Ever since Ted Bundy was first arrested in 1975, computers have been central to serial killer investigations. In Bundy’s case, a computer-based cross-referencing of lists, including ones that aggregated the high school classmates of one of his victims (Lynda Healy), owners of Volkswagens, and people known to live in the areas near his killings, led to his arrest.

But even as computer technology has significantly progressed in subsequent years, the way law enforcement tries to catch serial killers has not kept pace. In 1983, the FBI launched the Violent Criminal Apprehension Program, known as ViCAP, but with over 189 questions that investigators had to answer and input into the program (later trimmed to 95), it never became as widely used as intended.

Other technologies and algorithms have followed. In 1991, Kim Rossmo, a Vancouver policeman who became a professor of criminal justice at Texas State University, invented an algorithm to help predict where a serial killer might live based on where victims are found when compared to where suspects live; in 1992, Michael Aamodt, a professor of psychology at Radford University in Virginia, created the Radford Serial Killer Database, which provided demographic information on over 4,500 serial killers; and in 2015, Thomas Hargrove, a news-service journalist-turned-sleuth, created a nonprofit called the Murder Accountability Project, or MAP, which used an algorithm that accounted for the style, place, and time of killings as well as basic demographic information about the victims in order to narrow in on potential serial killers.

Yet, while all of these worked to provide more information to investigators and, in certain cases, to help narrow down a list of suspects, none of them could deal explicitly with the killers’ specific psychoses — how they thought, how they had developed, or, crucially, when they might next strike. To be able to understand the background of a serial killer is to begin to understand who he might have already killed and who he may soon kill.

“What drives the series of killings can only be truly understood in the context of the serial murderer’s experience of his life,” Candice A. Skrapec, a psychologist and criminologist at California State University, Fresno, wrote in a 2001 paper in Homicide Studies. “What has largely been neglected by researchers is the first-person, lived-meaning of killing a number of people over time.”

When it comes to serial killers — as with any homicide — the Holy Grail for law enforcement has always been to stop them before they strike. Reid believes it’s possible; however, she worries about an eventual Minority Report-style of policing that could spring from her algorithms. To start, though, she wants to stop active serial killers before they strike again, finding patterns in their first two or three kills that can lead to their apprehension.

“A lot of people, they look at things like very static traits, like, ‘Are they psychopaths, yes or no? Narcissist, yes or no?’” Reid says, pointing to a series of black-and-white photographs of serial killers that she has printed out and hung on her office wall at the University of Calgary, where she is currently an instructor. “They look at whether or not they were abused. Okay, that’s great. But in having a developmental-psych background, I understand it’s not enough just to know that a person was abused. At what time were they abused? How often were they abused? Who abused them? What type of abuse was it? Was it Mom? Was it Dad? There’s a trillion questions that come out of one factor. That’s why my database is so expansive. It’s because I’m asking those minute, little details. It’s not enough to know that a person was abused. You’ve got to know the how, the why — everything.”

With data on over 4,500 serial killers — and entirely complete data on 75 of them — Reid’s serial killer database currently includes nearly 600 variables for every killer, which covers almost every imaginable developmental trait or outlook the killers had. She tracks their development from even before birth with questions like: Was there prenatal exposure to drugs? To chemicals? Did Mom smoke? Was she particularly stressed? Then, there are questions of the birth itself: Was there a medical complication at birth? Any brain abnormalities? Then questions of childhood: Any head injuries? If so, at what age? Any physical deformities?

Many of these traits may seem to be related to physicality, but Reid is interested in their developmental implications. She points to the serial killer Gary Ridgway’s profile on her Excel sheet database that she’s now pulled up on her MacBook Air in her office. “Look,” she says, excitedly. “Low IQ. So that’s definitely a risk factor, but not for why a lot of people think. It’s a risk factor for making friends. Kids with lower IQs tend to have fewer friends because they don’t really know how to socially engage.” She goes quiet. “Sometimes they’re shunned, which is really sad.”

There are then questions of family: Were there parents separated? Divorced? If so, when? Did Dad have a stable job? Was he a criminal? What about Mom? Was she a housewife? Were they ever abandoned for a significant duration? What were the circumstances? Did they witness spousal abuse? Mom against Dad? Dad against Mom? Both? Then, there are questions of power: Did they ever apply to become a police officer? Were they successful? Any sexual fantasies?

“Look!” Reid says again, pointing to this data point, toggling between her online codebook and the Excel sheet. “Did the serial killer have sexual fantasies in his youth, yes or no? Look, look. That one started at six. Isn’t that incredible?” She reads down the line of data she and her undergraduate volunteers gathered from police reports, biographies, and archival research. “Age five, four, five, six, 11.”

Were they bullied? Did they bully others? Were they lonely? “Look at this, too,” she says. “Look at all these ones. Were they a loner? Poor things. They were.” She moves her finger across the screen. “Did they get along with their fellow students? Yes, no? Close peer group? One close friend? They might’ve been a loner, but if they had that one person, that usually helped a lot.”

In addition to the special attention she gives to the development of serial killers, Reid is also particularly stringent on who she counts as a serial killer. The FBI considers a person a serial killer if he or she has committed “two or more” homicides “in separate events.” For Reid’s definition, however, there must be three or more total murders (or two and an attempted murder), which must also be motivated by “personal gratification” and cannot be a response to a personal attack. The killer must also have killed after “conscious deliberation” and “planned forethought,” and the murders must be discreet events, not a one-time event where the killer murdered multiple people at once.

A central goal of her databases is to allow an investigator to narrow down a list of suspects and to predict where and when a serial killer might strike again. So, for instance, if non-college-educated, middle-aged Latina prostitutes from low-income families begin showing up with slit wrists across Chicago, regressing the relevant variables in the databases against one another would create an accurate characterization of the potential killer. Because serial killers aren’t always in police databases to begin with, the results of Reid’s regressions will rarely identify a single killer. A name and face won’t pop up like in an episode of CSI. Instead, a series of character traits and demographic possibilities of the killer, and potential locations and victim profiles of future killings would show up. From this, investigators can significantly narrow their search and hopefully stop subsequent murders.

“We can see childhood, adolescence, and adulthood factors occurring in sequence, and how they relate to later-life behaviors,” says David Keatley, a senior criminology lecturer at Murdoch University in Perth, Australia, and an independent consultant on cold-case homicides, who has been helping Reid with the statistical side of her database. “This can then be run backwards. So when we come to a crime scene and see the display of behaviors, we can work backwards through our sequences to see the likely type of offender life-history.”

Now that Reid has such comprehensive datasets, the next step is to use machine learning in order to automatically find behavioral and characteristic patterns in serial killers. Reid is consulting with Cosma, with whom Reid worked in Nottingham, in order to find patterns in serial killer behaviors that have never before been thought of, and which could be automatically updated as she gains more data and as future serial killings occur.

“We can train machine-learning models to classify killers based on their behavioral characteristics and types of attacks,” Cosma says. “Sasha’s dataset has chronological data, which means it can be used to train machine-learning models to predict when the next attack is likely to happen.”

From here, the technology will only advance, but, with it, a variety of positive and negative outcomes will also begin to arise. There is, for instance, the possibility of the privatization of certain types of policing if, for instance, a Silicon Valley machine-learning company were to purchase the databases. Reid wants to avoid this. She wants to keep the use of her databases to a relatively small scope, at least at first, by selecting a single police department with a responsible track record and giving them her database and algorithms to use in their investigations.

Her caution in moving too quickly is probably merited, given the history of psychological profiling gone awry, stemming from mistakes made by armchair investigators and professionals alike.

“I don’t want to be the person who drives the police down the wrong path,” Reid says. “Profiles should only be used as a way to narrow down and focus. It’s never your first line of defense.”