By Julia Stoyanovich (Assistant Professor of Computer Science at Drexel University) and Bill Howe (Associate Professor in the Information School at the University of Washington) In August 2016, Julia Stoyanovich and Ellen P. Goodman spoke in this forum about the importance of bringing interpretability to the algorithmic transparency debate. They focused on algorithmic rankers, discussed the harms […]
Ethics Education in Data Science: Classroom Topics and Assignments
April 26, 2018 by
[This blog post is a continuation of a recap of a recent workshop on data science ethics education.] The creation of ethics modules that can be inserted into a variety of classes may help ensure that ethics as a subject is not marginalized and enable professors with little experience in philosophy or with fewer resources […]
Announcing IoT Inspector: Studying Smart Home IoT Device Behavior
April 23, 2018 by
By Noah Apthorpe, Danny Y. Huang, Gunes Acar, Frank Li, Arvind Narayanan, Nick Feamster An increasing number of home devices, from thermostats to light bulbs to garage door openers, are now Internet-connected. This “Internet of Things” (IoT) promises reduced energy consumption, more effective health management, and living spaces that react adaptively to users’ lifestyles. Unfortunately, […]
No boundaries for Facebook data: third-party trackers abuse Facebook Login
April 18, 2018 by
by Steven Englehardt [0], Gunes Acar, and Arvind Narayanan So far in the No boundaries series, we’ve uncovered how web trackers exfiltrate identifying information from web pages, browser password managers, and form inputs. Today we report yet another type of surreptitious data collection by third-party scripts that we discovered: the exfiltration of personal identifiers from […]
Ethics Education in Data Science
April 17, 2018 by
Data scientists in academia and industry are increasingly recognizing the importance of integrating ethics into data science curricula. Recently, a group of faculty and students gathered at New York University before the annual FAT* conference to discuss the promises and challenges of teaching data science ethics, and to learn from one another’s experiences in the […]
