{"672057":{"#nid":"672057","#data":{"type":"event","title":"CSE Faculty Candidate Seminar - Angelina Wang","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EName: \u003C\/strong\u003EAngelina Wang, Ph.D. student at Princeton University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003ETuesday, January 23, 2024 at 11:00 am\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Second Floor, Room 230 (\u003Ca href=\u0022https:\/\/www.google.com\/maps\/place\/Coda\/@33.7752651,-84.3876426,15z\/data=!4m6!3m5!1s0x88f5046677950223:0x7fd1ad077b382c98!8m2!3d33.7752651!4d-84.3876426!16s%2Fg%2F11c6lvs7sl?entry=ttu\u0022\u003EGoogle Maps link\u003C\/a\u003E)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELink:\u0026nbsp;\u003C\/strong\u003EThe recording of this in-person seminar will be uploaded to\u0026nbsp;\u003Ca href=\u0022https:\/\/mediaspace.gatech.edu\/channel\/School%2Bof%2BComputational%2BScience%2Band%2BEngineering\/259332602\u0022 target=\u0022_blank\u0022\u003ECSE\u0027s MediaSpace\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EOperationalizing Responsible Machine Learning: From Equality Towards Equity\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp;\u003C\/strong\u003EWith the widespread proliferation of machine learning, there arises both the opportunity for societal benefit as well as the risk of harm. Approaching responsible machine learning is difficult because technical approaches may build on too many layers of abstraction, ending up prioritizing a mathematical definition of fairness that correlates poorly to real-world constructs of fairness. On the other hand, social approaches engaging with prescriptive theories may produce findings that are too abstract to translate well into practice. In my research, I bridge these approaches and use social implications to guide technical work. I will discuss three research directions that show how although the technically convenient thing to do is consider equality acontextually, through stronger engagement with societal context we can operationalize a more equitable formulation. First, I will introduce a dataset tool that we built to analyze complex, socially-grounded forms of visual bias. Then, I will give empirical evidence to support how we should incorporate societal context in bringing intersectionality into machine learning. Finally, I will talk about how to formulate the evaluation metric of bias amplification based on more realistic assumptions about the state of the world. Overall, I will cover how we can expand a narrow focus on equality in responsible machine learning to a broader understanding of equity that substantively engages with societal context.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003EAngelina Wang is a computer science Ph.D. student at Princeton University advised by Olga Russakovsky. Her research is in the area of machine learning fairness and algorithmic bias. She has been recognized by the NSF GRFP, EECS Rising Stars, and Siebel Scholarship. She has published in top machine learning (ICML, AAAI), computer vision (ICCV, IJCV), and responsible computing (FAccT, JRC) venues, including spotlight and oral presentations. Previously, she has interned with Microsoft Research and Arthur AI, and received a B.S. in Electrical Engineering and Computer Science from UC Berkeley.\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EName: \u003C\/strong\u003EAngelina Wang, Ph.D. student at Princeton University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003ETuesday, January 23, 2024 at 11:00 am\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Second Floor, Room 230 (\u003Ca href=\u0022https:\/\/www.google.com\/maps\/place\/Coda\/@33.7752651,-84.3876426,15z\/data=!4m6!3m5!1s0x88f5046677950223:0x7fd1ad077b382c98!8m2!3d33.7752651!4d-84.3876426!16s%2Fg%2F11c6lvs7sl?entry=ttu\u0022\u003EGoogle Maps link\u003C\/a\u003E)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELink:\u0026nbsp;\u003C\/strong\u003EThe recording of this in-person seminar will be uploaded to\u0026nbsp;\u003Ca href=\u0022https:\/\/mediaspace.gatech.edu\/channel\/School%2Bof%2BComputational%2BScience%2Band%2BEngineering\/259332602\u0022 target=\u0022_blank\u0022\u003ECSE\u0027s MediaSpace\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EOperationalizing Responsible Machine Learning: From Equality Towards Equity\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Seminar Title:\u00a0Operationalizing Responsible Machine Learning: From Equality Towards Equity"}],"uid":"36319","created_gmt":"2024-01-11 20:47:02","changed_gmt":"2024-01-22 15:39:05","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-01-23T11:00:00-05:00","event_time_end":"2024-01-23T12:00:00-05:00","event_time_end_last":"2024-01-23T12:00:00-05:00","gmt_time_start":"2024-01-23 16:00:00","gmt_time_end":"2024-01-23 17:00:00","gmt_time_end_last":"2024-01-23 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda, Room 230","extras":[],"hg_media":{"672745":{"id":"672745","type":"image","title":"Angelina Wang Headshot.jpg","body":null,"created":"1705006040","gmt_created":"2024-01-11 20:47:20","changed":"1705006040","gmt_changed":"2024-01-11 20:47:20","alt":"Angelina Wang Seminar","file":{"fid":"256041","name":"Angelina Wang Headshot.jpg","image_path":"\/sites\/default\/files\/2024\/01\/11\/Angelina%20Wang%20Headshot.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/01\/11\/Angelina%20Wang%20Headshot.jpg","mime":"image\/jpeg","size":847057,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/01\/11\/Angelina%20Wang%20Headshot.jpg?itok=i4KlLXc_"}}},"media_ids":["672745"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"9167","name":"machine learning"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EMary High\u003Cbr \/\u003E\r\nmhigh7@gatech.edu\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}