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Poster
in
Affinity Event: Muslims in ML

“Compassionately”: Increasing Plurality Awareness through Community-powered AI

Hala Sheta · Mohamed Ahmed · Syed Ishtiaque Ahmed

Keywords: [ HCI ] [ pluralism ] [ hate-speech detection ] [ community-powered AI ] [ religious interpretation ]


Abstract:

The prevalence of Islamophobia has resulted in the continual discrimination of Muslims in North America, where polls have found them to be viewed in a negative light, specifically as a rigid, violent and monolithic community. Furthermore, within the Muslim community, many are ignorant and intolerant of differing perspectives to their own beliefs, viewing Islamic jurisprudence as a one-sided, static truth. However, recent work in this domain rightfully reframe it as a human-centered field, and work to amplify minority voices (e.g. women) that are often undermined in textual interpretations. So, our research is centered around utilizing community-powered AI to increase plurality awareness and understanding, both within and outside of the Muslim community. The end goal is to develop a semi-automated hate-speech detection system that educates its users about the multiplicity of perspectives surrounding a topic of interest. This paper will serve as foundational work to this overarching goal by gauging the current climate surrounding the discussion of Islamic perspectives both through a qualitative analysis of online discussions on Reddit and conducting a controlled user study.

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