A new paradigm for public safety powered by responsible AI
Imagine a future where an entire city is monitored by responsible AI, providing law enforcement with the tools and intelligence to stop crime in real time. Cameras could detect people running or fighting, unattended items, hazards such as smoke or non-standard noise, and potentially suspicious activities. The system alerts police who react in real-time.
These cameras of the future are an extension of what is used today—the pervasive closed-circuit television (CCTV) cameras, which are one of the most popular tools for stemming crime. The effectiveness of these cameras varies widely based on the public’s perception of whether or not the CCTVs are properly monitored.
According to Accenture analysis, most video footage from public safety cameras today are only used for forensic or evidential purposes after criminal activity has occurred. In fact, on average only 2 percent of video footage is seen and even less is analyzed in real time today. This means that 98 percent of security video footage is “dark” data.
Integrating artificial intelligence and analytics with public safety’s current closed-circuit televisions can transform the ecosystem from reactive to proactive, allowing law enforcement to more effectively combat crime.
How technology enablers can help fight crime
In a public safety setting, AI capabilities—programmed by humans and trained over time—could analyze thousands of video feeds to track and alert authorities of anomalies. Current video feeds AI could analyze include those from CCTV, do-it-yourself video cameras, security services, badges, and smart locks. In the future, these could be joined by new data sources such as personal devices, connected cars, drones and robots.
Riding the prevailing technology wave, some public safety industry players—like China, Singapore, and startups globally—are already upgrading their capabilities. They’re leveraging robotics, computer vision, big data, and analytics to anticipate and prevent crimes in real time. As startups and established technology companies begin partnering, they can tap into each other’s expertise and continue to develop these technologies faster and more affordably.
And when these technologies come together, they can transform cameras from an illusion of protection to a real-time vigilant protector, thereby, accomplishing the unthinkable: detecting crime in just one second.
A tiered approach to adoption
While these technologies and data sources are just now emerging, broad adoption probably will not happen quickly given public concerns about privacy and the massive investment required. Instead, global adoption will likely unfold across three tiers of maturity:
- Tier 1 is the current mass public safety ecosystem, which primarily features CCTV feeds used retroactively by security and police forces to understand “what happened.” Data is typically in silos, making it difficult to create a broader and more comprehensive picture of a particular situation.
- Tier 2 takes the next step toward a mass real-time-oriented public safety ecosystem where through AI, police can see the unseeable. This tier is expected to arrive by 2025, by which smart cities become the norm and 88 municipalities are predicted to achieve “smart city” status. In addition, by 2025, 70 percent of security surveillance cameras will ship with on-device real-time monitoring and analytics functions within the camera, compared with less than 5 percent in 2018.
- At Tier 3 the most mature predictive-oriented public safety ecosystem emerges by 2035, the date by which all devices are connected via the Internet. Tier 3 relies on a rapidly growing public safety ecosystem where data is pulled from disparate databases such as social media, driver’s licenses, police databases, and dark data. The more data, the better the systems perform as deep learning enables the system to become more knowledgeable and, as a result, more accurate. With these new sources added to the mix, public safety covers virtually every inch of a city.
Implementing a comprehensive public safety system will clearly require significant investment, not to mention a sharp, ongoing focus on protecting citizens’ privacy. But the payoff could be worth it many times over in lives saved, mass shooting victims shielded, violent and property crimes reduced, and economic impact.
- Number of crimes AI public safety may prevent by 2040: 81.7 million
- Lives that may be saved by AI public safety by 2040: 115,000
- Mass shooting victims AI public safety may shield by 2040: 76,000
Forging ahead to a more transparent and responsible future
With so much data available today, it is understandable people are wary of proposals that suggest even greater data collection by government and law enforcement—knowing the potential exists for misuse of the data and, consequently, violations of privacy. However, the tradeoffs in the form of crime prevention— saving lives and property—and positive economic impacts argue in favor of more expansive, and more intelligent, public safety.