John Kahan – VP, Chief Data Analytics Officer for Microsoft, writes:
The invention of differential privacy was ahead of its time. The technology, pioneered by Microsoft researchers 15 years ago, makes it possible to extract useful insights from datasets, while safeguarding the privacy of the individuals included in the data. What was needed to realize its full potential? The marriage of cloud computing and artificial intelligence (AI), which allows for the sharing and analysis of huge amounts of data requiring that individual personal privacy is protected.
Over the past year, Microsoft collaborated with the OpenDP Initiative, led by Harvard’s Institute for Quantitative Social Science (IQSS) and School of Engineering and Applied Sciences (SEAS), and together we launched the open-source differential privacy platform, SmartNoise. We’re excited about the results and the learnings we’ve collected to date. My colleague Sarah Bird recently wrote about those learnings and how Microsoft is adopting differential privacy into some of our products. Differential privacy has also become a powerful new tool in Microsoft’s privacy and security ecosystem. Externally, we’re working with partners, exploring how differential privacy applies in real world scenarios, and today we’re launching the SmartNoise Early Adopter Acceleration Program to attract more.
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