Shootings are an epidemic in the US, but federal funding for research into gun violence has been in a deep freeze since 1996, thanks in part to the NRA-backed Dickey Amendment, which prevents the Center for Disease Control from pursuing research "to advocate or promote gun control." Basically, humans can't get money to research the problem of gun violence in the US. To get around this, some scientists want machines to do the job. On September 25, University of Pennsylvania computer scientists Ellie Pavlick and Chris Callison-Burch unveiled a new, human-annotated database of gun violence incidents in the US at the Bloomberg Data for Good Exchange Conference in New York. The database was created by workers on Amazon's Mechanical Turk platform, and carefully highlights information from thousands of news articles over the course of several years, Pavlick told me in an interview.

Federal agencies should be individually exploring how artificial intelligence could improve their operations, a White House report suggests. Agencies should consider building "DARPA-like organizations" for "high-risk, high-reward AI research and its application" in government, said the report, which outlined opportunities and challenges for the technology. The report was released Wednesday, months after the White House hosted a series of public workshops, including one focused on AI applications for social good. That document incorporated discussions from the workshops, and recommended the Executive Office of the President publish a second report by the yearend to delve deeper into the effects of AI on the U.S. job market and outline recommended policy responses. The White House recommended federal agencies prioritize open training data and open data standards for artificial intelligence so those systems could be trained to analyze government data sets.

This creates the false impression that the algorithms already exist for malware detection too. That is not the case. We at Kaspersky Lab have spent more than 10 years developing and patenting a number of technologies. And we continue to carry out research and come up with new ideas because … well, that's where the next myth comes in. There is a conceptual difference between malware detection and facial recognition.

FILE- In this March 1, 2013 file photo, anti-Syrian President Bashar Assad protesters hold the Jabhat al-Nusra flag, as they shout slogans during a demonstration, at Kafranbel town, in Idlib province, northern Syria. Insurgent groups like Hezbollah and the Islamic State group in Syria have learned how to weaponize surveillance drones and use them against each other, adding a new twist to the country's civil war, a U.S. military official and others say. FILE- In this March 1, 2013 file photo, anti-Syrian President Bashar Assad protesters hold the Jabhat al-Nusra flag, as they shout slogans during a demonstration, at Kafranbel town, in Idlib province, northern Syria. Insurgent groups like Hezbollah and the Islamic State group in Syria have learned how to weaponize surveillance drones and use them against each other, adding a new twist to the country's civil war, a U.S. military official and others say. WASHINGTON (AP) -- French and Kurdish forces in northern Iraq were attacked by an exploding drone, the Pentagon said Wednesday, adding a new worry to the wars in Iraq and Syria as militant groups learn to weaponize their store-bought drones.

New rules of the road for robot cars coming out of Washington this week could lead to the eventual extinction of one of the defining archetypes of the past century: the human driver. While banning people from driving may seem like something from a Kurt Vonnegut short story, it's the logical endgame of a technology that could dramatically reduce -- or even eliminate -- the 1.25 million road deaths a year globally. Human error is the cause of 94 percent of roadway fatalities, U.S. safety regulators say, and robot drivers never get drunk, sleepy or distracted. Autonomous cars already have "superhuman intelligence" that allows them to see around corners and avoid crashes, said Danny Shapiro, senior director of automotive at Nvidia Corp., a maker of high-speed processors for self-driving cars. "Long term, these vehicles will drive better than any human possibly can," Shapiro said.

FILE- In this March 1, 2013 file photo, anti-Syrian President Bashar Assad protesters hold the Jabhat al-Nusra flag, as they shout slogans during a demonstration, at Kafranbel town, in Idlib province, northern Syria. Insurgent groups like Hezbollah and the Islamic State group in Syria have learned how to weaponize surveillance drones and use them against each other, adding a new twist to the country's civil war, a U.S. military official and others say. FILE- In this March 1, 2013 file photo, anti-Syrian President Bashar Assad protesters hold the Jabhat al-Nusra flag, as they shout slogans during a demonstration, at Kafranbel town, in Idlib province, northern Syria. Insurgent groups like Hezbollah and the Islamic State group in Syria have learned how to weaponize surveillance drones and use them against each other, adding a new twist to the country's civil war, a U.S. military official and others say. WASHINGTON (AP) -- Militant groups like Hezbollah and the Islamic State group have learned how to weaponize surveillance drones and use them against each other, adding a new twist to Syria's civil war, a U.S. military official and others say.

In a head-to-head comparison, human doctors with access to the same information about medical history and symptoms as was put into a symptom checker got the diagnosis right 72 percent of the time, compared to 34 percent for the apps. The 23 online symptom checkers, some accessed via websites and others available as apps, included those offered by Web MD and the Mayo Clinic in the U.S. and the Isabel Symptom Checker in the U.K. "The current symptom checkers, I was not surprised do not outperform doctors," said senior author Dr. Ateev Mehrotra of Harvard Medical School in Boston. But in reality computers and human doctors may both be involved in a diagnosis, rather than pitted against each other, Mehrotra told Reuters Health. The researchers used a web platform called Human Dx to distribute 45 clinical vignettes - sets of medical history and symptom information - to 234 physicians. Doctors could not do a physical examination on the hypothetical patient or run tests, they had only the information provided.

The problem with the world today isn't that too many people are afraid--it's that too many people are afraid of the wrong things. Consider this: what scares you more, that your life could end because of a terrorist attack or because you get crushed to death under a large piece of furniture? Despite a media environment in which the threat of terrorism is omnipresent and the threat of furniture nonexistent, your gravestone is actually more likely to say, "Died under a couch recently bought from Ikea" than "Perished in a terrorist attack." In fact, asteroids are more likely to kill the average person than lightning strikes, and lightning strikes are more dangerous than terrorism. The point is that, as I've written elsewhere, our intuitions often fail to track the actual risks around us. We dismiss many of the most likely threats while obsessing over improbable events.

Car manufacturers will have difficulty demonstrating just how safe self-driving vehicles are because of what's at the core of their smarts: machine learning. "You can't just assume this stuff is going to work," says Phillip Koopman, a computer scientist at Carnegie Mellon University who works in the automotive industry. In 2014, a market research firm projected that the self-driving car market will be worth 87 billion by 2030. Several companies, including Google, Tesla, and Uber, are experimenting with computer-assisted or fully autonomous driving projects--with varying success because of the myriad technical obstacles that must be overcome. Koopman is one of several researchers who believe that the nature of machine learning makes verifying that these autonomous vehicles will operate safely very challenging.

During his eight years in office, President Barack Obama has seen hackers grow into a threat no president has faced before. US intelligence and law enforcement agencies have responded to everything from a Chinese hack of Google in 2009 to Russian digital meddling in this election. He's learned, as a result, to think a few moves ahead. And that includes preparing for possibilities that others might consider science fiction--like the possibility of an artificial intelligence trained through machine learning and tasked with stealing US nuclear codes. In an era when hackers can steal the fingerprints of 5.6 million federal employees and or pull off a modern version of Watergate, he wonders whether sophisticated adversaries might use AI to infiltrate the government's most sensitive systems.