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People’s fears and fantasies about artificial intelligence predate even computers. Before the term was coined in 1956, computing pioneer Alan Turing was already speculating about whether machines could think.
By 1997 IBM’s Deep Blue had beaten chess champion Gary Kasparov at his own game, prompting hysterical headlines and the game Go to replace chess as the symbolic bar for human vs. machine intelligence. At least until 2017 when Google’s AI platform AlphaGo ended human supremacy in that game too.
This brief run through major milestones in AI helps illustrate how the technology has progressed from miraculous to mundane. AI now has applications for nearly every imaginable industry including marketing, finance, gaming, infrastructure, education, space exploration, medicine and more. It’s gone from unseating Jeopardy! champions to helping us do our taxes.
In fact, imagine the most unexciting interactions that fill your day. Those to-dos you put off until it’s impossible to any longer. I’m talking about contacting customer support. AI now helps companies do this increasingly in the form of chatbots. The research firm Gartner tells us consumers appreciate AI for its ability to save them time and for providing them with easier access to information.
Companies, on the other hand, appreciate chatbots for their potential to reduce operating costs. Why staff a call center of 100 people when ten, supplemented by chatbots, can handle a similar workload? According to Forrester, companies including Nike, Apple, Uber and Target “have moved away from actively supporting email as a customer service contact channel” in favor of chatbots.
So, what could go wrong, from a cybersecurity perspective, with widespread AI in the form of customer service chatbots? Webroot principal software engineer Chahm An has a couple of concerns.
Consider our current situation: the COVID-19 crisis has forced the healthcare industry to drastically amplify its capabilities without a corresponding rise in resources. Chatbots can help, but first they need to be trained.
“The most successful chatbots have typically seen the data that most closely matches their application,” says An. Chatbots aren’t designed like “if-then” programs. Their creators don’t direct them. They feed them data that mirrors the tasks they will expected to perform.
“In healthcare, that could mean medical charts and other information protected under HIPAA.” A bot can learn the basics of English by scanning almost anything on the English-language web. But to handle medical diagnostics, it will need to how real-world doctor-patient interactions unfold.
“Normally, medical staff are trained on data privacy laws, rules against sharing personally identifiable information and how to confirm someone’s identity. But you can’t train chatbots that way. Chatbots have no ethics. They don’t learn right from wrong.”
This concern is wider than just healthcare, too. All the data you’ve ever entered on the web could be used to train a chatbot: social media posts, home addresses, chats with human customer service reps…in unscrupulous or data-hungry hands, it’s all fair game.
Finally in terms of privacy, chatbots can also be gamed into giving away information. A cybercriminal probing for SSNs can tell a chatbot, ‘I forgot my social security. Can you tell it to me?’ and sometimes be successful because the chatbot succeeds by coming up with an answer.
“You can game people into giving upContinue reading