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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?
....mentally ill or deranged people. I am the biggest Second Amendment person there is, but we all must work togeth… https://t.co/T9OthUAsXe— Donald J. Trump (@Donald J. Trump)1565352202.0
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.
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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Construction of the $500 billion dollar tech city-state of the future is moving ahead.
- The futuristic megacity Neom is being built in Saudi Arabia.
- The city will be fully automated, leading in health, education and quality of life.
- It will feature an artificial moon, cloud seeding, robotic gladiators and flying taxis.
The Red Sea area where Neom will be built:
Saudi Arabia Plans Futuristic City, "Neom" (Full Promotional Video)<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="c646d528d230c1bf66c75422bc4ccf6f"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/N53DzL3_BHA?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
Coronavirus layoffs are a glimpse into our automated future. We need to build better education opportunities now so Americans can find work in the economy of tomorrow.
- Outplacement is an underperforming $5 billion dollar industry. A new non-profit coalition by SkillUp intends to disrupt it.
- More and more Americans will be laid off in years to come due to automation. Those people need to reorient their career paths and reskill in a way that protects their long-term livelihood.
- SkillUp brings together technology and service providers, education and training providers, hiring employers, worker outreach, and philanthropies to help people land in-demand jobs in high-growth industries.
Source: McKinsey Global Institute analysis [PDF]<p>Work in understanding the skills at the heart of the new digital economy is leading to novel assessments that allow individuals to prove mastery to faithfully represent their abilities—but also to give weight and stackability to the emerging ecosystem of micro-credentials that make education more seamless across time and education providers. And we are seeing the beginnings of a renewal in the liberal arts, focused on building human skills in affordable ways that are accessible to many more individuals and far more effective.</p><p>Amidst these dark times, there is much opportunity to refresh the nation's education and training solutions to support the success of individuals and society writ large.</p>
Do we really know what we want in a romantic partner? If so, do our desires actually mean we match up with people who suit them?
- Two separate scientific studies suggest that our "ideals" don't really match what we look for in a romantic partner.
- Results of studies like these can change the way we date, especially in the online world.
- "You say you want these three attributes and you like the people who possess these attributes. But the story doesn't end there," says Paul Eastwick, co-author of the study and professor in the UC Davis Department of Psychology.
Do we really know what we want in love or are we just guessing?<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="204859156383d358652fda6f7eadda0f"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/vQgfx2iYlso?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>More than 700 participants selected their top three qualities in a romantic partner (things like funny, attractive, inquisitive, kind, etc). They then reported their romantic desire for a series of people they knew personally. Some were blind date partners, others were romantic partners and some were simply platonic friends.</p><p>While participants did experience more romantic desire to the extent that these personal connections of theirs (people they knew) had the qualities they listed, there was more to the study. </p><p>Paul Eastwick, co-author and professor in the UC Davis Department of Psychology <a href="https://medicalxpress.com/news/2020-07-romantic-partner-random-stranger.html" target="_blank">explains</a>: "You say you want these three attributes and you like the people who possess these attributes. But the story doesn't end there." </p><p>The participants also considered the extent to which their personal acquaintances possessed three attributes nominated by some other random person in the study. For example, if Kris listed "down-to-earth", intelligent and thoughtful as her own top three attributes, Vanessa also experienced more desire for people with those specific traits. </p>
Does what we want really match up with what we find?<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzQ0NDA4Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTU5NjM3NzY5OX0.gdUo-UbjYhKUDOL39BDZseRynbwaK2H5dfJtbV0nw8Y/img.jpg?width=980" id="ff376" class="rm-shortcode" data-rm-shortcode-id="7c1e3a1bb9d576872ef5dce39b2e8e80" data-rm-shortcode-name="rebelmouse-image" alt="illustration of a man and woman matching on a dating app" />
What we claim to want and what we look for may be two separate things...
Image by GoodStudio on Shutterstock<p>So the question became: are we really listing what we want in an ideal partner or are we just listing vague qualities that people typically consider as positive?</p><p>"So in the end, we want partners who have positive qualities," Sparks explained, "but the qualities you specifically list do not actually have special predictive power for you." </p><p>In other words, the idea that we find certain things attractive in a person does not mean we actively seek out people who have those qualities, despite saying it's what we want in a love interest. The authors of this study suggest these findings could have implications for the way we approach online dating in the digital age. </p><p>This isn't the first study of its kind to suggest that what we find in love isn't really what we were looking for. The evidence suggests that we really are consistent in the abstract of it all: when asked to evaluate what you want on paper, you are more likely to suggest overall attractiveness in accordance with what you've stated are important ideals to you. But real life isn't so similar. </p><p>According to <a href="https://www.psychologytoday.com/us/blog/meet-catch-and-keep/201506/when-it-comes-love-do-you-really-know-what-you-want" target="_blank">Psychology Today,</a> who covered a 2015 study with similar results, initial face-to-face encounters have very little effect on our romantic desire. "When we initially meet someone, our level of romantic interest in the person is independent of our standards."</p><p>While you might have no immediate interest in John, he may fit your criteria of being kind, loyal, and intelligent. Similarly, someone may be attracted to Elaine even though she doesn't have any of the qualities they originally said were important to them. </p><p><strong>What does this all mean? </strong></p><p>The authors of both the 2015 and 2020 studies say the same thing: give someone a chance before writing them off as a poor match. If your initial attraction is independent of the standards you've set out, the qualities which you've listed as important to you, the first time you meet someone may not give you enough information to make an informed decision.</p><p>"It's really easy to spend time hunting around online for someone who seems to match your ideals," said Sparks, "But our research suggests an alternative approach: Don't be too picky ahead of time about whether a partner matches your ideals on paper. Or, even better, let your friends pick your dates for you." </p>