"We at Apple reject the idea that our customers should have to make tradeoffs between privacy and security," said Apple CEO Tim Cook earlier this month during an Electronic Privacy Information Center (EPIC) event where he was honored for corporate leadership. "We can and we must provide both in equal measure."
Via a remote video feed, Cook chastised some of Silicon Valley's most notable companies for "lulling their customers into complacency about their personal information" and added that Apple thinks it's wrong to sell customer information for profit. "You might like these so-called free services, but we don't think they're worth having your email, your search history and now even your family photos data mined and sold off for God knows what advertising purpose," Cook said during the speech, according to TechCrunch.
These statements have won Cook accolades among consumer privacy advocates, but the CEO glossed over the various data Apple collects on its users for advertising and other purposes. Apple's iAd advertising platform pales in comparison to those of Google and Facebook, but to suggest that Apple has no interest at all in its users' data is simply inaccurate. However, advertising isn't Apple's main motivation for collecting information on its users. Some of that data is used to feed services that are core to its mobile experience.
The troves of personal information that Apple, Google and Microsoft collect from their users power the Siri, Google Now and Cortana artificial intelligence (AI) apps. The privacy trade-offs should be weighed on an individual basis, but for all intents and purposes these virtual assistants are only as good as the data they use to ascertain relevant recommendations.
Data is the fuel that powers artificial intelligence
Alexander Gray, CTO and cofounder of machine-learning company Skytree, says AI platforms deliver better results as they collect and use more data. "Predictive accuracy keeps improving as the amount of data keeps increasing, but only up to the limit defined by the fundamental amount of predictive information in the data," he says. AI models will reach a threshold in the value they provide unless the models become more complex and crunch different types of new data, says Gray.
"The more data AI can use, the better its models will be," Gray says. "Hence, there is a fundamental and unavoidable trade off between privacy and AI effectiveness."
However, it's not all about the volume of data points, according to Jonathan Crane, chief commercial officer at IPsoft, an IT infrastructure services firm. "It's about adding and joining relevant data together to form a body of knowledge that is relevant to a particular process," Crane says. "Truly intelligent systems need to be able to link the data points together in order to make a helpful and sensible recommendation."
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