We are deeply saddened but perhaps no longer shocked when we hear of yet another mass shooting in the United States. Perhaps one of the most frightening aspects is that they happen all over the country and in a wide variety of locations. This can make us feel that nowhere is safe. After a mass shooting, we are on alert when we go to public spaces such as entertainment events, sports stadiums, schools, malls, offices, shops and even hospitals. There is a lot of discussion about how to prevent another mass shooting, and then slowly our state of alert returns to normal until the next tragic incident. But to protect public facilities against mass shootings, we must be proactive. We must go beyond physical security and employ artificial intelligence and predictive analysis. Let’s look at where we are now and the most effective actions and technologies we can use to reduce risks.
To protect public facilities against mass shootings, we must be proactive. We must go beyond physical security and employ artificial intelligence and predictive analysis.
Mass Shootings Are on the Rise
There is no one, agreed-upon definition of “mass shooting”. H.R. 2076 (112th), the Investigative Assistance for Violent Crimes Act of 2012, defines “mass killing” as three or more killings in a single incident in a place of public use. The Gun Violence Archive defines “mass shooting” as “four or more shot or killed, not including the shooter”. Various reports and sources may impose their own definitions. Therefore, it’s necessary to understand exactly what a report is examining in order to understand analyses of mass shootings.
According to the Washington Post, there have been 154 shootings in which four or more people were killed by a lone shooter (two shooters in a few cases) in the time period from the tower shooting at the University of Texas on August 1, 1966, to the Capital Gazette shooting in Annapolis Maryland on June 28, 2018. This does not include gang shootings, robberies or shootings in the home.
Yet House Minority Leader Nancy Pelosi wrote a letter to House Speaker Paul Ryan in October 2017 stating there had been “273 mass shootings in 2017—one for each day of the year.” Pelosi used the definition of four or more people killed but did not subtract gang shootings, home invasion robberies or home violence. (When private homes are included in the definition of “mass shooting,” such shootings comprise 63%.)
The FBI uses yet another definition. It identifies an “active shooter” as “an individual actively engaged in killing or attempting to kill people in a confined and populated area.” The FBI tells us that mass shootings are on the rise and becoming more deadly. According to the FBI, in 2017 alone there were 30 separate active mass shootings in the United States, the largest number ever recorded by the FBI during a one-year period. From 2000 to 2015, the number of incidents more than doubled from the first part of the period to the second.
Profiling Mass Shooters
An FBI report analyzed 63 mass shooters over many years in an attempt to profile them. The FBI found some demographic attributes that shooters often hold in common, but unfortunately, they are not uniform enough on their own to readily identify shooters before they act.
The FBI sample study of 63 shooters determined that mass shooters are 94% male. A look at the Mother Jones’ open-source databasereveals that of 95 mass shootings between 1982 and 2017, in only about 2% of cases, three in total were the shooters female.
- According to the FBI study, 63% of mass shooters are white, but there have also been black, Asian, Hispanic and Native American shooters
- Some think that mass shooters are mostly people with mental problems who snap and spray public places with gunfire. This is generally not the case. The FBI report determined that only 25% of active shooters had ever been diagnosed with a mental illness, and of the 63 shooters studied, only three had been diagnosed with a psychotic disorder
- In 64% of mass shootings, shooters specifically target at least one of the victims. In some cases, the target may be a group such as employees of a business rather than an individual. In other words, mass shootings are usually not random.
- A history of domestic violence is common among many shooters. According to Everytown for Gun Safety, in 54% of cases, the shooter targeted his girlfriend, wife or ex-wife.
- The FBI study found that shooters usually exhibit four or five observable “concerning behaviors” before an attack. Someone who knew the shooter noticed at least one of these behaviors in every case analyzed. Behaviors are related to
- Mental health
- Interpersonal problems
- Communication of violent intent
- Half of adult shooters and nearly all of those who are teenagers tell someone about their plans in advance. But in most cases, people who see disturbing signs or are informed of the shooter’s plans do nothing at all or only talk to the shooter about it. Most people don’t expect someone they know to be a potential mass murderer and may fear becoming personally involved.
- In the FBI study, 79% of shooters were spurred by a grievance. Half of those 79 % were motivated by a specific precipitating event. Many people feel particularly threatened by dangers from without and worry about Islamic or other extremists. Though certainly extremists can be a threat, the FBI study shows that ideology or extremism only motivated an attack in 3% of cases. Compare that to the 33% of cases motivated by interpersonal action against the shooter.
Table 1. Primary Grievance
- Mass shooters typically plan in advance. 77% plan for a week, 46% for longer than a week and only 12% for less than a day.
- In the year before they act, most active shooters experience multiple stressors, 3.6 on average.
Human Analysis Alone Is Not Enough to Predict Who Will Be a Mass Shooter
Although there are some trends among shooters, it is impossible to predict them from demographics alone. Mass shooters’ ages have ranged from 12 to over 70. Table 2. Age of Shooter (N=63)
Shooters are predominantly male, but that’s half the population. They are usually white but not always. The main thing they have in common is that they exhibit concerning behaviors before the shootings, but these usually go unreported. It is up to the administrators of public venues to protect the public, but trying to determine who may become a mass shooter by demographics without more is ineffective.
Mass Shootings Take Place Almost Anywhere
Mass shootings do not usually occur at random locations. For 73% of them, the shooter has some kind of connection to the site of the attack. For shooters under age 18, that site is usually their current or former school. When there are multiple victims, it may seem at a glance that the gunman shot randomly, but usually the shooter targets at least one specific victim. But grievances one individual has against another does not help us much in predicting a mass shooting without more information.
Do the locations of the shootings have anything in common? Outside of usually having some connection to the shooter, the answer is no. Martin Prosperity Institute analyzed demographic data of all kinds of communities across the country that have been the sites of mass shootings. The data was from Stanford University’s database Mass Shootings in America, which includes data on 307 mass shootings that occurred in 223 locations between 1971 and 2016. The definition used for “mass shooting” was three or more shooting victims but not necessarily fatalities. 76% of these shootings took place outside of schools and the rest were school shootings.
The upshot is that there was very little any of these sites had in common, though it is worth noting that only 10% of the mass shootings had taken place in “gun-free zones,” that is, areas where there is a prohibition against carrying guns and where there is usually no armed law enforcement personnel. Mass shootings have occurred in small towns and big cities. They have occurred in low and high-income areas, though they have occurred less in very poor and very rich areas. Some were in white communities and some were in racially mixed areas. Most of the shootings have occurred in middle-class areas with a mean income of $65,900, somewhat below the national average of $77,866.Table 3. Map of Locations and Fatalities
Deadly Mass Shootings Take Place in a Wide Array of Venues
It’s not possible to reduce the risk of being in a mass shooting by avoiding going to certain types of venues. They can happen in any public space. Here is a list of just some mass shootings. They can happen anywhere there are people and in any area of the country.
Entertainment Events and Venues
- Mandalay Bay, October 1, 2017, Las Vegas – From the 32nd floor of the Mandalay Bay Resort and Casino, 64-year-old Stephen Paddock fired 1,100 rounds over 10 to 15 minutes on music lovers as they attended theHarvest Music Festival on the Las Vegas Strip, killing 58 and injuring almost 500 people. Paddock had carried at least 23 weapons to the room.
- Movie Theater, July 20, 2012, Aurora Colorado – 24-year-old James E. Holmes set off two devices then sprayed the theater with an AR-15 rifle and other weapons at a Batman film, killing 12 people.
- Pulse Nightclub, June 12, 2016, Orlando – 29-year-oldAmerican Omar Saddiqui Mateen killed at least 49 people and injured over 50 more when he opened fire at Pulse, a gay nightclub. The gunman had pledged allegiance to Isis.
- Westroads Mall, December 5, 2007, Omaha, Nebraska – 19-year-old Robert Hawkins killed eight people and wounded four before killing himself.
- Cascade Mall, September 23, 2016, Burlington, Washington – 20-year-old Arcan Cetin killed five people.
- Texas Baptist Church, November 5, 2017, Sutherland Springs, Texas – 26-year-old Devin Patrick Kelley killed 25 people and an unborn child and injured 20 more people.
- Emanuel African Methodist Episcopal Church, June 17, 2015, Charleston, South Carolina – 21-year-old Dylann Roof, shot and killed nine people in a racially motivated hate crime.
- Wat Promkunaram, a Buddhist temple, August 10, 1991, Waddell, Arizona – 17-year-old Jonathan Doody and 16-year-old Alessandro Garcia killed six monks, a nun, a mon-in-training, and a temple worker.
- Luby’s Cafeteria, October 16, 1991, Killeen, Texas – 35-year-old George Hennard crashed his pickup truck through the plate-glass window, then shot and killed 23 people.
- McDonald’s, July 18, 1984, San Ysidro, California – 41-year-old James Huberty shot and killed 21 adults and children at a local McDonald’s and wounding 19 more people.
Offices, Work Gatherings, and Shops
- 101 California Street Office Building, July 1, 1993, San Francisco, California – 55-year-old Gian Luigi Ferri shot and killed eight people, many in a law office where he had an old grievance regarding a real estate transaction, before killing himself.
- Standard Gravure Corporation, September 14, 1989 Louisville, Kentucky – 47-year-old Joseph Wesbecker shot and killed eight co-workers, injured 12 more and then killed himself.
- Salon Meritage, a hair salon, October 12, 2011, Seal Beach, California – 41-year-old Scott Evans Dekraai killed eight people including his ex-wife.
- Miami Machine Shop, August 20, 1982, Miami, Florida – 51-year-old Carl Robert Brown, killed eight people in anger about a repair bill.
- Sandy Hook Elementary School, December 14, 2012, Newtown, Connecticut – 20-year-old Adam Lanza shot and killed 20 children and six adults at Sandy Hook Elementary School. Before shooting at the school, the gunman killed his mother.
Colleges and Universities
- Virginia Tech, April 16, 2007, Blacksburg, Virginia – 23-year-old student Seung-Hui Cho shot and killed 32 people at Virginia Tech, injuring more.
- University of Texas, August 1, 1966, Austin, Texas – Before many of the now-famous mass shootings,University of Texas architectural student and former Marine-trained sniper Charles Joseph Whitman killed 18 and wounded at least 30 more people by shooting them from a tower. He killed both his wife and mother the same day before the tower shooting.
- Umpqua Community College, October 1, 2015, Roseburg, Oregon – Christopher Sean HarperMercer shot and killed nine people and injured nine more.
- Marjory Stoneman Douglas High School, February 14, 2018, Parkland, Florida – 19-year old Nikolas Cruz, a former student, killed at least 17 children and adults with a .223-caliber AR-15 rifle.
- Columbine High School, April 20, 1999, Littleton, Colorado – 17-year-old Dylan Klebold and 18-year-old Eric Harris gunned down 12 students and a teacher.
- Santa Fe High School, May 18, 2018, Santa Fe, Texas – 17-year-old Dimitrios Pagourtzis, shot and killed eight students and two teachers.
- Red Lake Senior High School, March 21, 2005, Red Lake, Minnesota – 16-year-old Jeff Weise shot and killed five students, a teacher, and a security officer at Red Lake Senior High School. Before going to the high school, Weise killed his grandfather and his grandfather’s companion at home.
Organizations and Clubs
- American Civic Association, an immigrant community center, April 3, 2009, Binghamton, New York – 41-one-year old Jiverly Wong killed 13 people and injured four before killing himself.
- Wah Mee Gambling and Social Club, February 18, 1983, Seattle, Washington – 20-year-old Benjamin Ng, 22-year-old Kwan Fai Mak and 26-year-old Wai-Chiu “Tony” Ng killed 13 people during a robbery.
- Nursing Home, March 29, 2009, Carthage, North Carolina – 45-year-old Robert Stewart shot and killed a nurse and seven elderly patients.
On the Street
- 32nd Street, Camden New Jersey, September 5, 1949 – 28-year-old Howard Unruh, a veteran of World War II, shot and killed 13 people as he walked down the street.
So What Can We Do to Reduce Risks of Mass Shootings?
Demographics alone are of very limited help in predicting who is likely to become a mass shooter. Even when individuals exhibit concerning signs, they are not usually reported. There is also little to tie together the locations of mass shootings beyond the fact that they are usually familiar to the shooter. We know that if we are only reactive, mass shootings will continue to escalate.
Gun Control Will Be a Long Wait
Most mass shooters use legally obtained firearms. Gun control is always discussed after an incident, but due to resistance to gun control by powerful lobbies and political factions, we cannot depend on new laws to help reduce mass terror anytime soon. Americans make upabout 4.4 percent of the global population but own 42% of the world’s guns. From 1966 to 2012, 31% of the gunmen in mass shootings worldwide were American. Administrators of malls, entertainment facilities, sports stadiums, hospitals, schools, and other public facilities cannot afford to wait for legislation that may never come.
Physical Security Is a Starting Point
Certainly physical security plays a role in reducing mass shootings. Security personnel, bag searches, x-rays of bags, metal detectors, cameras and gunshot detection systems all play a role. So do increasing perimeter and access control, though these measures are unlikely to be enough to protect against homemade explosives and vehicular attacks. Access control also cannot protect against people who have a right to be in the location.
Though physical security is necessary, it is the last defense. In order to predict and stop mass shootings, we need to be much more proactive than waiting until the shooter arrives at the venue with their weapons. In this age of automatic assault rifles, we need predictive analysis aided by artificial intelligence systems to sift, sort and carefully select data and machine learning to improve results. Only then can we look to humans to verify the data and its context, because it is simply impossible for humans to examine all the necessary data without technological help. We need to do all we can to stop threats before they turn into deadly actions
Employing Predictive Analytics to Detect Threats
Artificial intelligence and machine learning can now perform predictive analysis capabilities that enable identification of individuals engaged in suspicious activities that point to various levels of violent attack threats. Today, facility administrators can use technology-based predictive security solutions to foretell mass shootings and other violent acts before they happen and before the shooter gets anywhere near the site with his weapons. Artificial intelligence can be programmed to effectively sort vast amounts of data from all over the Internet, monitoring trillions of data points almost in real time. Not only that, but machine learning can enable these systems to become increasingly effective in pulling out relevant data as time goes on. Once data is sorted into useable, meaningful categories, humans can examine it to determine the context of the data and the extent of the threat. Let’s examine how this technology can help keep the public safe.
Using Online Behavior to Predict Mass Shootings
Artificial intelligence and machine learning can be used to sort through and correlate vast amounts of data to predict when people are planning mass violence. Artificial intelligence can also reveal worrisome patterns that it would be almost impossible for humans to uncover in enough time to stop an attack. An effective system will examine three things: means, motivation, and target. Means is how the violence will be carried out. For example, an AI system can capture when an individual shows interest in explosives or firearms. Motivation is what might drive a mass attack. This could be anything from Islamic extremist ideology to a personal grievance. Target in this context is the location of the planned attack.
When means, motivation, and target are analyzed with the help of artificial intelligence, we may see patterns emerge. Someone showing interest in firearms may just be planning a hunting trip. But, if they show interest in firearms, researching mass shooter incidents and belong to hate groups, that is a cause for concern.
Screening Vendors, Employees & Contractors
An effective Internet-based security system includes an ever-evolving database of people related to global extremist networks. A good artificial intelligence system with the help of human analysis should be able to assign a level of likelihood that an individual is likely to be a radical extremist who is likely to be involved in violent activity. Of course, cross-referencing a high-risk suspect database is more helpful in the case of religious extremists and hate groups than in the case of those who are motivated by personal grievances.
It’s not enough today to only screen vendors, employees, and contractors with a cursory background check. Artificial intelligence can sort through their online activity to pinpoint risks. An effective system would enable a facility administrator to upload the name and identifying information of individuals and get almost immediate feedback no matter what kind of facility they manage: entertainment facilities, events, sports stadiums, hospitals, and care facilities, work environments, malls or anywhere else.
Removing Barriers to Reporting
60% of terror plots are discovered through human reporting, so it’s critical to make it as easy as possible for people to report suspicious activity. We have seen that most shooters exhibit concerning behaviors before they carry out their plans. We have also seen that although virtually all shooters under 18 and half of adult shooters leak information prior to mass killings, most people who get such information do not report it. They may not want quite know what to do, don’t take it seriously or don’t want to get involved. Technology can remove many of the barriers to reporting through an app that students, employees, and others to report suspicious behavior or leaked information in real time. It’s easy and it’s fast, and it puts a tool into the hands of those who are most likely to hear or see something amiss. Reports can be automatically pushed to key law enforcement or security personnel a school’s geo-fenced facility to enable immediate action.
Anti-terrorism Technology is a Protection Against Liability
A facility can reduce its risks substantially, but there is no fool-proof way to guarantee against terrorists attacks. However, under the Support Anti-Terrorism by Fostering Effective Technologies Act, a facility that uses “qualified anti-terrorism technology” may not be held liable in a federal lawsuit.
Using Predictive Security to Secure Your Facility
Though physical security is the last bastion against violent extremism, to keep the public safe, facilities need the predictive analysis now available through artificial intelligence and machine learning systems that comb the Internet for relevant data and patterns. Predictive security helps to stop threats before they ever reach a facility and while they are still in the planning stages.