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.
| Time | Event | Location |
|---|---|---|
| June 23 18:00 KST |
MD4SG @ FAccT in person social | TBD |
| 1pm ET (UTC-4) (Convert to your timezone.) | MD4SG @ FAccT online social | MD4SG Discord |
CRAFT Sessions
CRAFT sessions co-organized by members of the MD4SG community.
| Organizers | Title |
|---|---|
| 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.
| Presenters | Title |
|---|---|
| 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.
| Authors | Title |
|---|---|
| Yuhao Du, Stefania Ionescu, Melanie Sage, Kenneth Joseph | A 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 Goel | Adaptive Sampling Strategies to Construct Equitable Training Datasets |
| Rediet Abebe, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, Rebecca Wexler | Adversarial Scrutiny of Evidentiary Statistical Software |
| Kristen Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska, Bettina Berendt | Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective |
| Marie-Therese Png | At 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 Crawford | Caring for Datasets: A Framework for Deprecating Datasets and Responsible Data Stewardship |
| Razvan Amironesei, Dylan Baker, Emily Denton, Mark DÍaz, Ian Kivlichan, Vinodkumar Prabhakaran, Rachel Rosen | CrowdWorkSheets: 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 Mitchell | Data Governance in the Age of Large-Scale Data-Driven Language Technology |
| Jad Salem, Deven Desai, Swati Gupta | Don'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 Zhu | Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits |
| Gourab K Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil Garg | Fair ranking: a critical review, challenges, and future directions |
| Hortense Fong, Vineet Kumar, Anay Mehrotra, Nisheeth K. Vishnoi | Fairness for AUC via Feature Augmentation |
| Nicolas Usunier, Virginie Do, Elvis Dohmatob | Fast online ranking with fairness of exposure |
| Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon Kleinberg, Hoda Heidari | Four 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 Heller | Healthsheet: 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 Zhu | Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders |
| Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice | Learning 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 Buchanan | Measuring Machine Learning Software Carbon Intensity in Cloud Instances |
| Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues | Minimax Demographic Group Fairness in Federated Learning |
| Neel Patel, Reza Shokri, Yair Zick | Model Explanations with Differential Privacy |
| Emily Black, Manish Raghavan, Solon Barocas | Model Multiplicity: Opportunities, Concerns, and Solutions |
| Lydia Reader, Pegah Nohkiz, Cathleen Power, Neal Patwari, Suresh Venkatasubramanian, Sorelle Friedler | Models for understanding and quantifying feedback in societal systems |
| Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam Shah | Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare |
| Chiara Longoni, Andrey Fradkin, Luca Cian, Gordon Pennycook | News from Generative Artificial Intelligence is Believed Less |
| Angelina Wang, Solon Barocas, Kristen Laird, Hanna Wallach | Operationalizing Representational Harms in Image Captioning |
| Eleonora Viganó, Corinna Hertweck, Christoph Heitz, Michele Loi | People 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 Clark | Predictability and Surprise in Large Generative Models |
| Rui-Jie Yew, Alice Xiang | Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA |
| Nikita Mehandru, Samantha Robertson, Niloufar Salehi | Reliable and Safe Use of Machine Translation in Medical Settings |
| Anay Mehrotra, Bary S. R. Pradelski, Nisheeth K. Vishnoi | Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints |
| Nic Fishman, Leif Hancox-Li | Should 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 Gabriel | Taxonomy of Risks posed by Large Language Models |
| Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi | The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations |
| Greg d'Eon, Jason d'Eon, James R. Wright, Kevin Leyton-Brown | The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models |
| Angelina Wang, Vikram Ramaswamy, Olga Russakovsky | Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation |
| Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick Fowler, Sanmay Das | Trade-offs between Group Fairness Metrics in Societal Resource Allocation |
| Nathan Kallus | Treatment Effect Risk: Bounds and Inference |
| J.D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, Emma Pierson | Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis |
| Samantha Robertson, Mark DÍaz | Understanding 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 Tramèr | What Does it Mean for a Language Model to Preserve Privacy? |
| Rebecca Johnson, Simone Zhang | What is the Bureaucratic Counterfactual? Categorical versus Algorithmic Prioritization in U.S. Social Policy |