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Communication, Mediation, and the Expectations of Data: Data Valences Across Health and Wellness Communities
Communication technologies increasingly mediate data exchanges rather than human communication. We propose the term data valences to describe the differences in expectations that people have for data across different social settings. Building on two years of interviews, observations, and participation in the communities of technology designers, clinicians, advocates, and users for emerging mobile data in formal health care and consumer wellness, we observed the tensions among these groups in their varying expectations for data. This article identifies six data valences (self-evidence, actionability, connection, transparency, “truthiness,” and discovery) and demonstrates how they are mediated and how they are distinct across different social domains. Data valences give researchers a tool for examining the discourses around, practices with, and challenges for data as they are mediated across social settings.
Uber removed blog post from data science team that examined link between prostitution and rides
I contributed to a great article at VentureBeat about Uber and its data management practices.
Earlier today, Gina Neff, an associate professor of communication at the University of Washington and the School of Public Policy at Central European University in Budapest, noticed something missing from Uber’s Data Blog. In a tweet, she wrote: The blog post in question was titled: “Location knowledge is a proxy for Uber demand.” Though based on the original URL, it was apparently first called something else: https://blog.uber.com/2011/09/13/uberdata-how-prostitution-and-alcohol-make-uber-better/.
Read More at VentureBeat:
Data Empathy: Learning from health care
I just published an essay on Medium about what the dinosaurs of health care can teach health startups.
Nude pictures of celebrities stolen from their own iCloud accounts. Facebook experimenting with the emotions in their users’ feeds. Google reading Gmail before their users do. Fitness trackers without privacy policies, vulnerable to security breaches, and bait-and-switch tactics to sell customers’ data. Almost every day there is a story about the gap between the expectations people have for their own data and what companies actually do with that data. To fix this gap, we first need to rethink the nature of data.
Continue reading at Medium:
https://medium.com/@ginasue/data-empathy-learning-from-health-care-5fb23b1f7289
