July 20, 2007	Friday	Rajab 04, 1428

LONDON: Can a statistical model reliably predict that you will buy the latest Harry Potter book, or add organic brie to your virtual shopping trolley this week? What about whether you might become violent in the next 15 years, or your unborn child grow up to be a delinquent?

The growing use of computerised techniques for forecasting what we might buy or do on the basis of how our data matches up to some statistical model would suggest that they are well proven. But a landmark paper recently published in the British Journal of Psychiatry has cast doubt on whether such techniques should be used for making decisions about anything beyond the trivial.

The personalised recommendations and special offers that pop up when you order books or groceries online, and even the specific sequence of questions an insurance call centre asks about your claim, are all generated by computerised predictive algorithms derived from analysing patterns, links and associations in large sets of data.

By classifying types of people and their behaviours on this basis, shops try to increase their profits by automatically targeting those of us in their databases that seem most likely to buy certain items. Insurance companies use similar methods to reduce fraud by investigating the claims of those whom the software decides are most likely to be lying.

But the government is adopting such techniques for more serious matters. Software at the Department of Work and Pensions, for instance, is beginning to try to detect fraudsters by analysing the voices of people who ring its call centres — so if you ask the wrong kind of questions, or perhaps ask the right kind of questions in the wrong way, the software could decide you’re not strictly kosher.

The Surveillance Society report from the Information Commissioner’s Office outlined worries about predictive social sorting on the grounds that it could amount to discrimination, create new underclasses and that by the totting up of negative indicators from health, school and other records, a predictive model could make its own worst predictions come true. “For instance, if your parents both have criminal records or you have a bad school attendance record because of poor health, even if you are the best-behaved kid in class, you will find that every teacher is likely to treat you with suspicion,” explains Jonathan Bamford, assistant information commissioner.

Predictive models are attractive because they represent an apparently scientific and rigorous yet simple approach to targeting resources and making decisions about complex human problems. But this latest study adds to concerns that such techniques are insufficiently accurate to make important decisions about individuals. —Dawn/The Guardian News Service