Most working in the emergency management and response field will understand that the manner in which law enforcement collects, processes, and uses data has a direct impact on its ability to respond effectively to every day emergencies as well as major disasters.
Put simply, when data use is effective, law enforcement is able to make better decisions more quickly, and usually that is a win for public safety.
But some recent analysis has revealed major problems with the way in which law enforcement uses data, and this is a matter of concern for all professionals working in the sector.
What issues have been identified?
The report from tech giant IBM reveals three main concerns with the present data systems and capabilities of law enforcement agencies:
- Most software is out of date, and in many cases no longer supported by the developer, meaning it is not able to be updated or troubleshooted if something goes wrong.
- Most software is not able to be interfaced with other departments’ systems and databases, meaning that agencies are not able to share and coordinate information effectively.
- Most software programs contain information that is out of date or unverified, meaning that decisions that are made on the basis of this data are un- or ill-founded.
The concerns raised by these findings are at once clear, and they have profound implications for the manner in which law enforcement is able to handle emergencies and disasters.
Indeed, not only does this prevent law enforcement agencies from properly sharing information about, say, gang violence in certain areas of a city, but it also prevents those same agencies from making good decisions about how to deploy personnel and resources in, say, mass violence terror incidents.
Why is data so important to public safety?
Data is critical to public safety for a number and variety of reasons, and that importance is only likely to compound considering the enormous rate of growth of existing data (90% of data in existence was created in the past two years, and a further 2.5 quintillion bytes of data are created each day).
In addition to helping law enforcement agencies make more informed decisions about their day to day work, data is also a vital source of information when an emergency threatens a large number of people.
Take the Boston Marathon Bombings, for example (an event that I, for one, experienced first hand). In the 24 hours following the explosion at the finish line, the Boston Police Department had collected nearly half a million separate images and videos of the incident before, during, and after the bombing. This mass of forensic information allowed BPD to catch the perpetrators and return Boston to normalcy in a remarkably short amount of time, given the circumstances. Data availability and analysis were absolutely critical to this task.
A turning point for data use in law enforcement
“We have reached a real inflection point where [law enforcement agencies] know they need to transform how they manage information.”Tim Paydos, Vice President of Worldwide Government Industry Solutions at IBM
This realization must be capitalized upon. As it stands, law enforcement agencies are held back by old information systems that do very little (if anything) to further interagency data cooperation and collaboration. The systems prevent effective data sharing, analysis, and management – all the while costing a disproportionate amount of money for the benefit they ultimately deliver (or purport to, anyway).
These problems are most acute in small and medium-sized agencies. The investment required to tackle these and related problems is considerable, and it is not only the ongoing costs of data systems that need to be taken into account. To be brought up to scratch, most departments will require a large amount of capital upfront, and the reality is that such an investment is beyond the resources of the vast majority of departments across the United States. Concerningly, of the 18,000 law enforcement agencies in the US, 16,000 of them have the same technology and data needs as two of the biggest agencies, the New York Police Department (NYPD) and Los Angeles Police Department (LAPD).
Even if capital were able to be raised, there remains an issue of expertise. Unfortunately, there is not sufficient knowledge within law enforcement of data management and practices, and that means that even if data were available on up to date systems, there would be a large knowledge gap in actually knowing how to use it. Again, this is a problem that would require time and resources to overcome.
What can be done to improve data use in law enforcement?
Despite the nature and prevalence of the concerns identified, effective data use in law enforcement – especially in the disaster context – is not a lost cause.
Cloud computing, for one thing, provides an excellent solution for law enforcement agencies – particularly those strapped for cash – as cloud solutions do not require large capital investments for on-site servers, and updates are able to be implemented automatically and are usually included in the subscription costs. Furthermore, cloud integrations are widely available, meaning the data that is collected and stored can be used more effectively by a greater number of people.
Parallel to developments in cloud technology have been developments in artificial intelligence (AI). The use of AI in law enforcement has been a contentious subject, but the fact remains that the technology is already proving useful in decision-making and other critical functions within law enforcement agencies, such as conditional resource allocation.
Cognitive systems, in particular, could have exponential benefits in disaster situations as they are able to aggregate, analyze, and propose actions based on mass quantities of data – far more than any human could handle at one time. Moreover, cognitive systems actually learn from the human inputs that they receive, ultimately getting more effective (or ‘smarter’) the more they are used. This is good news for disaster response because it means that technology can be programmed to learn from the mistakes of previous disaster responses – something that humans need to be better at in general.
What steps can law enforcement leaders take to improve their data practices?
While some departments may be able to invest heavily in data improvements, most will be looking for cost-effective solutions that are minimally disruptive.
For agencies with a budget for improvements, leaders should look to large technology companies for their bespoke solutions. IBM, for one, is building a platform for law enforcement that aggregates data from the government (state and federal levels), commercial data sources, and public access data. Its main focus will be delivering visible data that helps law enforcement to contextualize the figures and make better decisions.
Elsewhere, and perhaps at a lower cost, law enforcement leaders can begin to implement better data management and practices in every day work, and that in turn will serve to enhance responses to infrequent major emergencies and disasters.
Indeed, Paydos is urging ‘agency leaders to take a deliberate and thoughtful approach to their data and analytics initiatives.’ His advice is to identify one thing that, if done better, would provide real value to the agency and work on that first. Improvements should be incremental, as a complete system overhaul may overwhelm dependent systems as well as the people that are responsible for using them.
Whatever the case may be with budgets, one thing is clear. All law enforcement agencies have something to improve upon in their current data practices, and the importance of addressing persistent weaknesses in data systems cannot be stressed enough.
After all, these weaknesses compromise not only law enforcement’s ability to deal with day to day emergencies, but also its ability to respond adequately to the next major disasters.