Artificial intelligence refers, among other things, to machines’ capacity to demonstrate some degree of what humans consider “intelligence”. This process is being driven by the rapid advancement of machine learning: getting machines to think for themselves rather than pre-programming them with an absolute concept.

Take image recognition. Humans excel at this task, but it’s proved difficult to simulate artificially. Training a machine to recognise a cat doesn’t mean inputting a set definition of what a cat looks like. Instead, many different images of cats are inputted; the aim is that the computer learns to distil the underlying “cat-like” pattern of pixels.

This dependence on data is a powerful training tool. But it comes with potential pitfalls. If machines are trained to find and exploit patterns in data then, in certain instances, they only perpetuate the race, gender or class prejudices specific to current human intelligence.

But the data-processing facility inherent to machine learning also has the potential to generate applications that can improve human lives. “Intelligent” machines could help scientists to more efficiently detect cancer or better understand mental health. READ MORE ON: TECH XPLORE