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In his book Against Prediction, Bernard Harcourt presents a rationale for not using predictive profiles of offending population for three major reasons. The first reason Harcourt (2007) gives is that "reliance on predictions of future criminality may undermine the primary goal of law enforcement, namely, reducing crime." (pp. 2-3) Harcourt points out the main criteria for his judgment, which is based on a theoretical framework, that "probabilistic methods may increase the overall amount of targeted crime depending on the relative responsiveness of he profiled individuals." (p3) Harcourt (2006) says that though there is statistical evidence that a specific profile may respond, there is no actual documented evidence that that population will respond to the actuarial statistic and that "elasticity of offending to policing." (p 26) Harcourt (2006) defines elasticity further by adding, "the elasticity of offending to policing is the degree to which changes in policing affect changes in offending." (p 26) Harcourt (2007) goes on to show that "reliance on probabilistic methods produces a distortion in the carceral population." (p 3) Harcourt (2007) points out that the distortion places the profiled population of known offenders in greater relief over the unprofiled population, causing those without criminal records to have a harder time "obtaining employment, pursuing educational opportunities, or simply leading normal family lives." (p 3)
Relative Importance of Actuarial Instruments
Actuarial instruments, according to Harcourt (2007) have begun to "bias our concept of just punishment." (p 3) This seems to be a dilemma, which Harcourt explains further. Whether or not the profiled individual responds to law enforcement policy change or not; there is no profile to freedom of choice; that is, the elasticity of the offenders free will. Elasticity of free will is in-between the cause of the elasticity of that choice in a concrete situation. If a person who is a profiled offender does not meet the actuarial criteria there is no way of knowing that he/she will at one choose to offend and become closer to the criteria; on the other hand, for the repeated offender who is profiled, there is no way of knowing at some point in the future they will change and no longer meet the actuarial profile of an offending person nor change along with the policy of law enforcement. In fact, the person may exceed all expectations.
Harcourt (2007) clearly distinguishes the theoretical and the practical framework of law enforcement. Law enforcement will respond to an offending behavior when they encounter it, but the actuarial instruments, which are based on probabilistic methods, are only the theoretical foundation on which law enforcement use to make their predictive decisions-human free will cannot be predicted. That is why Harcourt argues Against Prediction. There are times when actuarial instruments are helpful in predicting repeated offenders. For example, profiling offenders African American and Hispanic on American Highways. However, Harcourt (2007) points out that though the actuarial predictive instruments help to profile repeated offenders on the American highways, at the same time, it is more likely that it will also raise the level of prejudice against race and ethnicity groups, which is an unwanted bias. (P 4) Harcourt (2007) argues that the use of actuarial instruments to use for predictive measures against criminal offenders is an argument "is a debate about mathematics, identifiable social costs, and social epistemic distortions." (p 22)
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