Past Princeton Bias-in-AI Reading GroupMeetings

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Fall 2022

9/20/22: Angelina Wang - Model Multiplicity: Opportunities, Concerns, and Solutions by Black et al. (FAccT 2022)
10/4/22: Rose Guingrich - Gender & Conversational Agents (UNESCO paper)
10/11/22: Sayash Kapoor and Angelina Wang - Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy
11/15/22: Vikram V. Ramaswamy - Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability
12/6/22: Christelle Tessono - Analyzing Canada's Proposed AI and Data Act

Spring 2022

1/28/22: Amy Winecoff - Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support by Madaio et al.
2/11/22: Robin Lee - The Use and Misuse of Counterfactuals in Ethical Machine Learning by Kasirzade and Smart
2/25/22: Ruth Fong - Interpretability in Computer Visino
3/11/22: Reading Group - Explaining Explanations in AI by Mittelstadt et al.
3/25/22: Nicole Meister - Gender Cues in Visual Datasets
4/8/22: Vikram Ramaswamy - ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features
4/22/22: Tanushree Banerjee - Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets by Blodgett et al.

Fall 2021

9/17/21: Angelina Wang - It's COMPASlicated: The Messy Relationship Between RAI Datasets and Algorithmic Fairness Benchmarks by Bao et al.
10/01/21: Sunnie S. Y. Kim - The Values Encoded in Machine Learning Research by Birhane et al.
10/15/21: Vikram Ramaswamy - Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development by Scheuerman et al.
10/29/21: Olga Russakovsky - Ethics in Computer Vision
12/03/21: Xuechunzi Bai - Emergence of Bias in Psychology

Spring 2021

2/5/21: Olga Russakovsky - What’s Unique About Fairness Research in Computer Vision?
2/19/21: Eli Lucherini - Simulation to Study Algorithmic Bias.
3/5/21: Kenny Peng - The Lives of Three Datasets and the Ethical Implications.
3/19/21: Sunnie S. Y. Kim - Costs and Risks of Large Language Models.
4/2/21: Mihir Kshirsagar - Discussion on Benjamin Eidelson's Respect, Individualism, and Colorblindness in the Yale Law Journal
4/16/21: Kaiyu Yang - Challenges in Reliably Measure Algorithmic Fairness

Fall 2020

9/18/20: Angelina Wang - REVISE: A Tool for Measuring and Mitigating Biases in Visual Datasets.
10/2/20: Felix Yu - How to Integrate FATE/CDS Into Data Science Curriculum.
10/15/20: Vikram Ramaswamy - Using Visual Grounding for Visual Question Answering.
10/30/20: Robin Lee - Testing Color-Blindness in Image Annotation Tasks.
11/13/20: Matthew Sun - Tyranny of the Majority? Exploring the Effects of Recommender Systems on Minority Populations through Agent-Based Modeling.
12/4/20: Dora Zhao - Understanding and Mitigating Racial Biases in Image Captioning Techniques.

Organizers:

Founded by Arvind Narayanan and Olga Russakovsky in Fall 2017

AY 2021-2022: Angelina Wang

AY 2020-2021: Angelina Wang

AY 2019-2020: Felix Yu

AY 2018-2019: Haochen Li