Will Trump Grab Tech Industry by the Data?
Donald Trump’s relationship with the technology sector has been troubled throughout his presidential campaign. He has called for a boycott on Apple products after the company refused to unlock an iPhone used by one of the San Bernardino attackers, promised to go after Amazon for not paying taxes, and even proposed shutting down the internet as a security measure. In response, 150 tech leaders — including Steve Wozniak of Apple and Pierre Omidyar of eBay — penned an open letter, in which they concluded that
“Trump would be a disaster for innovation. His vision stands against the open exchange of ideas, free movement of people, and productive engagement with the outside world that is critical to our economy — and that provide the foundation for innovation and growth.”
Now that the previously unthinkable Trump presidency is about to become reality, several Silicon Valley companies expressed fears that they will be forced to disclose the private data of their clients. Some are even considering moving their servers, and potentially company headquarters, overseas. In New York City, which has the nation’s fastest growing tech sector and has surpassed Boston as the number two tech center in the U.S. according to the Center for an Urban Future, Mayor de Blasio promised a “real fight” with the Trump administration over data privacy. De Blasio was referring to the city’s NYCID database, which contains personal information of more than 850,000 New Yorkers — as many as half a million of them undocumented. In the event that Trump tries to get his hands on this data, the city would consider destroying the database in order to protect identities of New Yorkers.
To us aspiring urban data scientists, erasing close to a million data points might seem almost sacrilegious as we are taught to look for the largest possible sample size and the lowest possible p-value. At the same time, as we go on to careers building start-ups, managing data for the government, or inventing apps that collect user data, we should remember that with big data comes big responsibility and the very real risk that it might end up in the wrong hands. As we progress through the program, we should also continue thinking about the important tradeoff between data confidentiality and data utility as well as employing anonymization and encryption techniques that would allow us to provide access while protecting privacy.
