Self-quantified trackers made possible what was once nearly unthinkable: for individuals to gather data on one’s activity level in order to manage and improve one’s performance. Some have remarked that self-quantified devices can hinge on the edge of over management. As we wait for more research reports on the right dose of self-management, we’ll have to define for ourselves what the right amount of self-quantifying is.
Meanwhile, it seems that businesses are also struggling with a similar dilemma: measuring the right amount of risk and harm as it relates to security and privacy.
Acting FTC Chairman Maureen Ohlhausen said at a recent privacy and security workshop, “In making policy determinations, injury matters. ... If we want to manage privacy and data security injuries, we need to be able to measure them."
A clearly defined measurement of risk and harm will become ever so important as the business world embrace deep learning and eventually artificial intelligence.
Other articles discussed:

Recovering “deleted” logs
Other perspectives on artificial intelligence
Transparency in algorthims required to curve bias

Panelists: Cindy Ng, Kilian Englert, Mike Thompson, Kris Keyser
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