SFPD PredPol emails 2.pdf

7/27/2019 SFPD PredPol emails 2.pdf

http://slidepdf.com/reader/full/sfpd-predpol-emails-2pdf 1/51

Q PREDPOL'

From Theory to Rractical Deployment

The Science Behind PredRol

Policing crime patterns is hard.

While crime may afflict the same neighborhoods year after year, the day-to-day

fluctuations in where and when crimes occur are large. Extensive research has shown that

day-to-day crime patte rns are the result of: (1) crime generators tha t are fixed features of

the environment; (2) repeat and near-repeat victimization that leads previous victims and

their neighbors to be at greater risk of follow-on crimes; (3) the routine activity patterns ofoffenders that keep risk local; and (4) substantial random noise. Each of these processes

is well known empirically, but when put together their impact on how crime hotspots

emerge, spread and disappear is incredibly complex. It is very hard to predict where crime

will occur in the next 10-12 hours given where it occurred yesterday.

Knowledge, skills and experience can reliably direct officers to the top two or three

riskiest locations in their operational environment. It is much harder for them to Identify

and choose between locations h e r e the risk may be lower and highly variable from day

to day. If an officer chooses to go to a location typically fourth in line for crime risk, but a

crime occurred at a location fifth in line on that day, then an opportunity to disrupt crime

is missed.

THE PREDICTIVE POLICING COMPANY."

The Rremise Behind

Predictive PolicingIfone can accurately predict

where and when crimes will

occur; then law enforcement

personn'el can disrupt those

crimes before they happen.

Using high-powered mathematics and real-time crime data, PredPol evaluates yesterday's crimes in the context of all crimes occurring

over a long time horizon and wide spatial field to calculate accurate probabilities of where and when crime will occur today. Officersusing this information can make it harder for offenders to commit crimes in those locations leading to a net reduction in crime.

Predictive Rolicing Evidence from the Field

If predictive policing does not perform better than existing practice, or makes the job of he officer

on the street harder, then it is better to stick with existing practice.

Controlled experimental trials of PredPol were conduc ted with the Kent Police, UK, and Los Angeles Police Departmen t, USA, with the

goal of assessing what (if any) advantages stem from the use of predictive policing. In each experiment, PredPol was tested head-to

head against crime analysts using existing practice. PredPol predic ts crime In 500' x 500' (150m x 150m) boxes with the number of

boxes deployed in a given shift calibrated to the policing resources available. The experimental deployments involved placement of 20prediction boxes per shift in designated policing divisions. Analysts were tasked with deploying the same number of prediction boxes

per shift using all of the tools at their disposal. In Kent West Division, the analyst focused on intelligence-led policing practices, while Los

Angeles Foothill Division focused on crime hot spot mapping. In the absence of directed police patrol effects, PredPol predicts between

1.6-2.5 more crime than existing practice. Increased opportuniti es to impact crime are therefore of a similar magnitude using PredPol.

831.311.45501 [email protected] 1www.predpol.com PREDICT CRIME IN REAL TIME®



Q PREDPOL' THE PREDICTIVE POLICING C O M P A N Y . ~

Accurate prediction leads not only to unique opportunities to disrupt crime, but also to serve the public at the scale at which crime

occurs. In live deployments In both Kent and Los Angeles, officers were d irected to use available time between calls or appointments to

police what they see. Kent police officers capitalized on these oppor tunities:

06105113 Whilst potro!fing PredPo/ Zone 8 Harmer Street, Gravesend, Neighborhood officers attended a call to a suspicious mole

seen rooking into vehicfes. This male was seen to then break into a vehicle and due to the close proximity the officers they were

quickly on scene and detained the mole after a short foot chose. The male, a prolific offender, hod 2 Sot Navs in his pocket stolen

from 2 vehicles in Royal Pier rood. Ifofficers hod not already been in the zone they would not have been in oposition to catch the

offender as he committed the crime.

04106113 PredPof duty in Gravesend with 4 officers in 2 managed ro visit all PredPo/ boxes at feast once during the shrft with

different teams to show a high and varied presence, consistingof oot and mobile patrol. While checking vehicles they noticed 2

SAT NAV systems and money in the way of change on display, traced the registered owners of he vehicfes and gave them advice

over the phone, which was much appreciated.

02105113 From a local resident who has lived in the west side ofMoidstone for manyyears: "great to see police around here again

you hove really made a big difference in cleaning up this port of own".

Disrupting crime during each and every shift can lead to significant crime declines over time. In Kent, the first six months of PredPol

deployment produced a steady decline In violent crime of -6%. In lo s Angeles, the first six months of deployment saw a -12% decline In

property crimes overall with a -25% decline in burglary alon.e.

The Limits of Predictive Policing

PredPo/ is about predicting where and when crime will occur; not who will commit a crime.

PredPol is not criminal profiling. It does not use any information about individuals or populations and their characteristics. The patterns

inherent In the crimes themselves provide ample information to predict where and when crimes will occur In the future.

Predictive policing disrupts the short-term, situa tional causes of crime. lt does not solve criminality, or the propensity for individuals

to commit crime. Predictive policing Is therefore not a replacement fo r policy and community engagement strategies needed to steer

people clear of criminal careers in the first place.

Key Contacts

PredPol- The Predictive Policing CompanyDr. P. jeffrey Brantingham

je/[email protected]

LosAngeles Police Department

Captain Sean Malinowski

sean.ma/[email protected]

Kent PoliceDetective Chief Superi ntendent on Sutton

[email protected]

Mr. Mark Johnson, Head of Analysis

[email protected]

831.331.4550 [email protected] Iwww.predpotrom PREDICT CRIME IN REAL TlMf®

@ 2013 PredPol, Inc.All dghls reserved. No part of this publication desui bed herein may be reproduced, stored in a retrieval system, used in aspreadsheet, or transmitted

In any form or by means elettronlc, mechanical, photocopying, recording. or otherwise without the permission of PredPol,ln(,



From:

To:

Date:

Subject:

Donnie Fowler <[email protected]>

[email protected], [email protected], [email protected]

Friday, September 06, 2013 10: 12AM

Completing the Predictive Policing Deployment

Chief Suhr, Susan, & Rod -

Page I of2

Happy September to you. I write to let you see the SFPD predictive policing system as it willrun when you are ready to deploy. It's one thing when I see deployments in another city andsomething else entirely when I see predictions where I live here in S. F.

You can find it with the simple log-in name and password below:

* once you log in, click ondistrict

red box at the top right and select the whole city or any

Per our most recent conversation, we were waiting for the Oracle work to finalize beforefinishing our integration with you on general property crimes and on the first-in-the-r;Jationrollout of gun violence predictions·(along with Seattle and Atlanta). I f my memory is correct, youthought September would be the likely time.

In the last few months, we have had tremendous success with deployments from Alhambra, CA,to Norcross, GA, to Kent, England. You will see some of our work in the attached white paperson results and on gun violence. There are also a few news stories below my signature.

All the best,Donnie

DONNIE FOWLER Director of Business Development

. . th Street,. . ISan Francisco, CA 94114

C : 4 1 · · · ~PREDPOL.COM

The Predictive Policing Company

In the News ...Fox News· Atlanta, August 2013 ("On the first day, they apprehended a suspect in the middle of committing aburglary.")http://www.myfoxatlanta.com/story/23177698/computer-tries-to-predict

The Economist, July 2013 ("easier to foresee wrongdoing and spot likely wrongdoers")http://www.economist.com/news/briefinq/21582042-it-gettinq-easier-foresee-wrongdoinq-and-spot-likely-

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wrongdoers-dent-even-think-about-it

NBC News- Los Angeles, January 2013 ("a cliff-like drop when predictive policing began")http://www.nbclosangeles.com/news/locai/LAPD-Chief-Charlie-Beck-Predictive-Policinq-Forecasts-Crime-185970452.html

Current TV with Santa Cruz Crime Analyst & Fmr. Michigan Gov. Jennifer Granholm, January 2013("Science fiction has become science fact.")https://current.box.com/s/c6bxouhsdugp3ifngz4s

San Francisco Chronicle, August 2012 ("a new web-bases system to monitor real· time crime data and predictwhen the next violence will occur")http://www.sfgate.com/bayarea/article/SF-mayor-announces-antiviolence-strategy-3770653.php

CBS Evening News - National, March 2012 ("It's not how many people you catch, it's how many crimes youprevent")

h t t p : / / w w w . c b s n e w s . c o m / v i d e o l w a t c h / ? i d ~ 7 404996n

Attachments:

White Paper Predicting Gun Violence (2013

July).pdf

White Paper Science and Testing of Predictive

Policing (2013).pdf

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From: Suzy Loftus <[email protected]>

To: Donnie Fowler <[email protected]>, "[email protected]" <[email protected]>

Date: Thursday, May 09, 2013 01:42PM

Subject: RE: Predictive Policing & Gun Violence

Thanks, Donnie.

Chief-- just let me know how you want to proceed. This is incredibly exciting and I think therewould be significant public Interest in the department utilizing this technology. Let me know howI can be helpful.

Suzy

Date: Thu, 9 May 2013 11:48:17-0700

Subject: Predictive Policing & Gun ViolenceFrom: [email protected]: [email protected]: [email protected]

Chief Suhr-

Thanks again for your decision to deploy predict'ive policing in San Francisco. We are just aboutready to roll, so I write to give you an update specifically on the new, first-In-the-nation gunviolence prediction technology that you will soon have as part of the overall PredPol tool. You

probably know that SFPD will be one of the first three cities, with Atlanta and Detroit. to usepredictive analytics to predict gun violence.

We hope you and the Mayor will agree. please. to join the announcement with those two cities onMay 23 or 24. This could be as significant as the kind of press conference the Seattle mayor andchief had a couple of months ago (see below) or as simple as a joint press statement that SanFrancisco will once again show up as a leader on tech innovation.

With Shotspotter locating gunshots after they happen, PredPol will be able to predict where someof this violence might occur before It happens. We are glad to be working on a partnership with

them to make both of these tactics better. And we are glad to be working with both Susan Giffinand Rod Castillo in your office to implement things.

Please do not hesitate to contact me with any suggestions or questions.

All the best,

Donnie FowlerSan Franciscopredpol. com415- cell

attachment: gun violence white paper

Predictive Policing in the News ...

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Page 2 of3

Seattle Times, February 2013 ("will allow us to be proactive rather than reactive")

http:i/bloqs.seattletimes.com/today/2013/02/seattle-police-turn-to-computer-software-to-fiqht-crime/

KPLU-Seattle (NPR), February 2013 ("will help them allocate patrols more effectively")

http://www.kplu.org/posUseattle-tacoma-rollinq-out-new-predictive-policing-software

NBC News -Los Angeles, January 2013 ("a cliff-like drop when predictive policing began")

http://www.nbclosangeles.com/news/locai/LAPD-Chief-Charlie-Beck-Predictive-Policing-Forecasts-Crime-185970452.html

Current TV with Santa Cruz Crime Analyst, January 2013 ("science fiction has become science fact")

https://current.liox.com/s/c6bxouhsdugp3ifngz4s [with former Michigan Governor Jennifer Granholm]

On Fri, May 18, 2012 at 3:59PM, Donnie Fowler <[email protected]> wrote:

Chief Suhr-

Suzy Loftus was good enough to reconnect us, so I'm following up with some details

on the predictive policing technology she mentioned to you. A summary is attachedto this email that you can share with your team. We will send along some additional

technology details shortly and look forward to talking.

We are moving from successful field experiments to full deployment this summer. It

would be great to see San Francisco (where I also live) take a front-row seat in the

state and nationally on this.

All the best,Donnie Fowler~ c e l l

Predictive Policing

The Problem: Police departments nationwide are facing budget freezes and deep cuts, requiringthem to manage their resources more effectively while still responding to public demand for crimeprevention and reduction.

The Solution: Like forecasting the weather, PredPol's patent-pending technology generatespredictions about which areas and windows of time are at highest risk for future crimes. In

http: //sfmai 104.sfgov org/mail/gsuhr.nsf /(%24 nbox)/3DE64C I F76A2E6F38E39129ED8A9 .. 9/23/13



Page 3 of 3

contrast to analysis that simply maps past crime data, this technology applies advancedmathematics and computer learning that has resulted in predictions twice as accurate as thosemade by experienced crime analysts and veteran police using only their own knowledge andexperience.

---"------ Forwarded message ----------

From: Suzy Loftus <[email protected]>Date: Fri, May 18, 2012 at 3:28PM

Subject: Re: Predictive Policing and all things good law enforcementTo: Donnie Fowler <dfowler@qmail .com>Cc: Debbie Mesloh <[email protected]>, Caleb Baskin<[email protected]>

Hey guys,

Good to meet both of you today - I am fascinated by what is possible here. I calledChief Suhr about it and told him that I met with you guys and think if he likes it, it

could be great for sf. He would like you two to send him an email and he'll get histechnology person lined up to do an initial vetting on how it would work and then .he'll follow up. His email is [email protected].

Let me know how It goes.

Best,

Suzy

Donnie Fowler4 1 · - [email protected]

http://sfmai104.sfgov .org/mail/gsuhr.nsf/(%24Inbox)/3DE64C 1F76A2E6F38E3 9129ED8A9... 9/23/13



From:

To:

Cc:

Date:

Subject:

Donnie Fowler <[email protected] >

greg.suhr@sfgov org

Suzy Loftus <[email protected]>

Thursday, May 09, 2013 11:47AM

Predictive Policing & Gun Violence

Chief Suhr-

Page I of3

Thanks again for your decision to deploy predictive policing in San Francisco. We are just about

ready to roll, so I write to give you an update specifically on the new, first-in-the-nation gunviolence prediction technology that you will soon have as part of the overall PredPol tool. Youprobably know that SFPD will be one of the first three cities. with Atlanta and Detroit. to usepredictive analytics to predict gun violence.

We hope you and the Mayor will agree. please. to join the announcement wi th those two cities on

May 23 or 24. This could be as significant as the kind of press conference the Seattle mayor andchief had a couple of months ago (see below) or as simple as a joint press statement that SanFrancisco will once again show up as a leader on tech innovation.

With Shotspotte r locating gunshots after they happen, PredPol will be able to predict where someof this violence might occur before it happens. We are glad to be working on a partnership with

them to make both of these tactics better. And we a ~ : e glad to be working with both Susan Giffinand Rod Castillo in your office to implement things.


All the best,Donnie Fowler

ell

attachment: gun violence white paper

Predictive Pol icing in the News ...

Seattle Times, February 2013 ("will allow us to be proactive rather than reactive")

http://blogs. seattletimes. com/today/2013/02/seattle-police-turn-to-computer -software-to-fight -crime/

KPLU-Seattle (NPR), February 2013 ("will help them allocate patrols more effectively")

http://www. kplu .org/posUseattle-tacoma-rolling-out -new-predictive-policing-software

NBC News - Los Angeles, January 2013 ("a cliff-like drop when predictive policing began")

http://sfmail04.sfgov org/mail/gsuhr.nsf/(%24Inbox)/4 FBE67F 52A40561E89 A264 B89E5 F... 9/23/13



Page 2 of3

http://www. nbclosanqeles. com/news/local/LAPD-Ch ief -Charlie-Beck -Predictive-Policinq-F orecasts-Crime-185970452.html

Current TV with Santa Cruz Crime Analyst, January 2013 ("science fiction has become science fact")

https://current.box.com/s/c6bxouhsduqp3ifngz4s (with former Michigan Governor Jennifer Granholm]

On Fri, May 18, 2012 at 3:59PM, Donnie Fowler <[email protected]> wrote:

Chief Suhr-

Suzy Loftus was good enough to reconnect us, so I'm following up with some details on the

predictive policing technology she mentioned to you. A summary is attached to this email that

you can share with your team. We will send along some additional technology details shortlyand look forward to talking.

We are moving from successful field experiments to full deployment this summer. I t would begreat to see San· Francisco (where I also live) take a front-row seat in the state and nationallyon this.

All the best,Donnie Fowler415 cell

Predictive Policing

The Problem: Police departments nationwide are facing budget freezes and deep

cuts, requiring them to manage their resources more effectively while stillresponding to public demand for crime prevention and reduction.

The Solution: Like forecasting the weather, PredPol's patent-pending technologygenerates predictions about which areas and windows of time are at highest riskfor future crimes. In contrast to analysis that simply maps past crime data, thistechnology applies advanced mathematics and computer learning that hasresulted in predictions twice as accurate as those made by experienced crimeanalysts and veteran police using only their own knowledge and experience.

---------- Forwarded message ----------

From: Suzy Loftus <[email protected]>Date: Fri, May 18, 2012 at 3:28PM

Subject: Re: Predictive Policing and all things good law enforcement

To: Donnie Fowler <[email protected]>

Cc: Debbie Mesloh <[email protected]>, Caleb Baskin <[email protected]>

Hey guys,

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Page 3 of3

Good to meet both of you today- I am fascinated by what is possible here. I called Chief Suhrabout it and told him that I met with you guys and think if he likes it, it could be great for sf.He would like you two to send him an email and he'll get his technology person lined up to doan initial vetting on how it would work and then he'll follow up. His email is

Greq.suhr@sfgov .org.

Let me know how it goes.

Best,

Suzy

Donnie Fowler415 [email protected]

Attachments:

Predicting Gun Violence White Paper (2013 April).pdf

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From: Susan Giffin/SFPD/SFGOV

To: Greg Suhr/SFPD/SFGOV@SFGOV, [email protected]

Date: Monday, May 13, 2013 12: 14PM

Subject: Fw: Predicting Gun Violence in SF, ATL, and Detroit May 23-24

History: <··This message has been replied to and forwarded.

Chief-

I corresponded with PredPol and suggested that we not participate in this announcement at thistime (prior to message below). While we will be rolling ou t PredPol and the gun violence module,I would like to wait until we are fully implemented before any announcements. I can elaboratefurther in person if you would like. Thanks.Susan

Susan GiffinChief Information Officer, SFPD(415) 553-1481 (Angel Yee)

------Forwarded by Susan Giffin/SFPD/SFGOV on 05/13/13 12:13 ----

From: Greg Suhr/SFPD/SFGOVTo: "Susan Giffin" <[email protected]>, "Lyn Tomioka" <[email protected]>Date: 05/09/13 18:05

Subject: Fw: Predicting Gun Violence In SF, ATL, and Detroit May 23-24

FYI

From: "Winnicker, Tony" [[email protected]]Sent: 05/10/2013 12:50 AM GMTTo: Christine Falvey; Jason ElliottCc: Greg Suhr

Subject: FW: Predicting Gun Violence in SF, ATL, and Detroit May 23-24

See below- Chief- are we working to deploy this technology? See below.

Christine, Jason- they would like us to join/consider an announcement with ATL and Detroit.

Donnie Fowler spoke to the Mayor about this following the Sandy Hook Promise gun event last

month at Bill Graham.

From: Donnie Fowler [mailto:[email protected]]Sent: Thursday, May 09, 2013 5:42 PM

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Page 2 of 4

To: Winnicker, TonySubject: Predicting Gun Violence in SF, ATL, and Detroit May 23-24

Tony-

Good to talk with you this afternoon about San Francisco's decision to be the first to deploy

technology that predicts gun violence along with Atlanta and Detroit. We at PredPol, based here in the

Bay Area, have had a great working relationship with ChiefSuhr and SFPD's CIO Susan Giffin as

they integrate predictive analytics into their overall technology plan. We are also partnering with the

Sandy Hook Promise group.

As I mentioned, Atlanta's Mayor and Chief want to announce that they intend to implement this gun

violence methodology on May 23 or 24th. We hope the Mayor and Chief will agree. please, to join theannouncement with the other two cities on May 23 or 24. This could be as significant as the kind of pressconference the Seattle mayor and chief had a couple of months ago (see below) or as simple as a joint pressstatement that San Francisco will once again show up as a leader on tech innovation.


All the best,Donnie FowlerSan Francisco

c I

attachment & copied below: gun violence summary points

Predictive Policing in the News ...

Seattlq Times, February 2013 ("will allow us to be proactive rather than reactive")http :1/blogs. seattleti mes. com/tod a y/2 0 13/02/seattle-pol ce-turn -to-com puler-software-to-fightcrime/

KPLU-Seattle (NPR), February 2013 ("will help them allocate patrols more effectively")h ip:I www. kplu.org/pos Useattle-tacoma-rolling-out new-pred ictive-po !icing-software

NBC News- Los Angeles, January 2013 ("a cliff-like drop when predictive policing began")http://www.nbclosangeles.com/news/locai/LAPD-Chief-Charlie-Beck-Predictive-PolicingForecasts-Crime-185970452.html

Current TV with Santa Cruz Crime Analyst, January 2013 ("science fiction has become

science fact")https://current.box.com/s/c6bxouhsdugp3ifngz4s [with former Michigan Governor JenniferGranholm]

DRAFT[May8, 2013]

PREDICTING GUN VIOLENCE

Cities Take Lead as First in the Nation to Deploy New Technology to Deter Gun Cl'ime

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The Challenge. In light of recent gun violence across the country, including schoolshootings, and as police departments across the nation face tighter budgets and scarcerresources, reducing violence and gun related crime remains a significant challenge.

The Leaders. Atlanta, Detroit, and San Francisco are taking the lead as the first cities topredict and deter gun violence by deploying a new application of PredPol's general crimeprediction methodology.

Predictive Policing. While no one strategy serves as a silver bullet, predictive policinggives officers a significantly better idea of when and where to be so that they can deter crimegenerally and gun violence in particular, sometimes even catching criminals in the act.

Precursor Crimes. PredPol's unique gun violence prediction methodology recognizes that

past homicides are not necessarily the best predictors of future gun violence. In fact, theoccurrence of serious violent crimes like weapons violations, assault, and battery provide asmuch, or more, information on where and when future homicides are most likely to occur.

Origins & Results of Predictive Policing. Predictive policing was first developed and

deployed in Los Angeles and Santa Cruz, California. Only six months after launch, those twocities enjoyed declines ranging from -12% to -25% in burglaries, car thefts, and thefts frommotor vehicles compared to the same periodjn the previous year.

Field Tested. PredPol's general crime prediction technology has been extensively evaluatedusing historical crime data and controlled field trials with multiple law enforcement agenciesover several years. Controlled trials show that PredPol predicts more than two-times as muchcrime as a veteran police and crime analysts. To be clear, though, PredPol is not a

replacement for veteran officers and crime analysts.

Modeled Using Real Crime Data. PredPol has also extensively modeled its new gunviolence methodology, predicting a greater number of gun homicides compared withalternative approaches, including traditional hotspot maps. In a test of public crime data outof Chicago, PredPol successfully predicted so% of gun homicides by flagging only 10.3% of

that city-- 66% more than hotspot mapping would predict.

Science for Patrol Officers. Developments in mathematical and statistical modeling, highperformance cloud computing, and GPS-enabled mobile devices now make it possible todeliver real-time crime forecasts on simple maps to patrol officers.

Not Crime Mapping. Without predictive analytics, police end up chasing yesterday's crimeby relying only on intuition and mapping of past crime data. As LAPD's Captain SeanMalinowski has noted, "We look at these maps and they're as accurate as we can get them.But I'm looking at a map from last week and the whole assumption is that next week is likelast week." Traditional mapping tools are calibrated less frequently, rely more on humans torecognize patterns, and allocate resources based on past crimes rather than predicted futureoffenses.

Timing. Although the actual deployment date for Atlanta, Detroit, and San Francisco differ,

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these cities have smartly added a new tool in the expanding national efforts to reduce gun

violence.

(See attached file: Gun Violence Announcement Summary Points PredPol (2013-05-0B).docx)

Attachments:

Gun Violence Announcement Summary Points PredPol (2013-05-0B).docx

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From: Susan Giffin/SFPD/SFGOV

To: Suzy Loftus <[email protected]>

Cc: "[email protected]" <[email protected]>, Rodrigo Castillo/SFPD/SFGOV@SFGOV

Date:

Subject:

Tuesday, May 28, 2013 !0:09AM

Re: Article about predictive policing

Hi Commissioner Loftus. Thank you for the article -good information. We have already implemented a pilotversion of this software. We can actually see our hot spots (our IT group can see them). However, we still havework to do to integrate the PredPol software and test it fully and we need Oracle for that. The hold up has beenthat we had to stop work with Oracle in order to renew our contract - and the city's contract renewal has takenover 6 months.

Short answer is I don't have a date yet and it is not likely to be before summer (which is upon us.) I will let youknow as soon as we get this into production. Thanks as always for your support.Susan

Susan GiffinChief Information Officer, SFPD(415) 553-1481 (Angel Yee)

From· Suzy Loftus <[email protected]>

To: "[email protected]" <[email protected]>, "[email protected]" <[email protected]>

Date: 05/28113 09:37

Subject: Article about predictive policing

Chief Suhr and Director Giffin,

I found the attached article in the Santa Clara University magazine-- it describes the methodology

and the team that built the algorithm behind predictive policing. They also reference a number of

other jurisdictions that are using the technology and infusing other data to achieve different goals. It

is very exciting. Please keep me posted on our progress rolling this out -- is the plan still to use the

technology to predict and deploy patrols to suppress gun violence? Are you going to deploy it

before the summer when kids are out?

I'm sure it is still in the early stages, but just wanted to get an update. Thanks, in advance.

Suzy

Attachments:

Article on Predictive Policing SCU Magazine.pdf

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From:

To :

Date:

Donnie Fowler <[email protected] >


Thursday, July 25, 2013 07:23AM

Subject: The Economist: "Predictive Policing -- Don't Even Think About It"

The Economist

Ju l 20th 20131From the print edition

Predictive Policing

Don't Even Think About It

It is getting easier to foresee wrongdoing and spot likely wrongdoers

http://www.economist. com/news/briefing/2158 2042-it -getting-easier-foresee-wrongdoing-and-spot likelywrongdoers-doni-even-think-about-it

Page I of3

THE meanest streets of Kent [England] are to be found in little pink boxes. Or at least they are if you look at themthrough the crime-prediction software produced by an American company called PredPol. Places in the countyeasl of London where a crime is likely on a given day show up on PredPol's maps highlighted by pink squares 150metres on a side. The predictions can be eerily good, according to M.ark Johnson, a police analyst: "In the first boxI visited we found a carving knife just lying in the road."

Pre.dPol is one of a range of tools using better data, more finely crunched, to predict crime. They seem to promisebetter law-enforcement. But they also bring worries about privacy, and of justice systems run by machines notpeople.

Criminal offences, like infectious disease, form patterns in time and space. A burglary in a placid neighbourhoodrepresents a heightened risk to surrounding properties; the threat shrinks swiftly if no further offences take place.These patterns have spawned a handful of predictive products which seem to offer real insight. During a four

month trial in Kent, 8.5% of all street crime occurred within PredPol's pink boxes, with plenty more next door tothem; predictions from police analysts scored only 5%. An earlier trial in Los Angeles saw the machine score 6%

compared with human analysts' 3%.

Intelligent policing can convert these modest gains into significant reductions in crime. Cops working withprepictive systems respond to call-outs as usual, but when they are free they return to the spots which thecomputer suggests. Officers may talk to locals or report problems, like broken lights or unsecured properties, thatcould encourage crime. Within six months of introducing predictive techniques in the Foothill area of Los Angeles,

in late 2011, property crimes had fallen 12% compared with the previous year; in neighbouring districts they rose0.5% (see chart). Police in Trafford, a suburb of Manchester in north-west England, say relatively simple and

sometimes cost-free techniques, including routing police driving instructors through high-risk areas, helped themcut burglaries 26 .6% in the year to May 2011, compared with a decline of 9.8% in the rest of the city.

For now, the predictive approach works best against burglary and thefts of vehicles or their contents. These

common crimes provide plenty of historical data to chew on. But adding extra types of information, such as detailsof road networks, can fine-tune forecasts further. Offenders like places where vulnerable targets are simple to spot,access is easy and getaways speedy, says Shane Johnson, a criminologist at University College London. Systemsdevised by IBM, a technology firm, watch how big local events, proximity to payday and the weather affect thefrequency and location of lawbreaking. "Muggers don't like getting wet," says Ron Fellows, IBM's expert. Jeff

Brantingham of PredPol thinks that finding speedy ways to ingest crime reports is more important than adding datasets. Timelier updates would allow PredPol to whirr out crime predictions constantly, rather than once per shift . Mr

Fellows enthuses about sensors that detect gunshots (already installed in several American cities) and smartCCTV cameras that recognise when those in their gaze are acting suspiciously. He promises squad cars directedby computers, not just control centres, which could continually calculate the most useful patrol routes.

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Minority report

Predicting and forestalling crime does not solve its root causes. Positioning police in hotspots discouragesopportunistic wrongdoing, but may encourage other criminals to move to less likely areas. And while datacrunching may make it easier to identify high-risk offenders-about half of American states use some form of

statistical analysis to decide when to parole prisoners-there is little that it can do to change their motivation.

Misuse and overuse of data can amplify biases. It matters, for example, whether software crunches reports of

crimes or arrests; if the latter, police activity risks creating a vicious circle. And report-based systems may favourrich neighbourhoods which turn to the police more readily rather than poor ones where crime is rife. Crimes suchas burglary and car theft are more consistently reported than drug dealing or gang-related violence.

But mathematical models might make policing more equitable by curbing prejudice. A suspicious individual'spresence in a "high-crime area" is among the criteria American police may use to determine whether a search isacceptable: a more rigorous definition of those locations will stop that justification being abused. Detailed analysisof a convict's personal history may be a fairer reason to refuse parole than similarity to a stereotype.

Technology may also sharpen debates about what people want from their justice systems, and what costs they are

willing to accept. For example, software developed by Richard Berk, an American statistician, which is creditedwith helping to cut recidivism among paroled prisoners in Philadelphia, requires the authorities to define in advancetheir willingness to risk being overly tough on low-risk offenders or to under-supervise nasty ones.

This sort of transparency about what goes on in predictive systems, and what their assumptions are, may also be apartial solution to worries voiced by Andrew Ferguson, a law professor in Washington, DC. Mr Ferguson fears thatjudges and juries could come to place too much credence in the accuracy of crime prediction tools, jeopardisingjustice. If transparency is a good counter to this, it will be important to preserve it as prediction becomes a biggerbusiness and gets further from its academic roots. ·

It is as prediction moves from places to people that it becomes most vexed. Police attending domesticdisturbances in Los Angeles have tried out a checklist, derived from much data-crunching, to determine whetherthe incident presages violence. Mr Berk is working with authorities in Maryland to predict which of the familiesknown to social services are likely to inflict the worst abuses on their children. Federal officials aim to forecastpotential health and safety infringements. America's Department of Homeland Security is seeking to perfect

software which scans crowds or airport queues to detect nervous behaviour such as fidgeting, shallow breathingand signs of a swift heartbeat.

So far, predictions have mostly been made about people who have already had contact with the justice system

such as convicted criminals. The growth of social media provides a lot of crunchable data on everyone else. Firmsthat once specialised in helping executives measure how web users feel about their brands now supply productsthat warn police when civil unrest approaches, and help them closely follow crises. Cops in Cillifornia admit totrawling social networks for early warnings of wild parties. ECM Universe, an American firm, offers software thatcrawls sites "rife with extremism" to identify people who deserve closer attention.

The legal limits on using social media to fish out likely wrongdoers, or create files on them, are contested. Mostlaws governing police investigations pre-date social networking, and some forces assert that all information postedto public forums is fair game. But Jamie Bartlett of Demos, a British think-tank, says citizens and police forcesneed clearer guidance about how to map physical-world privacy rights onto online spaces. He thinks gathering

information about how someone behaves on social sites ought to require the same clearance needed to monitorthem doggedly in public places. Officers who register anonymously or pseudonymously to read content, or sendweb crawlers to trawl sites against their owner's wishes, would require yet more supervision.

Identifying true villains among the oddballs and loudmouths found by social-media searches is tricky. Most policeefforts are embryonic. Evgeny Morozov, an academic and technology writer, thinks the privacy-conscious havemore to fear from crime detection algorithms cooked up by social networks themselves. Some of those firmsalready alert investigators when they suspect users of soliciting minors. Unlike the cops they employ clever coderswho can process private messages and other data that police may access only with a court order.

These projects make life difficult for many criminals. But smart ones use the internet to make predictions of their

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Page 3 of 3

own. Nearly 80% of previously arrested burglars surveyed in 2011 by Friedland, a security firm, said informationdrawn from social media helps thieves plan coups. Status updates and photographs generate handy lists of

tempting properties with absent owners. It does not take a crystal ball to work out what comes next.

From the print edition: Briefing


331 Soquel Ave. Ste. 100Santa Cruz, CA 95062

15

PREDPOLCOM


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Pagel of3

From: Donnie Fowler <[email protected]>To: Donnie Fowler <[email protected]>

Date: Thursday, July 25, 2013 07:22AM

Subject: Predicting Gun Violence: PredPol Deploys First-Of-Its-Kind Technology

First-Of-Its-Kind Technology Predicts Gun

Violence,

Providing Another Answer to Gun Crime

http://www predpol.com /gun-violence I

also see attached white paper on gun violence predictions

Santa Cruz I Silicon Valley, California - - PredPol, the Predictive Policing Company, hasdeveloped and is deploying first-of-its-kind technology to help police predict and deter

gun violence. · ·

"We are pleased to be working with innovative leaders in our partner cities," said Dr.

George Mohler, PredPol co-founder and professor of mathematics and computerscience at Santa Clara University. "While no single strategy can end gun violence,predictive policing gives officers a significantly better idea of when and where to be so

that they can deter crime generally, and gun violence in particular. I f we can prevent

just one gun crime, that will mean one less neighbor, friend, or family member whobecomes a victim."

PredPol's unique gun violence prediction methodology leverages existing crime data that

every city already has, advanced mathematics developed over more than six years,computer learning, cloud computing, and the indispensable experience of veteran

police. The crime data is analyzed through a sophisticated algorithm that applies provencriminal theories about crime in general and gun violence in particular. The results aremore accurate and more actionable recommendations for when and where gun violenceis most likely to occur, thus allowing police to show up before crime happens.

One key element of the gun violence methodology uses so-called precursor crimes to

best determine where and when future violence will happen. Specifically, and perhaps

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Page 2 of3

surprisingly, past homicides are not necessarily the best predictors of future homicides.The occurrence of incidents like weapons violations, assaults, and batteries provide asmuch or more information about where and when future homicides are most likely to

occur. In a manner similar to 'broken-windows' policing, targeting these precursorcrimes can have a significant impact on gun homicide and ultimately on crime reduction.

PredPol has extensively modeled this new approach to deterring gun violence, predictinga greater number of gun homicides compared with existing approaches, includingtraditional hotspot maps. PredPol successfully outperforms current best practices by66%.

This corresponds with even stronger performance that police agencies have seen withPredPol's broader technology for predicting and preventing other violent crimes andproperty offenses. In deployments to patrol officers in cities like Los Angeles and Kent,England, PredPol's predictions not only· reduced crime but were 100% more accuratethan existing best practices - predicting double the number of crimes as current crimemapping and hotspot analysis.

PredPol has already deployed its broad crime prediction tool for less violent crimes andfor property offenses in cities like Los Angeles and Santa Cruz in California, SouthCarolina's capital city of Columbia, Seattle and Tacoma in Washington, and in Kent,England. The gun violence prediction technology is part of this broader predictivepolicing technology package.

"We understand the challenges faced by city leaders and law enforcement and createdthis technology with police to help them do more with less," said Dr. Jeff

Brantingham, co-founder of PredPol and a criminology expert at UCLA. "Affordable,easy to use technologies allow police who have tight budgets and limited hiring ability tobetter direct the patrol resources they have."

Without predictive analytics, police are forced to chase yesterday's crime by relying onsimple mapping of past crime data. I t would be like forecasting the weather using only

historical weather patterns, but ignoring weather radar. Traditional crime mapping toolsare calibrated less frequently, rely more on humans to recognize patterns, and allocateresources based on past crimes rather than predicted future offenses. PredPol does not

replace the insights of veteran officers and crime analysts, but delivers an easy-to-useenhancement that lets police do more with their current resources.

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Page 3 of3

About PredPol

A secure, cloud-based software-as-a-service, PredPol's tool was developed by a team of

PhD mathematicians, criminologists, and social scientists at UCLA, Santa ClaraUniversity, and UC Irvine in close collaboration with crime analysts and line level officersat the Los Angeles and Santa Cruz Police Departments. Just six months after launch,those first two cities saw crime reductions of 12% to 25% in burglaries and auto theftscompared to the previous year.

After successful initial deployments in 2011 in Los Angeles and Santa Cruz, PredPol hasdeployed its groundbreaking technology in dozens of cities around the United States as

well as the United Kingdom. PredPol's core technology has grown from success withproperty crimes to include prediction of drug crime, gang crime, anti-social behavior,and now .gun violence.

For more information please visit < http://www.predpol.com/gun-violence > and seethe attached white paper.



PREDPOL.COM


Attachments:


July).pdf55 Map with Predictive Boxes.JPG

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From:

To:

Date:

Subject:



Friday, July 26, 2013 02:31PM

NPR: Predicting Gun Violence ("All Things Considered," Friday, July 26)

Can Software That Predicts Crime Pass Constitutional Muster?by MARTIN KASTE, NATIONAL PUBLIC RADIO

"All Things Considered," Friday, July 26, 2013

Page I of 4

It may be that PredPol is a constitutional basis for stopping someone. Some might consider it more ol

police officer's judgment- less prone to racism or other kinds ofprofiling, for example.

http://www.n pr.orq/20 13/07/2 6/20583 567 4I can-software- that-predicts-crime-pass-constitul

Typically, police arrive at the scene of a crime after it occurs. But rather than send cops to yesterday's

crime, a new trend in law enforcement is using computers to predict where tomorrow's crimes will be -

and then try to head them off.

The software uses past statistics to project where crime is moving. Police in Los Angeles say it's worked

well in predicting property crimes there. Now Seattle is about to expand it for use in predicting gun

violence.

It all started as a research project. Jeff Brantingham, an anthropologist at UCLA, wanted to see if

computers could model future crime the same way they model earthquake aftershocks. Turns out theycan.

"It predicts sort of twice as much crime as any other existing system, even going head-to-head with a

.crime analyst," Brantingham says.

Checking The Boxes

Older systems, like the famous CompStat in New York, show where crime has been. This system looks

forward.

"The model will actually predict other locations, that effectively say, even though there was a crime

somewhere else in your environment, the risk is still greatest in this location today for the next 10 hours 01

the next 12 hours," Brantingham explains.

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Seattle police officer Philip Monzon patrols

an area where the department's predictive

policing software has indicated car thefts

are likely to occur.

Marlin KasteiNPR

commit a future crime, just where it is likely to happen.

Page 2 of 4

In Seattle, police Sgt. Christi Robbin zooms in on a map of the city. Earlier this year, Seattle started using

PredPol to predict property crimes. It's now the first place to try predicting gun violence with the software.

"These red boxes [on the map] are predictions of where the next crimes are likely to occur," Robbin

explains.

At the start of every shi.ft, patrol cops are assigned to those red boxes. "So we're asking that they spent

the time in that 500-by-500-square-foot box, doing whatever proactive work they can to prevent that

crime," Robbin says.

On a recent shift, officer Philip Monzon pulls up inside his box; today, it's a city block near the Seattle

waterfront.

"[The police] want visibility, they want contacts with businesses as are appropriate, and anyone who's

wandering through the area," Monzon explains.

This area has parking lots, and PredPol's forecast includes car thefts. As Monzon passes a green Honda,

he pauses. The guy inside seems to be ducking under the dashboard.

"[I] wanna make sure to see if he's got the key or if he's gonna pull out anytime soon," Monzon says.

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Page 3 of 4

The car starts- the guy probably does have the key. But why didn't Monzon challenge him, just in case?

"I don't really have enough- I'm not just going to single out one guy in a Honda," he explains.

Computer Models And 'Reasonable Suspicion'

And this is where this gets tricky. The courts say police need "reasonable suspicion" in order to stop

somebody. That suspicion can come from a lot of th ings- even someone's "furtive movements," as

police like to say.

All Tech ConsideredPolice May Know Exactly Where You

Were Last Tuesday

Around the NationAt LAPD, Predicting Crimes Before

They Happen

But can it come from the fact that someone is occupying an imaginary red box drawn by a computer?

"Ah - no. No. I don't know. I wouldn't make a stop solely on that," Monzon says.

That's probably the right answer, says Andrew Guthrie Ferguson, a law professor at the University of the

District of Columbia who has taken a special interest in the constitutional implications of PredPol. He says

the departments using it have told police not to use it as a basis for stops. But he also wonders how long

that can last.

"The idea that you wouldn't use something that is actually part of the officer's suspicion and not put that

in- [that] may come to a head when that officer is testifying," Ferguson says. Either that officer will have

to omit the fact that he or she was prompted by PredPol, he says, or that officer will admit it on the

stand. "Then the issue will be raised for the court to address."

And it may be that PredPol is a constitutional basis for stopping someone. Some might consider it more

objective than an individual police officer's judgment- less prone to racism or other kinds of profiling, for

example.

Ferguson says that argument may have merit, but that police and society still need to be careful.

"I think most people are gonna defer to the black box," he says. "Which means we need to focus on

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Page 4 of4

what's going into that black box, how accurate it is, and what transparency and accountability measures

we have [for] it."

In other words, even though computers aren't biased, the statistics feeding it might be. And if police are

going to follow an algorithm, we should at least be willing to check the math.

DONNIE FOWLER


PREDPOL.COM


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Page I of2

From: Donnie Fowler <[email protected]>

To: [email protected], [email protected], [email protected]

Date: Monday, August 12, 2013 08:34PM

Subject: Georgia City Gets Two Arrests on First Day Using PredPol

Chief Suhr, Susan, and Suzy -

Looking forward to seeing you Tuesday in Berkeley. I thought you would like to see a report fromour first Southern city -- Norcross, Georgia - - to put the predictive technology in the hands of

their patrol officers. Following trainings last Thursday afternoon and Friday morning, this was theresult, as emailed to me by the deputy chief of police.

We look forward to completing our deployment here in San Francisco.

All the best,

Donnie Fowler4 ellpredool.com

---------- Forwarded message.----------

From: Bill Grogan <[email protected]>Date: Mon, Aug 12, 2013 at 5,:46 AM

Subject: press releaseTo: Donnie Fowler <[email protected]>

Donnie - we want to release something to the media about our PredPol integrat ion. Also, wantto tell you about 2 successes our day shift had Friday. Yes, the same day they received training2 officers were in a box and caught 2 burglars in a house. Solved several cases with it. Another

officer caught a wanted guy in a box - officer was there spending time because of the box -arrestee was wanted for probation violation on burglary charges out of Illinois.

So, give me a call please.

Bill

Lieutenant Bill GroganNorcross Police DepartmentCriminal Investigations Division I Crime Suppression [email protected] (dispatch)~ ( o f f i c e )._(cell)

770.248.1819 (fax)

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Page 2 of2

facebook

(LESIFOUO) LAWENFORCEMENT SENSITIVE· FOR OFFICIAL USE ONLY WARNING:

The information contained in this email is considered confidential and sensitive in nature as well as sensitive but unclassified andlor legallyprivileged information. It is not to be released to the media, the general public, or to non-law enforcement personnel who do not havea "need-to-know". This information is not to be posted on the Internet, or disseminated through unsecured channels, and is intended for lawenforcement personnel only. lt is solely for the use of the intended recipient(s). Unauthorized interception, review, use or disclosure isprohibited and may violate applicable Jaws including the Electronic Communications Privacy Act. lf you are not the intended recipient,please contact the sender and destroy all copies of the communication.


4104 24th Street, #445San Francisco, CA 94114

331 Soquel Ave. Ste. 100

Santa Cruz, CA 95062

PREDPOL.COM


Attachments:


July).pdf

PredPol Info Sheet How it Works (2013

July).pdf

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b u r g L ~ r i e . ' > ;md c.u rhdf.,. ;lrt-• not planned in : l l kmn· hut

arc ;-1pponuni,tic ;\ h;ld gu;· . ~ e e s an unlocked window

and dmb in. ''Bmgbrs typic1lly don't !r;wd fir. They

ccnd w commit u i ; l K ~ in their own n ~ · i g h b o r h n m l s . "~ . · x p h l i n . - . ,\{oh!er. " T h ~ . · y haw ,1 lnr of int{lf!n;ltion: They

know when their ncil!hhors :He ;H work and which

hnttsc<. <ll'l' c a ~ y w gc(. inw. And wlwn the;: sucLCL'tL tht'y

uo bad, .lg;Jin. You sec ir in dw dau." :-..-tapping tho)t'

f;.lll ' ' l ' l l\ c'-tn oive I)Oiict an cdt!,r in f l t : u r i n ~ nut when:· w< " ' ' 0 "' "' "'

d.:p\oy i.'Xtra ._·,m and cop,, to cud1 bad guy:.---,: or, bcr_r'-"r

wr, ki.'ep them from opening rhar unlocked wmdow I ll

flr.:;t p!a..:e.



)!1 ~ 0 1 \ l C ways, rlw llOtion of prtdicriny_ Wht'!\ ' crimes

will ktppl'll ha ..nl on wht:l\' rhcy'n: h;lppt·wx! in the

p<lSt is <1bviom. 'I 'hat om· l'\'Cilt i n c r l ' . 1 ~ t s the likelihood

o( simi Jar l'\"t'JllS Ol"t't!frillt.; llt:trh\' in ~ p : K I . " <!lld rime is

wdl c.\tabli.,hn! in or her JieJd,. o/ rcs;.·;tr.._·h, In f:1cL .nHt

can ~ t ' c it c'.-cr;·wherl' in orJin:try ! ik A punch rhrownin .1 b:lr i n c r o . . " , \ ~ e : : . rhc ..:h;ull·<:s of mnn· puncht.), On.._•

kb\ 1l'atb w ano1her. ;\n:dy\1" ,1ml :lcHlcmics U'>l' rhc

principle more mcrhodicJI!:· ro predict where b.uuna

r r c e ~ might hl' t ~ n u l d , or w!kJL' coqH;LHl' tf...·t:w!t'> will

d u ~ t n . Unt· uf \lohkr\ main comributiom to a new

m n d ~ l for pn:dictin· p o ! i c i n t ~ W ; l ~ fn lind .tnd :Hbpt :Ul

algoridm1 d l ' \ ' C l o ~ K · d by ~ l ' i ~ m o l o g i s c s to hdp pn:diL"t

wherL' . l f r c r . ~ I H h · k s will srrikt' after ,In e,u £hqu,th:.

If thl'rc han: IKt!l .1 lot of u ~ ~ i n g s on a p.micul.Jr

S!t\'t•r ll.1r the Lbt SO \\'t:t·b., thnt• will prnh:tbly he ~ n n wdK· I(JI!owing week. ( : o p ~ know th·.u, of cour..;;.:, But

che ide;t en make rhos(' ns.sumplion., ;md g u e . s s e ~

mot\:' accurah' .tnd to turn up p.mnns du ta r ~ . : n " t

ITad[[y <lpp<lfl' ll!.

Corponrinns lu\'t' long u ~ e d simil:H prl'di(ti\\.'

~ t n a l y t i t ' to ;unkip;He (on.r,umcr demand. tlnding dut

c r o _ ~ ~ - p o ! ! i n a t i n g d:ua em yidd tllll'.Xp<..'"cteJ l " l ' \ u l r ~ .r\ L1nwus e;.::!Tllple CO I l l ~ - ' ffom \X'al-.\t!n\ an:lly,\is

of wh:H ib ctb!OillCfS ill CO;!StaJ <lrt.JS Stock up Oil

bef(Jrt' hurric:JIW."o. Tht' Hst includes duct t:1pc .md

hun led warer. naturally: but J.bo ,l sut r i ~ c srrawhtrry

Pop-T1ns.

Ana!ping crime Jau can similarly ~ ~ i d dcounrerintuitin· con(!usions. :>.·!o..;r people think f.Ood

lighting makl'\ an :1r.:-a ~ a l ~ 1 , i0r ill.'lf<li\C('. hut . ~ t u d i _ e sh.tw lin1nd th,n it ;Kndlv intTL'.lSt'S rhc ch;llKt') of

bcin,t.; vicrimi?.ni. It ~ ~ ~ ~ n ~ rh;u mugr.ers w,lnt to ht: ·.1bl"'

to sec thdr porcntbl urgct.\ ck:u·ly.

!11 A u g u ~ t . ~ 0 1 0 . rhe IL\tnl \ wl)rk, dJOugh still in tht·

tlwnJL·ti;.al.'>t,lgt', pmrnp1cd an ;nride in the l.oJ ,i.;;/!,<'lt'.'

finu•. Th.l! CHigiH dh· ·.trrc'ntion of /;lth ! ; r i ~ ' I H L .t

L'fime .l!l;Jint wirh the s,ul(,} Cruz Polil"l' D..:parullc!lL

"I calkd uP :\-loh!er. wlw had iu:-.r t;lkcn his iob .1\ SaJll;tClara," S,l\ ' ' Friend, .:U. "! qjd. 'Wft''lll<lk,, this out of

tht· cbv.;r(,llllll :wd pur ir into rhe field. if you're willing.'''

The tt':lm •lgreed.

h i ~ · n d brought ;\lnhkr in tu hdp s(:IJ d1c idt'a to

his r o H L ' . l f . ; l l l ' ~ . The c o p ~ met rhc marlwm:Hi(ian with

; t < t . ' r t ~ t i n ;H1HHIIH ofhl ' tn l iSt ' l lH. ' I l t . "( )u r th·rd p;t!r'

one onlccr o l ! ~ ;'vlohkr wht·n I \'isit the dcpartmt'!H\

ht.:.Hlqu.mcr\ one spring <.by. "l·le's hringint, co1duroy

h ~ t c k ! ' ' ntks ·,mrnhn. )till. rhc br<1ss bl)ug!n in. "\\1t''ve

h.td b u ~ ! v e t cnr;, like l"\'Cfl'nne else. l k . ~ c ~ u r c e s an: ,,car..:e,,. .and we need to usc them . h c H i c i e m l ~ · possible."

'i·.lr' Sant:t Cruz Policl' Chief Kevin \'og_t:'L "I r h o u ~ h r ir

wou/J be worth~ i v i n g

rhi'> <l try."So every wnrl<tLty t(Jr d1e past two }'L'<lrs, Fril·nd ILlS

('Onlt' in t:arly w rvpc dh,' rime and gcncndt·d location

n f dH· JWJS! rccerH hurgLHY :Hld <HHo thd( rcporrs into

dlt' dl·p;tnlll l ' !H \ com \yst t'.H1. }.-fohl cr\ a! i thnt

thc>n crunche:-. thmt' report!\ togalwr with t!w la..,t seven

\'l':l(<;, worrh of crime data and spit\ out,} ll1:lp or S:una

Cn!L wirh I 0 h o x L · ~ oil it. t";Kh r'epresentinl!> .111 area 100

r ~ · e t long .H1d son l ~ t ' t widt: ·-ahmu h.llf a b!nck. Thov.'

·,tre the hor ~ p o t s rhat t h ~ . : ,llgorirhm d l ' t ' l l l ~ likdico;r rn

~ , · e t h d i ~ rh;H d.1y. The nnp,\ ,11\' hamh:d our tn nHin·r\

at the beginning oft 'xh ~ h i l l : . They t . : r u i . ~ c t h r o u ~ h tbt'

hoxe.; when thd· h.l\"l' ri111c in hetwn;:n <Ktin· ( ~ l l l . ' i ,;'\\?l''rc very Ptc.:l.\l:'d with t1K lnHh'>," U)'S (:hid'

Vogel. In 2012 burglarin w e r ~ · do\\'n ahnut 7 petu.•nt

c n t ~ l p ; m : d to 20 l l 'And the prngum Ius Jr;twn

'' ' ' 'y.! .Notj u ~ t , " t ~ e f e .;r_ime

h ~ s b e e . n ..butwhere It's l l ~ e l y

(to' ~ c c : u r · n E : X t



AlgorithmsFor predicting

quakes and crimeike the earthquake version of the

algorithm to predict where. an

aftershock will strike. mathematician

I)Porou f\llnilter's "expectationmaximization" algorithm For predictive policing

models the incidence of two sets phenomena.

The first is the "background rate" oF events that

occur randomly-earthquakes or spontaneouscrimes. Different geographical areas have

different background rates: Some areas have

more geologic Fautts, and some neighborhoods

havE' social and economic Factors that subject

them to more crime.

The second is the "branching structure"of similar events generated by the random.

spontaneous ones. With earthquakes. that's

aftershocks. With burglaries. it's more burglaries.

which oFten beget still more burglaries, spreadingout Uki? a tree's branches. You can further narrow

the list of likely locations of future crimes by

ruling out areas 11/here they are impossible; you

can't have a residential burglary in the middle of

a park. for Instance.

Mohler and his team analyzed several years

oF data on the time. place, and type of property

crimes In Los Angeles to see the patterns of

where and when they occurred and were followed

by others. (Murder and other violent crimes

are far less frequent and so don't offer enough

data For the algorithm to provide a reasonably

accurate forecast. says Mohler.) From there.

they derived a set of mathematical functions

to predict both the occurrence of spontaneous

crimes and the probabilistic distribution of where

the crime "aftershocks'' are likely to occur. The

result: a literal road map to future crimes. VB

international aw:ntion. J'imt Tn:lg:1zine, NPR. l11c Nr'/1!

h1rl> !Jm,'i. .111d new_, news from a:-> fir away Fr.HlLT

and ( ,;,_.'rm:Jny luve rt·pnncd nn ir, ant! s c o r ~ · ~ u( other

p o l i ~ . : t : agt'!Kics, .l'> well <I> d1t' 1kp:H rment of Defense.

han: gottt'll in to111.:h.

: \ : ' i i ( ; \1• ' rn·· J;J(•!j , l ' ' L i

One u!' rlw mo.-a i n l i : n . : , ~ t n l OlH -or-rown 1.:nps w.ls

L.\PD ( . l p t a i n S\:an ;\hlinowski, ;In ,uhktically huih

46--year-old with hair n:cnling t'rom a :-.:un-redd<:!H:d brow.

~ h l i n o w s k i h d p ~ . - · d coin the term "pn:dictiH· policing''

in an inllut'IHi;!l papa Ill· co-·amhon:-d in 2008 with

1hcn-·Los A n g t ' l c ~ o Police Chicl'\\li\liam Bratton.

M:tlinowski wnrknl l ~ 1 r _ . ; ~ . : v t • n l ye;H'\ cxcouivc

t)Hlccr m Br.ttton, who is a nt':lf-legl..'nd in American bw

t•nf(m:eml'lll cird..:,, d1c police c h i ~ , : f on w h o : ~ c watch

(rime plllJJllllcteJ firs( in New York, then in LA 1-k·

w ; l . ~ ;t\w,tys gt:tting invirt>d w give {alb oil the llnurt· t)rpolicing. :md part uf .Malinowski\ job was w br.tin:-wnn

with him <lhout what to ~ a . v . One of lkmon's k(·y

inno\'.Hiom w;t:; a cumpmcrized s y . ~ t c m C ; t l k ~ l CompStal,

whil h col!ccts d c t < ~ i k d n:ports on criml's and rll<lps where

[hL')' Wt'l"(' committed. V c r ~ i o n s of tht· system an· now

w.cJ by police ; . H : r o s : ~ America. Thinking about ways to

hui!d on :md improve CompSr;n's dat;Hlrivcn <lppro;Kh,

they C.lnlt' up wid1 the idt:;l (;tnd C;ttchy ride) of r c d i u i v ~policing wrmt' :tbnm the ronccpt for tlw Oxjim/

fonrntt! ~ / ' f h l i o ' n g ,\\lith Branon\ toweling rr:puutinn behind it, dh:'

idt::t c:tughr lire, Soon aftl.:'r tilL' ; u t i c l c ~ " publication, t!H:

Nation;ll lmfitutc ufJusticC' org,miznl :1 omll•rcncc un

predini\'C policing, and the D c p ; t r l n k ~ n r ofJus£icc h:tndcd

OUt !llOI(' than $\ million in seed gf\tll{S W ,l ( i ~ t f u J or

police dl'p<tflmclH.\ i m . : r e ~ t c J in pur:-.uing dw idea.

Vo11 in us ;lgcncin are now nying out diffacnt

.lppm,ldws, pulling in ;111 kinds of d:H:l. In Arlin,(!ton,

Texas, cops have neat.:d m;tps on:rlaying n . : ~ i d c m i a lb u r g l a r i t . ~ with building code vioLuions. They tinllld

rlur" ;1-'> physk·al decay ~ o e s up .so do b u r g l a r i ~ s . Thty're

t t ~ i H g t h o ~ l · findings to dt•ploy polkt.• more d'l1ciendy.

In · r t · n n t : . ~ . - . c e , Univl.:'rsily of \ · h : m p h i ~ crimino!ngist.\

;tnd !ot:a! police are ming bmincss-;Hhllytics sohw;ue wrompill' crime- tepons ;tnd layer in v<l!'i:Ihks like wc:uhcr,

lighdng (onditiom, and proximity ro c.:on<.Trt v<:nucs,

along with reporting from PDi\-cquippcd heal c o p ~ ,ro tlnd cunnccriom. Tht· i ) ' _ ~ t t ' m noticl.:'d, for imhtncc.

dJ:ll colkgcs' - ; p r i n g - h r ~ - ; t k wct:k rdiahly spawns a rash orhurgbrit\'>. And in , \ J i n m ' < t p o l i . ~ . :1 s p c c i ~ 1 l Crimt' An;tlysis

Unit idcnritl,s locninns wht't't' gun crimt':. h.w-.· bctn

rcpnrtcd. dlt'n b\.'tor.'i in geogra\Jhic det,Ji!s o11 thing>.

like hu.; rotHl:'i ,md proximity tu p:1rks, li{jllot : o . r n r c . ~ ,,llld pnhlic lihr.HiL'.\, Combining rhat with ~ ~ - a s o n ; d d;tt;l

en:tble< rhem to predict when cm:tin public p:trb :tndotlwr an_'<l" "·ill bL'Conw .JrctJas l ~ n - gun viok·ncc.

Tht' L.\PD, tnl.:':mwhilc. Ius conrinucd working with

1!w t\\1111 dut ith.:ltKk\ B r a n t i n ~ ; : ! l ; t l l 1 .nUCLA .1nd A·lohkr



:n SCl}. lmpn.'-"sed wirh the n : . ' > u h ~ their a!gorirhm

'iccmcd to bl' gening in San{a Crnz, :\blinow-.ki got

;1ppro\·;d !0 ptll ir into jH\Kticc in l . o ~ Angelc .. '>t<lning

ht<' in 201 L

Angdc:. m ~ : l n s a trial on a comph:rcly ditrnem

sc1k·. S:mt",l Cnu. a b111ously ! a i d - h ~ 1 C k town of only

'lS,OOOp ~ . · o p l e :

in 2012 it a tnt:tl nf two homicide,,l.o:-. Angel..:" i.., a spnwling m c t r n p n l i . ~ td. more th:w

.) million, where someoJH.' gets killed almost ~ ' \ ' t ' J ) ' day.

E1ced with rlh· size of rhe city and irs pulice

t'or(e, 1\blinow<>ki h : 1 ~ been intmducing pn:dicrivc

polic.ing nne divi.\ion :u :1 1ime. Th e 0 ! 1 ~ n h H o l l ~ · w o n dJ i v i s i ~ . m , whid1 parrols a chunk of the .San Fernando

Va!k.)' rhat h o m t ~ to snnw 2tH.OOO }H.'ople. \\"J.'\ tlw

-.:econd, beginning rome .\!ohh:r\ algorithm ,·arly in

sprinf 2() 12.

"Awo theft, burgLuy frnm v e h i c l e . ~ . and rc,idctHi;d

bmgbrics ;H\' do\\ n I(} p c r c ~ n t comp.trt•d to rhc :i<tll'll,.'

period bst )'L\lr," Captain .Justin E i s ~ . : n b e r g tells me

i n s i d ~ · tilt"

l\otth

Holl)·wood divisionhe.Jdqu:IIT(T\, ;t

spr.l\vling nwderni\t building on a husy, s u n - h l : l ~ r ~ . : J<1\Tnuc. ""rJ,,H\ prnry inrn:dible. Prt:Jicrivc polidng

isn't a p,lll<Kca, but it i-.: \tlfpri,ingly m.di.d."

!"he program is now runninf!, in ;t h:llldfu! of

divisinm. with tri:lls under way in c.Kh of rhc cir/;; 21

dlvisinm. Crimc has dropped [n the divi\iolh \\-hen: the

p ~ e l t : : r a t n i;, .tlrc:Jdy l · ~ t ; 1 h L i ~ ! H . : d . Ncidn:J . \ l a l i n o w ~ h : i nor

I I H ~ s c h o l a r . ~ ;H S.\Jlt,t Ch1r.1 and UCL\ an .· ready to s.ty

that all th:lt t rime rl'dtKtion is dul' to rh,· algorirhm.

"Bill evn_nmc '" n we'rl· ~ e u i n g ~ r t . \ H nutnh('r.<; and

\ \ " ; l i l t ~ it in rheir :Ire,\." .\ldinmnki : t d m i r ~ .

!"ht· idca·of r ~ ; · d i C ! i v e policing h:1" i!s crirics. Civil

lihcna1 ians ;1!\.' con....-crncd ir L"rJtdd ! c ~ l ! ! t in cxrr.l pollee

p r t ' ~ ~ t ! l \ ' nn poor ·,md minority ! l l ' ! t ! h h n r h u o d ~ . I! L·np

. ~ p o t s . ~ o n h ' O ! W ho!din1; ,1 b:tg .tnd l o n b n ~ <H ,\ h u i l d i n ~O(l :1 .\t!\'(.'1 tlw :dgnrit!l!ll h:1.\ n ~ ~ ~ g e d ,\S ,I !ikl·1y \pO!

f(H· burglar in . he may be more likd;· to '>top :1nd fri..,k

t!w lnii<.Tet, p o i n t ~ out Andr...:·w Cmhrie h:r,l{U\llll, an

; l . \ \ i ~ u n r law f l r n i ~ ' ~ . w r at rhc l l n i r e r . ~ i t _ \ ' o( dw l i ~ t r i uut"<.:ohllnbi;J, in .1 fl'Cent paper. Thl" officer m i ~ h ,c;Hch ;I rhief----or might opL'n himself" up w ,l ch.ng,c o(

ra,;i;d profiling.

Thcr..:- Jl\ ' also ".otnc· U!Hlt'I"VingJy A / i n r H i ~ ) ' Rtpon-Ltw-cntOrcc.:mt•nt cxpt'filllL'IH' unllcr w:1y tiJ;H tbl '

p ~ < : d k d v e rechnlquc.\ to hrlp dt:!ermine whedu:r an

i ; ~ t / i v i t l f l f l l is !ikdy w commir ;t crime. Pt.·nn..,ylvJnia

probarion :md p:trnlc oftlci:1ls :Hl' working- with

a U n i v e r ~ i r y 11f Pennsylv:1nia ~ t ; n i . \ r i c i o l n who h<L'

~ k · v d o p . . : d: l l l <ligorithm to hd p

e ~ r i m : H l . 'rhc

r i . ~ kIll'

\peciHc i n m a t e ~ rt··off-(-ndint, ari:cr r d t ~ l s ~ . ;\nJ thl'

Dcp.trrment of Hon1ebnd Sccmity i<> ' ' : \ l ) ~ · r i m c n r i n t ;with <1 .sy t.:m ·or scnmr, t!wt trade> airport p:l:.'\l'ngcr..,'

hcart nth.') and other phy.\iGd indicttor:; w help

dctcrmi1K who ,!Joukl ~ i n t ! I L ' d nw li.H ;HI t'Xtrd

::.earch. ,\lnhl,,[ ' r r e . . , s < ' ~ th:H hi., t e a m ' ~ :dwnithm [nok::.

only at gcoe,r;iphit: .let:'.ts, nvt indi\·iduals. ''\\1c don'r

pur demogr.1phio in h) the model,'' he . \ ; l ~ ' \ . " T h e r t ~ ' s no

individu.1l infi)rnl<ltion b._·i11g fl'l! in."

O n a more practic:d lcvd. h;Hd-hc.tded succt c o p ~;He u n d e r . ~ r a n d a b ! y .,kt>ptkal <thour dw whnk· no! inn.Hack in Alhu-r:tll's cruiser, we move on w <lllothn box

indit·.w:d by dK algMithm. <l hi1Kl< on busy- Ventura

Bnukv,ml. "'Thi.., box lH:re ... \,1\'s Alharr.m. jabbing .1

i l n g 1 ~ r ;H rht> map, "if doem't r ~ ! l u · . ; whar ... rime o; who

ro w.uch om t ~ H . \'('e know rhis ;1 ! n t ~ \ ' - c ; r r c ~ , r with a

k>l nf" \ tu(( ~ t : u i n g .>,tn!..:n ou t tJ( p;trk..;d ·c.u:;, \V.:· don't

necd pn.:::dictivc policing ro tdl th;iL

''I pcrsouall:' don't rhink it\ V'.'ry helpful."' lw

wumbl:;:s. ",\ln:-.t nfnty guy\ the .\.lint: w;t)'··· I hl

w h ~ } h : poin1. chougb. is no! f(Jr A!b;lrLlH to . ~ p o r .1

uimt·-·it·, I(H· hi:-. p n : ~ c t K c > ro stOp orw ho m happen

''\\r'e dl)n't see this .l way to :trf('.\1 pcopk· but to deter

nimc," _qys .\·luhln. "The L\PD rrnh.,bl:- ;ll\11111).', thertl!)\f snphiqicncd departments in thl' l rnircd St:Ho.:s. ··he

£.UCS 011. 'They do a good joh. hw wc'vc ~ l u m · n _\'tHl ...·,tn

do h , ' t t ~ ' r . ' " Lt. :\lharr:\11 mig!H . ~ , , o f f a r th;n. Hut polil",.

:Hound dw u.nHllry <lfl' p : 1 y i n ~ ~ ,\ttl'nrinn. \·lohlc1 and

h i . ~ collt<l)!Uc-. LHHl<.."hcd :1 (ornnh'n:i;l! Ycrsion ot. rhcir

ptof,L!Ill, duhh.:d PH·dPoL in 2012, ;uld h<lW \t } Lu made

\:de:; tO '>;:\·cr.l! po!icL' depoH f l l h ' n r ~ <!nd ridded inquiriv.

r:-orn score.\ more . \) [Hnhi!c tn:hnnlnt-:r d n · c l n ~ l . \ , w \\'ill

th e progr;lm-----:llhl:ht· i n t e t f i t l ~ \ wc!l.h \\h.u kind

of n f ~ l f m n i o n i" p n n · i d ~ , d w nl1!cers. For pn.-didiv"

pol"!cin!!,. it SC'<.'!ib, thv futuJ\' i-.: lonking g(lnd, ..ffi;



Page I of2

From: Donnie Fowler <[email protected]>

To: [email protected], [email protected], [email protected]

Date: Friday, August 16, 2013 10:46AM

Subject: Georgia City Gets Two Arrests on First Day Using Predictive Policing

Chief Suhr, Susan, and Suzy -

Hello again. I thought you would like to see a report from our first Southern city -- Norcross,Georgia -- to put the predictive technology in the hands of their patrol officers. Followingtrainings last Thursday afternoon and Friday morning, this was the result, as emailed to me bythe deputy chief of police ...

We look forward to completing our deployment here in San Francisco.

All the best,

Donnie Fowler4 L cell

predpol.com

---------- Forwarded message ----------

From: Bill Grogan <[email protected]>Date: Mon, Aug 12, 20p at 5:46AM

Subject: press release ·To: Donnie Fowler <[email protected]>

Donnie - we want to release something to the media about our PredPol integration. Also, want

to tell you about 2 successes our day shift had Friday. Yes, the same day they received training2 officers were in a box and caught 2 burglars in a house. Solved several cases with it. Another

officer caught a wanted guy in a box - officer was there spending time because of the box -arrestee was wanted for probation violation on burglary charges out of Illinois.

So, give me a call please.

Bill

Lieutenant Bill GroganNorcross Police DepartmentCriminal Investigations Division I Crime Suppression [email protected] (dispatch)

)

http://sfmai 104.sfgov .org/mail/gsuhr.nsf/(%241nbox)/E4 E590E6BFFC6C355CB9170E2A26F... 9/23/13



Page 2 of2

facebook

(LESIFOUO) LAW ENFORCEMENT SENSIT IVE- FOR OFFICIAL USE ONLY WARNING:

The information contained in this email is considered confidential and sensitive in nature as well as sensitive but unclassified and/or legallyprivileged information. It is not to be released to the media, the general public, or to non-law enforcement personnel who do not havea "need-to-know". This information is not to be posted on the Internet, or disseminated through unsecured channels, and is intended for lawenforcement personnel only. It is solely for the use of the intended recipient{s). Unauthorized interception, review, use or disclosure is

prohibited and may violate applicable laws including the Electronic Communications Privacy Act. If you are not the intended recipient,please contact the sender and destroy all copies of the communication.

DONNIE FOWLER


PREDPOL.COM


Attachments:

PredPol Reading & News (2013 August).pdfPredPol Info Sheet How it Works (2013

July).pdf

http://sfmail04.sfgov org/mail/gsuhr.nsf/(%24 Inbox)/E4 E590E6BFFC6C355CB9170E2A26F ... 9/23/13



DRAFT [May 8, 2013]

PREDICTINGGUNVIOLENCE

Cities Take Lead as First in the Nation to Deploy New Technology to Deter Gun Crime

The Challenge. In light of recent gun violence across the country, including schoolshootings, and as police departments across the nation face tighter budgets and scarcerresources, reducing violence and gun related crime remains a significant challenge.

The Leaders. Atlanta, Detroit, and San Francisco are taking the lead as the first citiesto predict and deter gun violence by deploying a new application of PredPol's generalcrime prediction methodology.

Predictive Policing. While no one strategy serves as a silver bullet, predictive policinggives officers a significantly better idea of when and where to be so that they can detercrime generally and gun violence in particular, sometimes even catching criminals in theact.

Precursor Crimes. PredPol's unique gun violence prediction methodology recognizesthat past homicides are not necessarily the best predictors of future gun violence. In

fact, the occurrence of serious violent crimes like weapons violations, assault, andbattery provide as much, or more, information on where and when future homicides are

most likely to occur.

Origins & Results of Predictive Policing. Predictive policing was first developedand deployed in Los Angeles and Santa Cruz, California. Only six months after launch,those two cities enjoyed declines ranging from -12% to -25% in burglaries, car thefts, andthefts from motor vehicles compared to the same period in the previous year.

Field Tested. PredPol's general crime prediction technology has been extensivelyevaluated using historical crime data and controlled field trials with multiple lawenforcement agencies over several years. Controlled trials show that PredPol predictsmore than h\•o-times as much crime as a veteran police and crime analysts. To be clear,though, PredPol is not a replacement for veteran officers and crime analysts.

Modeled Using Real Crime Data. PredPol has also extensively modeled its new gunviolence methodology, predicting a greater number of gun homicides compared withalternative approaches, including traditional hotspot maps. In a test of public crime dataout of Chicago, PredPol successfully predicted so% of gun homicides by flagging only10.3% of that city-- 66% more than hotspot mapping would. predict.

Science for Patrol Officers. Developments in mathematical and statistical modeling,high-performance cloud computing, and GPS-enabled mobile devices now make itpossible to deliver real-time crime forecasts on simple maps to patrol officers.

Not Crime Mapping. Without predictive analytics, police end up chasing yesterday's

crime by relying only on intuition and mapping of past crime data. As IAPD's CaptainSean Malinowski has noted, "We look at these maps and they're as accurate as we can getthem. But I'm looking at a map from last week and the whole assumption is that nextweek is like last week" Traditional mapping tools are calibrated less frequently, relymore on humans to recognize patterns, and allocate resources based on past crimesrather than predicted future offenses.

Timing. Although the actual deployment date for Atlanta, Detroit, and San Franciscodiffer, these cities have smartly added a new tool in the expanding national efforts toreduce gun violence.



PREDPOL'" THE PREDICTIVE POLICING COMPANY.™

PredPol Predicts Gun Violence With OpenGovernment Data

PredPol accurately predicts where and when crimes are most likely to occur. It is the

only predictive analytic system that has repeatedly demonstrated the ability to predict

more than double the amount of crime in head-to-head field deployments against

dedicated crime analysts with all of the tools of the trade. PredPol can now deliver the

same predictive accuracy for gun violence using unique mathematical methods. A study

of Chicago data shows that PredPol successfully predicts so% of gun homicides by

flaggingin

real-time only~ 0 . 3 % of

city locations. Knowing where andwhen

gunhomicides are most likely to occur empowers law enforcement to use their knowledge,

skills and experience to disrupt gun crime before it happens.

mile Gllallenge ofGun Miolence - ~ - ~ - -- ---- ~ - - - - - - ~ - -

In 2 0 ~ 2 there were 507 homicides and ~ 2 , ~ 3 7 crimes involving handguns in Chicago, Illinois. In

light of recent gun violence across the country including school shootings and as police

departments across th e nation face tighter budgets and scarcer resources, reducing violence

and gun related crime from the current high levels observed in cities like Chicago is a

significant challenge.

While no one strategy may serve as a silver bullet, PredPol makes possible th e efficient

distribution of limited policing resources. Developments in mathematical and statistical

modeling, high-performance cloud computing, and GPS-enabled mobile devices make it

possible for real-time crime forecasts to be at the disposal of officers in the field. PredPol

technology gives officers the best chance to be in the right place, at the right time, to stop

crime before it occurs.

PREDICT CRIME IN REAL TIME.™



PREDPOL'"

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Figure 1. Prediction map in 2on: 1% (red boxes), 2% (red and orange boxes), and 3% (red, orange and

yellow boxes) of Chicago flagged, corresponding to 6km\ 12km1

, and 18km2

. The percentage of

homicides predicted at t h e s ~ thresholds are 10%, 13%, and 20%.

The purpose of this white paper is to show how big data, predictive analytiCs, and hotspot

policing are currently used in practice, and how they are adapted for the purpose of

suppressing gun violence in a city like Chicago. Our methodology allows for several years of

crime data and many different crime types to be systematically combined to yield accurate,

real-time crime predictions. PredPol predictions provide tactically clear recommendations

about where and when to deploy precious police resources. We illustrate the methodology

with a large, open-sou rce data se t from the Chicago Police Department.

~ r e C J ~ o l Success in tl'ie EieiCJ ·

PredPol has been extensively evaluated using historical crime data and controlled field trials

with multiple law enforcement agencies. Analyses demonstrate that PredPol outperforms

existing methods for forecasting crime such as kernel density estimation, which underlies mostcrime hot spot mapping programs. Controlled trials also showthat PredPol predicts more than

two-times as much crime as a trained crime analyst.




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Figure 2. Property crime rates fell during the period of PredPol deployment in LAPD's Foothill Division.

Serious property crimes include burglary1

car theft and burglary/theft from vehicle. Comparisons are

between Foothill Division and six other geographica lly adjacent Divisions in LAPD.

The PredPol technology offers microscale, real-time geospatial intelligence, displayed

in a way that is tactically clear to supervisors and patrol officers; unlike current models

such as hotspot maps that are often underused because they are ambiguous and

confusing. Over the course of a six-month period of deployment from November 2011

to May 2012 with the Los Angeles Police Department (LAPD), patrol officers nearly

doubled the amount of time on predictive missions from 48 hours per week to 88 hours

per week. Setting clear mission expectations and regular reinforcement of mission

priorities from supervisors were important during this process.

Crime rates can be impacted significantly by the use of PredPol. In the two longeststanding deployments, with the Santa Cruz and Los Angeles Police Departments,

declines ranging from -12% to -25% during the same period in the previous year were

seen in burglary, car theft and theft from motor vehicle (Figure 2). PredPol serves as a

force-multiplier in allowing officers to use their expert knowledge, skills and experience

in a timely manner in the highest risk locations on the landscape.

BreCiicting Gun Miolenc:e witlil BreCIBol

PredPol is based upon a marked point process methodology that allows for several

years of crime data, and multiple crime types, to be utilized by hotspot maps,

incorporating both fixed risk heterogeneity across the city and temporally dynamic risk.

Chronic hotspots are long term in duration and necessitate problem-oriented policing

strategies to address the root causes of crime. Temporary hotspots, on the other hand,

www.predpol.com PREDICT CRIME IN REAL TIME.™



PREDPOL'"

last on the time scale of days to weeks. Policing strategies must be able to anticipate

emerging trends to disrupt emerging hotspots. Without predictive analytics, officers

end up chasing yesterday's crime. The Los Angeles Police Department updates its

PredPol models for every 8-hour shift and directs patrols accordingly.

In many instances there may be little difference in the situation and intent separating

gun violence and a homicide. The occurrence of serious violent crimes may provide as

much, or more, information on where and when homicides are most likely to occur as

actual homicides themselves. We take the following marked point process approach to

modeling the intensity of homicides. Given marks, M, representing crime types

believed to be precursory to homicide, the intensity of homicide is modeled as:

A.x,y,t=rtx,y+t>tig(x-xi,y-yi,Hi,Mi)

The background rate flX,y represents fixed risk across the city, whereas the kernel

g(x,y,t) determines the time and spatial scales over which near-repeat crime patternsoccur.

. .

€Hicago Gun.€rirne &. Gun ""'orniciCfe

We apply PredPol to an open source data set consisting of 38,740 violent crimes

occurring in Chicago, Illinois in the years 2oog, 2010, and 2011. In total there are 1,331

homicides and the following gun related crimes with "handgun" in the descriptionfield: 17,020 robberies, 6,560 assaults, 8,252 weapons violations, 5,274 batteries, and

303 criminal sexual assaults. The data can be downloaded from the website

· · https://data. c tyofchicag o. o rg/Pu b I -Safety/Crimes-2001- to- prese nt/ijzp-q 8t2".

Table 1. Most significant precursor crimes to PredPol predictions ofgun

homicides.

Homicide Robbery Assault Weapons Battery

sth 1St 2nd

Crimes involving guns continue to have an impact on future gun homicides for 30-100

days and risk spreads over as much as 1/2 mile in area. With knowledge of the increasein crime risk following precursory gun-related crimes, officers are in a better position to

deter more serious gun crimes through directed patrol. In Table 1, we display the crime

types that comprise the highest portion of the estimated risk of homicide and thus play

the largest role in predicting homicide. We note that past homicides are not the

highest predictor of future homicides rather weapons violations, batteries, and then

assaults are the highest predictors in decreasing order. PredPol predictions leverage




PREDPOL'"

these relationships allowing resources to be directed to .where they have the greatest

potential impact.

80

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45 67.5 90 112.5 135 157.5

Area of Chicago flagged (km2)

Figure 3. Percentage of crime occurring within flagged areas vs. total area of Chicago flagged

with predictions using 2011 historical data. PredPol accurately predicts a greater number of

gun homicides at all levels of deployment compared with standard hotspotting.

PredPol predicts a greater number of gun homicides using its unique prediction

methodology compared with alternative approaches. Figure 3compares the predictive

accuracy of PredPol against both 3·month and 3-week kernel density hotspot maps. As

police resources increase, more of the city can by flagged for directed patrol and the

number of gun homicides correctly predicted increases. PredPol successfully predicts

so% of gun homicides by flagging in real-time only 10.3% of Chicago.

BreCIBol GuiCies Bolice Bractice

PredPol fits seamlessly into existing police practice and creates strategic and tactical

opportunities that would not exist otherwise. PredPol accurately predicts where and

when gun homicides are most likely to occur. Police can therefore position their

resources to make the best use of officer knowledge, skills and experience to disrupt

gun violence. Moreover, the PredPol methodology creates clear tactical guidelines to

focus on weapons violations, assault and battery as the major drivers of gun homicides.

In a manner similar to 'broken-windows' policing, targeting these precursor crimes can

have a significant impact on gun homicide and ultimately on crime reduction.

For more information about this paper or PredPol,

please contact us at: [email protected]




Q PREDPOL' THE PREDICTIVE POLICING COMPANY."

Rt%eCiie't lt%ime im R.eal mime®

Cloud-based, easy-to-use crime prediction software

How PredPol Works

Only three data points from an agency's RMS database:

1) Crime type 2) Crime location 3) Crime time

Predictions are translated onto a map as distinctive red boxes representing an area

of 500 feet by 500 feet. Maps can be broken down into divisions, districts or beats

Predictions are recalibrated for each patrol shift with real-time crime data

Reports are delivered to any Int ernet-connected device, viewed on an MDT

(Mobile Data Terminal), or printed on paper

How PredPol Benefits Law Enforcement

Twice as accura te as human analysts in Predicting when and where crime will occur

Clear and simple visuals are easy to understand and immediately usable

Complement s officer judgment to problem solve while "in/around-the-box", and to

help new officers get up-to-speed more quickly on crime risks in their environment

Identifies precise locations for the most effective use of police resources

PredPol, a force multiplier to disrupt and deter crime

tactical ambiguity tactical clarity

831.331.4550 1 nfO@predpol.<om 1www.predpol.tom

--- -

-

PredPol software uses

a pattern-recognition

algorithm and existing

crime data to make real

time crime predictions

for safer communities.

Background

PredPol's te chnology has been

developed over six years by

Internationally recognized PhDs

in mathemat ics, crimiilology

and anthropology.

The program puts officers on

the scene before crimes occur,

targeting prediction "boxes" as

small as 500 feet by 500 feet.

Successful deployments in

dozens of cities large and small

in th e U.S. an d abroad.

"''m notgoing to get more

money I'm notgoing to

get more cops. Ihave to be

better at using what Ihave,

and that's what predictive

policing is about."

-los Angeles Police Chief Charlie Beck



Q PREDPOL' THE PREDICTIVE POLICING COMPANY.''

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Using PredPol, serious property crimes have fallen

by 12% in the Los Angeles Police Department's

Foothill Division.

PredPol is NOT

a replacement for knowledge, skills & experience

profiling of individuals

PredPoiiS

accurate prediction of crime location & time

a focal po int for effec tive local policing

a means for engaging & protecting the public

a way to make best use of your resources

To request a price quote, or for additional information about our custom design

and developme nt services, please contact us at: [email protected] or 831.331.4550

831.331.4550 1 [email protected] 1www.predpol.com

User Features

1. https:/1 .. secure login

2. deliver reports on paper, any

Internet connected device or MDT

3. 500' x 500' place-based

prediction boxes

4. crime mapped instantaneously

5. specific to crime type

6. specific to your shifts

7. crime mapping & prediction settings

Applications

Neighborhood policing

Milita ry intelligence and policing

Emergency management and

public health applications

PredPol Requirements

3-10 years of crime data from RMS

database and continuous data updates

Crime type, crime address, and

crime times from RMS database

No new hardware or software required

No incremental training

or maintenance fees

<9 2013 PredPol. Inc. All rights reserved. No part of this publication described herein may be reproduced, stored in a retrieval system, used in aspreadsheet, or transmitted

In any form or by meam eledronic, mechanical, P:hotocopj!ng, recordlng:J or othei'Y!_IS!_ ~ ! l t ! ! ! U h ~ 11er_missLon of PredPol, Inc.



q ' PRE D POL'" THE PREDICTIVE POLICING COMPANY.'"

Reading & Newspredpol.com

PredPol's patent-pending technology generates predictions about which areas andwindows of time are at highest risk for future crimes, including property crime, gunviolence, and traffic incidents. In contrast to "hot spot" analysis that simply maps pastcrime data, this technology applies advanced mathematics and computer learning thathas predicted twice as many crimes as those made by experienced crime analysts and

veteran police using existing best practices.

Academic Research:

A screenshot ofPredPol's predictive

boxes that areprovided to patrolofficers on paper orany mobile device.

Predictions arespecific to iheir shift

and sortable bycrime type.

Please find a link below to ongoing background research that led to the creation of

PredPol, Inc. after successful development and deployment by the Los Angeles andSanta Cruz police departments. Note that Dr. George Mohler (Santa Clara University)and Dr. Jeff Brantingham (UCLA) are co-founders of PredPol and remain very active in

its deployments and its ongoing research.

Univ. of California Mathematical & Simulation Modeling of Crime (UC-MaSC)Dr. Jeff Brantingham: http://paleo.sscnet.ucla.edu/Publications List: http://paleo.sscnet. ucla .edu/ucmascPubs. htm

I'm no t going to get more money. I'm not going to get more cops. I haveto be better at using what I have, and that's what predictive policing is

about ... If this old street cop can change the way that he thinks about

this stuff, then I know that my [officers] can do the same.· Los Angeles Police Chief Charlie Beck

831.331.4550 info red ol.com www. red ol.c:om



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PredPol in the News:

THE PREDICTIVE POLICING COMPANY.'"

TIME ~ ~NBC

( 1 ~ S ®CBS Evening News- National, March 2012 ("il's not how many people you catch, it's how many

crimes you prevent") I http:llwww.cbsnews.comtvicteolwatch/?ict=7404996n

NPR ·Al l Things Considered, July 2013 ("Older systems show where crime has been. This

system looks forward.")h ip: /www. npr.orq/2 0 13/0 7/26/2058 356 7 41can-softv.la re-that-predicts- crime-pass-co nsli tuliona -muster

The Economist, July 2013 ("Its easier to foresee wrongdoing and spot likely wrongdoers.")http 1/www .econom s .com/news/brie finq/2158204 2 -it-q ettinq-e a sie r foresee-wrong doing-a nd-spot-lik.ely-wro ngdo e s-d o nt

even-think-about-it

NBC News- Los Angeles, January 2013 ("a cliff-like drop when predictive policing began")hllp://www.nbctosangefes.com/news/!ocai/LAPD-Chief-Chartie-Beck-Prediclive-Poticinq-Forecasts-Crime-

185970452.html

Seattle Times, February 2013 ("will allow us to be proactive rather than reactive")htto://bloqs.seatttetimes.com/today/2013/02/seallfe-police-tUrn-to-computer-software-to-fiqht-crime/

NBC News- Columbia, SC: First City in South to Use Technology to Predict Crime, May2013 ("going to take us to the next level when it comes to the absence of crime in this city")http: lwww.wistv. com/storv/2 227 7055/po!ice-usi nq-tech n o!ogy-to-help-pred ict-crime

LA, Daily News, Alhambra Cops Test Drive Predictive Policing, May 2013 ("PredPol might

tell us here's an area to focus on today. That may be different from what a police officer knowsbased on hot-spot data within the last 30 days.") http://www.dailynews.com/newslci 23243829/cops-test

drive-preemptive-poHcinq?source=rss&utm source=feedly

BBC -The

Ageof

Big Data, March 2013 ("Crime data represents a treasure trove of potentialinformation for understanding the nature of crime.")http://www.bbc.eo.uk/iplayer/episode/b01rt4c7/Horizon 20122013 The Age of Big Data/

MIT's Technology Review, June 2012 ("we are seeing a tipping point")http://www.technofoqyreview.com/news/428354/!a-cops-embrace-crime-predicling-alqorithml?ref=rss

Associated Press- National, "Sci-fi Policing," June 2012 ("early successes could serve as amodel for cash-strapped agencies")http://articles.bostoncom/2012-07-02fbusiness/32493939 1 crime-mapping-patrol-officers-police

Time Magazine - National, "Invention Issue," November 2011 ("getting ahead of the bad guys")http://www.time.com/lime/maqazine/article/O 9171 2099708-13 OO.html

New York Times, August 2011 ("we have to deploy our resources in a more effective way")

http://www. nytimes.com/2011/08/16/us/16police.html? r=1

news



Q PREDPOL" THE PREDICTIVE POLICING COMPANY.'"

More Practical & More

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Evolution of Policing

This is the next era ofpolicing. , ,Very soon, we wdl be using a predictive policing model where, by studying real-time cnme patterns, we

can anticipate where a cn·me is likely to occur_

-WilliAmBullon, f o r m . . r C n r r u n i ~ • i < m < > f of NYPO mrtd Form.,., Chief oflAPD

LA PO's toolkit now relies heavily on predictive policing.-Ma)'<X Anto-m-o Vo1hu.ig<lsa ,loiAngef<".s (al!fom;.;,

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Q PREDPOL' THE PREDICTIVE POLICING C O M P A N Y . ~

PredPol Predicts Gun Violence With OpenGovernment DataPredPol accurately predicts where and when crimes are most likely to occur. It Is the only predictive analytic system that has repeatedly

demonstrated the ability to predi ct more than double the amount of crime In head-to-head field deployments against dedicated

crime analyst s with all of the tools of the trade. PredPol can now deliver the same predictive accuracy for gun violence using unique

mathematical methods. A study of Chicago data shows that PredPol successfully predicts 50% of gun homicides by flagging in real-time

only 10.3% of city locations. Knowing where and when gun homicides are most likely to occur empowers Jaw enforcement to use their

knowledge, skills and expe rience to disrupt gun crime before it happens.

rl"he Challenge ofGun Miolence-- - ~ ~ ~ - ~ - ~

In 2012 there were 507 homicides and 12,137 crimes involving handguns in Chicago, Illinois. In light of recent gun viOlence ac ross the

country InclUding school s hoot ings and as police departments across the nation face tighter budgets and scarcer resources, reducing

violence and gun related crime from th_e current high levels observed in cities like Chicago Is a significant challenge:'

While no one strategy may serve as a silver bullet, PredPol makes possible the efficient distribution of limited policing resources.

Development s in mathematical and statistical modeling, high-performance cloud computing, and GPS-enabled mobile devices make it

possible for real-time crime forecasts to be at the disposal of officers in the field. PredPol technology gives officers the best chance to be

in the right place, at the right time, to stop crime before it occurs.

The purpose of this white paper is to show how big data, predictive analytics, and hotspot policing are currently used in practice, and

how they are adapted for the purpose of suppressinggun violence in a city like Chicago. Our methodology allows for several years

of crime data and many different crime types to be systematically combined to yield accurate, real-time crime predictions. PredPol

predictions provide tactically clear recommendat ions about where and when to deploy precious police resources. We illustrate the

methodol ogy with a large, open -source data set from the Chicago Pollee Department.

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Figure 1. Prediction map in 2011:1% (red

boxes), 2% (red and orange boxes), and 3%

(red, orange and yellow boxes) of Chicago

flagged, corresponding to 6km2, 12km2

,

and 18km2• The percentage of homicides

predicted at these thresholds are 10%,

13%, and 20%.

1of4

831.331.4550 [email protected] 1www.predpol.com PREDICT CRIME IN REAL TIME®

. - - -



Q PREDPOL" THE PREDICTIVE POLICING C O M P A N Y . ~

-

Rr:eCIRol Success in tile liielct -

PredPol has been extensively evaluated using historical crime data and controlled field trials with multiple law enforcement agencies.

Analyses demonstrate that PredPol o utperfo rms existing methods for forecasting crime such as kernel density estimation, which

underlies most crime hot spot mapping programs. Controlled trials also show that PredPol predicts mo re than two-times as much crime

as a trained crime analyst.

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Figure 2. Property crime rates fell during

the period of PredPol deployment in

LAPD's Foothill Division. Serious property

crimes include burglary, car theft and

burglary/theft from vehicle. Comparisons

are between Foothill Division and six other

geographically adjacent Divisions in LAPD .

The PredPol technology offers microscale, real-time geospatial intelligence, displayed in a way that is tactically clear to supervisors and

patrol officers; unlike current models such as hotspot maps that are often underused because they are ambiguous and confusing. Overthe course of a six-month period of deployment from November 2011 to May 2012 with the Los Angeles Police Dep artment (LAPD),

patrol officers nearly doubled the amount of time on predictive missions from 48 hours per week to 88 hours per week. Setting clear

mission expectations and regular reinforcement of mission priorities from supervisors were important during this process. Crime rates

can be impac ted significantly by the use of PredPol. In the two longest-standing deployments, with the Santa Cruz and Los Angeles

Police Departments, declines ranging from -12% to -25% during the.same period in the previous year were seen In burglary, car theft

and theft from motor vehicle (Figure 2). PredPol serves as a force-multiplier in allowing officers to use their expert knowledge, skills and

experience in a timely manner in the highest risk locations on the landscape.

Rr:ecticting Gun Ntiolence witl:i Rr:eCIRol :""

PredPol is based upon a marked point process methodology that allows for several years of crime data, and multiple crime types, to be

utilized by hotspot maps, incorporating both fixed risk heterogeneity across the city and temporally dynamic risk. Chronic hotspots are

long term in duration and necessitate problem-oriented policing strategies to address the root causes of crime. Temporary hotspots,

on the other hand, last on the time scale of days to weeks. Policlng strategies must be able to anticipate emerging trends to dis rupt

emerging hotspots. Without predictive analytics, officers end up chasing yesterday's crime. The lo s Angeles Police Depar tment updates

its PredPol models for every 8-hour shift and directs patrols accordingly. In many instances there may be little difference in the situation

and intent sep arating gun violence and a homicide. The occurrence of serious violent crimes may provide as much, or more, information

2 of 4

811,331.45!0 llnf<>@predpol.<omlwww.predpol.<om PREDICT CRIME IN REAL TIME<>~ ~ - ~

-



Q PREDPOL' THE PREDICTIVE POLICING COMPANY."

on where and when homicides are most likely to occur as actual homicides themselves . We take the following marked point process

approach to modeling the intensity of homicides. Given marks, M, representing crime types believed to be precursory to homicide, the

intensity of homicide is modeled as:

;\(x, y, t) = ~ t ( x , y) +L (x- x1, y - y1, t - t1, M1)

t>ti

The background rate JJX,y represents fixed risk across the city, wher eas the kernel g(x,y,t) dete rmines the time and spatial scales over

which near.repeat crime pat terns occur.

CHicago Gun €rime 8l Gun l±lomiciCie ·- " - - - ~ ~ - - ~ -

We apply PredPol to an open source data set consisting of 38,740 violent crimes occur ring in Chicago, Illinois in the years 2009, 2010, and

2011. In total there are 1,331 homicides and the following gun related crimes with · 'handgun" in the description field: 17,020 robberies,

6,560 assaults, 8,252 weapons violations, 5,274 batteries, and 303 criminal sexual assaults. The data can be downloaded from the

website "h ttps: Idata d yofch icago.org/Publ i -Safety/Crimes-2001-to-p resen lij zp-qBt2 ,

Homicide Robbery Assault Weapons Battery

5th 4th 3rd 1st 2nd Table 1. Most significant pre cursor crimes

to PredPol predictions of gun homicides.

Crimes involving guns continue to have an Impact on future gun homicides for 30-100 days and risk spreads over as much as 1/2

mile in area . With knowledge of the increase in crime risk following precur sory gun-relat ed crimes, officers are in a better position to

deter more serious.gun crimes through directed patrol. in Table 1, we display the crime types that comprise the highest portion of

the estimated risk of homicide and thus play the largest role in predicting homicide. We note that past homicides are not the highest

predictor of future homicides rather weapons violations, batteries, and then assaults are the highest predictors in decreasing order.

PredPol predictions leverage these relationships allowing resources to be directed to where they have the greatest potential impact.

PredPol predicts a great er number of gun homicides using its unique prediction methodology compared with alternative approac hes.

Figure 3 compares the predictive accuracy of PredPol against both 3-month an d 3-week kernel density hotspot maps. As police

resource s increase, more of the city can by flagged for directed pat rol and the number of gun homicides correctly predicted increases.

PredPol successfully predicts 50% of gun homicides by flagging in real-time only 10.3% of Chicago.

3of 4

831,331.4550 1 [email protected] 1www.predpol.com PREDICT CRIME IN REAL TIME®



Q PREDPOL'

- - - - - - - - - ~ p ~ , ~ , d ~ < ~ I ; ~ , , ~ A ~ ~ ~ " ~ ' ~ a o ~ y ____________

SO - P r edPo l

-Random

70- Hotsp(ll Mop (3 month) i- Hotspct Map (3 week) !

1'loo

"

2 40

45 67.5 90 112.5

Area or Chicago /lagged (km2)

135 157.5

"

THE PREDICTIVE POLICING C O M P A N Y . ~

Figure 3. Percentage of crime

occurring within flagged areas vs.

total area of Chicago flagged with

predictions using 2011 historical data.

PredPol accurately predicts a greater

number of gun homicides at all

levels of deployment compared with

standard hotspotting.

- ---Rrec.fBol Guictes Bolice Rractice ----------- - -

PredPol fits seamlessly into existing police practice and creates strategic and tactical opportunities that would not exist otherwise. PredPol

accurately predicts where and when gun homicides are most likely to occur. Police can theref ore position their resources to make the best

use of officer knowledge, skillsand experience to disrupt gun violence. Moreover, the PredPol methodology creates clear tactical guidelines

to focus on weapons violations, assaul t and battery as the major drivers of gun homicides. In a manner similar to 'broken-windows' policing,

targeting these precursor crimes can have a significant impact on gun homicide and ultimately on crime reduction.

Documents

SFPD PredPol emails 2.pdf