{"type":"ScholarlyArticle","title":"Disentangling Societal Inequality from Model Biases: Gender Inequality in Divorce Court Proceedings","authors":[{"name":"Sujan Dutta","slug":"sujan-dutta","given":"Sujan","family":"Dutta","affiliation":"Rochester Institute of Technology"},{"name":"Parth Srivastava","slug":"parth-srivastava","given":"Parth","family":"Srivastava","affiliation":"Indian Institute of Technology , Kanpur"},{"name":"Vaishnavi Solunke","slug":"vaishnavi-solunke","given":"Vaishnavi","family":"Solunke","affiliation":"Rochester Institute of Technology"},{"name":"Swaprava Nath","slug":"swaprava-nath","given":"Swaprava","family":"Nath","affiliation":"Indian Institute of Technology , Bombay"},{"name":"Ashiqur R. KhudaBukhsh","slug":"ashiqur-r-khudabukhsh","given":"Ashiqur R.","family":"KhudaBukhsh","affiliation":"Rochester Institute of Technology"}],"abstract":"Divorce is the legal dissolution of a marriage by a court. Since this is usually an unpleasant outcome of a marital union, each party may have reasons to call the decision to quit which is generally documented in detail in the court proceedings. Via a substantial corpus of 17,306 court proceedings, this paper investigates gender inequality through the lens of divorce court proceedings. To our knowledge, this is the first-ever large-scale computational analysis of gender inequality in Indian divorce, a taboo-topic for ages. While emerging data sources (e.g., public court records made available on the web) on sensitive societal issues hold promise in aiding social science research, biases present in cutting-edge natural language processing (NLP) methods may interfere with or affect such studies. A thorough analysis of potential gaps and limitations present in extant NLP resources is thus of paramount importance. In this paper, on the methodological side,  we demonstrate that existing NLP resources required several non-trivial modifications to quantify societal inequalities. On the substantive side, we find that while a large number of court cases perhaps suggest changing norms in India where women are increasingly challenging patriarchy, AI-powered analyses of these court proceedings indicate striking gender inequality with women often subjected to domestic violence.","doi":"10.24963/ijcai.2023/661","url":"https://ijcai.org/proceedings/2023/661","pdf":"https://ijcai.org/proceedings/2023/0661.pdf","markdown":"https://ijcai.org/proceedings/2023/661.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/661","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"AI for Good","track":"AI for Good","number":661,"pages":{"first":5959,"last":5967},"keywords":["AI for Good: Natural Language Processing","AI for Good: Machine Learning"],"videos":[],"references":[{"position":1,"raw":"[Ahmad, 2008] Nehaluddin Ahmad. 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