‑recognition systems misclassifying certain ethnic groups.
Privacy – AI often requires large datasets containing personal information, raising questions about consent and data protection.
Transparency and Explainability – Complex models (e.g., deep neural networks) can be “black boxes,” making it difficult to understand how decisions are made.
Accountability – Determining who is responsible when an AI system causes harm (the developer, the user, or the system itself).
Job Displacement – Automation may replace certain roles, leading to economic and social impacts.
Autonomous Weapons – Use of AI in military contexts raises profound moral questions about lethal decision‑making without human oversight.
3. Ownership and Intellectual Property (IP) in AI
Ownership issues become complex when AI creates new content or inventions.
Aspect
Key Considerations
Typical Legal Position
Data Ownership
Who owns the training data? Consent, licensing, and anonymisation are critical.
Usually the data provider retains rights; users must comply with data‑use agreements.
Model Ownership
Who owns the trained model – the developer, the organisation, or the user?
Often governed by contracts; open‑source licences may apply.
AI‑Generated Works
Can a machine be an author? Who holds copyright?
Most jurisdictions require a human author; AI‑generated output may be unprotected unless a human contributes sufficient creativity.
Patents for AI Inventions
Is an invention created autonomously by AI patentable?
Current law generally requires a natural person as inventor; some regions are reviewing this stance.
4. Evaluating AI Ethics – A Decision‑Making Framework
When assessing an AI system, consider the following checklist:
Is the purpose of the AI system lawful and socially beneficial?
Has the data been collected with informed consent and is it adequately anonymised?
Are the algorithms transparent enough for stakeholders to understand key decisions?
What mechanisms exist for human oversight and intervention?
How will potential harms be mitigated and who will be accountable?
5. Example: AI in Healthcare
Consider an AI system that predicts disease risk from medical images.
Explainability – can clinicians understand why a particular risk score was assigned?
Responsibility for misdiagnosis – who is liable?
Suggested diagram: Flowchart showing data collection → model training → decision output → human oversight.
6. Summary
Artificial Intelligence offers powerful capabilities but also introduces significant ethical and ownership challenges. Understanding these issues is essential for responsible development and deployment of AI systems, especially at the A‑Level where students must be prepared to evaluate both technical and societal impacts.