"A Method for Integrating Data Science Into Managerial Thought" and "Collective Blocklists and the Algorithmic Moderation of Privately-Owned Public Spaces"
A Method for Integrating Data Science Into Managerial Thought
While data science is often concerned with analyzing past data to understand and predict future outcomes, managerial thought is primarily concerned with achieving future outcomes. In this talk, I illustrate how adopting the ordinary but often tacit tools and perspectives of data scientists can improve deductive thinking about real-world problems and help generate good ideas. The focus of this talk will be on building up and deconstructing the humble 2x2 as a way to engage with analytical business thinkers about how mindsets and assumptions interact with behaviors and decisions.
Collective Blocklists and the Algorithmic Moderation of Privately-Owned Public Spaces
R. Stuart Geiger
In Twitter, a number of people are facing increasing harassment and abuse from others, particularly individuals associated with the "GamerGate" movement. In response, many people have begun using collective blocklists, in which a group curates a shared list of accounts which they believe should not be able to message or mention them. Any account that is added to one of these blocklists is automatically no longer able to be seen by the blocklist's subscribers. While there are many important implications of these collective blocklists, I focus on the fact that such an feature is not built into the Twitter platform and was not designed or developed by staff at Twitter. Rather, these collective blocklists are made possible through a variety of different automated software agents (or bots) that are designed, developed, and operated by independent groups of volunteers. I discuss the short but complex history of these bot-based blocklists, showing how their designs (and re-designs) are bound up in competing ideas about what it means for counterpublic groups to collectively moderate a privately-owned public space like Twitter.
Peter Norlander studies the globalization of knowledge work and human resources management. He completed his Ph.D. in management at UCLA Anderson in 2014 on the topic of organizational sponsorship of knowledge workers through the skilled worker visa programs, and is currently a postdoc at the Berkeley I School and instructor in the Master of Information and Data Science program.
R. Stuart Geiger is a doctoral candidate at the UC Berkeley School of Information and the Berkeley Center for New Media. He studies highly-decentralized virtual organizations and online communities, particularly those assembled around the public production and curation of information. Stuart’s research currently focuses on the social and organizational roles of automated software agents (or bots) in Wikipedia, reddit, and Twitter.