A Career Path to Data Science Through Privacy & Confidentiality
A Career Path to Data Science Through Privacy & Confidentiality

Abstract: 

Most empirical work involves data on units such as individuals, households and/or organizations of various types. In circumstances such as these, analysts must ensure that such data are used responsibly and ethically. In practical terms, this requires that the private interests of individual privacy and data confidentiality be balanced against the social benefits of access and use.

It is critical to address privacy and confidentiality issues if the full public value of data is to be realized. This presentation will highlight why the challenges need to be met; review the past, point out challenges with this approach in the new data world; briefly describe the current state of play from a legal, technical, and statistical perspective; and point to open questions that need to be addressed in the future.

Bio: 

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