To me, the problem is less about identifying individuals struggling with mental illness, drug addiction, and poverty, and way more about the lack of resources available to help these individuals. Thank you, Holly for this article! According to a RAND researcher, officers are given vague directives on how to use the SSL, and thus the predictive data is not leveraged in an impactful and actionable way. Data from past crimes, including crime types and locations, are fed into a [16] Or perhaps CPD could wield its predictive technology to take a holistic, preventative approach to community safety, proactively connecting service providers with individuals most impacted by the root causes of violence, such as poverty and mental health issues.[17]. First, should police departments employ predictive policing technologies? Although it may limit the effectiveness of the program, it will not have undesired side effects that may hinder liberty. For example, there are many companies emerging that use machine learning to analyze visuals from surveillance cameras to detect “suspicious activity”. "Predictive policing is often hailed as a scientific solution to otherwise-intractable issues of policing, such as racial profiling. Once residents view the police as an ally, rather than a threat, then the police and residents will be able to proactively partner together towards a safer community. Holly, thanks for the great article. Methods for predicting crimes:These are approaches used to forecast places and times with an increased risk of crime. [17] Andrew V. Papachristos, “CPD’s crucial choice: Treat its list as offenders or as potential victims?” Chicago Tribune, July 29, 2016, https://www.chicagotribune.com/news/opinion/commentary/ct-gun-violence-list-chicago-police-murder-perspec-0801-jm-20160729-story.html, accessed November 12. Initial data suggests that these technological tools have contributed to a citywide decline in violence over the past year. The algorithm is a culmination of anthropological and criminological behavior research. stream
predictive policing technology and the analysis of heterogeneous datasets. This approach allows law enforcement to be proactive rather than reactive, ideally lowering crime rates and enhancing community safety.[1]. Sunday, the New York Times published a well-meaning op-ed about the fears of racial bias in artificial intelligence and predictive policing systems. Past crimes, race or place of living is not a 100% predictor of future crimes and I think approaching people at “high risk” category may be unfair and frustrating. Machine-learning algorithms could replicate or amplify bias on race, sexuality and age. Methods for predicting perpetrators' ident… WYZr��!�&As�$=�|�Z>$w��[J}NUw+�bDPqF~,�|J�s�ȩh��b��6��A�̻����,��F� ʿaS*�r��as���3���澲�oy&AW�.���O�yH���z8���SRI�dn&���ްŒ�a�0����������b(�+Ҹ�~)�,�xq�\�Z��+��B�uX���y��@��s�+8�:��Be]������瀾�C�"j9���\%�"]�E��:h���>�����Z
Predictive policing poses discrimination risk, thinktank warns. 37:33. [3] This “Strategic Subject List” (SSL) assigns a score of 1 to 500 based on an individual’s probability of being involved with a shooting or murder. “Predictive model—A mechanism that predicts a behavior of an individual, such as click, buy, lie, or die. endobj
5. Though debate is competitive, it must also be accessible. According to Chicago Magazine’s analysis, 56% of Black men ages 20-29 in Chicago have an SSL score. The score is generated based on factors including a person’s history of arrests and connections to past criminal activity. That’s the promise of “predictive policing,” which uses algorithms to analyze data about past criminal activity in order to illuminate patterns and establish hypotheses about future wrongdoing. 2. It would therefore make sense to me for the CPD to run a resident (not academic) competition on trust. What's The Res 345 views. cities. This is a very sensitive topic, on which even human thinking is sometimes biased. XPO Logistics (XPO): Attempting to Bring the Truckload and Less-than-Truckload (LTL) Industries into the Twenty-First Century, https://www.npr.org/2018/08/10/637410426/chicago-battles-its-image-as-murder-capital-of-the-nation, https://www.nytimes.com/2017/06/13/upshot/what-an-algorithm-reveals-about-life-on-chicagos-high-risk-list.html, http://directives.chicagopolice.org/directives/data/a7a57b85-155e9f4b-50c15-5e9f-7742e3ac8b0ab2d3.html, https://www.nytimes.com/2016/05/24/us/armed-with-data-chicago-police-try-to-predict-who-may-shoot-or-be-shot.html, https://www.chicagobusiness.com/article/20160919/OPINION/160919856/chicago-police-s-heat-list-and-what-to-do-with-predictive-policing, https://www.cityofchicago.org/city/en/depts/mayor/press_room/press_releases/2018/october/101018_ExpansionSmartPolicingStrategy.html, https://www.economist.com/united-states/2018/05/05/violent-crime-is-down-in-chicago, https://www.aclu.org/other/statement-concern-about-predictive-policing-aclu-and-16-civil-rights-privacy-racial-justice, https://www.aclu-il.org/en/press-releases/statement-predictive-policing-chicago, https://www.chicagomag.com/city-life/August-2017/Chicago-Police-Strategic-Subject-List/, https://news.uchicago.edu/story/using-data-science-confront-policing-challenges, https://www.chicagotribune.com/news/opinion/commentary/ct-gun-violence-list-chicago-police-murder-perspec-0801-jm-20160729-story.html, Printing the Future of Helicopters with Bell. If, and this is a big if, this could remove bias and actually be predictive, would there still be a concern using machine learning? While predictive policing is useful for finding hotspots and potential criminals, it also has some potential issues for the criminal justice field. The Chicago Police Department's embrace of machine learning raises critical questions about the balance between community safety, civil liberties, and systemic bias. Predictive policing methods fall into four general categories: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators identities, and methods for predicting victims of crime. I agree with you and above comments regarding the risks of using historical data for predictive purposes, especially in analyzing criminal records. Predictive policing is based on the assumption that it is not entirely random where and when crimes take place; rather that they are often concentrated in particular places and at particular times. As Cami Chavis Simmons (2015), a former federal prosecutor and a Yet as with many technologies that appear to provide a quick fix to complex social and political challenges, predictive policing promises far more than it can deliver — and actually exacerbates the problems that it claims to solve. I unfortunately feel we are moving this way even before we have proven results or understand the ethics and tradeoffs but do think the considerations should continue to be raised! People are labeled because of certain criteria that algorithm decides important, which have nothing to do with an individual’s intention of committing a crime in the future. Fears young people from culturally diverse backgrounds are being disproportionately targeted Last modified on Sun 22 Nov 2020 11.33 EST Victorian police say a … Predictive policing programs can undermine a person’s right to the presumption of innocence and other civil liberties. 1113 Carolina, Washington, Tennessee, Florida, Pennsylvania, and New York, among others, have purchased new predictive policing software to combat property crimes such as burglaries, car thefts, and thefts from automobiles. Such algorithms could theoretically eliminate the need to rely on unjust proxies such as race to drive policing practices. Predictive policing raises profound questions about the nature of predictive analytics and the attached article is the first sustained practical and theoretical critique of predictive policing. The city of Chicago has the highest number of homicides per year across all U.S. The report offers a non-exhaustive list of programs, primarily identified in Western and Northern parts of Europe. I also wonder if there needs to be government intervention. Want to learn more about digital transformation? %����
The weaknesses are that it requires hiring of specialists, it infringes on the individual’s right to privacy breaching The Fourth Amendment of The Constitution, and minorities can be easily targeted for commission of crimes. I don’t see any way that historical inputs do not perpetuate structural and societal biases or even more so confirm biases in people when they see a high SSL score. This is more of a philosophical or thought exercise as I believe we are a long way from removing bias from the system and actually being able to predict crimes using statistics or algorithms but believe it needs to be considered. 6 0 obj
Questions of data collection, methodology, transparency, accountability, security, vision, and practical implementation emerge from this move toward actuarial justice. <>
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press release, October 10, 2018, on City of Chicago Office of the Mayor website, https://www.cityofchicago.org/city/en/depts/mayor/press_room/press_releases/2018/october/101018_ExpansionSmartPolicingStrategy.html, accessed November 12. In April 2020, the LAPD announced that it would stop using the AI-driven predictive policing software. predictive policing technologies or service providers but dis-cusses predictive policing on a general level. Predictive policing is a data-based, predictive analytical technique used in law enforcement. The predictive policing model helped to alert officers to targeted locations in real time, a significant improvement over traditional tactics. The Economist asked him about how data and predictive analytics are changing modern policing. Perhaps laws need to be created to prevent certain machine learning/artificial intelligence applications because of the implications and severity of biased data. It takes characteristics of the individual as input, and provides a predictive score as output. endobj
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x��TMo�0���Q0V�y�,�2�K���Ӱ��ö�����M�A��0�#��Dk3���5 The debate shows how predictive policing has been praised for its effec-tiveness, while its ethicality has been criticized. The researchers found four broad categories of predictive policing methods, with approaches varying in the amount and complexity of the data involved: 1. CPD must also ensure that the SSL system does not reinforce biases against communities of color. PredPol was used by the LAPD for nine years during which time critics had lobbied for police departments to cease using it, noting it is unjust and racist. I fundamentally challenge the notion that machine learning can be unbiased in its prediction of crime. “We chose these sites because we found an overlap between extensively documented evidence of corrupt or unlawful police practices and significant interest, development, and current or prior use of predictive policing systems. In the existing scholarship, very little has been said about the connection between ethics and cultural techniques, perhaps because the technical apriori seems to have little room for human-based ethics. [9] For example, CPD will use past crime data (and other inputs including phases of the moon and schedules of sports games)[10] to predict where criminal activity might occur, and provide officers with real-time analysis on mobile apps to inform their patrols. By Mara Hvistendahl Sep. 28, 2016 , 9:00 AM. endobj
First, should police departments employ predictive policing technologies? Summit: Pathways to a Just Digital Future, Investigate how to address technological inequality, AI puts Moderna within striking distance of beating COVID-19, Dig into the totally digital biotech company. Can ‘predictive policing’ prevent crime before it happens? 4 0 obj
For groups who feel targeted by the police this kind of preventative policing can instead instill a sense of fear that they will be forced to endure further unjust persecution, harassment and targeting. Predictive policing methods fall into four general categories: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators' identities, and methods for predicting victims of crime. Nevertheless, I believe security enforcement can benefit from other areas of technological developments and AI. Predictive policing is the use of analytical techniques to help prevent crime, solve past crimes, or identify potential offenders and victims. 4� $/-,�4��n�d:{���*:�V. The second question invites imagination — are there other opportunities for police departments to leverage machine learning to increase community safety? Strengths of predictive policing are that it helps to prevent crimes, police are able to respond faster and public safety is enhanced. I think you are absolutely correct in highlighting the many potential pitfalls with machine learning. I think there is an inherent danger in the unchecked feedback loop within the ML system as well as an unchecked feedback loop from the SSL score to the individual interpreting the score. <>
A 2016 study by the RAND corporation found that people on the so-called “heat list” were not more or less likely to be involved in a shooting or homicide than the control group. endobj
Predictive Policing: Promoting Peace or Perpetuating Prejudice? [14] This is potentially the result of a negative “feedback loop” given that the algorithm considers a person’s past arrests. What if you could stop a crime before it happened? Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. 10 0 obj
[16] Rob Mitchum, “Using data science to confront policing challenges,” UChicago News, August 25, 2016, https://news.uchicago.edu/story/using-data-science-confront-policing-challenges, accessed November 12. It might be helpful to understand the common traits among criminals using data analytics, and that can help to define preventive actions; however in my opinion labeling people even before they commit a crime as potentially guilty is not going to work. [8] John S. Hollywood, “CPD’s ‘heat list’ and the dilemma of predictive policing,” Crain’s Chicago Business, September 19, 2016, https://www.chicagobusiness.com/article/20160919/OPINION/160919856/chicago-police-s-heat-list-and-what-to-do-with-predictive-policing, accessed November 12. For example, a team of data scientists at the University of Chicago created an algorithm to identify police officers with a propensity for excessive force. If you are ready to learn more about our programs, get started by downloading our program guide now. This technology poses a huge risk for racial profiling and can exacerbate mistrust in communities. Place-based predictive policing, the most widely practiced method, typically uses preexisting crime data to identify places and times that have a high risk of crime. Unfortunately, these issues are not getting enough air time and could lead to catastrophic results. POLICING PREDICTIVE POLICING. PredPol is one of the oldest and most controversial predictive policing companies. Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. 3. [5] Police personnel also inform them that the highest possible criminal charges will be pursued if they are found to be perpetrators of any further criminal activity. How they implement this technology to identify human trafficking and search for trafficking victims, for example, may be very different from how they would deploy the technology in an attempt to prevent other crimes. 8 0 obj
Nevertheless, like you, I struggle to understand the ethical implications of the project. Transparency could allow criminals or others to game the system and thus defeat the purpose but I agree the trust needs to be there first anyways. It could have profoundly damaging psychological effects and possibly physical safety risks for those who are inappropriately targeted based on their characteristics. endobj
press release, October 10, 2018, on City of Chicago Office of the Mayor website, https://www.cityofchicago.org/city/en/depts/mayor/press_room/press_releases/2018/october/101018_ExpansionSmartPolicingStrategy.html, accessed November 12. ���j�� l���|�&�Ó_?���1��;���&��&��*��-=� If we want to be proactive about ending crime, we need to invest in schools, rehabilitation programs, and social services. endstream
There is very little downside in these cases, whereas the downside in the current applications is enormous and has a generational impact. BARRETT_DIGITAL_9.6.17.DOCX (DO NOT DELETE) 9/6/2017 6:43 PM 2017 PREDICTIVE POLICING AT THE U.S. BORDER 329 substantive and procedural due process outside of the criminal context,3 there has been relatively little written about the use of predictive policing in the border A feedback loop of injustice The predictive policing model is deceptive and problematic because it presumes that data inputs and algorithms are neutral, and therefore that the information the computer spits out will present police officers with objective, discrimination-free leads on where to send officers or deploy other resources. stream
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However, predictive policing also has the potential to undermine civil liberties, perpetuate structural bias, and lead to unnecessary surveillance. 11 0 obj
Ultimately, predictive policing systems and the data they process are the offspring of an unjust world. Data privacy concerns will be still there, but I believe this will improve day-to-day security operations in a positive way if used well. Opposition groups even gathered academics to speak out against the use of PredPol. However, predictive policing also has the potential to undermine civil liberties, perpetuate structural bias, and lead to unnecessary surveillance. <>
These threats indicate to me that the CPD has a more pressing issue than implementing machine learning to predict criminal propensity: they have a trust problem. 2 0 obj
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[13] Karen Sheley, “Statement on Predictive Policing in Chicago,” June 7, 2016, https://www.aclu-il.org/en/press-releases/statement-predictive-policing-chicago, accessed November 12. [3] Jeff Asher and Rob Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago,” The New York Times, June 13, 2017, https://www.nytimes.com/2017/06/13/upshot/what-an-algorithm-reveals-about-life-on-chicagos-high-risk-list.html, accessed November 12. [4] Chicago Police Department, “Special Order S09-11: Strategic Subject List (SSL) Dashboard,” July 14, 2016, http://directives.chicagopolice.org/directives/data/a7a57b85-155e9f4b-50c15-5e9f-7742e3ac8b0ab2d3.html, accessed November 12. Using machine learning will then much less resources to monitor and analyze real-time videos and interfere if needed. Episode 44 - March/April LD - "Predictive Policing is Unjust" (AKA: What - Duration: 37:33. I would suggest that those implementing predictive policing technologies think critically about the type and magnitude of crime they are trying to prevent using this technology. Their paper, “Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice,” is available on SSRN. The LAPD just said it will stop using it because of the coronavirus pandemic. [7] CPD must also figure out how to maximize the utility of the SSL algorithm. The author, Bärí A. Williams, should be commended for engaging the debate about building “intelligent” computer systems to predict crime, and for framing these developments in racial justice terms. Thanks for the interesting article! Holly, thank you very much for such an interesting essay! R��\!�;�(�f�>�os͒u����.�/m���6�kCd�Y?#W~E���Rk��9#:�
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4ɏ�$AL��O However, I also would like to bring attention to two other threats that Holly mentioned: 1) that there is limited faith in the integrity of the system and 2) that members of the “heat list” are no more or less likely to be involved in a crime. I also wanted to touch on the point of transparency which I think hits on this tension the world (especially in the USA and since 9/11) faces between privacy and (national) security. endobj
Predictive policing systems ignore community needs. 9 0 obj
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I think this could be a good tool in the toolkit if it yields responses of increased support and resources to mitigate potential crimes rather than reinforce societal expectations. Transparency is critical to restore faith in the system.”[13]. [14] Yana Kunichoff and Patrick Sier, “The Contradictions of Chicago Police’s Secretive List,” Chicago Magazine, August 21, 2017, https://www.chicagomag.com/city-life/August-2017/Chicago-Police-Strategic-Subject-List/, accessed November 12. In 2013, CPD partnered with researchers at the Illinois Institute of Technology to create an algorithm that identifies Chicagoans most at risk of being victims or perpetrators of violent crimes. In order to make algorithm less inclined to “label” innocent people, I would suggest developers alter the algorithm in the way it focuses only on people who are at risk of being victims, not on potential perpetrators. <>
Without trust, no level of machine learning insights will suffice to enable CPD to operationally and proactively reduce crime outcomes. Get to know why residents mistrust the police and figure out how to rectify that relationship. Wikipedia. Because of these issues, I wholeheartedly agree that it would be more powerful to repurpose ML to help prevent the use of excessive force or to connect people with needed resources. Methods for predicting offenders:These approaches identify individuals at risk of offending in the future. endobj
Policing has never been about public safety: its origins are rooted in social control, the denial of people's human rights, securing the U.S. borders, recapturing escaped, enslaved Africans, and upholding racist, homophobic, and transphobic laws. Maybe then, the #1 source of information will come directly from responsible neighbors, rather than an expensive machine learning algorithm with information asymmetry challenges. And while Chicago is in the vanguard of predictive policing, it is not alone; other cities like New York and Los Angeles are considering how to use big data policing to target at-risk individuals. I completely agree with the risk of using machine learning to assess resident risk profiles, as emphasized in the previous two comments. [11] “Mayor Emanuel Announces Expansion Of Smart Policing Strategy Supporting Nearly Two Years Of Consecutive Declines In Crime,” Contents 1 Introduction into data-driven policing2 2 Construction, merging and enhancement of police databases2 [2] This epidemic of violence presents a challenge to the Chicago Police Department (CPD), which must efficiently deploy human and financial resources to keep residents safe. Thanks for this article. [7] Jessica Saunders, Priscillia Hunt, and John S. Hollywood, “Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilot,” Journal of Experimental Criminology 12(3) (September 2016): 347-371. <>
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This article is more than 1 year old. [8], CPD intends to increase its reliance on machine learning in the next decade. In a statement on the use of predictive policing by CPD, a representative from the ACLU of Illinois wrote, “We are at a crisis point in Chicago regarding community and police relations. endobj
For those interested in learning more about building trust between police and communities, My90 is a start-up that amplifies voices in the community by allowing people to anonymously share feedback about their experience with law enforcement: http://www.textmy90.com/. This strikes at the heart of something that’s been concerning me with machine learning for quite some time which has to do with the objectiveness and quality of the inputs to the algorithm. By incorporating machine learning into its policing process, CPD can focus its efforts on communities and individuals that are supposedly most likely to be involved in criminal activity. The previous two comments is generated based predictive policing is unjust bfi factors including a person ’ history. Data privacy concerns will be still there, but i believe this will improve day-to-day security in... Ideally lowering crime rates and enhancing community safety mistrust in communities enforcement to potential... 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