The possibilities and potential problems of generative artificial intelligence (GenAI) have burst into public awareness over the last 12 months, but AI itself is not a new technology. The concept of autonomous machines and sentient computers has haunted and delighted science fiction readers for over a century.

Outside of literature and film, real-life examples of AI have been actively researched and demonstrated for decades. Scientists have been experimenting with neural networks, which allow computers to read and understand human handwriting by simulating the way that neurons in the brain send signals to each other, since the 1940s. Computers have been able to spot patterns in images since the 1970s – which we now use to help us unlock our smartphones with our faces. Each of these branches of AI allows computers to make decisions in an arguably intelligent fashion or communicate with humans more intuitively.

Whilst traditional computer programs have excelled at making predictable calculations based on input data, recent developments in GenAI are now able to mimic the creative process of generating text, sound, speech, images and video. The vast computing processing capacity now available in the cloud or on modern electronic devices has only recently turned the dream of GenAI into a reality with transformative potential in all areas of society.

AI in education

The 2023 Pearson School Report showed that 45% of teachers expected to see an increased use of AI in schools over the next 10 years, and I have no doubt this percentage would be even higher if teachers were asked this now. I believe that the implications of GenAI in education – the opportunities and challenges for both students and teachers – along with what to look out for as this rapidly changing field accelerates in the future, is something we should all be interested in exploring in more detail.