AI Ethics - Bias, Privacy & Employment
AI raises ethical questions for individuals, businesses and society. This lesson explores bias and discrimination, privacy and the law, the effect on jobs, accountability and transparency, the environment, and driverless vehicles, and ends with exam questions.
Key terms
- Artificial intelligence (AI)
- Computer systems that perform tasks normally needing human intelligence, such as recognising speech or making decisions.
- Algorithmic bias
- When an algorithm produces systematically unfair results, often because of biased training data.
- Training data
- The examples a machine learning model learns from. Its quality and balance affect the model's fairness.
- Privacy
- A person's right to control how their personal information is collected and used.
- Job displacement
- Jobs lost because automation or AI can do the work instead of people.
- Accountability
- Being answerable for the decisions and effects of a system, including when software gets it wrong.
- Transparency and explainability
- Being able to understand and explain how an AI system reached its decision.
- Environmental impact
- The effect of computing on the environment, such as energy use and electronic waste.
Part of Ethics and Ownership.