The people who study nuclear war for a living are certain that artificial intelligence will soon power the deadly weapons. None of them are quite sure what, exactly, that means. In the middle of July, Nobel laureates gathered at the University of Chicago to listen to nuclear war experts talk about the end of the world. In closed sessions over two days, scientists, former government officials, and retired military personnel enlightened the laureates about the most devastating weapons ever created. The goal was to educate some of the most respected people in the world about one of the most horrifying weapons ever made and, at the end of it, have the laureates make policy recommendations to world leaders about how to avoid nuclear war.

An unknown object with flashing lights appeared to hover over Marine base in Twentynine Palms, California, in 2021. A Stanford University pathology professor said, "Aliens have been on Earth for a long time and are still here," and claims there are experts working on reverse engineering unknown crashed crafts. Dr. Garry Nolan made the bold statements during last week's SALT iConnections conference in Manhattan during a session called, "The Pentagon, Extraterrestrial Intelligence and Crashed UFOs." The host, Alex Klokus, said that's tough to believe and asked him to assign a probability to that statement that extraterrestrial life visited Earth. "I think it's an advanced form of intelligence that using some kind of intermediaries," Nolan said.

In the fall of 2015, Rob Reich, a philosopher and a political scientist at Stanford, was chatting with a freshman during office hours. "I asked him what he planned to study," Reich recalled recently. "He said, 'Definitely computer science. I have some ideas for startups.' " In the spirit of small talk, Reich asked, What kind? "He looked at me with total earnestness and said, 'To tell you that, I'd have to ask you to sign a nondisclosure agreement.'

It may sound like a plot from a science fiction film, but NASA and the world governments are concerned about alien viruses contaminating Earth. As the first humans prepare for the Mars mission, experts warn that protocols are necessary to keep extraterrestrial pollutants from hitchhiking on space ships and astronauts when returning home from the Red Planet. Stanford professor of aeronautics and astronautics Scott Hubbard said in an interview that the solution is'planetary protection'. Mechanical systems will have to undergo a combination of chemical cleaning and heat sterilization, while the tubes containing samples from Mars need to be treated'as though they are the Ebola virus until proven safe.' Hubbard also suggests that astronauts must be quarantine once they touch down on our planet, as the first men who visited the moon in the Apollo mission did. As the first humans prepare for the Mars mission, experts warn that protocols need to be created to keep extraterrestrial pollutants from hitchhiking on space ships and astronauts when returning home.

Implicit in his comment is the notion that, someday, these systems will be ready. But work by Adina Sterling, an assistant professor of organizational behavior at Stanford Graduate School of Business, questions this optimism, linking it to a deep–and deeply problematic–misconception of hiring's strategic role. In a new paper coauthored with Daniel W. Elfenbein of Washington University in St. Louis and published in Strategy Science, Sterling articulates how smart hiring is inextricable from long-term corporate strategy; she also explains why delegating the responsibility of hiring to machines, at least in the near future, is likely to undermine its strategic potential. "With technology increasingly stepping into this role, we're at a moment in which these questions of higher-level strategy ought to be of great importance," she says. The use of machines in hiring became widespread roughly a quarter-century back, when career platforms like Monster.com emerged on the web.

Artificial intelligence is advancing at a rocket's pace, and every year the field looks fundamentally different than the year before. It's often difficult to keep up with all the news and exciting results. The best way I've found is to follow the machine learning community on Twitter. Keeping track of advancements in AI is not only fun but will also help in interviews by demonstrating to hiring managers your investment in the field. To get you started following the machine learning community, here's a fairly extensive list of AI researchers and pioneers I'm following.

"Our findings expose a threat to the privacy and safety of gay men and women," wrote Michal Kosinski in a paper set to be published by the Journal of Personality and Social Psychology--only he's the one now finding himself in danger. The New York Times takes a look at the quagmire Kosinski finds himself in following his decision to try--and, in some fashion, succeed--at building what many are referring to as "AI gaydar." The Stanford Graduate School of Business professor tells the Times he decided to attempt to use facial recognition analysis to determine whether someone is gay to flag how such analysis could reveal the very things we want to keep private. The Times delves into the research--first highlighted by the Economist in early September--and the many bones its many critics have to pick with it. Kosinski and co-author Yilun Wang pulled 35,000 photos of white Americans from online dating sites (those looking for same-sex partners were classified as gay) and ran them through a "widely used" facial analysis program that turns the location, size, and shape of one's facial characteristics into numbers.

A Stanford University expert has claimed that computer programmes will soon be able to guess your political leaning and IQ based on photos of your face. Dr Michal Kosinski went viral last week after publishing research suggesting artificial intelligence (AI) can tell whether someone is straight or gay based on photos. Now the psychologist and data scientist has claimed that sexual orientation is one of many character traits the AI will be able to detect in the coming years. Stanford researcher Dr Michal Kosinski went viral last week after publishing research (pictured) suggesting AI can tell whether someone is straight or gay based on photos. AI-powered computer programmes can learn how to determine certain traits by being shown a number of faces in a process known as'training'.