Can you trust them?
The Defense Department announced five ethical principles it plans to live by as it develops and uses artificial intelligence.
Category: robotics/AI – Page 1,921
Users of Gmail get 300 billion attachments each week. To separate legitimate documents from harmful ones, Google turned to AI—and it’s working.
L1gh t, a fledgling AI startup that wants to help technology companies combat online toxicity, bullying, and abuse, has raised $15 million in a seed round of funding from Mangrove Capital Partners, Tribeca Venture Partners, and Western Technology Investment.
The company’s substantial seed funding comes as tech companies are struggling to contain offensive and harmful behavior on their platforms. It’s nearly impossible to monitor massive platforms manually, which is why automation and AI are playing increasing roles in the gatekeeping process — but they still can’t detect every piece of abusive content. Moreover, technology companies have other priorities to juggle — such as making more money and growing their user base. Against this backdrop, L1ght is hoping to carve out a niche by focusing on safeguarding children.
Waiting in a service station waiting room purgatory one day, Victor Darolfi had a simple thought. “I sat at America’s Tires for three hours and thought, hey, we use robots to put tires on at the factory,” the founder explains. “Why don’t we bring robots into the service industry?”
The notion was the first seed behind RoboTire, the Bay Area-based robotics company, which the former Spark Robotics CEO founded in October 2018. Now ready to come out of stealth as part of the latest batch of Y Combinator startups, RoboTire has already generated interest in the industry for its ability to change car tires in a fraction of the time of most mechanics.
“We can do a set of four tires, put in to pull out, in 10 minutes,” Darolfi explains. “It normally takes about 60 minutes for a human operator to do a set of four. Some can go faster, but they really can’t do that eight hours a day.”
Handicaps: weak private sector, Soviet-style bureaucracy. Helps: Great STEM education — and history.
More than Western governments and even more than China’s, the Russian government is trying to position itself as a facilitator of innovation in artificial intelligence, the technology that Vladimir Putin said will lead whoever masters it to global advantage. Russia seeks “to go our own way,” said Prime Minister Dmitry Medvedev, borrowing Lenin’s 1917 words about various anti-capitalist ideologies to describe his government’s 21st-century attempt to shake the world.
Those who doubt that this uniquely state-heavy approach can succeed would do well to remember that today’s internet and mobile telecommunications grew out of Pentagon-funded research, that the Soviet Union led the Space Race for a decade, and that U.S. astronauts currently ascend to orbit atop Russian rockets.
The Pentagon is adopting new ethical principles as it prepares to accelerate its use of artificial intelligence technology on the battlefield.
The sophistication of autonomous systems currently being developed across various domains and industries has markedly increased in recent years, due in large part to advances in computing, modeling, sensing, and other technologies. While much of the technology that has enabled this technical revolution has moved forward expeditiously, formal safety assurances for these systems still lag behind. This is largely due to their reliance on data-driven machine learning (ML) technologies, which are inherently unpredictable and lack the necessary mathematical framework to provide guarantees on correctness. Without assurances, trust in any learning enabled cyber physical system’s (LE-CPS’s) safety and correct operation is limited, impeding their broad deployment and adoption for critical defense situations or capabilities.
To address this challenge, DARPA’s Assured Autonomy program is working to provide continual assurance of an LE-CPS’s safety and functional correctness, both at the time of its design and while operational. The program is developing mathematically verifiable approaches and tools that can be applied to different types and applications of data-driven ML algorithms in these systems to enhance their autonomy and assure they are achieving an acceptable level of safety. To help ground the research objectives, the program is prioritizing challenge problems in the defense-relevant autonomous vehicle space, specifically related to air, land, and underwater platforms.
The first phase of the Assured Autonomy program recently concluded. To assess the technologies in development, research teams integrated them into a small number of autonomous demonstration systems and evaluated each against various defense-relevant challenges. After 18 months of research and development on the assurance methods, tools, and learning enabled capabilities (LECs), the program is exhibiting early signs of progress.
This chapter appears concurrently in Age of Robots and includes content and quotes garnered from interviews with James J. Hughes, Jerome Glenn, Ian Pearson, Richard Yonck, John C. Havens and Alexandra Whittington on the Seeking Delphi™ podcast between April of 2017 and November of 2018. **.