Methodological Responses

These methodological vulnerabilities lead to four main lessons for the future adoption of predictive technologies. First, because predictive policing is largely untested, jurisdictions must independently evaluate initial claims of success. The San Francisco Police Department examined the possibility of adopting predictive policing, but declined to adopt the PredPol technology due to concerns about effectiveness.287 _{Currently, independent} data does not exist to verify the methodology of the companies selling the technology.288 _{Because the efficacy remains unknown, jurisdictions seeking} to purchase the technology need to check the methodology and prepare responses to future legal and community challenges.

Second, adopting jurisdictions must remain cautious about extending

conclusions from one jurisdiction to another. Problems of

overgeneralization can be addressed by recognizing that the urban landscape, police culture, and economic realities might be very different in different parts of the country. Just because predictive policing works in sprawling areas of Los Angeles does not mean it would work in the vertically constructed New York City. Just because burglaries appear to encourage repeat offending in nearby areas does not mean that aggravated assault or other crimes will follow suit.

285. SOC. PSYCHOL. ANSWERS TO REAL-WORLD QUESTIONS, STRATEGIES FOR CHANGE:

RESEARCH INITIATIVES AND RECOMMENDATIONS TO IMPROVE POLICE-COMMUNITY RELATIONS IN

OAKLAND,CALIF. (Jennifer L. Eberhardt ed., 2016); REBECCA C.HETEY ET AL.,SOC.PSYCHOL.

ANSWERS TO REAL-WORLD QUESTIONS,DATA FOR CHANGE:ASTATISTICAL ANALYSIS OF POLICE

STOPS,SEARCHES,HANDCUFFINGS, AND ARRESTS IN OAKLAND,CALIF.,2013–2014 (2016).

286. Slobogin, supra note 39, at 292 (“The accuracy of expert predictions can be fully understood only if base rates of recidivism are taken into account.”).

287. Bond-Graham & Winston, supra note 4.

288. Moraff, supra note 282 (“[T]he vast majority of what we know about predictive policing comes from data released unilaterally by individual police agencies, or by the firms peddling software to them. This not only makes it hard to compare results from city to city, but raises serious questions of data reliability.”).

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Third, communities adopting predictive policing must remain cognizant of the temporal limitations of the predictions. One of the oft-ignored limitations of predictive policing involves its timeframe for predictions. For example, PredPol’s property-based predictions occur on a daily (and even hourly) basis, allowing for a rather sophisticated matching of time and place. However, PredPol’s violence-predicting technologies look at a 30– 100 day window, allowing for far less useful actionable data.289 _{Both might} be accurate in their predictions, but the former provides a much more useful and relevant dataset for police officers looking for immediate suspicious activity.

Finally, the predictive technologies targeting individuals face even harder questions. Correlation should not be confused with causation when individual liberties are concerned.290 _{When the physical and emotional} impact of police authority is involved, some individualized suspicion is required.291 _{The fact that a prediction identifies a particular individual} should not, without more, be enough to initiate investigation. Strikingly, Jeffrey Brantingham, one of the founders of modern predictive policing and the creator of PredPol, was quoted saying: “These ‘person-centric’ models are problematic . . . because they carry an elevated margin of error and can legitimize racial, gender-based and socioeconomic-driven profiling. As a scientist you better be damn sure the model of causality is right or else it’s going to lead to a lot of false positives.”292 _{These false positives have grave,} liberty-eroding consequences, and so responses must be built in to ensure accuracy. Even if sufficient suspicion could be generated through pattern- matching or social network theory, acting on that suspicion should not be a foregone conclusion. While perhaps these predictive techniques could be useful for an initial lead, further screening mechanisms must be created before reliance on correlation leads to the physical and sometimes painful power of the state being brought to bear on an individual.

These methodological responses can be summarized into two simple recommendations. First, the acknowledged vulnerabilities of predictive

289. The near repeat effects of violent crime have not been strongly demonstrated, which may provide a second reason to qualify the utility of this approach.

290. Underwood, supra note 38, at 1446 (“A statistical correlation in data about one group of people may not hold when used as a basis for predictions about another group of people. A causal theory helps to identify any relevant differences between the two groups, or differences in the surrounding circumstances.”).

291. Arguably, if all that were at issue were therapeutic interventions without coercive law enforcement or judicial impacts, a looser correlation standard might be justified. But, as predictive policing is connected with real policing, more than therapy is at issue.

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methodologies need to be addressed before adopting the technology. Second, the limitations should encourage a more scientifically rigorous approach. The second response will be the subject of the next section.