Precrime profiling is no longer a fantasy
With attacks on prison officers increasing, AI profiling of inmates is the latest example of so-called precrime technology, based on the dubious theory that science can foresee individual criminal behaviour and prevent it by disrupting, punishing or restricting potential law-breakers.
The idea was popularised in the 1956 Philip K Dick novel The Minority Report, adapted by Steven Spielberg into a 2002 movie starring Tom Cruise, in which teams of psychic 'precogs' exercise foreknowledge of criminal activity, including premeditated murder, to identify and eliminate persons who will commit crimes in the future.
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In the film, set in 2054, the chief of the Precrime agency explains the advantages of pre-emptive justice: 'In our society we have no major crimes … but we do have a detention camp full of would-be criminals.' Thirty years ahead of schedule, instead of clairvoyance as a crime prevention tool, we have AI.
The theory of precrime dates to the early 19th century and the Italian eugenicist Cesare Lombroso, who is purported to have invented the term 'criminology'. Lombroso believed that criminals were born lawless, inheriting atavistically villainous characteristics and physiognomies. Criminal anthropometry, the precise measurement of faces and bodies, he argued, could be used to identify crooks and stop them from committing crimes.
This 'positivist' school of criminology claimed to recognise criminals not only by biological characteristics but also through psychological and sociological forms of behaviour. 'Born criminals', nature's psychopaths and dangerous habitual offenders, could thus be eliminated using capital punishment, indefinite confinement or castration.
The sinister notion that a system might detect the mere intention to offend is echoed in the 'thought crime' of George Orwell's 1984. Richard Nixon's psychiatrist, Arnold Hutschnecker, advised the president to run mass tests for 'pre-delinquency' and confine those juveniles to 'camps'. A refugee from Nazi Germany, Hutschnecker insisted these would not be concentration camps but holiday camps in a 'pastoral setting'.
In the 1970s, the University of California, Los Angeles attempted to set up a Centre for the Long-Term Study of Life-Threatening Behaviour, using scientific data to predict 'dangerousness'. It planned to 'compile stocks of behavioural data to understand crimes that had not yet occurred but were 'in formation'.' The project foundered when it was suggested the centre intended to use 'psychosurgery' to modify behaviour.
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But precrime is not some sci-fi fantasy or a wacko theory from the fringes of eugenics; it is already here. 'Predictive policing' — using data to forecast future criminal activity — is expanding rapidly. The UK Ministry of Justice is said to be developing a 'homicide prediction project' using police and government data to profile individuals with the aim of forecasting who is more likely to commit a murder.
The project, revealed in April by the investigative group Statewatch, will 'review offender characteristics that increase the risk' and 'explore alternative and innovative data science techniques to risk assessment of homicide'.
In the US, the software system Compas (Correctional Offender Management Profiling for Alternative Sanctions) is used by police and judges to forecast the risk of recidivism among more than one million offenders. The software predicts the likelihood that a convicted criminal will reoffend within two years based on data that include 137 of each individual's distinguishing features as well as criminal or court records.
This is where actuarial science (mathematical and statistical methods used to assess risk in insurance, pensions and medicine) meets crimefighting and sentencing guidelines: a technological tool to predict the risk of reoffending by rating factors such as type of crime, age, educational background and ethnicity of the offender.
In Chicago, an algorithm has been created to predict potential involvement with violent crime to draw up a strategic subject list — or 'heat list' — of those the algorithm calculates to be the city's most dangerous inhabitants.
Precrime is most obvious and advanced in the context of counterterrorism to identify threatening individuals, groups or areas, but inevitably invites conflict between the ideal of impartial criminal justice and the needs of national security.
In the traditional justice and criminal system, the law attempts to capture and punish those responsible after crimes have been committed. AI could invert that equation by meting out punishment or imposing surveillance where no crime has been committed — yet. As the chief of the Precrime agency in Minority Report observes: 'We're taking in individuals who have broken no law.'
Critics fear that precrime techniques could remove the presumption of innocence, the cornerstone of the justice system, and increase guilt by association since an individual's known contacts would influence any risk assessment. It also threatens to dehumanise individuals by reducing people to the sum of their accumulated data.
Latter-day predictive policing already deploys data analysis and algorithms to identify higher risks of criminality, triggering increased police presence in certain areas and communities. Critics argue that this leads to increased racial profiling, with certain populations disproportionately flagged as high risk. If the data pool being 'learnt' by AI is already racially biased, then its predictions will be similarly skewed.
Until the digital age, crimefighting was based on solving crimes or catching criminals in the act. In the age of AI, the sleuth will rely on machine learning to uncover clues to crimes that have yet to be perpetrated. 'It is a capital mistake to theorise before one has data,' said Sherlock Holmes. In the brave new world of precrime, the data will take over from the detectives.
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