Predictive technology: helping law enforcement to detect crime and keep communities safe.

Posted by:
Kannan Jayaraman

Publish Date:
12 Oct, 2021

Policing and regional governments are under pressure operationally and financially. Law enforcement remains complex, becoming more multi-agency and more international as a result of global, economic, and social media. The global uptake of social media has provided exposure to more intelligent crime needing a rapid change to local accountability. Borders of crime have been extended, financial cuts and cadence are still increasing, and antisocial behaviour is rising against a backdrop of pandemics, leading to high unemployment and financial hardship. Senior police officers have many new things to digest and manage against this backdrop, pushing proactive policing strategies and best practices to deliver the order to communities.

Here are some samples of concerns facing public-serving business leaders:

  • How can we optimise better our resources?
  • How can we collaborate further with the regional government?
  • How can we adopt better analytics and use our data more collaboratively?
  • How can we ensure the policy is met?
  • How can we be more integrated?

Information is vital to the success of law enforcement. Law enforcement must make smart decisions supporting and enhancing their practices and processes to reduce cost but increase productivity and efficiency. Finding the optimal solutions can also be a significant challenge to those who are not non-IT related professionals. Powerful IT solutions will always be present in the world of law enforcement and in the current financial climates globally must demonstrate the rapid return on investment with lower total cost ownership (TCO). The pressure to justify such solutions remains – but the need to justify the cost over police effectiveness also remains. The following paper will look at the needs and opportunities for transformation and operational effectiveness – aiming to clarify thinking to outline needs to vision ensuring that you achieve a successful law enforcement service and business efficiency outcomes.

Focus

No person or business should choose a technical solution to any problem until requirements are clearly understood. Delivering a needs analysis and GAP analysis is the best starting point detailing the as-is and to-be; the future point is very important, carefully measuring requirements over the short and long term. Today, in the technology market, it is clear organisations are still focused on moving from legacy to more modern solutions. Analysis, data, and social have seen us focus on artificial intelligence (AI), data lake strategies, and robotic process automation (RPA). However, many of the challenges today pre-change are routed in the historical decision-making process often bought by an individual, poorly configured, poorly maintained, and disparate. Many police organisations invest in IT to support just one key area of the business such as Asset Management, Incident Reporting, Evidence Management, and Finance.

It’s clear that a more holistic approach to thinking is being adopted due to the pressures of governance, policy and economics. Policing organisations are thinking smarter about the transformation of their organisations and processes. The deployment of cloud solutions, mobile data, analytics, and big data is very accessible allowing everyone to capture intelligence and knowledge across all communities.

Policing, Data, Analytics and AI

Law enforcement needs to improve technology to meet the changing needs of people and enable next-generation policing. This is about ensuring value, making services accessible for everyone to use, and for people to deliver in the most efficient and effective way. Emergency services across the UK have invested in technology far sooner than anticipated. Investment in new technologies is proving valuable to service improvement. Some are reducing channels to voice, text and video for emergency contact, and using self-service online transactions for all other contacts. The focus should be on the value of new technology, channels and functionality for meeting the needs of citizens and the community.

Other police services are seeing the benefits of more interactive websites which offer basic incident reporting, transactional services (such as licence applications, feedback), live chat, personalised content – including an individual history of police interactions – and also a means of contacting the police anonymously. For the police, the platform provides a means to develop relationships and communicate with the public, as well as tools for monitoring the progress of ongoing interactions. They are also using other digital options for contact and reporting, such as live chat, social media, SMS messaging, WhatsApp, chatbot messaging programmes, and smart technology. Virtual reality tools are being used to train officers in different scenarios. Many digital, data and IT strategies set out an approach for updating public contact platforms with enabling new technologies and integrating systems and data.

Social media provides an entirely alternate opportunity to engage with citizens. Finding the balance in social challenges often makes decision-makers and law enforcement uncomfortable in concluding on the right action to take the first time. Every criminal has unparalleled opportunities to find out information, share that information, collaborate, and plan. Chatter and Sentiment carry very valuable information exposing specific threats and crimes in the planning. Large volumes of data and information are communicated every second of every day – the new normal, placing a high demand for solutions that are more automated.

Cities are leveraging AI to ensure safety and security for their citizens while safeguarding the privacy and fundamental human rights. Social vulnerability, surveillance and predictive policing through AI is the most important implication for the future of cities and societies. There are doubts and uncertainties about the impact of AI on communities and cities, however, one cannot disconnect the discussions about surveillance and predictive policing from recent debates about the societal, ethical, and even geopolitical dimensions.

AI has recently helped create and deliver innovative police services, connect police forces to citizens, build trust, and strengthen associations with communities. There is a growing use of smart solutions such as biometrics, facial recognition, smart cameras, and video surveillance systems. A recent study found that smart technologies such as AI could help cities reduce crime by 30-40% and reduce response times for emergency services by 20-35%. The same study found that cities have started to invest in real-time crime mapping, crowd management and gunshot detection. Cities are making use of facial recognition and biometrics, in-car and body cameras for police (55%), drones and aerial surveillance (46%), and crowdsourcing crime reporting and emergency apps (39%) to ensure public safety. However, only 8% use data-driven policing.

The AI Global Surveillance (AIGS) Index 2019 states that 56 out of 176 countries used AI for surveillance for safe city platforms. The International Data Corporation (IDC) has predicted that by 2022, 40% of police agencies will use digital tools, such as live video streaming and shared workflows to support community safety and drive public confidence.

Cities are exploring capabilities to predict crime by analysing surveillance data and improving security. Cities already capture images for surveillance purposes, but now, by using AI, images can be analysed and acted on rapidly. Machine learning and big data analysis make it possible to navigate through voluminous data on crime and terrorism, to identify patterns, correlations, and trends. When the right relationships are in place, technology is the layer that supports law enforcement agencies to better deliver their job and trigger behaviour change. Ultimately, the goal is to create agile security systems that can detect crime or terrorism networks and suspicious activity, and even contribute to the effectiveness of justice systems.

In summary, prevention and reduction of crime can make communities more secure. Predictive solutions in regional government and policing can be the most efficient and effective way of keeping communities safe, increasing public trust and confidence in collaborative services while reducing response times. AI can improve the seamless interconnection between municipal bodies, cities where security systems are spread across police departments, firefighters, and other agencies or security entities who may benefit from AI that can detect complex patterns and connections between events in different departments. The safeguarding of the lives of police, law enforcers, community officers, and social care resources can use technologies such as video surveillance and robotic security devices for identifying and preventing potential threats. They can prevent crimes from happening and avoid putting the safety and lives of public servants at risk.

Blog Author

Kannan Jayaraman

EVP & Head of Digital Transformation, AI & Analytics

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