Ghosts in the machine

Artificial Intelligence is starting to play a big role in our lives. What’s next and what could go wrong?

Articles about Artificial Intelligence (AI) rarely get very far before they reference science fiction films. HAL in ‘2001’; the Skynet computer in ‘Terminator’; and the Replicants in ‘Blade Runner’. In fiction, when technology appears to gain intelligence, it develops its own ideas, and becomes malevolent. Is this really what awaits us over the next decade as technologies such as voice recognition and autonomous driving develop?

The truth is that robotics, automation, and AI are already everywhere: from pushing new songs we might like on Spotify; suggesting who we might fall in love with on dating apps; detecting suspicious payment activity from our bank accounts; enabling biometric identity checks such as voice recognition; getting insurance quotes via a price comparison website like MoneySuperMarket; and undertaking credit checks applying for an online loan.

 

Significant jumps in computer processing power have enabled AI in the form of complex algorithms to emerge. These learn from experience and have come to play an increasing role in business, not least finance. Tasks which would previously take days are completed in fractions of a second and are there for the convenience of customers and the security of the financial institution.

Over the next decade there is set to be an increasing use of AI in medicine, backed by evidence that it can spot abnormalities in scans for eye disease and cancer cells which should help improve the speed and accuracy of diagnosis and treatment. Wearable technologies such as the Apple Watch are able to use AI combined with internal sensors to warn of heart rhythm problems: technology which will surely develop and advance to other applications, such as strokes, in the coming years.

 

“Any sufficiently advanced technology is indistinguishable from magic”
Arthur C Clarke

In farming, services from the likes of Microsoft can be combined with soil-based sensors and drones to detect diseased crops or provide farmers with a heat map of the farm, identifying which areas most require nutrient supplementation. These systems can process vast volumes of data to automatically learn patterns and trends, helping farmers make decisions. As the AI learns over time, data inputs (including soil composition, weather trends and crop yields) will provide ever more sophisticated outputs.

Eliminating human error is the aim of selfdriving cars. Computers famously don’t feel pity, or remorse, or fear, but neither do they get tired or distracted. Autonomous cars are developing rapidly and are able to identify signs, road markings and objects coming into view and decide what to do about them. Unfortunately, as a headline on Bloomberg News recently explained, ‘Tesla’s Autopilot could save millions of lives, but it will kill some people first’. Will society accept this, despite the fact human error is in large part to blame for current accidents? Tesla are very careful to stress that, for now, humans must monitor the system and keep their hands on the wheel, but at some point in the future the system will fully take over – who would be to blame for an accident then? Society will have to decide on the trade-offs.

“For now AI is only as good as the programming – Garbage In, Garbage Out”

The combination of AI and facial recognition cameras open up some chilling applications and the tragic loss of two Boeing 737 Max jets highlight the other main issue – the AI is only as good as those programming it. As well as being poorly programmed, they could have in-built biases along racial or gender lines. Last year, Amazon scrapped its machine learning algorithm when it discovered it had an in-built bias against women. It was built to filter CVs of job applicants, having learnt from previous hiring patterns. The problem was those patterns, especially in technical jobs, had previously been filled by men and so the AI favoured them.

In short, whilst improvements over the next decade should improve our lives, AI for now is only as good as the programming and the information they are given. Or, to use the snappy computer industry acronym, ‘GIGO’ – Garbage In, Garbage Out.

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