Skip to main content

The AI Paradox - Virginia Dignum ****

This is a really important book in the way that Virginia Dignum highlights various ways we can misunderstand AI and its abilities using a series of paradoxes. However, I need to say up front that I'm giving it four stars for the ideas: unfortunately the writing is not great. It reads more like a government report than anything vaguely readable - it really should have co-authored with a professional writer to make it accessible. Even so, I'm recommending it: like some government reports it's significant enough to make it necessary to wade through the bureaucrat speak.

Why paradoxes? Dignum identifies two ways we can think about paradoxes (oddly I wrote about paradoxes recently, but with three definitions): a logical paradox such as 'this statement is false', or a paradoxical truth such as 'less is more' - the second of which seems a better to fit to the use here. 

We are then presented with eight paradoxes, each of which gives some insights into aspects of the overriding first, which Dignum calls 'the AI paradox' - 'The more AI can do, the more it highlights the irreplaceable nature of human intelligence.' Because of potential misunderstandings of what AI is and what it can do, many of the paradoxes arise from the assumption that it can replace human intelligence, or indeed is intelligent at all in the same sense of humans. As Dignum points out, there is no doubt AI is better at some things than humans, just as a calculator is better at doing arithmetic. But because it is purely data driven and lacks any understanding or empathy (even it tries to fake it), it will never be a substitute for our abilities. Used properly it's a great asset, but we need to understand its limitations to use it well.

I won't go through all the other paradoxes here, but to give a flavour, we get the Agreement paradox 'The more we explore AI, the harder it becomes to agree on a definition', the beautifully paradoxical intelligence paradox 'AI is what AI cannot do' and the Regulation paradox (which I can't really see as a paradox at all) 'Responsible innovation need regulation'. For each paradox we get a chapter explaining why the paradox exists, what it means and in some cases (like regulation) why it's difficult to do anything about it.

A couple of small moans - Dignum refers to Ada King (Countess of Lovelace) as 'the world's first programmer' where in reality she was second as Babbage wrote several algorithms for the Analytical Engine (they weren't really programs in the modern sense) before her contribution. And the selection of examples of AI LLMs etc. was strangely limited - Anthropic got one mention of Claude (though not of the company), and X/Grok was not mentioned at all, which is odd given how often the latter gets picked up in the media when it hits problems.

The main weakness, apart from the writing style was that the book is far stronger on the issues than on solutions, which tend to be strongly oriented to relying on international bodies that seem incapable of much action. The two come together in the Solution paradox chapter where we get text like 'To move beyond AI-solutionism, a critical, multidisciplinary perspective is necessary... Aligning technological advances with democratic and human rights principles is crucial for ensuring just and equitable outcomes... A balanced approach, combining top-down and bottom-up strategies, is essential. Ethical frameworks must be adaptable to different cultural contexts, supporting a variety of interpretations and values.' A practical roadmap it isn't.

However, if you come to this book without great expectations for readability, it does provide genuine insights into the benefits and limitations of AI and how we need a better understanding of what it can do and how to use it safely and effectively, even if it can't sensibly get us from here to that desired position. As such it's valuable contribution to the AI debate.

Hardback:   
Kindle:  
Using these links earns us commission at no cost to you
These articles will always be free - but if you'd like to support my online work, consider buying a virtual coffee or taking out a membership:
Review by Brian Clegg - See all Brian's online articles or subscribe to a weekly email free here

Labels:

Comments

Post a Comment

Popular posts from this blog

The Laws of Thought - Tom Griffiths *****

In giving us a history of attempts to explain our thinking abilities, Tom Griffiths demonstrates an excellent ability to pitch information just right for the informed general reader.  We begin with Aristotelian logic and the way Boole and others transformed it into a kind of arithmetic before a first introduction of computing and theories of language. Griffiths covers a surprising amount of ground - we don't just get, for instance, the obvious figures of Turing, von Neumann and Shannon, but the interaction between the computing pioneers and those concerned with trying to understand the way we think - for example in the work of Jerome Bruner, of whom I confess I'd never heard.  This would prove to be the case with a whole host of people who have made interesting contributions to the understanding of human thought processes. Sometimes their theories were contradictory - this isn't an easy field to successfully observe - but always they were interesting. But for me, at least, ...
Post a Comment
Read more

The Infinity Machine - Sebastian Mallaby ****

It's very quickly clear that Sebastian Mallaby is a huge Demis Hassabis fan - writing about the only child prodigy and teen genius ever who was also a nice, rounded personality. After a few chapters, though, things settle down (I'm reminded of Douglas Adams' description of the Hitchhiker's Guide to the Galaxy ) and we get a good, solid trip through the journey that gave us DeepMind, their AlphaGo and AlphaFold programs, the sudden explosion of competition on the AI front and thoughts on artificial general intelligence. Although Mallaby does occasionally still go into fan mode - reading this you would think that AlphaFold had successfully perfectly predicted the structure of every protein, where it is usually not sufficiently accurate for its results to have direct practical application - we get a real feel for the way this relatively unusual company was swiftly and successfully developed away from Silicon Valley. It's readable and gives an important understanding of...
Post a Comment
Read more

Nanotechnology - Rahul Rao ****

There was a time when nanotechnology was both going to transform the world and wipe us out - a similar position to our view of AI today. On the positive transformation side there was K. Eric Drexler's visions in the 1986 Engines of Creation. Arguably as much science fiction as engineering possibilities, it predicted the ability to use vast armies of assemblers to put objects together from individual atoms.  On the negative side was the vision of grey goo, out of control nanotechnology consuming all in its path as it made more and more copies of itself. In 2003, for instance, the then Prince Charles made the headlines  when newspapers reported ‘The prince has raised the spectre of the “grey goo” catastrophe in which sub-microscopic machines designed to share intelligence and replicate themselves take over and devour the planet.’ These days the expectations have been eased down a notch or two. Where nanotechnology has succeeded, it has been with the likes of atom-thick mat...
Post a Comment
Read more