While some believe that fundamental privacy protections will be challenged by the operation of Big Data analytics, Dr. Cavoukian dispels the notion that privacy acts as a barrier to analytics and the innovations they can spark. She argues that the limiting paradigm of “zero-sum” – that you can either have privacy or innovation, but not both – is an outdated, win/lose model of approaching the question of privacy in the age of Big Data. Instead, a “positive-sum” solution is needed in which the interests of both sides may be met, in a doubly-enabling, “win-win” manner though Privacy by Design (PbD). PbD is predicated on the rejection of zero-sum propositions by proactively embedding the necessary measures into the design and data architecture involved. Dr. Cavoukian will demonstrate that you can embed privacy into virtually any system or operation to achieve positive sum outcomes, enabling Big Data and Big Privacy – not one at the expense of the other.