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Brian Clegg's Reviews > The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking
The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking
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Some titles tell you nothing about the book itself - but The AI Mirror puts Shannon Vallor's central argument front and centre: that artificial intelligence, particularly generative AI such as ChatGPT, is not intelligence at all, but rather holds a mirror up to our own intelligence. As Vallor points out, your reflection in a mirror certainly looks and acts like you - but it is not a person.
This is a metaphor that works impressively well. It reflects (get it?) the total lack of understanding in systems that are simply reflecting back data from a vast amount of human output. That's not to say that they have no value, but we always have to be aware of their nature and their abilities both to produce errors as a result and to reflect our in-built biases, which we may consciously suppress but nonetheless come through in the data. To quote Vallor, these systems 'aren't designed to be accurate, they are designed to sound accurate'.
What Vallor tells us we have that AI doesn't is 'practical wisdom' or prudence - you might doubt this if you listen to some politicians (say), but the point is that we are able to engage this kind of filter where the AI lacks the ability - and though there can be tinkering at the margins when AIs get things badly wrong, it won't stop them continuing to trip up.
As someone with a science background, I usually find reading philosophy books a real struggle, as they are rarely anything but clear - however Vallor puts forward her arguments in what is usually well-worded, comprehensible English. The only exception is a near-obsessive love of the painful word 'valorize' (I don't know if this is nominative determinism).
One very small moan - Vallor makes use of science fiction parallels and a couple of times refers to a SF source called iRobot - I think this is meant to be Isaac Asimov's I, Robot, not the vacuum cleaner manufacturer.
There is some powerful stuff here, though at one point Vallor notes how we're all becoming poor armchair non-experts in subjects like climate change, a subject she refers to consistently throughout the book despite it not being her subject. But there is one big issue: for me this is the classic 'article stretched to be a book'. The key points are excellent and thought-provoking, but they are all made at length and could have been condensed into far fewer words with more impact. I am, nonetheless giving the book four stars for its readability and central argument.
This is a metaphor that works impressively well. It reflects (get it?) the total lack of understanding in systems that are simply reflecting back data from a vast amount of human output. That's not to say that they have no value, but we always have to be aware of their nature and their abilities both to produce errors as a result and to reflect our in-built biases, which we may consciously suppress but nonetheless come through in the data. To quote Vallor, these systems 'aren't designed to be accurate, they are designed to sound accurate'.
What Vallor tells us we have that AI doesn't is 'practical wisdom' or prudence - you might doubt this if you listen to some politicians (say), but the point is that we are able to engage this kind of filter where the AI lacks the ability - and though there can be tinkering at the margins when AIs get things badly wrong, it won't stop them continuing to trip up.
As someone with a science background, I usually find reading philosophy books a real struggle, as they are rarely anything but clear - however Vallor puts forward her arguments in what is usually well-worded, comprehensible English. The only exception is a near-obsessive love of the painful word 'valorize' (I don't know if this is nominative determinism).
One very small moan - Vallor makes use of science fiction parallels and a couple of times refers to a SF source called iRobot - I think this is meant to be Isaac Asimov's I, Robot, not the vacuum cleaner manufacturer.
There is some powerful stuff here, though at one point Vallor notes how we're all becoming poor armchair non-experts in subjects like climate change, a subject she refers to consistently throughout the book despite it not being her subject. But there is one big issue: for me this is the classic 'article stretched to be a book'. The key points are excellent and thought-provoking, but they are all made at length and could have been condensed into far fewer words with more impact. I am, nonetheless giving the book four stars for its readability and central argument.
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Reading Progress
Finished Reading
July 3, 2024
– Shelved
