The US Census Bureau is convinced that traditional methods of statistical disclosure limitation have not done enough to protect privacy. These methods may have been adequate in the past, but it no longer makes sense to implicitly assume that those who would like to violate privacy have limited resources or limited motivation. The Bureau has turned to differential privacy for quantifiable privacy guarantees that are independent of the attacker’s resources and determination.
John Abowd, chief scientist for the US Census Bureau, gave a talk a few days ago (March 4, 2019) in which he discusses the need for differential privacy and how the bureau is implementing differential privacy for the 2020 census.
Absolutely the hardest lesson in modern data science is the constraint on publication that the fundamental law of information recovery imposes. I usually call it the death knell for traditional method of publication, and not just in statistical agencies.