Big Data - Citizen Perspective
Oral Presentation
Prepared by A. Garcia
Chicago Council on Global Affairs - Emerging Leaders Class 2014, 100 N. Riverside Plaza, MC 5003-1001, Chicago, IL, 60606, United States
Contact Information: tgarciaathome@aol.com; 312-821-6861
ABSTRACT
With an estimated 1,163,146 violent crimes reported in the United States in 2013, law enforcement agencies are searching for new tools to combat and prevent crime (1). The use of big data to analyze, understand, and impact issues related to public safety is perhaps one of the most promising applications of integrated data analytics to date. Law enforcement's ability to gather and analyze data has improved significantly, and it has used big data analysis in new and innovative ways to support public safety programs. Looming over law enforcement's gathering and use of data are the competing interests of public safety and privacy.
The sources of big data for public safety provide law enforcement with new tools and solutions for preventing and solving crime. Law enforcement have relied on a variety of sources to gather information for public safety programs, including 911 calls, private sector data, arrest records, crime databases, and court documents (2). However, law enforcement now have access and can effectively incorporate geospatial data from squad cars, information related to vacant and abandoned buildings, and social media (3).
The use of surveillance cameras by law enforcement has become an issue of contention. The use of red light cameras, cameras from public transportation, and shot-cameras has raised privacy concerns but U.S. Courts have ruled that the cameras do not violate a person's right to privacy if the cameras capture activity on a public way (4). Although many civil rights groups advocate placing body cameras on police officers to monitor the officer's actions, the cameras will also provide invaluable information and evidence for law enforcement to combat crime. The cameras will not only record the event in which the officer is engaged but also everything and everyone in the area of the event. Public safety organizations will have the opportunity to monitor the use of locations for crime and take steps to improve the area. As facial recognition technology improves, the recordings will one day allow law enforcement to identify individuals with outstanding arrest warrants, gang members who are outside of the area where they normally reside, and other individuals wanted in the criminal justice system.
The city of Chicago has used its collection of data to create an innovative prevention strategy that focuses on not only "hot spots" but also "hot people (5)." A study by Chicago-born sociologist and professor at Yale, Andrew Papachristos suggests that a person's "social network is a key predictor in whether an individual will become a victim of gun homicide, even more so than race, age, gender, poverty, or gang affiliation (6)." The Chicago Police Department (CPD) is using this theory to prevent crime. The CPD is using data to create social networking maps of defendants and victims to predict future behavior. This effort assists law enforcement in identifying "parties to violence," individuals who are likely to become victims or perpetrators of crime (7). The social networking theory not only considers the relationships of individuals, but also considers gang affiliation, criminal history, and other factors that would identify parties to violence (8). However, the theory does not include the individual's race or gender when mapping social networks (9). Once a party of violence has been identified, the CPD participates in intervention strategies to engage them and, hopefully, prevent them from becoming an offender or victim (10).
Integration of information technology and sharing data amongst agencies are areas in which law enforcement need improvement. Development and enhancement of integrated data systems, including systems and equipment that provide in-field access for police officers, will allow law enforcement to better use and analyze the data it gathers (11). The incompatibility of the various agencies limit the sharing of data, which could otherwise be beneficial to all.
One of the most pressing questions facing the use of big data for public safety is privacy. Big data provides a treasure trove of information for government actors. However, when viewed in the light of law enforcement, national security, and limited resources, there has to be a balance that addresses the public's safety and privacy concerns (12). Privacy and security do not have to be mutually exclusive. Law enforcement agencies should be capable of providing adequate security while guaranteeing that individual privacy will not be unreasonably infringed upon.
Government agencies store and have access to vast amounts of internal data that are typically for use by that agency only. The data may be subject to legal limitations on interagency sharing and agency rules and regulations. For example, law enforcement and public schools do not share information. The routine sharing of data between agencies raises major concerns regarding privacy, profiling, the potential for overreach, and data management in the case of security breaches.
However, limited resources and legal constraints do not have to be a hindrance to law enforcement capabilities. Through collaboration with institutions, such as the University of Chicago Crime Lab, which can receive personalized data from various city agencies, innovative public safety initiatives can be undertaken (13). These collaborative partnerships optimize the available data by linking no personalized information between agencies to help meet the challenges that are raised by residents, privacy advocates, and public safety institutions.
Two other approaches to help privacy issues: first, seeking judicial approval through standard warrants, law enforcement can help ensure that the rights of citizens are protected. Judicial oversight may also help build public trust in law enforcement initiatives. Second, gaining public trust and support through transparency and information campaigns.
Big data will provide law enforcement with new and enhanced tools to protect society. However, integrating data amongst multiple agencies and ensuring the security of the data will be hurdles that law enforcement will have to overcome. Law enforcement will also have to balance privacy concerns with public safety to ensure both are properly protected.
Footnotes:
1 Federal Bureau of Investigation, Uniform Crime Reporting (UCR) Program, http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2013/crime-in-the-u.s.-2013/violent-crime/violent-crime-topic-page/violentcrimemain_final
2 The Chicago Council on Global Affairs, "The Emerging Power of Big Data: The Chicago Experience," June 2014, http://www.thechicagocouncil.org/sites/default/files/ELBigDataCities.pdf
3 Ibid.
4 See United States v. Knotts, 460 U.S. 276, 281-282(1983); Delaware v. Prouse, 440 U.S. 648, 663 (1979) (citation omitted); See, e.g., Rodriguez v. United States, 878 F. Supp. 20, 24 (S.D.N.Y. 1995) (finding no expectation of privacy in public street); McCray v. State, 84 Md. App. 513, 519 (1990) (finding no expectation of privacy where complainant filmed walking across a public street).
5 See http://www.nbcnews.com/news/other/small-world-murder-homicides-drop-chicago-police-focus-social-networks-f2D11758025
6 Amy Athey McDonald, "Study finds social networks are key to city violence," Yale News, November 14, 2013.
7 Interview with Commander Jonathan Lewin, February 10, 2014.
8 Whet Moser, "The Small Social Networks at the Heart of Chicago Violence," Chicago Magazine, December 9, 2013; Interview with Commander Jonathan Lewin.
9 Interview with Commander Jonathan Lewin.
10 Frank Main, "Top cop 'optimistic' that visiting gang leaders' homes cuts violence," Chicago Sun-Times, February 24, 2014, http://www.suntimes.com/news/25722451-418/top-cop-optimistic-that-visiting-gang-leaders-homes-cuts-violence.html
11 Christopher S. Koper, Bruce G. Taylor, and Bruce E. Kubu, "Law enforcement needs assessment: future technologies to address the operational needs of law enforcement," January 16, 2009, http://www.policeforum.org/assets/docs/Free_Online_Documents/Technology/law%20enforcement%20technology%20needs%20assessment%202009.pdf
12 Omer Tene and Jules Polonetsky, "Privacy and Big Data: Making Ends Meet," Stanford Law Review, 66 Stan. L. Rev. Online (September 3, 2013), http://www.stanfordlawreview.org/online/privacy-and-big-data/privacy-and-big-data.
13 Interview with Roseanna Ander, executive director, University of Chicago Crime Lab, February 5, 2014.
Oral Presentation
Prepared by A. Garcia
Chicago Council on Global Affairs - Emerging Leaders Class 2014, 100 N. Riverside Plaza, MC 5003-1001, Chicago, IL, 60606, United States
Contact Information: tgarciaathome@aol.com; 312-821-6861
ABSTRACT
With an estimated 1,163,146 violent crimes reported in the United States in 2013, law enforcement agencies are searching for new tools to combat and prevent crime (1). The use of big data to analyze, understand, and impact issues related to public safety is perhaps one of the most promising applications of integrated data analytics to date. Law enforcement's ability to gather and analyze data has improved significantly, and it has used big data analysis in new and innovative ways to support public safety programs. Looming over law enforcement's gathering and use of data are the competing interests of public safety and privacy.
The sources of big data for public safety provide law enforcement with new tools and solutions for preventing and solving crime. Law enforcement have relied on a variety of sources to gather information for public safety programs, including 911 calls, private sector data, arrest records, crime databases, and court documents (2). However, law enforcement now have access and can effectively incorporate geospatial data from squad cars, information related to vacant and abandoned buildings, and social media (3).
The use of surveillance cameras by law enforcement has become an issue of contention. The use of red light cameras, cameras from public transportation, and shot-cameras has raised privacy concerns but U.S. Courts have ruled that the cameras do not violate a person's right to privacy if the cameras capture activity on a public way (4). Although many civil rights groups advocate placing body cameras on police officers to monitor the officer's actions, the cameras will also provide invaluable information and evidence for law enforcement to combat crime. The cameras will not only record the event in which the officer is engaged but also everything and everyone in the area of the event. Public safety organizations will have the opportunity to monitor the use of locations for crime and take steps to improve the area. As facial recognition technology improves, the recordings will one day allow law enforcement to identify individuals with outstanding arrest warrants, gang members who are outside of the area where they normally reside, and other individuals wanted in the criminal justice system.
The city of Chicago has used its collection of data to create an innovative prevention strategy that focuses on not only "hot spots" but also "hot people (5)." A study by Chicago-born sociologist and professor at Yale, Andrew Papachristos suggests that a person's "social network is a key predictor in whether an individual will become a victim of gun homicide, even more so than race, age, gender, poverty, or gang affiliation (6)." The Chicago Police Department (CPD) is using this theory to prevent crime. The CPD is using data to create social networking maps of defendants and victims to predict future behavior. This effort assists law enforcement in identifying "parties to violence," individuals who are likely to become victims or perpetrators of crime (7). The social networking theory not only considers the relationships of individuals, but also considers gang affiliation, criminal history, and other factors that would identify parties to violence (8). However, the theory does not include the individual's race or gender when mapping social networks (9). Once a party of violence has been identified, the CPD participates in intervention strategies to engage them and, hopefully, prevent them from becoming an offender or victim (10).
Integration of information technology and sharing data amongst agencies are areas in which law enforcement need improvement. Development and enhancement of integrated data systems, including systems and equipment that provide in-field access for police officers, will allow law enforcement to better use and analyze the data it gathers (11). The incompatibility of the various agencies limit the sharing of data, which could otherwise be beneficial to all.
One of the most pressing questions facing the use of big data for public safety is privacy. Big data provides a treasure trove of information for government actors. However, when viewed in the light of law enforcement, national security, and limited resources, there has to be a balance that addresses the public's safety and privacy concerns (12). Privacy and security do not have to be mutually exclusive. Law enforcement agencies should be capable of providing adequate security while guaranteeing that individual privacy will not be unreasonably infringed upon.
Government agencies store and have access to vast amounts of internal data that are typically for use by that agency only. The data may be subject to legal limitations on interagency sharing and agency rules and regulations. For example, law enforcement and public schools do not share information. The routine sharing of data between agencies raises major concerns regarding privacy, profiling, the potential for overreach, and data management in the case of security breaches.
However, limited resources and legal constraints do not have to be a hindrance to law enforcement capabilities. Through collaboration with institutions, such as the University of Chicago Crime Lab, which can receive personalized data from various city agencies, innovative public safety initiatives can be undertaken (13). These collaborative partnerships optimize the available data by linking no personalized information between agencies to help meet the challenges that are raised by residents, privacy advocates, and public safety institutions.
Two other approaches to help privacy issues: first, seeking judicial approval through standard warrants, law enforcement can help ensure that the rights of citizens are protected. Judicial oversight may also help build public trust in law enforcement initiatives. Second, gaining public trust and support through transparency and information campaigns.
Big data will provide law enforcement with new and enhanced tools to protect society. However, integrating data amongst multiple agencies and ensuring the security of the data will be hurdles that law enforcement will have to overcome. Law enforcement will also have to balance privacy concerns with public safety to ensure both are properly protected.
Footnotes:
1 Federal Bureau of Investigation, Uniform Crime Reporting (UCR) Program, http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2013/crime-in-the-u.s.-2013/violent-crime/violent-crime-topic-page/violentcrimemain_final
2 The Chicago Council on Global Affairs, "The Emerging Power of Big Data: The Chicago Experience," June 2014, http://www.thechicagocouncil.org/sites/default/files/ELBigDataCities.pdf
3 Ibid.
4 See United States v. Knotts, 460 U.S. 276, 281-282(1983); Delaware v. Prouse, 440 U.S. 648, 663 (1979) (citation omitted); See, e.g., Rodriguez v. United States, 878 F. Supp. 20, 24 (S.D.N.Y. 1995) (finding no expectation of privacy in public street); McCray v. State, 84 Md. App. 513, 519 (1990) (finding no expectation of privacy where complainant filmed walking across a public street).
5 See http://www.nbcnews.com/news/other/small-world-murder-homicides-drop-chicago-police-focus-social-networks-f2D11758025
6 Amy Athey McDonald, "Study finds social networks are key to city violence," Yale News, November 14, 2013.
7 Interview with Commander Jonathan Lewin, February 10, 2014.
8 Whet Moser, "The Small Social Networks at the Heart of Chicago Violence," Chicago Magazine, December 9, 2013; Interview with Commander Jonathan Lewin.
9 Interview with Commander Jonathan Lewin.
10 Frank Main, "Top cop 'optimistic' that visiting gang leaders' homes cuts violence," Chicago Sun-Times, February 24, 2014, http://www.suntimes.com/news/25722451-418/top-cop-optimistic-that-visiting-gang-leaders-homes-cuts-violence.html
11 Christopher S. Koper, Bruce G. Taylor, and Bruce E. Kubu, "Law enforcement needs assessment: future technologies to address the operational needs of law enforcement," January 16, 2009, http://www.policeforum.org/assets/docs/Free_Online_Documents/Technology/law%20enforcement%20technology%20needs%20assessment%202009.pdf
12 Omer Tene and Jules Polonetsky, "Privacy and Big Data: Making Ends Meet," Stanford Law Review, 66 Stan. L. Rev. Online (September 3, 2013), http://www.stanfordlawreview.org/online/privacy-and-big-data/privacy-and-big-data.
13 Interview with Roseanna Ander, executive director, University of Chicago Crime Lab, February 5, 2014.
