AI Seminar sponsored by Fortive

Ashiqur R. KhudaBukhsh -- Hope Speech and Help Speech: Surfacing Positivity Amidst Hate

Abstract: Tackling online attacks targeting certain individuals, group of people, or communities is a major modern-day web challenge. Research efforts in hate speech detection thus far have largely focused on identifying and subsequently filtering out negative content that specifically targets such communities. However, this blocking the hate approach alone may not suffice in certain scenarios. We focus on two important cases where amplifying the positives is equally important: refugee crisis in the era of ubiquitous internet, and heated online discussions during heightened political tension between nuclear adversaries. In the context of the Rohingya refugee crisis and the India-Pakistan conflict triggered by the Pulwama terror attack, we describe two lines of work, help speech and hope speech, exhibiting a thematic similarity of surfacing positivity amidst hate.

Bio: Ashique KhudaBukhsh is currently a Project Scientist at the School of Computer Science, Carnegie Mellon University (CMU). Prior to this role, he was a postdoc mentored by Prof. Jaime Carbonell at CMU. His PhD thesis (Computer Science Department, Carnegie Mellon University, also advised by Prof. Jaime Carbonell) focused on referral networks, an emerging area at the intersection of Active Learning and Game Theory. His Master's thesis at the University of British Columbia (UBC), advised by Prof. Kevin Leyton-Brown and Prof. Holger H. Hoos, focused on automated algorithm design for combinatorial hard problems. More details are here: https://www.cs.cmu.edu/~akhudabu/