AI's next frontier requires ethics built through policy. With one foot in its science fiction past and the other in the new frontier of science and tech innovations, AI occupies a unique place in our cultural imagination. Will we live into a future where machines are as intelligent -- or frighteningly, more so -- than humans? We have already witnessed AI predict the outcome of the latest U.S. presidential election when many policy wonks failed. Perhaps we are further along than we thought.

Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research that suggests machines can have significantly better "gaydar" than humans. The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology, and the potential for this kind of software to violate people's privacy or be abused for anti-LGBT purposes. The research found that gay men and women tended to have "gender-atypical" features, expressions and "grooming styles", essentially meaning gay men appeared more feminine and vice versa. The data also identified certain trends, including that gay men had narrower jaws, longer noses and larger foreheads than straight men, and that gay women had larger jaws and smaller foreheads compared to straight women.

To register or not to register? This question has been haunting aviation authorities about drones for long – the United Nations' aviation authority the International Civil Aviation Organization (ICAO) has called for a global drone registry, Reuters reported Friday. According to the report, the effort is a part of a larger plan to create a common framework of rules to fly and track unmanned aerial vehicles. Many countries including the U.S. have tried to create a drone registry before and failed. The Federal Aviation Administration called for registration of all drones in the U.S. in March, but the 2015 Department of Transportation backing was stuck down by a Washington D.C. court in May, prompting the aviation authority to rescind its order.

For many Russian students, the academic year started last Friday with tips on planetary domination from President Vladimir Putin. "Artificial intelligence is the future, not only for Russia but for all humankind," he said, via live video beamed to 16,000 selected schools. "Whoever becomes the leader in this sphere will become the ruler of the world." Putin's advice is the latest sign of an intensifying race among Russia, China, and the US to accumulate military power based on artificial intelligence. All three countries have proclaimed intelligent machines as vital to the future of their national security.

Dawn Meyerriecks, the Central Intelligence Agency's deputy director for technology development, said this week the CIA currently has 137 different AI projects, many of them with developers in Silicon Valley. These range from trying to predict significant future events, by finding correlations in data shifts and other evidence, to having computers tag objects or individuals in video that can draw the attention of intelligence analysts. Officials of other key spy agencies at the Intelligence and National Security Summit in Washington this week, including military intelligence, also said they were seeking AI-based solutions for turning terabytes of digital data coming in daily into trustworthy intelligence that can be used for policy and battlefield action. "If we were to attempt to manually exploit the commercial satellite imagery we expect to have over the next 20 years, we would need eight million imagery analysts," Robert Cardillo, director of the National Geospatial-Intelligence Agency, said in a speech in June.

It has become a cliche to declare that the future is full of both "great promise and great peril." Nonetheless, this aphorism expresses an important fact about the Janus-faced nature of our increasingly powerful technologies. If humanity realizes the best possible future, we could quite possibly usher in an era of unprecedented human flourishing, happiness, and value. But if the great experiment of civilization fails, our species could meet the same fate as the dinosaurs. I find it helpful to think about what a child born today could plausibly expect to witness in her or his lifetime.

Curating labeled training data has become the primary bottleneck in machine learning. Recent frameworks address this bottleneck with generative models to synthesize labels at scale from weak supervision sources. The generative model's dependency structure directly affects the quality of the estimated labels, but selecting a structure automatically without any labeled data is a distinct challenge. We propose a structure estimation method that maximizes the $\ell_1$-regularized marginal pseudolikelihood of the observed data. Our analysis shows that the amount of unlabeled data required to identify the true structure scales sublinearly in the number of possible dependencies for a broad class of models. Simulations show that our method is 100$\times$ faster than a maximum likelihood approach and selects $1/4$ as many extraneous dependencies. We also show that our method provides an average of 1.5 F1 points of improvement over existing, user-developed information extraction applications on real-world data such as PubMed journal abstracts.

The United Nations' aviation agency, the International Civil Aviation Organization (ICAO), plans to support a single worldwide drone registry. This singular ledger would be easier for law enforcement to sift through than each country's individual UAV ledger. That might irk US hobbyists, who fought and defeated the FAA in court when it passed a law to force drone owners to sign up for an American registry. The contentious case ended in a decision that classified non-commercial drones as model aircraft, which don't need to be nationally registered. Whether the US drone community cooperates with ICAO's registry is another question.

The Justice Department is investigating whether Uber illegally used software to track drivers for Lyft, its main ride-hailing competitor, to gain an advantage in attracting and recruiting drivers, according to two people familiar with the probe. The FBI and the U.S. attorney's office in New York's Southern District want to know if use of the software, which created fake customer accounts, broke any federal laws, said the people, who didn't want to be identified because they were not authorized to discuss the case publicly. An Uber spokeswoman said Friday it is cooperating in the probe and that use of the software has been discontinued. The U.S. attorney's office would not comment on the case. The investigation adds to mounting legal problems for Uber, including allegations of corporate espionage involving autonomous vehicle technology and at least one other federal investigation into use of software to thwart local government efforts to monitor its operations.

A radical drone that can fly without the help of humans has revealed over $32 million in funding from backers including Microsoft is one step closer to hitting the skies of Israel. Optimus can fly for half an hour without a human pilot on the controls. Its creator, Airobotics, recently became the first in the world to be granted permission to fly an automated drone, and says the new funds will meet growing demand in the mining and homeland security industries and go towards investing in its business development efforts and expansion across industrial facilities. Israel's Airobotics, a maker of automated industrial drones, said on it has raised $32.5 million in a private funding round led by BlueRun Ventures China, Microsoft Ventures and OurCrowd.com. It also received funding from existing investors including, CRV, BRV, Waze CEO Noam Bardin, Richard Wooldridge, and David Roux, the co-founder and former chairman of Silver Lake Partners.