Skynet Today Last Week in AI News #38
Last Week in AI News #38
Subscribe for future emails here!
Senate passes legislation to combat ‘deepfake’ videos
The Senate passed legislation on Thursday to help understand the risks posed by “deepfake” videos, those altered by AI to change the meaning of the video.
The Deepfake Report Act would require the Department of Homeland Security to publish an annual report on the use of deepfake technology that would be required to include an assessment of how both foreign governments and domestic groups are using deepfakes to harm national security.
Deepfakes have been an increasing source of concern on Capitol Hill this year, especially after a video of Speaker Nancy Pelosi that was edited to make her appear intoxicated went viral online. Due to the potential for deepfakes to affect our political process by manipulating what we see online, there was strong bipartisan support for the bill.
Hailing a Driverless Ride in a Waymo
Despite progress, Waymo’s promise of a driverless future appeared stagnated. But now, customers of Waymo’s early rider program can complete their rides in a diverless car.
There are, of course, caveats to this milestone. Waymo is conducting these “completely driverless” rides in a controlled geofenced environment. Early rider program members are people who are selected based on what ZIP code they live in and are required to sign NDAs. And the rides are free, at least for now.
The source of Waymo’s confidence in its driverless cars is still unclear, and according to TechCrunch it’s therefore difficult to tell whether the driverless rides now being offered indicate a significant benchmark in Waymo’s efforts or simply confidence in an unchallenging route.
Regardless of technical challenges, Waymo’s early driverless rides mark the beginning of a new phase in which challenges that can’t be approached with technology alone will need to be dealt with. It will require lots of work by humans to research human behavior, understand the chaotic interactions of the modern curbside, and develop relationships and protocols with local authorities. Despite the difficulty of these challenges, the fact that Waymo is addressing them is encouraging.
Advances & Business
A neural net solves the three-body problem 100 million times faster - Machine learning provides an entirely new way to tackle one of the classic problems of applied mathematics involving the motions of the Earth, Moon, and Sun. A neural network trained to predict such motions should make it possible to simulate the motion of black bodies inside galactic nuclei and globular star clusters much more accurately than ever before.
DARPA is betting on AI to bring the next generation of wireless devices online - In the agency’s latest grand challenge, teams competed for $2 million and a chance to shape the future of communication technology by finding a better way to carve up the radio spectrum. DARPA posed teams a series of increasingly difficult tasks, culminating in incorporating machine learning to make collaborative radios autonomous.
Using AI to Eliminate Bias from Hiring - It is impossible to correct human bias, but it is demonstrably possible to identify and correct bias in AI. If we take critical steps to address the concerns that are being raised, we can truly harness technology to diversify the workplace. In this article, Frida Polli argues that AI holds the greatest promise for eliminating bias in hiring.
AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning - AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar challenged two of the world’s top players in StarCraft II, one of the most enduring and popular real-time strategy video games of all time. Since then, DeepMind has taken on a much greater challenge: playing the full game at a Grandmaster level under professionally approved conditions.
An exclusive look at Facebook’s efforts to speed up MRI scans using artificial intelligence - A partnership between the Facebook AI Research Division and the NYU School of Medicine has a simple goal: use AI to develop quick yet high-quality MRI scans that could someday allow busy medical centers to care for more people, countries with scant resources to make better use of the equipment they do have, and the elderly, young, and claustrophobic to spend less time in a narrow and loud magnetic tube.
AI could help us unpick why some songs just make us feel so good - Machine learning can map which musical qualities trigger what types of physical and emotional responses. One day the technique could even be used in music therapy.
Concerns & Hype
Facial recognition is on the rise, but artificial intelligence is already being trained to recognize humans in new ways - including gait detection and heartbeat sensors - For private companies and government agencies trying to track peoples’ movements, technology is making the task increasingly easy. Emerging technologies can recognize humans and track people’s location by detecting their heartbeat, walking gait, and even microbial traces left behind by skin cells or sweat.
AI May Not Kill Your Job - Just Change It - Don’t fear the robots, according to a report from MIT and IBM. Worry about algorithms replacing any task that can be automated.
Expert Opinions & Discussion within the field
Artificial Intelligence: Reality vs Hype - Landing AI Founder and CEO Andrew Ng sits down with Bloomberg’s Austin Carr at Sooner Than You Think in Brooklyn to discuss impacts of the industry-wide push towards AI and its potential effects.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead - There has been a increasing trend in healthcare and criminal justice to leverage machine learning (ML) for high-stakes prediction applications that deeply impact human lives. The lack of transparency and accountability of predictive models can have (and has already had) severe consequences.
What does it mean for a machine to “understand”? - Critics of recent advances in artificial intelligence complain that although these advances have produced remarkable improvements in AI systems, these systems still do not exhibit “real”, “true”, or “genuine” understanding. In this article, Thomas Dietterich argues that “understanding” exists along a continuous spectrum of capabilities.
What’s Still Lacking in Artificial Intelligence - Before we can design ethical artificial intelligence, regulate AI appropriately or allocate tasks to the right systems, we need to know what AI is. What is still lacking in AI is the faculty of judgment.
AI Strategies of U.S., China, and Canada in Global Governance, Fairness, and Safety
Google’s LYmph Node Assistant - a Boost, not Replacement, for Doctors
Amazon Rekognition Mistook Congressmen for Criminals? A Closer Look
Google Translate’s ‘Sinister Religious Prophecies’, Demystified