The Origins of Information Sharing
In terms of technology and the development and deployment within law enforcement, I have been fortunate to have been involved in this space for a long time and throughout most of that time I have observed that change especially technological change has traditionally come about in an evolutionary process.
When I look back on the early conversations we had on information sharing, the initial goal was to solve the information sharing challenge within a given jurisdiction. This challenge was because over time a series of internal disparate databases had sprung up (i.e. homicide data bases, gang data bases, sex offender registries, etc.) to solve specific problems. However, none of these disparate sources were communicating with each other. This meant that if an investigator was looking for a bad guy they would have to sit down and search multiple databases, using multiple interfaces and then have to manually correlate the results. All that proved to be time consuming, labor intensive and inefficient, this was a problem ripe for a technological solution.
There was also a belief that if you could solve the internal jurisdictional information sharing challenge, we could then move on to sharing data outside of the jurisdiction but within the county (i.e., the city needs to share with the county). Once that was resolved, the next logical step was addressing the intrastate sharing (this city/county needs to share with other city/counties, DPS needs to share across the state, etc.). Once intrastate sharing was solved that would lead to Interstate sharing, interstate sharing can lead to federal sharing etc. All small steps but the benefits to solving this challenge were and remain huge.
Unfortunately, when we started working on the practical implementation of information sharing many people were just not ready. Change is difficult and even more difficult within institutions that have a long history of success and internal process. We were fortunate, however, to have been able to work with visionary Chiefs (like Bill Bratton in Los Angeles), forward thinking Law Enforcement consortiums (ILJOC in Orange County, FDLE in Florida) and Leadership Organizations like IACP, Major Cities Chiefs and Major County Sheriffs that recognized the game changing role of information sharing. It was through that leadership, along with many others, that allowed the community to experience the information sharing paradigm.
Changing Attitudes
Sharing information today is table stakes, you just have to do it. I think it would be difficult today to find any jurisdiction that is not participating in some information sharing initiative. It is a capability that can give us a view of the bigger picture, enhance situational awareness and deliver more investigative flexibility. Overtime people began to embrace the power of technology, the paradigm shifted most definitely after 9/11 when the whole sharing initiative became incredibly important.
Technology Advocates
What has been revolutionary rather than evolutionary in the embracement of technology is the younger workforce. A generational influence. A workforce that is accustomed to using things like facial recognition technology on their phones and are comfortable with the concept of relationship association analytics to find non-obvious relationships. This is a generation that has grown up on Facebook, LinkedIn, YouTube and Google search. All data they want in their lives is easily and quickly available on apps, tablets, TVs etc. They have a high expectation of how IT works. And when they enter law enforcement, they expect technology to play a major role.
A common search capability across all data is essential to making onboarding, training, and retention run smoothly for younger employees. Their expectation levels for IT systems usability and performance are different to older generations. They have little patience for substandard user experiences and are not afraid to express these opinions. For them technology is not a nice to have, it’s a must have. On the other side of the coin, more mature law enforcement professionals who were brought up using a PC in the 80’s are also making the argument for the greater use of technology.
The Times They Are a Changing and the Explosion of Big Data
The one thing I have always believed is that the promise of technology is that it can move faster than the speed of threat. However, the challenge is how quickly can people assimilate what the technology is telling us.
Currently we are in the midst of one of the most prolific trends since the computing revolution, the explosive growth of big data. While this is a trend that virtually touches every sector both public and private, it is incredibly valuable to the law enforcement community. This trend is not only affecting traditional LE sources like RMS, court citations, wants and warrants databases and surveillance data, but it is also opening up new avenues of insight from areas like open source, call data records, dark web, consolidated commercial offerings (think LexisNexis, Thomson Reuters), public data (business licenses, utilities, hunting and fishing licenses) crowdsource, and many more. This trend is happening everywhere, in fact over the next five years up to 2025, global data creation is projected to grow to more than 180 zettabytes (that’s 1 with 21 zeros). The question is how can LE best take advantage of this trend?
AI and Law Enforcement
Provided this ocean of data that can be made available, the question becomes what is the most effective way LE can assimilate it to their advantage. If, for example, during an investigation you know you have to “connect the dots” but there are 4 million dots, yet you only care about 4 of them how do you sort and sift to find the critical dots?
It is without debate that, in order to significantly unlock and action the insight within this data growth paradigm, Artificial Intelligence (AI) / Machine Learning (ML) must play a significant role. In fact, many approaches to date have included some form of AI/ML.
We could spend hours in debate bestowing the pros and cons of AI and ML, and spend even longer discussing what is really “Artificial”, however, I believe fundamentally that in order for AI/ML to truly become the best discipline and the most effective technological assist for the LE community, we have to ensure that we are building a new AI, one that includes an auditable justification layer. This justification layer ensures that the steps the AI engine took in reaching its conclusions are based on a set of evidentiary inputs; are well documented in readable in human form; that the engine reached its conclusions free of bias; and that every step is auditable. In my opinion if it doesn’t provide that level of accountability, it’s not really AI.
Given this rubric the role that AI can play is limitless, whether it’s in providing identity deconfliction, deep dive visual analytics, object consolidation, facial recognition, or tactical lead generation (as just a few exemplar’s).
Time-Based Data
Based on these global trends, what is clear is that data is never going to get any smaller and law enforcement needs to be in a position to assimilate all of the data it possesses and collects. As the proliferation of big data continues, one of the fastest growing data types across the globe is time-based (i.e., audio, video, waveform) data. This data can play an important role in everything from critical infrastructure protection and security to human trafficking and exploitation. As such the need to index, search, analyze, and unlock insights from and respond to this data is growing in importance and necessity. This is another area where AI can and will become the enabler.
Currently it feels that video analytics is an underserved discipline that will become the next frontier for breakthrough technology, especially with the advent of 5G/B5G technology and the study of Vision AI. I think wearables in car, surveillance, CCTV, drones will all play a more important evidentiary role – they can provide a more complete picture.
Why Technology Can Help Solve Cold Cases
It is widely believed that of all the new digital data created in the last 10 years less than 10% of that data has ever been analyzed. – imagine what can be discovered when you can unlock greater insights within that data.
Except for the utilization of DNA, I think the application of AI technology on cold cases has the possibility to be game changing. Specifically in cases where the bulk of the data associated with a cold case is information around individual interrogation, witness statements and historical documents. The power of an AI engine to consume vast amounts of both structured and unstructured data, correlate individual and witness statements and details given at specific times, discover and highlight irregularities, inconsistencies and anomalistic patterns can provide a new avenue of lead generation.
Privacy and Predictive Policing
There is a lot of discussion and concern right now about the use of Facial Recognition technology, specifically in reference to privacy, individual rights and bias. Most everyone I speak with believes that facial recognition technology is critically important within specific use cases. If for example there is video of an individual committing a crime, the need to identify the individual is important in keeping the community safe and facilitating an arrest. If there is a search on for individuals that are on watch lists, or an Alzheimer patient that has walked away for a care facility, the need to scan transportation centers and populated areas are essential. In the time of pandemics, the ability to monitor quarantine or hot zones is a must have, given the need to provide critical infrastructure protection identifying individuals trying to gain access to restricted areas feels like a priority.
But I do understand the issues regarding privacy, it is clear that you can’t have 100% protection and 100% privacy, this is an issue of balance. According to a study by Safety.com the average person in the US is recorded on camera over 230 times a week. But privacy is an issue that can be accommodated through technology, to abandon or legislate the restriction or removal of critical technology like facial recognition, feels like throwing the baby out with the bath water. Developing new forms of facial recognition technology that allows for the anonymization of individual identity during the collection process and provides auditable results that are fee of bias are critical in getting the community to feel comfortable and supportive.
It is also incumbent on vendors and integrators not to overpromise on their offerings. I learned a long time ago never confuse marketing with delivery. Predictive policing which was the hot topic a few years back, is a good example. The reality of predictive policing is that it is fundamentally enhanced pattern analysis (i.e., network science, relationships of relationships, cause and effect), something that machines are very good at.
As example, identifying that more and more cars are being stolen from a particular shopping centre parking lot during the hours 6PM-8PM on Tuesdays is a pattern. Further enhancement analysis can determine that the likelihood of theft goes up on cars of a specific make, model and year, more likely on nights when there is a covered moon, or a light rain (weather conditions). Put a bait car with surveillance on it in the parking lot that fit those conditions and you are likely to get a result. That’s a form of predictive policing.
On the fear side and based on some of the vendor marketing, people were making comparisons with the Tom Cruise film Minority Report - a specialized police department which apprehends criminals based on foreknowledge. Obviously, that is not how it works. Enhanced pattern analysis can contribute to predictive policing and in the hands of skilled analysts and investigators is a powerful tool.
Final Words
Technology is most effective when it is utilized as an augmentation tool in support of the overall Law Enforcement resource lifecycle, from most advanced to the most novice of law enforcement officers. It can assist the novice in where to look, recommend perhaps what to look for, it can quickly identify patterns, and help to amplify weak signals in the information. Yet, it can also supplement the seasoned professional by producing results, providing visual hypothesis, generate potential leads all at machine speed and scale and all within the constraints of audit and compliance laws and regulations pertaining to data. Classified, open and commercial sources coming together to make today’s law enforcement officers more data aware and tech savvy than ever before. Using technology as a skills enhancer, improves the probability for keeping people, assets, and networks safe are for greatly enhancing our communities.
About the Author
Robert Griffin is currently the Managing Partner for DVI Equity Partners a Private Equity Investment arm of Diamond Ventures. As the Managing Partner he focuses on technology investments that are concentrated on delivering disruptive or disintermediating technology in areas of B2B, critical infrastructure, national security, and emerging trends.
Mr. Griffin has been a key player and successful serial entrepreneur in the Software and Services industry for more than 40 years. In Oct. of 2011 he facilitated the sale of his company, i2, to IBM into their Industry Solutions, Software Product Group, where he remained as the General Manager for the Safer Planet and Smarter Cities brand until February of 2017. Mr. Griffin had the global leadership responsibility for solutions that address the Intelligence and Law Enforcement Industries, for the development and deployment of Counter Fraud and Financial Crimes solutions and for solutions that make cities more resilient and sustainable (Smarter Cities).
Mr. Griffin conducted his undergraduate studies in Business Management at Franklin Pierce College in New Hampshire. He is a distinguished alumnus of the Naval Post Graduate School’s Center for Homeland Defense and Security’s Executive Leadership Program (ELP 1001) in Monterey, California, the Founder of the Network Science Research Center and the Center for Resiliency and Sustainability while at IBM in partnership with MIT, a Distinguished Lecturer at the Johns Hopkins School of Education, a Distinguished Lecturer at the University of Arizona’s Eller School of Business, has addressed the World Economic Forum on the use of technology for critical infrastructure protection and is a graduate of the NASDAQ Mindshare Entrepreneur program in Washington DC.
Mr. Griffin is a on the Board of Trustees for the Intelligence and National Security Foundation (INSF), a former member of the Board of Directors for the Intelligence and National Security Alliance (INSA), a member of the Board of Directors for the National Cyber Forensics and Training Alliance (NCFTA), the Board of Advisors to the Asian Pacific Institute for Resiliency and Sustainability (AIRS) and a member of the Board of Advisors for the University of Arizona’s Tech Launch Arizona (TLA).
Mr. Griffin has served on the Board of Advisors to the Adjutant General for the State of Hawaii, on the National Advisory Board for InfraGard (a public-private non-profit between US Businesses and the FBI), as a member of the Whitehouse taskforce on Human Trafficking on the Internet and has twice been the recipient in the UK of the Queen’s award for Enterprise Innovation. He was the 2001 Ernst & Young Entrepreneur of the Year for Greater Washington DC and holds several U.S. patents focused on Law Enforcement and Intelligence and carries an active TS security clearance
