Artificial Intelligence (OCR A-Level Computer Science): Revision Notes

Artificial Intelligence

Overview

Artificial Intelligence (AI) refers to computer systems designed to perform tasks that typically require human intelligence, such as problem-solving, decision-making, and learning. AI is a rapidly evolving field, with applications in healthcare, finance, transportation, and more. However, as AI becomes more integrated into daily life, it raises important moral, social, ethical, and cultural questions.

Understanding these impacts is crucial to evaluating the benefits and risks of AI in society.

Moral Issues

• Definition: Concerns about what is right or wrong in the design and use of AI.
• Examples:
  • Accountability: Who is responsible if an AI system causes harm (e.g., self-driving car accidents)?
  • Privacy: AI systems that collect and analyse vast amounts of personal data can infringe on individual privacy.
  • Fair Use: Ensuring AI technologies are used for the benefit of society, not for exploitation or harm (e.g., AI in warfare).

Social Issues

• Definition: The impact of AI on society and social structures.
• Examples:
  • Job Displacement: Automation through AI can replace human workers, leading to unemployment in certain sectors.
  • Inequality: Access to advanced AI technology may be limited to wealthier individuals or nations, exacerbating social inequalities.
  • Public Safety: The use of AI in critical systems (e.g., healthcare or transportation) must be carefully regulated to prevent harm.

Ethical Issues

• Definition: Principles that govern the fair and just use of AI.
• Examples:
  • Algorithmic Bias: AI systems can inherit biases from their training data, leading to discriminatory outcomes (e.g., biassed hiring practices).
  • Transparency: AI decisions, especially in high-stakes areas like finance or criminal justice, should be explainable and understandable.
  • Informed Consent: Users should be aware when interacting with AI systems and understand how their data is being used.

Cultural Issues

• Definition: How AI affects and is influenced by cultural norms and practices.
• Examples:
  • Globalisation of AI: AI developed in one culture may not align with the values or norms of another (e.g., differing views on privacy or surveillance).
  • Cultural Representation in AI: AI systems trained on data from specific regions may fail to represent diverse cultures accurately.
  • Language Barriers: AI tools, such as language translation systems, might privilege widely spoken languages, marginalising less common ones.

Opportunities for Artificial Intelligence

1. Improved Efficiency and Productivity: AI can perform tasks faster and more accurately than humans, leading to increased efficiency in various industries.
2. Healthcare Advances: AI aids in early diagnosis, personalised treatment, and drug discovery.
3. Enhanced Accessibility: AI-powered tools, like speech recognition and translation, improve accessibility for people with disabilities or language barriers.
4. Innovation in Daily Life: From smart assistants to autonomous vehicles, AI enhances convenience and safety.

Risks of Artificial Intelligence

1. Job Loss and Economic Disruption: Automation may lead to unemployment, particularly in sectors like manufacturing, retail, and transportation.
2. Loss of Privacy: AI systems that track user behaviour (e.g., facial recognition) pose significant privacy risks.
3. Bias and Discrimination: AI can perpetuate or even amplify societal biases, leading to unfair treatment of certain groups.
4. Ethical Concerns in AI Usage: The use of AI in areas such as surveillance, military applications, or deepfake technology raises significant ethical questions.

Note Summary