According to statistics provided by Education Week, 13 school shootings resulting in injuries or deaths occurred in the U.S. during the first four months of 2024. Four people died from those shootings, including a sixth-grade student and a school principal in Perry, Iowa.
The shootings so far this year, which are on pace to surpass the number recorded for 2023, are a chilling reminder of the intense challenge today’s school security personnel face. The threat landscape impacting our schools is more complex and dangerous than ever. It requires heightened vigilance and rapid response capabilities that conventional security protocols have consistently proven incapable of providing.
Many schools are turning to a new generation of threat detection tools powered by artificial intelligence to meet the challenge and enhance conventional systems. These tools enhance safety by unleashing new deterrence, detection, and response capabilities. When properly utilized, they level the playing field for school security personnel, giving them the power to identify and neutralize threats before they escalate.
Utilizing AI to Empower Automated Threat Detection
Automated threat detection is the core capability that artificial intelligence brings to school security. By integrating AI with existing video surveillance systems, schools can identify weapons and other threats in real-time without the aid of human agents. These systems act as an always-on sentinel, providing security personnel with an advanced warning at the first hint of a threat or anomaly.
By utilizing advanced machine learning algorithms, AI threat detection systems can continuously learn what constitutes a threat and refine their learning. Video data collected by cameras is passed through the system, where AI analyzes it for patterns that indicate a threat is emerging. AI's speed and insights to the process empower a security framework based on visual data analysis to predict when threats will emerge.
AI’s analytical capabilities also reduce the number of false alarms that can emerge from surveillance activity. Because AI’s threat detection is data-driven rather than intuitive, it improves a system’s capability to discern between genuine threats and benign activities, reducing costs associated with false alarms and allowing security personnel to focus their resources on actual threats.
AI also provides the power to enhance threat reporting systems. Once a credible threat is detected, AI can capture critical information—including images that identify the intruder and data that identifies the threat's location—and rapidly deliver it to security personnel, law enforcement, and all others who could benefit from the knowledge. AI can also automatically track intruders and provide updates to response teams.
Adding Advanced Deterrence Capabilities to Existing Systems
Surveillance cameras are designed to serve as a deterrent. Their presence alone can discourage wrongdoers, communicating that their activity is being watched by those prepared to respond to a threat.
Providing constant monitoring, however, is a herculean task for human security agents, especially on large campuses where dozens of security feeds are in use. If wrongdoers suspect surveillance systems are not actively monitoring for threat detection, they can be emboldened to carry out a threat and cause harm.
Adding AI-supported monitoring capabilities to existing video surveillance systems dramatically improves their deterrent capabilities. The chance that a threat or other unusual activity will go undetected is reduced to zero. When would-be intruders are put on notice that AI-driven detection systems are in place, they know that their activity will be immediately detected, identified as a threat, and automatically reported to security personnel.
Shifting Systems from Reactive to Proactive
The capabilities AI brings to traditional surveillance systems shift them from reactive to proactive tools for security. Traditional systems detect when a threat emerges; while valuable, they keep security one step behind intruders. AI-supported systems flip the script by placing security teams one step ahead.
Several factors come together to give AI its proactive capabilities. The first is the speed with which it can process data.
Proactively identifying emerging security threats requires tracking multiple data streams. A video surveillance system, for example, regularly includes feeds from multiple cameras. A human agent must move from one feed to the next, assessing each individually. AI-driven systems can assess all feeds simultaneously, identifying even the smallest anomaly in real-time.
Pattern recognition is another factor that empowers proactive threat detection in AI-driven systems. Even the most subtle shifts in activity — a door left open, a team member out of place, an unusual shadow in a hallway — are quickly identified and flagged by AI due to its advanced capability to identify data patterns and rapidly and accurately detect when they shift.
AI’s capacity for predictive modeling also contributes to proactive threat detection by analyzing and learning from historical data to build models that can predict how future events are most likely to unfold. This allows AI to predict what normal security footage should look like in a security setting, meaning it can immediately identify unusual activity. Predictive modeling also empowers AI to anticipate how a threat will unfold once it is detected.
The improved consistency in security coverage provided by AI-driven systems also supports a more proactive response. With human-driven security, a shift change constituted an intelligence reset — the patterns of activity witnessed by one security shift walk out the door when a new shift comes on — but AI never goes off shift, meaning it has access to a more complete picture of the patterns of activity occurring in a school.
Providing Enhanced Safety Without Ethical Concerns
Ethics questions are common in situations where AI is utilized. However, ethical concerns are easily addressed in the case of AI-supported security.
Safeguarding data is one common AI-related ethical concern, but with AI-driven security monitoring, no additional data is collected. AI assesses the video data already being collected by existing surveillance systems.
AI-driven threat detection systems avoid common ethical concerns because they are trained to identify potential weapons rather than focusing on facial recognition or other biometric identifiers. Thus, AI can be deployed in school security without concerns for racial and other common biases.
Effective school security systems involve many components, including access control, video surveillance, intruder detection, and emergency alerts. Artificial intelligence enhances each of those components, resulting in a system that is proactive, intelligent, and highly deterrent to those who pose a threat.
Integrating AI into traditional systems empowers security teams to preserve schools' sanctity better and keep students, teachers, and administrators safe from harm.
