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Artificial Intelligence: Functionality and Applications Explained

Reading Time: 4 minutes

Reading Time: 4 minutes

Rise of AI and Policy Responses

Artificial intelligence technology has developed swiftly in recent years. Governments worldwide, including Scotland and the UK, have taken steps to address AI. Scotland’s Artificial Intelligence Strategy was published in 2020, followed by the UK’s pro-innovation approach to AI regulation in 2023. The EU also approved the Artificial Intelligence Act 2024.

Defining AI: A Complex Task

AI lacks a universal definition. Scotland’s Artificial Intelligence Strategy describes it as technologies enabling computers to perform tasks requiring human intelligence, like visual perception and speech recognition. In contrast, the UK’s white paper defines AI as adaptable and autonomous products and services, highlighting the uniqueness of AI compared to traditional automation techniques.

Basics of AI: Algorithms and Rules

AI fundamentally relies on algorithms. Algorithms are sets of instructions for tasks like analysis or calculations. Early AI systems used rule-based methods with explicitly programmed instructions, often called expert systems.

Machine Learning: The Game Changer

Machine learning has driven much of AI’s recent progress. Unlike rule-based systems, machine learning algorithms infer their own rules from data, improving performance over time. They can handle complex tasks, such as image recognition, where explicit programming is unfeasible.

Types of Machine Learning

Machine learning includes supervised, unsupervised, and reinforcement learning. Supervised learning trains AI using labeled data. Unsupervised learning involves identifying data patterns without labels, while reinforcement learning uses a system of rewards and punishments to refine algorithms.

Deep Learning: Neural Networks

Deep learning, a subset of machine learning, employs multiple neural network layers. Neural networks mimic the human brain, consisting of interconnected artificial neurons. Notable examples include Google’s search algorithm and OpenAI’s GPT series, including ChatGPT.

AI Applications Across Sectors

AI tools are now employed in various sectors. Prominent examples include:

  • Communications: Search engines, spam filters, and machine translation.
  • Banking: Market prediction and fraud detection.
  • [More examples and elaborations]

AI Adoption Rates

Despite widespread potential, AI adoption is limited among businesses in Scotland. Scottish Enterprise found that only 16% of businesses used AI, though rates were higher among larger companies and in the Information and Communications sector.

Future Trends in AI

UK-wide adoption of AI is expected to increase. A 2022 study estimated AI use will reach 22.7% by 2025 and exceed 34% by 2040.

Additional Resources

For more information on AI, the UK Parliamentary Office for Science and Technology (POST) has published various resources, including an explainer and briefs on policy implications and potential issues.

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