Perhaps we want to build systems that ‘fill the gaps that humans cannot reach’, whether it’s AI that thinks in non-human ways or AI that doesn’t think at all
- José Hernandez-Orallo
We are well on the way to a world in which many aspects of our daily lives will depend on AI systems.
Within a decade, machines might diagnose patients with the learned expertise of not just one doctor but thousands. They might make judiciary recommendations based on vast datasets of legal decisions and complex regulations. And they will almost certainly know exactly what’s around the corner in autonomous vehicles.
“Machine capabilities are growing,” says Dr Stephen Cave, Executive Director of the Leverhulme Centre for the Future of Intelligence (CFI). “Machines will perform the tasks that we don’t want to: the mundane jobs, the dangerous jobs. And they’ll do the tasks we aren’t capable of – those involving too much data for a human to process, or where the machine is simply faster, better, cheaper.”
Dr Mateja Jamnik, AI expert at the Department of Computer Science and Technology, agrees: “Everything is going in the direction of augmenting human performance – helping humans, cooperating with humans, enabling humans to concentrate on the areas where humans are intrinsically better such as strategy, creativity and empathy.”
Part of the attraction of AI requires that future technologies perform tasks autonomously, without humans needing to monitor activities every step of the way. In other words, machines of the future will need to think for themselves. But, although computers today outperform humans on many tasks, including learning from data and making decisions, they can still trip up on things that are really quite trivial for us.
Take, for instance, working out the formula for the area of a parallelogram. Humans might use a diagram to visualise how cutting off the corners and reassembling it as a rectangle simplifies the problem. Machines, however, may “use calculus or integrate a function. This works, but it’s like using a sledgehammer to crack a nut,” says Jamnik, who was recently appointed Specialist Adviser to the House of Lords Select Committee on AI.
“When I was a child, I was fascinated by the beauty and elegance of mathematical solutions. I wondered how people came up with such intuitive answers. Today, I work with neuroscientists and experimental psychologists to investigate this human ability to reason and think flexibly, and to make computers do the same.”
Image: Artificial intelligence
Credit: The District
Reproduced courtesy of the University of Cambridge