Politicians have the tech industry in their cross hairs following recent high-profile data blunders like Facebook’s Cambridge Analytica scandal.
The question is what to do.
One big issue for tech companies is consumers losing trust in the industry overall rather than individual companies every time a high-profile data breach makes the news, University of Maryland economics professor Ginger Jin said Tuesday at the National Association of Business Economics conference in San Francisco.
“In other words, a few bad apples pollute the whole thing,” Jin said.
Here are three more interesting tidbits about data privacy, regulation, and policy from the event.
Google’s privacy dilemma
Google’s chief economist Hal Varian explained several problems Google faces today involving data and privacy. In some cases, they conflict.
“People say they want privacy but their actions indicate that they don’t really care about it,” Varian said. Although many people say they dislike companies tracking their locations, “everyone loves this feature of Google Maps that tells you how long it will take to get home.”
As for possible new laws limiting use of customer data, Varian said, “We shouldn’t kid ourselves—of course there will be regulation of the tech industry.” He gave the example of the early days of cars, when it “didn’t matter what side of the road you drive in.”
“So, of course the industry will become more regulated in various ways,” Varian said. His hope is that any future laws don’t “constrict the flow of innovation.”
How antitrust laws could conflict with data privacy
When considering how to regulate the tech industry, lawmakers typically think of either antitrust or data privacy issues, Jin explained.
In terms of antitrust, lawmakers worry whether companies have an unfair advantage over rivals by using the data they collect to improve their products, internal functions, or help them better understand consumer demand.
As a potential solution, some policymakers want to increase the sharing of data between companies so that they can operate on a more level playing field, Jin said. The problem is that sharing can conflict with the idea of privacy as a human right.
Essentially, making data more available to companies may anger consumers who worry about their information being available to more than just the major players.
“These two, to some extent, can be contradictory to each other,” Jin said.
Federal government is worried about AI’s “black box” issue
Nancy Potok, the chief statistician of the United States, explained that federal agencies are looking at cutting-edge machine learning to improve operations and create more reliable statistics. The U.S. Census Bureau, for instance, is using machine-learning techniques to improve the accuracy of its economic surveys.
However, it’s a mystery how many AI systems come up with their answers, leading researchers to call the technology a mysterious “black box.” This lack of visibility creates a conflict within the government because “one of the founding principles of high quality data is that you have transparency,” Potok said.
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“I don’t have the solution,” Potok said. “It’s something we’re grappling with at the federal level.”