Monday, November 21, 2016

Weapons of 'Math' Destruction - sexed up dossier on AI?

Unfortunate title, as O’Neil’s supposed WMDs are as bad as Saddam Hussein’s mythical WMDs, the evidence similarly weak, sexed up and cherry picked. This is the go-to book for those who want to stick it to AI by reading a pot-boiler. But rather than taking an honest look at the subject, O’Neil takes the ‘Weapons of Math Destruction’ line far too literally, and unwittingly re-uses a term that has come to mean exaggeration and untruths. The book has some good arguments and passages but the search for truth is lost as she tries too hard to be contrarian.
Bad examples
The first example borders on the bizarre. It concerns a teacher who is supposedly sacked because an algorithm said she should be sacked. Yet the true cause, as revealed by O’Neil, are other teachers who have cheated on behalf of their students in tests. Interestingly, they were caught through statistical checking, as too many erasures were found on the test sheets. That’s more man than machine.
The second is even worse. Nobody really thinks that US College Rankings are algorithmic in any serious sense. The ranking models are quite simply statistically wrong. The problem is not the existence of fictional WMDs but poor schoolboy errors in the basic maths. It’s a straw man, as they use subjective surveys and proxies and everybody knows they are gamed. Malcolm Gladwell did a much better job in exposing them as self-fulfilling exercises in marketing. In fact. most of the problems uncovered in the book, if one does a deeper analysis, are human. The main problem is that these case studies are very complex.
Take PredPol, the predictive policing software. Sure it has its glitches but the advantages vastly outweigh the disadvantages and the system and its use evolve over time to eliminate the problems. I could go on but the main problem with the book is this one-sidedness. Most technology has a downside. We drive cars, despite the fact that well over a million people die gruesome and painful deaths every year from in car accidents. Rather than tease out the complexity, ecven comparing uosides with downsides, we are given over-simplifications. The proposition that all algorithms are biased is as foolish as all algorithms are free from bias. This is a complex area that needs careful thought and the real truth lies, as usual, somewhere in-between. Technology often has this cost-benefit feature. To focus on just one side is quite simply a mathematical distortion, which is what O’Neil does in many of her cases.
The chapter headings are also a dead giveaway - Bomb Parts, Shell Shocked, Arms Race, Civilian Casualties, Ineligible to serve, Sweating Bullets, Collateral Damage, No Safe Zone, The Targeted Civilian and Propaganda Machine. This is not 9/11 and the language of WMDs is ridiculously hyperbolic- verging on propaganda itself.
At times O’Neil makes good points on ‘data' – small data sets, subjective survey data and proxies – but this is nothing new and features in any 101 stats course. The mistake is to pin the bad data problem on algorithms and AI – that’s a misattribution. Time and time again we get straw men in online advertising, personality tests, credit scoring, recruitment, insurance, social media. Sure problems exist but posing marginal errors as a global threat is a tactic that may sell books but is hardly objective. In this sense, O'Neil plays the very game she professes to despise - bias and exaggeration.
The final chapter is where it all goes a bit weird, with the laughable Hippocratic Oath. Here’s the first line in her imagined oath “I will remember that I didn’t make the world, and it doesn’t satisfy my equations” – a line worthy of Donald Rumsfeld, There is, however one interesting idea – that AI be used to police itself. A number of people are working on this and I think it is a good example of seeing technology realistically, as being a force for both good and bad, and that the good will triumph if we use it for human good.

This book relentlessly lays the blame at the door of AI for all kinds of injustices, but mostly it exaggerates or fails to identify the real root causes. The book is readable, as it is lightly autobiographical, and does pose the right questions about the dangers inherent in these technologies. Unfortunately it provides exaggerated analyses and rarely the right answers. Let us remember that Weapons of Mass Destruction turned out to be lies, used to promote a disastrous war. They were sexed up through dodgy dossiers. So it is with this populist paperback.

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