Handling Web Bias Workshop

A key aspect of the Web Science conference is exploring the ethical challenges of technologies, data, algorithms, platforms, and people in the web as well as detecting, preventing and predicting anomalies in web data including algorithmic and data biases. Handling Web Bias (HWB) is a new workshop focusing on best practices for identifying and handling web bias. Awareness of the problems of algorithmic and data bias has been growing but even with careful review of the algorithms and data sets, it may not be possible to delete all unwanted bias, particularly when systems learn from historical data that encodes historical biases. This workshop will take a rich and cross-domain approach to this complicated problem, providing a venue for researchers to move beyond awareness of the problem of algorithmic and data bias to focus on practical strategies for handling it.

Handling Web Bias is a three-quarter day workshop held in conjunction with Web Science 2019. The workshop will be held in the 17th floor of the East Village building at Northeastern University, Boston, MA, USA.

Call For Participation

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Program – June 30, 2019

Session 1 (10:30-12)

10:30 – 11:00 – Introduction to Handling Web Bias
Ricardo Baeza-Yates(Northeastern University), Jeanna Matthews (Clarkson University)

11:00 –12:00 Keynote 1: Measuring bias in social network ad targeting and delivery
Alan Mislove (Northeastern University)

Lunch Break (12:00-1:00)

Session 2 (1:00-2:00)

1:00 – 1:30 Understanding Demographic Bias and Representation in Social Media Health Data
Nina Cesare, Elaine Nsoesie (Boston University); Christian Grant (University of Oklahoma)

1:30 – 2:00 On Bias in Social Reviews of University Courses
Taha Hassan (Virginia Tech)

Coffee Break (2:00-2:30)

Session 3 (2:30-4:00)

2:30 –3:30 Keynote 2: Fair machine learning in industry: from research to practice
Jean Garcia-Gathright (Spotify)

3:30 – 4:00 – Open Discussion

Workshop Chairs and Organizers

Ricardo Baeza-Yates (NTENT & Northeastern Univ., USA; UPF, Spain; UChile)
Jeanna Neefe Matthews (Clarkson Univ., USA)

Program Committee

Francesco Bonchi (ISI, Italy)
Michael Ekstrand (Boise State, USA)
Leo Ferres (UDD, Chile)
Fosca Gianotti (ISTI/CNR, Italy)
Krishna Gummadi (Max Planck Institute, Germany)
Darakhshan Mir (Buckell Univ, USA)
Chiara Renso (ISTI/CNR, Italy)
Drew Roselli (Parallel-M, USA)
Lívia Ruback (Federal University of Rio de Janeiro, Brazil)
Nisha Talagala (Pyxeda AI, USA)