Over the last few decades, CIOs have seen the convergence of three trends. First, the role and value of data as a cornerstone of the business models of more and more companies. Second, the protection of the privacy of data has moved to the front of mind for consumers, businesses and governments. Finally, the role and expectations of the CIO has continued to evolve from a technology-focused, vertical leader, to a strategic business leader.
Progressive CIOs today understand that while fundamental performance metrics of systems such as uptime, speed, cost, etc remain important, CIOs are expected to be more than efficient order takers. They increasingly must lead strategically, shaping the business models of even the most traditional industries to adapt to new value propositions, network effects, and multi-side platforms.
Data underlies virtually all new business models. Machine learning and AI rest on foundations of sufficient data to produce usable models. Historically, data usage faces headwinds — regulations and evolving public perspectives combine to dampen commercial value….particularly externally.
Conventional methods to protect the privacy of data have turned out to often not be truly private. Numerous research studies have found “anonymized” data can be reverse engineered to identify specific individuals. In addition to privacy risks, techniques to mask or change data create complex workflows that require substantial resources to manage and maintain. Finally, conventional anonymization techniques can remove important signal content in the data, diminishing its commercial value
Fortunately, like other areas of technology, academic research has led to new capabilities that allow both data access and mathematically proven privacy . This new approach to data is called Differential Privacy, and represents a giant step forward in how to think about and use data. Since first published in academic research nearly fifteen years ago, Differential Privacy is rapidly becoming a key capability in leveraging data while mathematically ensuring privacy.
For CIOs, Differential Privacy can be a game-changer. First, the approach moves data privacy from a “data based operation” to a compute operation – streamlining how quickly we can get data into the business and create value. Second, it does not rely on “removing signal” from data but rather ensures that maximum signal can be returned while simultaneously ensuring privacy. Finally, it moves privacy to a model where a platform is certified once and used in multiple ways, versus attempting to certify every data set.
CIOs today are looking to demonstrate business leadership by transforming business models with new capabilities. Differential Privacy is a unique opportunity for the CIO to shift the commercialization of data from an area of high-risk “no, better not” to “yes, we can, while mathematically ensuring privacy.” CIO’s have a unique purview to the entire spectrum of the challenges of data and the tremendous business value that can be unlocked with the right technology. Those CIOs looking to commercialize data should see how Differential Privacy can unlock value while protecting privacy.