Bestavros: MPC helps orgs achieve data transparency while maintaining privacy
Founding Director Azer Bestavros wrote in a Washington Post op-ed that secure multiparty computation can help organizations move past a common impasse they face when they want to be transparent with data for the public good while also maintaining their privacy.
The technology, based on a complex algorithm developed decades ago by theoretical mathematicians but recently developed into a software application at BU, was successfully used by the Boston Women’s Workforce Council to reveal in January 2017 the pay disparity between women and men working in Greater Boston. Bestavros said it allowed participating companies to contribute salary data with the guarantee that it would remain private.
“No party ever glimpsed data from another, but everyone learned of the disparity in pay: Women at the Boston companies were paid 77 cents for every dollar paid to men,” Bestavros wrote.
According to Bestavros, the secure multiparty computation technology would be particularly useful in helping move along a pair of Senate bills that would make data about college outcomes more publicly available. The proposed legislation is currently stalled because it is caught, Bestavros wrote, “in the tension between two constituencies who mean well.”
“It’s an increasingly familiar conflict between privacy and the public good, and because of a little-used cryptographic technology that has been used to solve similar clashes, it need not exist,” he added.