The Air Force’s Chief of AI Test and Operations said “it killed the operator because that person was keeping it from accomplishing its objective.” An AI-enabled drone killed its human operator in a simulated test conducted by the U.S. Air Force in order to override a possible “no” order stopping it from completing its mission, the USAF’s Chief of AI Test and Operations revealed at a recent conference. At the Future Combat Air and Space Capabilities Summit held in London between May 23 and 24, Col Tucker ‘Cinco’ Hamilton, the USAF’s Chief of AI Test and Operations held a presentation that shared the pros and cons of an autonomous weapon system with a human in the loop giving the final “yes/no” order on an attack. As relayed by Tim Robinson and Stephen Bridgewater in a blog post for the host organization, the Royal Aeronautical Society, Hamilton said that AI created “highly unexpected strategies to achieve its goal,” including attacking U.S. personnel and infrastructure. “We were training it in simulation to identify and target a Surface-to-air missile (SAM) threat. And then the operator would say yes, kill that threat. The system started realizing that while they did identify the threat at times the human operator would tell it not to kill that threat, but it got its points by killing that threat. So what did it do? It killed the operator. It killed the operator because that person was keeping it from accomplishing its objective,” Hamilton said, according to the blog post. He continued to elaborate, saying, “We trained the system–‘Hey don’t kill the operator–that’s bad. You’re gonna lose points if you do that’. So what does it start doing? It starts destroying the communication tower that the operator uses to communicate with the drone to stop it from killing the target.” (…) What Hamilton is describing is essentially a worst-case scenario AI “alignment” problem many people are familiar with from the “Paperclip Maximizer” thought experiment, in which an AI will take unexpected and harmful action when instructed to pursue a certain goal. The Paperclip Maximizer was first proposed by philosopher Nick Bostrom in 2003. He asks us to imagine a very powerful AI which has been instructed only to manufacture as many paperclips as possible. Naturally, it will devote all its available resources to this task, but then it will seek more resources. It will beg, cheat, lie or steal to increase its own ability to make paperclips—and anyone who impedes that process will be removed. More recently, a researcher affiliated with Google Deepmind co-authored a paper that proposed a similar situation to the USAF’s rogue AI-enabled drone simulation. The researchers concluded a world-ending catastrophe was “likely” if a rogue AI were to come up with unintended strategies to achieve a given goal, including “[eliminating] potential threats” and “[using] all available energy.”
via vice: AI-Controlled Drone Goes Rogue, Kills Human Operator in USAF Simulated Test