Skip to main content

Snapshot (SF) - Brandon Sanderson ****

Although a science fiction story is just as capable of having all the usual furniture of a novel - character building, human reactions, locations and environment and so on - there is the added depth science fiction gains by being a genre of ideas. Some of the early greats of science fiction - Asimov, for example - managed the ideas and the 'What if?' far more eloquently than they did the traditional elements of fiction writing, presenting us with cardboard characters. Although Snapshot is nowhere near as bad as the old brigade in this respect, there is no doubt that Brandon Sanderson scores significantly more on the 'What if?' aspect. This is very much an idea-driven novella.

It's a dramatic idea at that. What if it were possible to recreate a day in a city with all its inhabitants, going through exactly what happened on the day? It would enable, for instance, police officers to go in and attempt to solve a crime, able to revisit the scene and interact with those involved. But Sanderson piles on the implications by making this not a virtual reality recreation, but a meatware one. By means we'll come back to, the whole physical reality of the city is recreated, then destroyed again at the end of the day. And to make the whole thing more laden with ethical dilemmas, the police officers carry a badge that makes inhabitants of the recreated city aware that they are copies who have less than a day to live.

Although some aspects of the story are a little predictable (Sanderson, in his afterword, actually says that he assumed that readers would guess one major twist), others still manage to surprise. It's a nicely constructed story within that jaw-dropping concept of a physical recreation of the city.

There are, I suppose, two issues to be addressed. One is that, as mentioned above, this is a novella, not a full length novel. I've a lot of time for the novella format, and they work well as ebooks, but I would usually expect it to be accompanied in physical form by a good bunch of short stories. Here it's left to fend for itself, and it's possible that a book that can be read on a shortish train journey is one that feels a little skimpy for the price.

The other issue is one that, again, Sanderson brings up in his postscript. The mechanism here is pure magic (though given a vague science-like wrapper with hints of an alien involvement). It has to be magic when you think about it. It's physically impossible to recreate anything at a quantum level other than making a copy and destroying the original. The practicalities are endlessly impossible (how to capture all the information, how to store it, how to manufacture the objects and people, what happens at the boundaries etc. etc.). So it requires a little more suspension of disbelief than most SF. I was also slightly surprised that Sanderson didn't refer to one of my favourite movies, Inception, when talking about the inspiration for the story - it's hard to read this and to believe that he's never seen Inception.

Overall, though, a truly interesting novella, which, though hardly creating deep characters, at least has some magnificent ideas to play with.

Hardback:  

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

Review by Brian Clegg

Comments

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