The complexity and scale of crime, cyber-crime included, in the public safety sector demands real-time responses; something that can’t be guaranteed entirely by human capability. As a consequence, the implementation of advanced technologies with artificial intelligence (AI) at the core has proven to be an excellent use case in public safety. According to a survey done by Accenture, 65% of citizens across countries like Germany, France, the US, UK, and Australia, want their governments to start leveraging AI to help fight public threats and boost security, both online and online.
With raw data at the heart of AI, an integrated data environment is required for use cases to be transformed into mission outcomes. For example, AI-based web crawlers can track cyber-criminals across the web and take down illicit or harmful online content. In public safety agencies, artificial intelligence can help increase both efficiency and productivity by automating mundane procedural and administrative tasks that are normally done by people.
Operations re-imagined in public safety agencies
Public safety agencies can leverage the power of AI to re-imagine operations via AI-based Labs such as the Accenture Federal Digital Studio; a turnkey solution that can help agencies identify new opportunities for using data in the public safety sector. In policing, for example, AI is morphing into operational areas like investigation management, intelligence, and case file preparation to free up time and enable law enforcement officers to focus on high-priority activities within the community.
According to a recent market report published by the HSRC, the Public Safety & Homeland Security market is estimated to grow from $431 billion in 2018 to $606 billion by 2024. Throughout the forecast period, dominating technologies like intrusion detection systems will become replaced by big data analytics and AI.
Given that it can process huge volumes of information at record speed, artificial intelligence is invaluable from a data analysis point of view. It can generate insights and identify patterns that the human eye can’t, thus enabling public safety agencies to better analyze unstructured data from videos and images to keep employees more focused on tasks with real value, such as create alerts to identify real threats.
AI-based innovation in public safety
Earlier this October, AI provider GreenKey Technologies (GK) partnered with public safety command software Motorola Solutions to provide 911 call center respondents with real-time emergency call transcriptions. CEO and founder of GreenKey, Anthony Tassone, mentioned that the purpose of the partnership was to lower administrative burdens and decrease response times for 911 respondents.
AI-based technologies are excellent at spotting patterns and identifying glitches that don’t fit into a specified pattern. Financial crimes such as account fraud and credit card fraud can be easily detected with AI machines, which can assess transactional reports and flag whether or not a certain transaction is valid or not.
To accelerate further innovation in the public safety sector, Israeli startup Waycare raised $7.21 million to improve city traffic with big data and AI. The role of AI in this scenario was to train Waycare’s algorithm to make sense of the historical data concerning road behavior, and use that information to identify anomalies. The end goal was to understand real-time traffic so that city officials can make informed decisions, such as make correlations between congestion and traffic light changes, and even spot neighborhoods that are predisposed to erratic driving; which could benefit from additional police presence and speed cameras to ensure more precise public safety.
Most public safety agencies have a fundamental service mission, and that is to do whatever is required to protect the citizens. Given this context, it’s no wonder that consumer-focused companies are looking to integrate AI-based chatbots into various customer support functions. Automating experiences is not the sole purpose of artificial intelligence because AI is not an all-in-one solution that can ensure safety at a click of a button. Before getting started, agencies should define a business context first. Following this step, data must be attentively collected, and last but not least, AI must be taught to speak public safety language to operate at full speed.