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Advances in technology are quickly leading to levels of productivity that will qualitatively change the structure of society. This talk will touch on various technology trends, their potential impact on employment, and possible approaches to living in a society where a significant proportion of the population will be able to pursue their avocation.

Data science is an interdisciplinary field that extracts insights from data through a multi-stage process of data collection, analysis and use. When data science is applied for social good, ethical considerations arise at every stage. Our goal in this paper is to propose that care when applied to data science for social good can highlight and confront ethical concerns as well as suggest how “good” extends well beyond the domain of the project work to the modality of working. Consideration of care in practice has its origins in Science and Technology Studies (STS) and has recently been applied by HCI researchers to understanding technology repair and use in under-served environments. We bring care to the practice of data science by the detailed examination of our engaged research with a community group in Atlanta focused on affordable housing.

In this talk, David provides a unifying, clear, accessible and factually grounded framework for public sector leaders to use when evaluating potential applications of predictive analytics to public interest goals. He identifies recurrent challenges and means to address those challenges. In the latter part of the talk, David will explore possibilities for updating institutional design in the public sector to align with the operational requirements of sound statistical prediction.