Where is Digital Policing Today?
Editor’s Note: The following is excerpted from Policing 2025: Envisioning a New Framework for Investigations, (©2020 IDC #US46946220 2) a recent white paper created by Alison Brooks at IDC and sponsored by Cellebrite. The paper may be downloaded in its entirety here.
Law enforcement agencies today find themselves at a critical juncture as they wrestle with three profound challenges:
- The complexity of digitally mediated crime in the 21st century is extremely challenging. Law enforcement’s central goals — to protect the communities they serve, maintain public order and safety, solve crimes, and bring criminals to justice in the courts — are becoming harder to deliver on as agencies struggle to manage the growth and variety of digital assets involved in investigations.
- With data privacy and data manipulation scandals on the rise, agencies around the world are having to address a “techlash” against surveillance. Agencies are thus increasingly having to tightly scope “acceptable use” policies to leverage next-generation technological capabilities.
- Pressures to fundamentally rethink the role of law enforcement, and to re-establish trust, have gained momentum globally.
Combined, these challenges strike at the core of policing. But they also present an opportunity to reenvision a new digital policing framework. More now than ever, law enforcement agencies need solutions that can address the complexities of digital investigations, help manage the volumes of data, and solve crimes in a timely and legal fashion.
Agencies must begin by asking a series of difficult questions:
- What must policing look like in 2025?
- How can law enforcement vastly better demonstrate its value to the community?
- How can law enforcement professionals underscore the value that technology investment delivers to communities?
- What is needed now to start delivering on that vision?
At a minimum, policing 2025 must be trusted, ethical, digital, and intelligent. Core operational technologies — increasingly embedded with artificial intelligence (AI) and machine learning (ML), and rendered in real time using data visualization tools — must be predicated on digital trust. To meet the ever-evolving tech-mediated criminal landscape, policing 2025 will need to be evidence based, data driven, usable, and intelligence led. By 2025, the future of policing intelligence will reside in digital intelligence platforms. This white paper examines how digital intelligence platforms can provide the strategic vectors through which agencies deliver on a reenvisioned policing framework for 2025 and beyond.
Go to our Policing 2025 page to continue watching the discussion with Mark Gambill and Alison Brooks on establishing a new digital policing framework with Digital Intelligence.
Where is Policing Today? At the Nexus of Confluent Crises, Coping with the Digital Deluge
Criminal investigations are increasingly becoming unmanageable given not only the volume and variety of digital assets coming into agencies but also the velocity at which those digital assets arrive. This includes net-new data sources such as large, heterogeneous data sets generated by communications service providers, cloud service providers, laptops, and smartphones, as well as the skyrocketing volume of video and photographic evidence.
The above image illustrates IDC’s understanding of the data-driven policing market landscape. Consider the middle layer: “next-generation data sources, management, and advanced analytics.” Within this slice of the market, we see a plethora of video sources, sensors, and biometrics, all of which need to be managed within a digital evidence platform leveraging complex analytical tools like AI to rein in the digital deluge. Many of these digital assets, and the solutions to make sense of them, did not exist even five years ago.
Amid this technology explosion, it is also clear that crime today, and the resulting investigations, is far more complex, mobile, digital, and global in nature. Furthermore, many of the same solutions — mobile technology, advanced analytics, and cryptocurrency, for example — are both the conduits of crime and the tools used to investigate those crimes. Using the internet to engage in cybercrime and fraud, for instance, is a growing problem for law enforcement, exacerbated by the pandemic. Both INTERPOL and the United Nations have cited increases in cybercrime ranging from 30% to 600% during COVID-19, depending on the particular type of cybercrime.
Stymied by Siloed/Unusable/Underutilized Data
Underutilized data is commonly cited as one of the biggest challenges in policing. Many agencies are:
- Unable to see recurring patterns because of poor institutional knowledge retention and dissemination
- Unable to synthesize diverse internal and external data sources into information, often across jurisdictional boundaries, resulting in substandard decision making and situational awareness
- Taking too long to move from data to information to knowledge to wisdom, resulting in high latency in decision making and an inability to act within needed time windows
- Lacking enough granular visibility into end-to-end workflow to be able to automate
- Lacking the big picture (Data usage is low, and data exists in pockets or resides in the hands of a select few.)
In addition, there are insidious cultural challenges such as:
- Data aversion, or what some have termed the ostrich effect, whereby valuable information is ignored in lieu of gut feeling
- Lack of data literacy and the resultant inability to have a common language around data
- Lack of data intelligence and the resultant mistrust of data, information, and insight
Complicating the situation further, agencies struggle with a mix of core legacy technology (CAD and RMS) that can be 20 years old and next-generation technology like body-worn video cameras. Not only do these thwart operations, but the default tends to skew to manual workflow. For many agencies, day-to-day operations and workflow remain largely manual, disconnected, and archaic. Contrary to popular public opinion, most police agencies do not currently operate like CSI-type televised crime dramas.
Propelled to Digital by COVID-19
Like much of the broader business community, the COVID-19 pandemic forced police agencies to digitally transform at a breakneck pace. In the first stage of the pandemic, we saw agency IT scrambling to leverage underutilized but now crucial technology such as mobile solutions, remote working solutions, and virtual tools and to procure technology such as enhanced networking capabilities and software-defined security solutions that would allow the workforce to function virtually. The pandemic highlighted the need to digitally transform to share information and data assets internationally and to work smarter across multiple jurisdictions and nation-states. Last, it fundamentally challenged the traditional, in-person, face-to-face police culture.
For many police agencies, COVID-19 pointedly highlighted gaps in digital maturity. Even agencies with very advanced digital workflows found themselves unable to provide core services because of fundamental gaps in core infrastructure — that is, missing elements of the tech-stack foundations — that would allow them to work remotely and securely. Police agencies find themselves on different points of the digital transformation (DX) maturity continuum. They also struggle to find a clear path to reinvention and transformation.
Coping with the Techlash Against Surveillance
While residents are keen to take advantage of “intelligence everywhere” in a consumer capacity, they are not keen on state intelligence/surveillance everywhere. As technology development continues to outpace the regulatory environment — artificial intelligence and facial recognition are good examples of this phenomenon — there are urgent calls from technology providers, privacy advocates, and police agencies alike to frame the appropriate legal, policy, and ethical environments to proactively and thoughtfully guide technology deployment.
Artificial intelligence, critical to forward-thinking digital policing, is often perceived as a black box technology, with a lingering fear of unintended negative consequences, including the ones not yet known or experienced. Using algorithms to automate important decisions based on machine learning of data that is biased risks biasing the decisions and raises important questions about AI ethics.
Part 2 in this series of excerpts will look at reenvisioning policing 2025 to be ethical, digital, and intelligent.
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