Skip to main content

Klara and the Sun (SF) - Kazuo Ishiguro ***

There is always a significant danger when a member of the literari takes on a science fiction theme - the result can easily seem derivative and dull when covering a topic that has already been better explored by others. (Of course the literary fiction audience are unlikely to realise this.) Sadly, there is an element of this danger manifest in Kazuo Ishiguro's new novel.

The theme is a well-trodden one. A robot with strong artificial intelligence faces up to emotions and is used to explore the human condition. Here called 'artificial friends' we can see a progression to such companion robots from the current wave of cuddly robot pets, producing a device that has general artificial intelligence giving it the abilities and emotions of a human being. Klara is both a companion to and a replacement for a dying child.

Of course there is nothing wrong with exploring a well-trodden path if you have something new to say, but most what occurs in Klara and the Sun is anything but original. Most recently we've had Set my Heart to Five, with a robot discovering emotions - but there were plenty of closer parallels to this storyline earlier. One should even be familiar to film fans in the troubled movie AI, started by Kubrick and finished by Spielberg, where a robot child is manufactured for similar reasons to Klara - a story that despite the clunkiness of the film manages still to be moving, and that is done far better in the original Brian Aldiss short story.

Earlier, of course, Isaac Asimov covered robots and society over a wide range of short stories and novels - and it's a topic that has been covered many times since by master in the field. One problem that emerges once comparisons are made is that SF writers tend to know a lot more about the science. General artificial intelligence is nightmarishly complex thing to create, far beyond our current capabilities. To think that this could be done any time soon is itself unlikely. But that Klara would at the same time be totally unworldly and lacking in the abilities that even IBM's Jeopardy-winning computer Watson had to look information up and give it context from online sources is simply ignorant. We know all SF gets it wrong about the future - look at some of the technology in the original series of Star Trek, for instance - but at least it starts from what's known at the time, rather than ignoring science and technology.

I had genuinely hoped to find something new and interesting in Ishiguro's take on the subject, but the core is very much more of the same, with the addition of frankly tedious over-writing. There's a meme doing the rounds of social media headed 'Book Blurbs - glossary of terms' which defines 'Epic' as 'cowed by the author's reputation'. That has clearly happened here in a book that could do with a sweeping edit to clear out the deadwood. 

It's not all bad. But it could have been so much better.



Using these links earns us commission at no cost to you

Review by Brian Clegg


Popular posts from this blog

Models of the Mind - Grace Lindsay *****

This is a remarkable book. When Ernest Rutherford made his infamous remark about science being either physics or stamp collecting, it was, of course, an exaggeration. Yet it was based on a point - biology in particular was primarily about collecting information on what happened rather than explaining at a fundamental level why it happened. This book shows how biologists, in collaboration with physicists, mathematicians and computer scientists, have moved on the science of the brain to model some of its underlying mechanisms. Grace Lindsay is careful to emphasise the very real difference between physical and biological problems. Most systems studied by physics are a lot simpler than biological systems, making it easier to make effective mathematical and computational models. But despite this, huge progress has been made drawing on tools and techniques developed for physics and computing to get a better picture of the mechanisms of the brain. In the book we see this from two directions

The Ten Equations that Rule the World - David Sumpter ****

David Sumpter makes it clear in this book that a couple of handfuls of equations have a huge influence on our everyday lives. I needed an equation too to give this book a star rating - I’ve never had one where there was such a divergence of feeling about it. I wanted to give it five stars for the exposition of the power and importance of these equations and just two stars for an aspect of the way that Sumpter did it. The fact that the outcome of applying my star balancing equation was four stars emphasises how good the content is. What we have here is ten key equations from applied mathematics. (Strictly, nine, as the tenth isn’t really an equation, it’s the programmer’s favourite ‘If… then…’ - though as a programmer I was always more an ‘If… then… else…’ fan.) Those equations range from the magnificent one behind Bayesian statistics and the predictive power of logistic regression to the method of determining confidence intervals and the kind of influencer matrix so beloved of social m

How to Read Numbers - Tom Chivers and David Chivers *****

This is one of my favourite kinds of book - it takes on the way statistics are presented to us, points out flaws and pitfalls, and gives clear guidance on how to do it better. The Chivers brothers' book isn't particularly new in doing this - for example, Michael Blastland and Andrew Dilnot did something similar in the excellent 2007 title The Tiger that Isn't - but it's good to have an up-to-date take on the subject, and How to Read Numbers gives us both some excellent new examples and highlights errors that are more common now. The relatively slim title (and that's a good thing) takes the reader through a whole host of things that can go wrong. So, for example, they explore the dangers of anecdotal evidence, tell of study samples that are too small or badly selected, explore the easily misunderstood meaning of 'statistical significance', consider confounders, effect size, absolute versus relative risk, rankings, cherry picking and more. This is all done i