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Meetup @ FAccT 2022

June 21-24, Seoul, South Korea and virtual

FAccT 2022, curated by MD4SG #

Welcome to FAccT 2022, MD4SG-style. We’ve curated a list of programming that members of the MD4SG community are involved in.

This MD4SG meetup at FAccT'22’ is organized by Logan Stapleton and Corinna Hertweck from the MD4SG Community Engagement team.

MD4SG social @ FAccT'22 #

We will have two organized MD4SG socials: one in person in Seoul and one online. To signal your interest in these, please fill out this form.

The online social will take place on the MD4SG Discord on the #facct2022 channel. The Discord channel will be open throughout the conference — we encourage you all to visit and discuss throughout the conference.

TimeEventLocation
June 23
18:00 KST
MD4SG @ FAccT in person socialTBD
1pm ET (UTC-4) (Convert to your timezone.)MD4SG @ FAccT online socialMD4SG Discord

CRAFT Sessions #

CRAFT sessions co-organized by members of the MD4SG community.

OrganizersTitle
Robert Soden (Toronto), Aleks Berditchevskaia (Nesta), Erin Coughlan de Perez (Tufts), Manveer Kalirai (Toronto), Shreyasha Paudel (Toronto), Isabel Stewart (Nesta), Saurav Poudel (CCI), and Sakun Joshi (Nepal Red Cross)What Could Possibly Go Wrong? Speculative Practice Towards Anticipating the Negative Consequences of Humanitarian AI (Online)
Arjun Subramonian (Queer in AI and UCLA), Anaelia Ovalle (UCLA), Luca Soldaini (Queer in AI and Allen Institute for AI), Nathan Dennler (University of Southern California), Zeerak Talat (Digital Democracies Institute, Simon Fraser University), Sunipa Dev (UCLA), Kyra Yee (Twitter), William Agnew (Queer in AI and University of Washington), Irene Font Peradejordi (Twitter), Avijit Ghosh (Queer in AI, Northeastern University, and Twitter (intern))Collaboratively Developing Evaluation Frameworks for Queer AI Harms (In-person and online)
Genevieve Smith, Julia Nee and Ishita Rustagi (UC Berkeley)Applying a Justice Framework to Natural Language Processing (NLP): Decentering Standard Language Ideology in Pursuits of Fair and Equitable NLP (Online)
Ushnish Sengupta (Toronto) and Peaks Krafft (University of Arts London)Application Denied: A Global Coalition to Expose and Resist Discrimination in Automated Decisions (Online)

Tutorial #

Tutorials presented by members of the MD4SG community.

PresentersTitle
Angelina Wang (Princeton), Seungbae Kim (UCLA), Olga Russakovsky (Princeton) and Jungseock Joo (UCLA)Fairness in Computer Vision: Datasets, Algorithms, and Implications (In-person)
Margarita Boyarskaya (NYU), Solon Barocas (Microsoft Research/Cornell), Hanna Wallach (Microsoft Research), and Michael Carl Tschantz (ICSI)What Is a Proxy and Why Is It a Problem? (In-person)

Papers #

Papers co-authored by members of the MD4SG community.

AuthorsTitle
Yuhao Du, Stefania Ionescu, Melanie Sage, Kenneth JosephA Data-Driven Simulation of the New York State Foster Care System
William Cai, Ro Encarnacion, Bobbie Chern, Sam Corbett-Davies, Miranda Bogen, Stevie Bergman, Sharad GoelAdaptive Sampling Strategies to Construct Equitable Training Datasets
Rediet Abebe, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, Rebecca WexlerAdversarial Scrutiny of Evidentiary Statistical Software
Kristen Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska, Bettina BerendtAlgorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective
Marie-Therese PngAt The Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance
Alexandra Sasha Luccioni, Frances Corry, Hamsini Sridharan, Mike Ananny, Jason Schultz, Kate CrawfordCaring for Datasets: A Framework for Deprecating Datasets and Responsible Data Stewardship
Razvan Amironesei, Dylan Baker, Emily Denton, Mark DÍaz, Ian Kivlichan, Vinodkumar Prabhakaran, Rachel RosenCrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation
Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson, Rishi Bommasani, Margaret MitchellData Governance in the Age of Large-Scale Data-Driven Language Technology
Jad Salem, Deven Desai, Swati GuptaDon’t let Ricci v. DeStefano Hold You Back: A Bias-Aware Legal Solution to the Hiring Paradox
Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, Haiyi ZhuExploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Gourab K Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil GargFair ranking: a critical review, challenges, and future directions
Hortense Fong, Vineet Kumar, Anay Mehrotra, Nisheeth K. VishnoiFairness for AUC via Feature Augmentation
Nicolas Usunier, Virginie Do, Elvis DohmatobFast online ranking with fairness of exposure
Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon Kleinberg, Hoda HeidariFour Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects
Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine HellerHealthsheet: development of a transparency artifact for health datasets
Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi ZhuImagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric RiceLearning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery
Jesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz, Emma Strubell, Alexandra Sasha Luccioni, Noah A. Smith, Nicole DeCario, Will BuchananMeasuring Machine Learning Software Carbon Intensity in Cloud Instances
Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel RodriguesMinimax Demographic Group Fairness in Federated Learning
Neel Patel, Reza Shokri, Yair ZickModel Explanations with Differential Privacy
Emily Black, Manish Raghavan, Solon BarocasModel Multiplicity: Opportunities, Concerns, and Solutions
Lydia Reader, Pegah Nohkiz, Cathleen Power, Neal Patwari, Suresh Venkatasubramanian, Sorelle FriedlerModels for understanding and quantifying feedback in societal systems
Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam ShahNet benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
Chiara Longoni, Andrey Fradkin, Luca Cian, Gordon PennycookNews from Generative Artificial Intelligence is Believed Less
Angelina Wang, Solon Barocas, Kristen Laird, Hanna WallachOperationalizing Representational Harms in Image Captioning
Eleonora Viganó, Corinna Hertweck, Christoph Heitz, Michele LoiPeople are not coins: Morally distinct types of predictions necessitate different fairness constraints
Deep Ganguli, Danny Hernandez, Liane Lovitt, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Nova Dassarma, Dawn Drain, Nelson Elhage, Sheer El Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Scott Johnston, Andy Jones, Nicholas Joseph, Jackson Kernian, Shauna Kravec, Ben Mann, Neel Nanda, Kamal Ndousse, Catherine Olsson, Daniela Amodei, Tom Brown, Jared Kaplan, Sam McCandlish, Christopher Olah, Dario Amodei, Jack ClarkPredictability and Surprise in Large Generative Models
Rui-Jie Yew, Alice XiangRegulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA
Nikita Mehandru, Samantha Robertson, Niloufar SalehiReliable and Safe Use of Machine Translation in Medical Settings
Anay Mehrotra, Bary S. R. Pradelski, Nisheeth K. VishnoiSelection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints
Nic Fishman, Leif Hancox-LiShould attention be all we need? The ethical and epistemic implications of unification in machine learning
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, Iason GabrielTaxonomy of Risks posed by Large Language Models
Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh GhassemiThe Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Greg d’Eon, Jason d’Eon, James R. Wright, Kevin Leyton-BrownThe Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models
Angelina Wang, Vikram Ramaswamy, Olga RussakovskyTowards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick Fowler, Sanmay DasTrade-offs between Group Fairness Metrics in Societal Resource Allocation
Nathan KallusTreatment Effect Risk: Bounds and Inference
J.D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, Emma PiersonTrucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis
Samantha Robertson, Mark DÍazUnderstanding and being understood: user strategies for identifying and recovering from mistranslations in machine translation-mediated chat
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian TramèrWhat Does it Mean for a Language Model to Preserve Privacy?
Rebecca Johnson, Simone ZhangWhat is the Bureaucratic Counterfactual? Categorical versus Algorithmic Prioritization in U.S. Social Policy