758 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Microsoft (United States)US53 papers
- Cornell UniversityUS15 papers
- Carnegie Mellon UniversityUS9 papers
- University of Massachusetts AmherstUS8 papers
- Princeton UniversityUS7 papers
- Columbia UniversityUS6 papers
- Microsoft Research (United Kingdom)GB6 papers
- University of PennsylvaniaUS6 papers
- University of Maryland, College ParkUS5 papers
- University of MichiganUS5 papers
- Harvard UniversityUS4 papers
- Stanford UniversityUS4 papers
82 papers
Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics
Nari Johnson, Deepthi Sudharsan, Hamna +7
Measurement is essential to improving AI performance and mitigating harms for marginalized groups. As generative AI systems are rapidly deployed across geographies and contexts, AI…
Effects of Generative AI Errors on User Reliance Across Task Difficulty
Jacy Reese Anthis, Hannah Cha, Solon Barocas +2
The capabilities of artificial intelligence (AI) lie along a jagged frontier, where AI systems surprisingly fail on tasks that humans find easy and succeed on tasks that humans fin…
Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao +2
Large language models (LLMs) can produce erroneous responses that sound fluent and convincing, raising the risk that users will rely on these responses as if they were correct. Mit…
Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage
Jenny S Wang, Samar Haider, Amir Tohidi +5
Mainstream media, through their decisions on what to cover and how to frame the stories they cover, can mislead readers without using outright falsehoods. Therefore, it is crucial…
From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debate
Alexandra Sasha Luccioni, Emma Strubell, Kate Crawford
As the climate crisis deepens, artificial intelligence (AI) has emerged as a contested force: some champion its potential to advance renewable energy, materials discovery, and larg…
What Constitutes a Less Discriminatory Algorithm?
Benjamin Laufer, Manish Raghavan, Solon Barocas
Disparate impact doctrine offers an important legal apparatus for targeting discriminatory data-driven algorithmic decisions. A recent body of work has focused on conceptualizing o…
Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work
Wesley Hanwen Deng, Solon Barocas, Jennifer Wortman Vaughan
Recent years have witnessed increasing calls for computing researchers to grapple with the societal impacts of their work. Tools such as impact assessments have gained prominence a…
The Human Factor in AI Red Teaming: Perspectives from Social and Collaborative Computing
Alice Qian Zhang, Ryland Shaw, Jacy Reese Anthis +9
Rapid progress in general-purpose AI has sparked significant interest in "red teaming," a practice of adversarial testing originating in military and cybersecurity applications. AI…
Fast and Interpretable Mortality Risk Scores for Critical Care Patients
Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova +4
Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (…
Mimetic Models: Ethical Implications of AI that Acts Like You
Reid McIlroy-Young, Jon Kleinberg, Siddhartha Sen +2
An emerging theme in artificial intelligence research is the creation of models to simulate the decisions and behavior of specific people, in domains including game-playing, text g…
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
Zijie J. Wang, Alex Kale, Harsha Nori +6
Machine learning (ML) interpretability techniques can reveal undesirable patterns in data that models exploit to make predictions--potentially causing harms once deployed. However,…
Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics
Richmond Y. Wong, Michael A. Madaio, Nick Merrill
Numerous toolkits have been developed to support ethical AI development. However, toolkits, like all tools, encode assumptions in their design about what work should be done and ho…
Blocks as geographic discontinuities: The effect of polling place assignment on voting
Sabina Tomkins, Keniel Yao, Johann Gaebler +4
A potential voter must incur a number of costs in order to successfully cast an in-person ballot, including the costs associated with identifying and traveling to a polling place.…
Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha +1
A core element in decision-making under uncertainty is the feedback on the quality of the performed actions. However, in many applications, such feedback is restricted. For example…
Examining the consumption of radical content on YouTube
Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset +3
Although it is under-studied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world. Recently, Y…
Learning Models of Individual Behavior in Chess
Reid McIlroy-Young, Russell Wang, Siddhartha Sen +2
AI systems that can capture human-like behavior are becoming increasingly useful in situations where humans may want to learn from these systems, collaborate with them, or engage w…
Aligning Superhuman AI with Human Behavior: Chess as a Model System
Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg +1
As artificial intelligence becomes increasingly intelligent---in some cases, achieving superhuman performance---there is growing potential for humans to learn from and collaborate…
Mathematical Foundations for Social Computing
Yiling Chen, Arpita Ghosh, Michael Kearns +2
Social computing encompasses the mechanisms through which people interact with computational systems: crowdsourcing systems, ranking and recommendation systems, online prediction m…
Bandits with adversarial scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme
We study "adversarial scaling", a multi-armed bandit model where rewards have a stochastic and an adversarial component. Our model captures display advertising where the "click-thr…
Equitable Allocations of Indivisible Chores
Rupert Freeman, Sujoy Sikdar, Rohit Vaish +1
We study fair allocation of indivisible chores (i.e., items with non-positive value) among agents with additive valuations. An allocation is deemed fair if it is (approximately) eq…
Scalable Hierarchical Clustering with Tree Grafting
Nicholas Monath, Ari Kobren, Akshay Krishnamurthy +2
We introduce Grinch, a new algorithm for large-scale, non-greedy hierarchical clustering with general linkage functions that compute arbitrary similarity between two point sets. Th…
Decentralized & Collaborative AI on Blockchain
Justin D. Harris, Bo Waggoner
Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; pre…
Truthful Aggregation of Budget Proposals
Rupert Freeman, David M. Pennock, Dominik Peters +1
We consider a participatory budgeting problem in which each voter submits a proposal for how to divide a single divisible resource (such as money or time) among several possible al…
The Perils of Exploration under Competition: A Computational Modeling Approach
Guy Aridor, Kevin Liu, Aleksandrs Slivkins +1
We empirically study the interplay between exploration and competition. Systems that learn from interactions with users often engage in exploration: making potentially suboptimal d…