{"id":8911,"date":"2017-04-01T03:33:04","date_gmt":"2017-04-01T03:33:04","guid":{"rendered":"http:\/\/www.lifeandnews.com\/articles\/?p=8911"},"modified":"2017-04-02T03:36:36","modified_gmt":"2017-04-02T03:36:36","slug":"how-understanding-animals-can-help-us-make-the-most-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.lifeandnews.com\/articles\/how-understanding-animals-can-help-us-make-the-most-of-artificial-intelligence\/","title":{"rendered":"How understanding animals can help us make the most of artificial intelligence"},"content":{"rendered":"

Heather Roff<\/a>, Arizona State University<\/a><\/em><\/span><\/p>\n

Every day countless headlines emerge from myriad sources across the globe, both warning of dire consequences<\/a> and promising utopian futures<\/a> \u2013 all thanks to artificial intelligence. AI \u201cis transforming the workplace,\u201d writes the Wall Street Journal<\/a>, while Fortune<\/a> magazine tells us that we are facing an \u201cAI revolution\u201d that will \u201cchange our lives.\u201d But we don\u2019t really understand what interacting with AI will be like \u2013 or what it should be like. \"The<\/p>\n

It turns out, though, that we already have a concept we can use when we think about AI: It\u2019s how we think about animals. As a former animal trainer (albeit briefly) who now studies how people use AI, I know that animals and animal training can teach us quite a lot about how we ought to think about, approach and interact with artificial intelligence, both now and in the future. <\/p>\n

Using animal analogies<\/a> can help regular people understand many of the complex aspects of artificial intelligence. It can also help us think about how best to teach these systems new skills and, perhaps most importantly, how we can properly conceive of their limitations, even as we celebrate AI\u2019s new possibilities.<\/p>\n

Looking at constraints<\/h2>\n

As AI expert Maggie Boden<\/a> explains<\/a>, \u201cArtificial intelligence seeks to make computers do the sorts of things that minds can do.\u201d AI researchers are working on teaching computers to reason, perceive, plan, move and make associations. AI can see patterns in large data sets, predict the likelihood of an event occurring, plan a route, manage a person\u2019s meeting schedule and even play war-game scenarios. <\/p>\n

Many of these capabilities are, in themselves, unsurprising: Of course a robot can roll around a space and not collide with anything. But somehow AI seems more magical when the computer starts to put these skills together to accomplish tasks.<\/p>\n

Take, for instance, autonomous cars. The origins of the driverless car are in a 1980s-era Defense Advanced Research Project Agency project called the Autonomous Land Vehicle<\/a>. The project\u2019s goals were to encourage research into computer vision, perception, planning and robotic control. In 2004, the ALV effort became the first Grand Challenge<\/a> for self-driving cars. Now, more than 30 years since the effort began, we are on the precipice of autonomous or self-driving cars in the civilian market. In the early years, few people thought such a feat was impossible: Computers couldn\u2019t drive!<\/p>\n

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