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Evernote CEO: 'We let our users down' with privacy policy change

Blair Hanley Frank | Dec. 19, 2016
The company will anonymise data that employees see to help with machine learning

Evernote CEO Chris O'Neill has had a long couple of days. The company he runs recently ignited a firestorm among its users when it announced a privacy policy change that would have required users to open up all their notes for analysis in order to take advantage of forthcoming machine learning features. 

"We let our users down," he said in an interview. "We really tactically communicated in about as poor a way as we could."

Evernote is going back to the drawing board and reversing course on the proposed policy. Users won't have their data shared with employees to help with machine learning unless they explicitly opt in. 

"If any human is going to be involved, it’s going to be on an opt-in basis, period," O'Neill said.

Furthermore, he said that he wanted to be clear that the company isn't in the business of reading users' notes. He joined Evernote as a heavy user of its service, and he keeps private information in his own account. 

"Evernote never has and won't read people’s notes without their permission," he said. “I want to be really clear on that. We've not done that. We don’t plan to do that, period.”

Trust matters

This reversal is an important move for Evernote because it's competing in a tough market against Microsoft, Google, Apple, and a host of other companies to be the service for people to store their notes. When it comes to storing deeply personal data, trust matters. 

"We're not a social media outlet that's reading your stuff to then schlep ads in front of you," O'Neill said. "The only thing that matters is trust and the quality of our product. You have to trust us, and you have to find value in our product. And if you don’t, guess what? You don’t pay us."

Going forward, Evernote is still going to be working on features based on machine learning, though it's shelving the privacy policy change that kicked off this wave of concern. CTO Anirban Kundu said the company is working on two broad types of functionality.

The first type is a capability can be trained using public data sets and information provided to the company but don't require data from all of Evernote's users. An example he gave was a way to extract tasks from meeting notes.

"There’s a defined manner in which you can extract tasks out of a particular meeting note," Kundu said. "We don’t need to look at your notes to figure out what the task is."

In order to train that type of machine learning system, Evernote may ask its users to submit notes they're comfortable sharing with the company as part of a beta program. In addition, users will be able to choose to submit their notes for review if a system didn’t identify them correctly.

 

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