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06/07/2023
Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Large language models (LLMs) can be used to generate text data for train...
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03/22/2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refini...
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10/31/2022
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
In September 2016, Stanford's "One Hundred Year Study on Artificial Inte...
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03/17/2022
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection
Toxic language detection systems often falsely flag text that contains m...
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03/28/2021
A Bayesian Approach to Identifying Representational Errors
Trained AI systems and expert decision makers can make errors that are o...
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03/10/2021
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs
Several pieces of work have uncovered performance disparities by conduct...
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03/10/2021
Understanding the Representation and Representativeness of Age in AI Data Sets
A diverse representation of different demographic groups in AI training ...
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12/22/2020
Can I Still Trust You?: Understanding the Impact of Distribution Shifts on Algorithmic Recourses
As predictive models are being increasingly deployed to make a variety o...
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08/24/2020
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems
Autonomous agents acting in the real-world often operate based on models...
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07/13/2020
Security and Machine Learning in the Real World
Machine learning (ML) models deployed in many safety- and business-criti...
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06/26/2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Increasingly, organizations are pairing humans with AI systems to improv...
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05/01/2020
Learning to Complement Humans
A rising vision for AI in the open world centers on the development of s...
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04/27/2020
Optimizing AI for Teamwork
In many high-stakes domains such as criminal justice, finance, and healt...
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04/05/2020
Personalization in Human-AI Teams: Improving the Compatibility-Accuracy Tradeoff
AI systems that model and interact with users can update their models ov...
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02/04/2020
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism
Understanding how racial information impacts human decision making in on...
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01/20/2020
SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions
Existing VQA datasets contain questions with varying levels of complexit...
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09/08/2019
What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring
Although systematic biases in decision-making are widely documented, the...
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07/04/2019
Toward Fairness in AI for People with Disabilities: A Research Roadmap
AI technologies have the potential to dramatically impact the lives of p...
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06/04/2019
A Case for Backward Compatibility for Human-AI Teams
AI systems are being deployed to support human decision making in high-s...
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09/19/2018
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure
As machine learning systems move from computer-science laboratories into...
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08/28/2018
Investigating Human + Machine Complementarity for Recidivism Predictions
When might human input help (or not) when assessing risk in fairness-rel...
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08/01/2018
Studying Preferences and Concerns about Information Disclosure in Email Notifications
The proliferation of network-connected devices and applications has resu...
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05/23/2018
Discovering Blind Spots in Reinforcement Learning
Agents trained in simulation may make errors in the real world due to mi...
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07/04/2017
Interpretable & Explorable Approximations of Black Box Models
We propose Black Box Explanations through Transparent Approximations (BE...
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10/28/2016
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
Predictive models deployed in the real world may assign incorrect labels...
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05/03/2015
Metareasoning for Planning Under Uncertainty
The conventional model for online planning under uncertainty assumes tha...
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04/22/2014
