“The first attacks will come very soon against online classification systems,” McDaniel says. This could include modern spam filters, systems designed to detect illicit or copyright material, and advanced machine-learning-based computer security systems.   A new paper suggests that the problem could be more widespread than previously known. It shows that certain deceptions can be reused against different machine-learning systems, or even against a large “black box” system about which an attacker does not have prior knowledge. Bugs lurking in these popular machine-learning tools could provide another way to target them. New machine-learning tools are developing at a rapid pace, and are often released for free online before being employed in active services such as image recognition or natural language analysis tools.

https://www.technologyreview.com/s/603116/how-long-before-ai-systems-are-hacked-in-creative-new-ways/