This article considers what can be learned regarding the ethical acceptability of intrusive interventions intended to halt the spread of infectious disease (‘Infection Control’ measures) from existing ethical discussion of intrusive interventions used to prevent criminal conduct (‘Crime Control’ measures). The main body of the article identifies and briefly describes six objections that have been advanced against Crime Control, and considers how these might apply to Infection Control. The final section then draws out some more general lessons from the foregoing (...) analysis for the ethical acceptability of different kinds of Infection Control. (shrink)

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the (...) resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

This article analyses the moral status of racial profiling from a consequentialist perspective and argues that, contrary to what proponents of racial profiling might assume, there is a prima facie case against racial profiling on consequentialist grounds. To do so it establishes general definitions of police practices and profiling, sketches out the costs and benefits involved in racial profiling in particular and presents three challenges. The foundation challenge suggests that the shifting of burdens onto marginalized minorities may, even when profiling (...) itself is justified, serve to prolong unjustified police practices. The valuation challenge argues that although both costs and benefits are difficult to establish, the benefits of racial profiling are afflicted with greater uncertainty than the costs, and must be comparatively discounted. Finally, the application challenge argues that using racial profiling in practice will be complicated by both cognitive and psychological biases, which together reduce the effectiveness of profiling while still incurring its costs. Jointly, it is concluded, these challenges establish a prima facie case against racial profiling, so that the real challenge consists in helping officers practice the art of the police and not see that which it is useless that they should see. (shrink)

This essay begins with a current case involving racial profiling and DNA testing. The two combine to raise some troubling issues involving the use of each in police investigation. It is argued that racial profiling is unethical and ought to be avoided and that DNA testing on general populations of innocent people is fraught with dangers.

There are many objections to statistical discrimination in general and racial profiling in particular. One objection appeals to the idea that people have a right to be treated as individuals. Statistical discrimination violates this right because, presumably, it involves treating people simply on the basis of statistical facts about groups to which they belong while ignoring non-statistical evidence about them. While there is something to this objection—there are objectionable ways of treating others that seem aptly described as failing to treat (...) them as individuals—it needs to be articulated carefully. First, most people accept that many forms of statistical discrimination are morally unproblematic, let alone morally justified all things considered. Second, even treating people on the basis of putative non-statistical evidence relies on generalizations. Once we construe treating someone as an individual in a way that respects this fact, it becomes apparent: (1) that statistical discrimination is compatible with treating people as individuals, and (2) that one may fail to treat people as individuals even without engaging in statistical discrimination. Finally, there are situations involving the expression of messages of inclusion where we think it is good, morally speaking, that we are not treated as individuals. (shrink)