Gloria Laycock is putting science in the spotlight in the fight against crime.

“I could walk into any laboratory and generate a crime-prevention application from their last few papers,” claims Ken Pease, a criminologist who is a visiting fellow at University College London (UCL).

For many in Pease's discipline, the idea that biologists, chemists or physicists have much to offer the field is unfamiliar. But a small band of criminologists is now arguing that science can be central to preventing crime. “It's about giving scientists a dirty mind,” says Paul Ekblom, a criminologist at the Home Office, the British government department responsible for criminal justice and law enforcement. “Getting them to think 'thief',” he says — or 'rapist', or 'terrorist', for that matter.

The Jill Dando Institute of Crime Science, based at UCL, exemplifies this fresh approach. Dando, a British television presenter, was gunned down at her London home in 1999 in an apparently motiveless attack for which Barry George, a local man with a history of mental problems, was later jailed. Colleagues and friends of Dando — who presented a show called Crimewatch, which appeals for public help in solving crimes — raised funds for an institute to be formed in her memory. It opened its doors in spring 2001.

At the helm is Gloria Laycock, who previously worked as a psychologist in prisons and for the Home Office. “The institute is a reaction against traditional criminology,” she says. “Criminologists look for social causes of crime. A crime scientist would ask what science has got to offer.”

Crime scientists recast criminals as ordinary people reacting to a situation in which a crime can be committed, rather than as individuals driven to deviance by their social circumstances. About a third of all British men in their mid-forties have a conviction for at least one offence, Laycock points out. Against this background, scientific methods can be used to analyse the circumstances under which crimes are committed, and to seek practical means to change those circumstances. For those who find criminology too ideological, crime science sounds like a Realpolitik alternative.

This approach has not endeared Laycock to some criminologists, who accuse her of neglecting crime's social origins. But her institute's researchers — 19 have been recruited so far, including visiting fellows — are bubbling over with speculative ideas. Pease, for example, wonders whether we might learn about the best way to deploy closed-circuit television (CCTV) cameras by studying the strategies used by groups of foraging primates to watch out for predators. Laycock speculates that mathematicians working on network theory could help to tease patterns from crime statistics that might prove useful in devising prevention strategies.

Some scientific disciplines — computer science, for instance — already have a track record of contributing to crime prevention. Sergio Velastin of Kingston University in Surrey, near London, is currently testing a software system that could help CCTV operators spot problems on the London Undergound, from packages that might contain bombs to people who are considering committing suicide. The software aims to take the pressure off CCTV operators, who often miss such things because they have to monitor large numbers of screens simultaneously. “We know they only look at 10% of cameras at any given time,” says Velastin.

The software starts by focusing on one area for up to an hour. This helps it to distinguish fixed areas of the image that it can ignore, such as the floors and walls. It can then spot suspect packages in the area of the image more easily. “There is always lots of movement,” says Velastin. “The biggest clue is something that is not the background but is not moving.”

The system can also be primed to spot potential suicides. Train drivers and CCTV operators have learnt to recognize the movements of people who are thinking about jumping in front of a train. Such people, says Velastin, tend to position themselves at the end of the platform, stay there while several trains pass by, and often walk up to and away from the platform edge. Tested at a London Underground station last August, the system spotted 90% of events of interest and raised false alarms 2% of the time. Importantly, CCTV operators said that they were happy working with it.

Family conflict

Laycock, Pease and their colleagues are even more interested in drawing in researchers from disciplines that haven't traditionally been seen as relevant to the fight against crime. So far, they have made only a few firm links with UCL's mainstream science departments — recruitment and fund-raising have taken up most of the Jill Dando Institute's first year. But as an example of the type of work that crime scientists hope to promote, Ekblom points to the research of evolutionary psychologists Martin Daly and Margo Wilson of McMaster University in Hamilton, Ontario, who in the 1980s began to challenge traditional ideas about homicides within families.

Sociologists have often asserted that violence is far more common between family members than between those who are not related. But Daly and Wilson thought that this idea was strange — evolutionary theory says that animals sharing genes by common descent should be less inclined to enter into conflict with relatives, not more so.

Controlling for the many different factors involved in homicide is difficult. For example, family members are more likely to fight each other simply because they have more opportunity to do so. So Daly and Wilson analysed a homicide data set collected by Detroit police, which provided information on whether the murderer and victim lived together. Taking just the latter cases, the researchers found that genetically unrelated people who shared accommodation were eleven times more likely to kill one another than co-residing blood kin. This higher homicide rate applied equally to married couples and individuals without any relationship other than the fact that they shared accommodation1. Significantly, Daly and Wilson also showed that stepchildren were at particular risk of being killed by their step-parents2 — a finding that might help social workers prioritize their registers of 'at risk' children.

Such work provides some support for the idea that there is untapped crime-prevention potential within mainstream science. But is Pease's confidence really justified? Nature decided to call his bluff, and presented him with six recent papers from UCL labs, selected by arbitrarily picking two departments and noting the three most recent papers listed on their web pages. We gave him two weeks to come up with crime-prevention ideas from at least two of the papers. Pease happily accepted — although he was a little flummoxed when the manuscripts arrived in his inbox. “My first reaction was: 'Oh shit!',” he admits.

Arresting ideas

Ken Pease seeks inspiration from scientific papers.

One paper3, from climate researchers Mark Saunders and Budong Qian, examined how records of sea surface temperatures in the north Atlantic could be used to predict the North Atlantic Oscillation — the pattern of high and low sea-level air pressure that dominates winter weather around the region. Pease admits to not having a specific application for this paper, but notes that some studies have suggested that burglary rates fall during cold weather. The paper by Saunders and Qian made him wonder whether more effort should be put into investigating the links between crime and variations in seasonal weather patterns, in the hope that this might help in deploying police resources.

Another paper4, from Sham Kakade and Peter Dayan of UCL's computational neuroscience unit, compared theoretical models of animal learning. The models make use of variables such as the rate at which a particular reward is obtained, in this case the number of times the animal received food over a set time interval. Pease was struck by the fact that similar variables are used to compare crimes. Burglary, for example, has a lower rate of reward than shop theft, as the latter is easier and quicker to carry out. But the variability of the reward from shop theft is low as it is unlikely to yield a big return.

Studies of criminals in New York have shown that groups of illegal squeegee merchants — people who demand to be paid for washing car windows at traffic lights — contain a high proportion of armed robbers5. Pease speculates that criminals sometimes choose to combine crimes with a high rate of reward and low variability — such as illegal car washing or shop theft — to one with a low rate of reward and high variability, such as armed robbery or burglary. If so, asks Pease, might these choices be modelled using the learning theories studied by Kakade and Dayan? A better understanding of the links between different kinds of crime might help law-enforcement agencies to devise crime-prevention strategies, he argues.

Dayan, however, declined to comment on Pease's speculations about his work. Does this indicate that the Jill Dando Institute will face some scepticism from UCL's mainstream science departments as it tries to interest them in crime-prevention applications? As Laycock, Pease and their colleagues begin to ramp up their efforts to bridge the cultural divide between science and criminology, this question will be under the magnifying glass.

Jill Dando Institute of Crime Science→ http://www.jdi.ucl.ac.uk