Innovation | Trends

Data collection raises key questions about privacy, ethics

‘People would be up in arms if they knew how much information was being collected on them. But they turn a blind eye,’ expert says

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Woman in kitchen, using a smart-speaker device“People would be up in arms if they knew how much information was being collected on them. But they turn a blind eye,” says Michael Albo, CEO and co-founder of the Data Science Institute (Shutterstock/Daisy Daisy)

Do you know what data your devices collect and for what purpose? Probably not. 

And yet, the number of collection points is growing exponentially. This not only includes all phone’s apps (even some of the deleted ones), but increasingly everyday appliances and objects as well. 

“All connected products generate data that can be of interest to third parties,” says Philippe Nieuwbourg, a French independent analyst specializing in information technology. “It’s as if products have become secondary to the value of the data they provide. Just think of big-screen HD smart TVs, and how they’ve become much more affordable. That’s because they’ve never collected this much data before.” [See Data analytics: Is it working for your company?]

Even simple chores are being monitored. Whirlpool sells connected washers that allows users to start and check in on wash cycles (even remotely) with their smart phone. And soon, it will be possible to do the same on an Apple Watch. Whirlpool’s washing machines also respond to Amazon’s assistant, Alexa, and work with the smart thermostats sold by home security system provider Nest.

For three years now, Samsung has had a connected refrigerator, called Family Hub, in the market. Equipped with a built-in camera, it lets owners remotely view its contents to make grocery shopping easier. The door’s tactile-screen can be used to synchronize the fridge with a Google account or Outlook calendar, load photos or stream music with Spotify. And this coming April, a software update will enable the fridge to ID all the food in it, and flag any missing items—so owners can either order what’s missing through an integrated app or book an Uber ride to a favourite restaurant if they prefer to dine out.

“People would be up in arms if they knew how much information was being collected on them. But they turn a blind eye,” says Michael Albo, CEO and co-founder of the Data Science Institute. “Pretty soon, the question won’t be whether you’re for or against smart devices, but how you can avoid them.”

But in the race to monetize our data, Nieuwbourg asks, “Who will ensure that all this data is handled in a transparent and ethical manner?” [See Positioning Canada to lead in a digital and data-driven economy for more]

Many insurers already use algorithms that measure stress and anxiety levels over the phone to verify if clients are lying about their claims. If they could access their refrigerator’s contents, would they lower their premiums, as a number of automobile insurers did after monitoring their clients’ on-road driving behaviour through mobile telematics systems? Or, will insurers use algorithms to cross-check data with other readily available information—geographic location, biometrics, purchase history, and so on—to penalize certain consumers by charging them additional premiums?

“Algorithms are there to maximize data collection,” Albo says. “But they tend to enhance biases.” 

Adds Nieuwbourg: “Algorithms don’t really think. And while they may be instructed to follow legal rules, they don’t necessarily abide by ethical ones.”

As real-life examples he points to airlines that deliberately employ family-splitting algorithms to force family members to pay seat selection fees to sit together; and Uber, which kept its surge-pricing algorithm on immediately following the 2017 London terror attack, causing fares to drastically increase as demand surged while people tried to escape the affected areas.

So while more people are concerned about the use of their data (particularly through laws such as the GDPR), many continue to turn a blind eye.

LEARN MORE ABOUT BIG DATA

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