Skip to main content

How Smart Machines Think - Sean Gerrish ****

While it will become apparent I think this book should have been titled 'How Dumb Machines Think', it was a remarkably enjoyable insight into how the well publicised AI successes - self-driving cars, image and face recognition, IBM's Jeopardy! playing Watson, along with  game playing AIs in chess, Go and Atari and StarCraft, perform their dark arts.

There's no actual programming presented here, so no need for non-programmers to panic, though there is some quite detailed discussion of how the software architectures are structured and how the different components - for example neural networks - do their job, but it isn't anything too scary if you take it slowly.

One thing that comes across very strongly, despite the AI types' insistence that their programs are of general use, is how very specifically tailored programs like the AlphaGo software that beat champions at the game Go, and the Watson computer that won at the US TV quiz show Jeopardy! were - incredibly finely designed to meet use and that use only.

The reason I make the remark about dumb machines is that what doesn't come across sufficiently in Sean Gerrish's book is that, because these programs are not in any sense intelligent, when they get things wrong, they often get things dramatically wrong. So some of Watson's answers on Jeopardy! did not make any sense at all. Similarly, image recognition software can be fooled by apparently abstract patterns that happen to have the right components to appear to be a distinguishable object. And when you bear in mind we're suggesting putting this kind of software in charge of cars that 'getting it dramatically wrong' bit is more than a little unnerving.

There was, though, a great section on the development of self-driving cars, from the original feeble attempts, where all the competitors in a race failed before completing 10 percent of the course, through to more recent and more successful versions that can handle basic traffic scenarios - though it would have been nice if Gerrish had gone beyond the old prize challenges to describe what the latest Google and Uber vehicles do. (It may be that their approaches are too proprietary.)

However, what was missing was any serious assessment of the big problems still faced. There have been two excellent books recently on the huge holes in AI that practitioners rarely admit to - The AI Delusion and Common Sense, The Turing Test and the Quest for Real AI - Gerrish would have produced an even better book if he could have addressed the concerns that these books raise.

Even so, in How Smart Machines Think we have a hugely informative and very readable book for anyone with an interest in finding out just what the much-trumpeted AI systems really do, and what lies beneath the hype.

Hardback:  

Kindle:  
Using these links earns us commission at no cost to you

Review by Brian Clegg

Comments

Popular posts from this blog

Mathematics with Love – Mary Stopes-Roe *****

Admittedly it’s early days (this review is written in January), but this, for me, is the surprise hit of the year so far! I approached this book with trepidation, but found it absolutely delightful. It is described on the cover as the “courtship correspondence of Barnes Wallis, inventor of the bouncing bomb”, and contains a series of letters between Wallis and his cousin and eventual wife Molly Bloxham, along with some useful annotation by their daughter, Mary. The courtship itself is not without difficulties, as Wallis was 18 years older than the 17-year-old Molly at the start of the correspondence, and her father, not surprisingly, wasn’t too pleased about the interest of such an elderly suitor, but that isn’t the only reason the letters are interesting – it’s also because of maths, and Wallis’s position in the UK as the engineering hero of the Second World War. (Incidentally, it seemed very strange to see letters addressed to “Barnes” – I had always assumed Barnes Wallis was a ...

Data Empire - Roopika Risam ****

The central thesis presented by Roopika Risam is that information gives us (and particularly countries) the power to organise, control and dominate others. Although I have a couple of issues with the presentation, this is a genuinely interesting trip through the history of our use of stored information from the earliest tallies to the latest information technology. I loved a quote from Lisa Gitelman that data is is always 'cooked' so 'raw data is an oxymoron'. This neatly underlines Risam's thesis that data and information are not neutral facts, but rather tools that (like everything from fire to electronics) can be used for good or evil. As we are taken through the historical context, it can sometimes be a little difficult to judge whether Risam regards a particular example as bad or good, even when the outcome is disastrous. One thing I didn't like too much is the adherence to a popular science writing approach that has got distinctly hackneyed: opening chapte...

Andrew Jaffe - Five way interview

Andrew Jaffe is professor of astrophysics and cosmology at Imperial College, London and director of the Imperial Centre for Inference and Cosmology. His new book is The Random Universe. Why science? I’ve always been interested in science, in particular in  astronomy, astrophysics, and space. One of my earliest memories - back in nursery school in New Jersey, I think - was watching one of the moon launches. I wanted that excitement to be part of my life! I never got to be an astronaut, but I did get to be part of the Planck Satellite team, and was privileged to be able to travel to the ESA Spaceport in French Guiana to watch the launch.  In between, I was lucky enough to have a supportive family, get a good education, and find inspiring teachers, mentors, and collaborators. They helped me model the universe, and helped me learn how to refine those models in the face of experimental and observational evidence. That is, they taught me to be a scientist. Why this book? The Random...