Could A.I. detect mass shooters before they strike?

President Trump has called for Silicon Valley to develop digital precogs, but such systems raise efficacy concerns.

  • President Donald Trump wants social media companies to develop A.I. that can flag potential mass shooters.
  • Experts agree that artificial intelligence is not advanced enough, nor are current moderating systems up to the task.
  • A majority of Americans support stricter gun laws, but such policies have yet to make headway.

On August 3, a man in El Paso, Texas, shot and killed 22 people and injured 24 others. Hours later, another man in Dayton, Ohio, shot and killed nine people, including his own sister. Even in a country left numb by countless mass shootings, the news was distressing and painful.

President Donald Trump soon addressed the nation to outline how his administration planned to tackle this uniquely American problem. Listeners hoping the tragedies might finally spur motivation for stricter gun control laws, such as universal background checks or restrictions on high-capacity magazines, were left disappointed.

Trump's plan was a ragbag of typical Republican talking points: red flag laws, mental health concerns, and regulation on violent video games. Tucked among them was an idea straight out of a Philip K. Dick novel.

"We must recognize that the internet has provided a dangerous avenue to radicalize disturbed minds and perform demented acts," Trump said. "First, we must do a better job of identifying and acting on early warning signs. I am directing the Department of Justice to work in partnership with local, state and federal agencies as well as well as social media companies to develop tools that can detect mass shooters before they strike."

Basically, Trump wants digital precogs. But has artificial intelligence reached such grand, and potentially terrifying, heights?

A digitized state of mind

It's worth noting that A.I. has made impressive strides at reading and quantifying the human mind. Social media is a vast repository of data on how people feel and think. If we can suss out the internal from the performative, we could improve mental health care in the U.S. and abroad.

For example, a study from 2017 found that A.I. could read the predictive markers for depression in Instagram photos. Researchers tasked machine learning tools with analyzing data from 166 individuals, some of whom had been previously diagnosed with depression. The algorithms looked at filter choice, facial expressions, metadata tags, etc., in more than 43,950 photos.

The results? The A.I. outperformed human practitioners at diagnosing depression. These results held even when analyzing images from before the patients' diagnoses. (Of course, Instagram is also the social media platform most likely to make you depressed and anxious, but that's another study.)

Talking with Big Think, Eric Topol, a professor in the Department of Molecular Medicine at Scripps, called this the ability to "digitize our state of mind." In addition to the Instagram study, he pointed out that patients will share more with a self-chosen avatar than a human psychiatrist.

"So when you take this ability to digitize a state of mind and also have a support through an avatar, this could turn out to be a really great way to deal with the problem we have today, which is a lack of mental health professionals with a very extensive burden of depression and other mental health conditions," Topol said.

Detecting mass shooters?

However, it's not as simple as turning the A.I. dial from "depression" to "mass shooter." Machine learning tools have gotten excellent at analyzing images, but they lag behind the mind's ability to read language, intonation, and social cues.

As Facebook CEO Mark Zuckerberg said: "One of the pieces of criticism we get that I think is fair is that we're much better able to enforce our nudity policies, for example, than we are hate speech. The reason for that is it's much easier to make an A.I. system that can detect a nipple than it is to determine what is linguistically hate speech."

Trump should know this. During a House Homeland Security subcommittee hearing earlier this year, experts testified that A.I. was not a panacea for curing online extremism. Alex Stamos, Facebook's former chief security officer, likened the world's best A.I. to "a crowd of millions of preschoolers" and the task to demanding those preschoolers "get together to build the Taj Mahal."

None of this is to say that the problem is impossible, but it's certainly intractable.

Yes, we can create an A.I. that plays Go or analyzes stock performance better than any human. That's because we have a lot of data on these activities and they follow predictable input-output patterns. Yet even these "simple" algorithms require some of the brightest minds to develop.

Mass shooters, though far too common in the United States, are still rare. We've played more games of Go, analyzed more stocks, and diagnosed more people with depression, which millions of Americans struggle with. This gives machine learning software more data points on these activities in order to create accurate, responsible predictions — that still don't perform flawlessly.

Add to this that hate, extremism, and violence don't follow reliable input-output patterns, and you can see why experts are leery of Trump's direction to employ A.I. in the battle against terrorism.

"As we psychological scientists have said repeatedly, the overwhelming majority of people with mental illness are not violent. And there is no single personality profile that can reliably predict who will resort to gun violence," Arthur C. Evans, CEO of the American Psychological Association, said in a release. "Based on the research, we know only that a history of violence is the single best predictor of who will commit future violence. And access to more guns, and deadlier guns, means more lives lost."

Social media can't protect us from ourselves

First Lady Melania Trump visits with the victims of the El Paso, Texas, shooting. Image source: Andrea Hanks / Flickr

One may wonder if we can utilize current capabilities more aggressively? Unfortunately, social media moderating systems are a hodgepodge, built piecemeal over the last decade. They rely on a mixture of A.I., paid moderators, and community policing. The outcome is an inconsistent system.

For example, the New York Times reported in 2017 that YouTube had removed thousands of videos using machine learning systems. The videos showed atrocities from the Syrian War, such as executions and people spouting Islamic State propaganda. The algorithm flagged and removed them as coming from extremist groups.

In truth, the videos came from humanitarian organizations to document human rights violations. The machine couldn't tell the difference. YouTube reinstated some of the videos after users reported the issue, but mistakes at such a scale do not give one hope that today's moderating systems could accurately identify would-be mass shooters.

That's the conclusion reached in a report from the Partnership on A.I. (PAI). It argued there were "serious shortcomings" in using A.I. as a risk-assessment tool in U.S. criminal justice. Its writers cite three overarching concerns: accuracy and bias; questions of transparency and accountability; and issues with the interface between tools and people.

"Although the use of these tools is in part motivated by the desire to mitigate existing human fallibility in the criminal justice system, it is a serious misunderstanding to view tools as objective or neutral simply because they are based on data," the report states. "While formulas and statistical models provide some degree of consistency and replicability, they still share or amplify many weaknesses of human decision-making."

In addition to the above, there are practical barriers. The technical capabilities of law enforcement vary between locations. Social media platforms deal in massive amounts of traffic and data. And even when the red flags are self-evident — such as when shooters publish manifestos — they offer a narrow window in which to act.

The tools to reduce mass shootings

Protesters at March for Our Lives 2018 in San Francisco. Image source: Gregory Varnum / Wikimedia Commons

Artificial intelligence offers many advantages today and will offer more in the future. But as an answer to extremism and mass shootings, experts agree it's simply the wrong tool. That's the bad news. The good news is we have the tools we need already, and they can be implemented with readily available tech.

"Based on the psychological science, we know some of the steps we need to take. We need to limit civilians' access to assault weapons and high-capacity magazines. We need to institute universal background checks. And we should institute red flag laws that remove guns from people who are at high risk of committing violent acts," Evans wrote.

Evans isn't alone. Experts agree that the policies he suggests, and a few others, will reduce the likelihood of mass shootings. And six in 10 Americans already support these measures.

We don't need advanced A.I. to figure this out. There's only one developed country in the world where someone can legally and easily acquire an armory of guns, and it's the only developed country that suffers mass shootings with such regularity. It's a simple arithmetic.

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New research establishes an unexpected connection.

Reactive oxygen species (ROS) accumulate in the gut of sleep-deprived fruit flies, one (left), seven (center) and ten (right) days without sleep.

Image source: Vaccaro et al, 2020/Harvard Medical School
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The study, from researchers at Harvard Medical School (HMS), is published in the journal Cell.

An unexpected culprit

The new research examines the mechanisms at play in sleep-deprived fruit flies and in mice — long-term sleep-deprivation experiments with humans are considered ethically iffy.

What the scientists found is that death from sleep deprivation is always preceded by a buildup of Reactive Oxygen Species (ROS) in the gut. These are not, as their name implies, living organisms. ROS are reactive molecules that are part of the immune system's response to invading microbes, and recent research suggests they're paradoxically key players in normal cell signal transduction and cell cycling as well. However, having an excess of ROS leads to oxidative stress, which is linked to "macromolecular damage and is implicated in various disease states such as atherosclerosis, diabetes, cancer, neurodegeneration, and aging." To prevent this, cellular defenses typically maintain a balance between ROS production and removal.

"We took an unbiased approach and searched throughout the body for indicators of damage from sleep deprivation," says senior study author Dragana Rogulja, admitting, "We were surprised to find it was the gut that plays a key role in causing death." The accumulation occurred in both sleep-deprived fruit flies and mice.

"Even more surprising," Rogulja recalls, "we found that premature death could be prevented. Each morning, we would all gather around to look at the flies, with disbelief to be honest. What we saw is that every time we could neutralize ROS in the gut, we could rescue the flies." Fruit flies given any of 11 antioxidant compounds — including melatonin, lipoic acid and NAD — that neutralize ROS buildups remained active and lived a normal length of time in spite of sleep deprivation. (The researchers note that these antioxidants did not extend the lifespans of non-sleep deprived control subjects.)

fly with thought bubble that says "What? I'm awake!"

Image source: Tomasz Klejdysz/Shutterstock/Big Think

The experiments

The study's tests were managed by co-first authors Alexandra Vaccaro and Yosef Kaplan Dor, both research fellows at HMS.

You may wonder how you compel a fruit fly to sleep, or for that matter, how you keep one awake. The researchers ascertained that fruit flies doze off in response to being shaken, and thus were the control subjects induced to snooze in their individual, warmed tubes. Each subject occupied its own 29 °C (84F) tube.

For their sleepless cohort, fruit flies were genetically manipulated to express a heat-sensitive protein in specific neurons. These neurons are known to suppress sleep, and did so — the fruit flies' activity levels, or lack thereof, were tracked using infrared beams.

Starting at Day 10 of sleep deprivation, fruit flies began dying, with all of them dead by Day 20. Control flies lived up to 40 days.

The scientists sought out markers that would indicate cell damage in their sleepless subjects. They saw no difference in brain tissue and elsewhere between the well-rested and sleep-deprived fruit flies, with the exception of one fruit fly.

However, in the guts of sleep-deprived fruit flies was a massive accumulation of ROS, which peaked around Day 10. Says Vaccaro, "We found that sleep-deprived flies were dying at the same pace, every time, and when we looked at markers of cell damage and death, the one tissue that really stood out was the gut." She adds, "I remember when we did the first experiment, you could immediately tell under the microscope that there was a striking difference. That almost never happens in lab research."

The experiments were repeated with mice who were gently kept awake for five days. Again, ROS built up over time in their small and large intestines but nowhere else.

As noted above, the administering of antioxidants alleviated the effect of the ROS buildup. In addition, flies that were modified to overproduce gut antioxidant enzymes were found to be immune to the damaging effects of sleep deprivation.

The research leaves some important questions unanswered. Says Kaplan Dor, "We still don't know why sleep loss causes ROS accumulation in the gut, and why this is lethal." He hypothesizes, "Sleep deprivation could directly affect the gut, but the trigger may also originate in the brain. Similarly, death could be due to damage in the gut or because high levels of ROS have systemic effects, or some combination of these."

The HMS researchers are now investigating the chemical pathways by which sleep-deprivation triggers the ROS buildup, and the means by which the ROS wreak cell havoc.

"We need to understand the biology of how sleep deprivation damages the body so that we can find ways to prevent this harm," says Rogulja.

Referring to the value of this study to humans, she notes,"So many of us are chronically sleep deprived. Even if we know staying up late every night is bad, we still do it. We believe we've identified a central issue that, when eliminated, allows for survival without sleep, at least in fruit flies."

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