Artificial Intelligence (AI) (Cambridge (CIE) A Level Computer Science) : Revision Note

Understanding AI

What is artificial intelligence?

• Artificial intelligence (AI) is a machine that can simulate intelligent behaviours similar to that of a human

• AI is a system that can:

  • Learn - acquire new information

  • Decide - analyse and make choices

  • Act autonomously - take actions without human input

• There are two main types of AI:

  • Weak AI, also known as narrow AI, is designed to perform a specific task or set of tasks

  • Strong AI, also known as artificial general intelligence (AGI), is designed to perform any intellectual task that a human can do

Advantages and disadvantages of AI

Characteristics of AI

• AI shares three common characteristics:

  • Collection of data

  • Rules for using data

  • Ability to reason

Impact of AI

Social

Workforce

• AI adoption is expected to significantly change employment structures:

  • Automation may replace some roles, leading to unemployment or job role changes

  • At the same time, new jobs will emerge that require AI knowledge or human–AI collaboration

  • To support this shift, reskilling and upskilling programmes are essential, ensuring the workforce is prepared for AI-driven transformations

Education & Accessibility

• The rise of AI introduces concerns around equal access:

  • Those with better technology, education, and internet access may benefit more from AI, creating a digital divide

  • To prevent social disparities, it is important to ensure equal access to AI education, tools, and training for all communities

Healthcare

• AI has the potential to transform healthcare, but raises important ethical and safety concerns:

  • AI can improve diagnosis, treatment planning, and patient monitoring

  • However, AI systems are not infallible – a wrong diagnosis or treatment recommendation can have serious consequences

  • It is vital to determine the extent of human oversight

  • Decisions made solely by AI in critical situations can be risky

  • The question of who is responsible when something goes wrong (the developer, the AI system, or the healthcare provider) creates complex legal and ethical challenges

  • Clear guidelines and regulations are needed to define responsibility and ensure patient safety

Economic

Employment & industry

• AI adoption can significantly reshape entire industries, leading to:

  • Job displacement in sectors that rely heavily on routine or manual work

  • Increased productivity and efficiency in areas such as manufacturing, logistics, and finance

  • A growing demand for AI-related roles, such as data scientists and machine learning engineers

• To minimise negative effects, governments and businesses must invest in retraining and upskilling programmes to help workers transition into new roles

Business & innovation

• AI can be a catalyst for economic growth by:

  • Enabling new business models, such as personalised services or automated customer support

  • Supporting faster innovation cycles by improving R&D processes.

  • Reducing operational costs through automation and predictive analytics

• However, small businesses may struggle to compete with large companies that have more resources to invest in AI

• Potentially widening economic inequalities between organisations

Market dynamics & inequality

• The deployment of AI can:

  • Concentrate wealth and power in large tech companies that control key AI tools and data

  • Create monopolistic advantages, leading to reduced market competition

  • Require policymakers to consider new economic models and regulation to ensure fair access to AI technologies and prevent deepening income inequality

Environmental

Energy consumption

• AI systems, especially large-scale models, require vast computing power, which can:

  • Lead to high electricity usage and significant carbon emissions

  • Strain power grids if deployed at scale without renewable energy support

• Efforts must be made to:

  • Optimise AI models to be more energy-efficient

  • Encourage the use of green data centres powered by renewable energy sources

Climate modelling & sustainability

• AI can be a powerful tool for environmental protection:

  • Helps in climate modelling, predicting weather patterns and analysing environmental data

  • Aids in optimising energy use, improving efficiency in smart grids and buildings

  • Supports sustainable agriculture by analysing soil, weather, and crop data to reduce waste and overuse of resources

• However, the positive environmental applications of AI must be weighed against its resource demands, ensuring that the net impact supports climate goals

E-waste and hardware lifespan

• AI adoption drives demand for specialised hardware (e.g. GPUs, TPUs), which:

  • Can shorten the lifespan of devices due to rapid advancements in AI capability

  • Increases the volume of electronic waste, adding pressure to recycling systems

• Sustainable practices in hardware design, recycling, and component reuse are essential to reduce AI’s environmental footprint