|How artificial intelligence works|
From the earliest days of artificial intelligence (AI), its definition focused on how its results appear to show intelligence, rather than the methods that are used to achieve it. Since then, AI has become an umbrella term which can refer to a wide range of methods, both current and speculative. It applies equally well to tools that help doctors to identify cancer as it does to self-replicating robots that could enslave humanity centuries from now. Since AI is simultaneously represented as high-risk, low-risk and everything in between, it is unsurprising that it attracts controversy. This briefing provides accessible introductions to some of the key techniques that come under the AI banner, grouped into three sections to give a sense the chronology of its development. The first describes early techniques, described as 'symbolic AI' while the second focuses on the 'data driven' approaches that currently dominate, and the third looks towards possible future developments. By explaining what is 'deep' about deep learning and showing that AI is more maths than magic, the briefing aims to equip the reader with the understanding they need to engage in clear-headed reflection about AI's opportunities and challenges, a topic that is discussed in the companion briefing, Why artificial intelligence matters.