565 citations · 837 across the 31 of their papers we have counts for
32 papers
Evaluating Intellectual Property Guardrails of Generative Image Models: A Technical Report
Austin T. Hoag, Apostolos Modas, Yunhao Ba +9
Generative image models are capable of producing images that bear a strong resemblance to, or replicate, recognizable intellectual property (IP). In this technical report, we prese…
Yes, But Not Always. Generative AI Needs Nuanced Opt-in
Wiebke Hutiri, Morgan Scheuerman, Shruti Nagpal +2
This paper argues that a one-size-fits-all approach to specifying consent for the use of creative works in generative AI is insufficient. Real-world ownership and rights holder str…
Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions
Saleh Afroogh, Syed Ishtiaque Ahmed, Petra Ahrweiler +46
This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs…
Attribution-by-design: Ensuring Inference-Time Provenance in Generative Music Systems
Fabio Morreale, Wiebke Hutiri, Joan Serrà +2
The rise of AI-generated music is diluting royalty pools and revealing structural flaws in existing remuneration frameworks, challenging the well-established artist compensation sy…
TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation
Wiebke Hutiri, Mircea Cimpoi, Morgan Scheuerman +2
Dataset transparency is a key enabler of responsible AI, but insights into multimodal dataset attributes that impact trustworthy and ethical aspects of AI applications remain scarc…
Efficient Bias Mitigation Without Privileged Information
Mateo Espinosa Zarlenga, Swami Sankaranarayanan, Jerone T. A. Andrews +3
Deep neural networks trained via empirical risk minimisation often exhibit significant performance disparities across groups, particularly when group and task labels are spuriously…
Position: Measure Dataset Diversity, Don't Just Claim It
Dora Zhao, Jerone T. A. Andrews, Orestis Papakyriakopoulos +1
Machine learning (ML) datasets, often perceived as neutral, inherently encapsulate abstract and disputed social constructs. Dataset curators frequently employ value-laden terms suc…
Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes
Yusuke Hirota, Jerone T. A. Andrews, Dora Zhao +4
We tackle societal bias in image-text datasets by removing spurious correlations between protected groups and image attributes. Traditional methods only target labeled attributes,…
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…
A Taxonomy of Challenges to Curating Fair Datasets
Dora Zhao, Morgan Klaus Scheuerman, Pooja Chitre +5
Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation. Drawing from intervie…
Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators
Wiebke Hutiri, Oresiti Papakyriakopoulos, Alice Xiang
The rapid and wide-scale adoption of AI to generate human speech poses a range of significant ethical and safety risks to society that need to be addressed. For example, a growing…
Estimating the Likelihood of Arrest from Police Records in Presence of Unreported Crimes
Riccardo Fogliato, Arun Kumar Kuchibhotla, Zachary Lipton +3
Many important policy decisions concerning policing hinge on our understanding of how likely various criminal offenses are to result in arrests. Since many crimes are never reporte…
Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color
William Thong, Przemyslaw Joniak, Alice Xiang
This paper strives to measure apparent skin color in computer vision, beyond a unidimensional scale on skin tone. In their seminal paper Gender Shades, Buolamwini and Gebru have sh…
Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data
Keziah Naggita, Julienne LaChance, Alice Xiang
Biases in large-scale image datasets are known to influence the performance of computer vision models as a function of geographic context. To investigate the limitations of standar…
Augmented Datasheets for Speech Datasets and Ethical Decision-Making
Orestis Papakyriakopoulos, Anna Seo Gyeong Choi, Jerone Andrews +5
Speech datasets are crucial for training Speech Language Technologies (SLT); however, the lack of diversity of the underlying training data can lead to serious limitations in build…
Considerations for Ethical Speech Recognition Datasets
Orestis Papakyriakopoulos, Alice Xiang
Speech AI Technologies are largely trained on publicly available datasets or by the massive web-crawling of speech. In both cases, data acquisition focuses on minimizing collection…
A View From Somewhere: Human-Centric Face Representations
Jerone T. A. Andrews, Przemyslaw Joniak, Alice Xiang
Few datasets contain self-identified sensitive attributes, inferring attributes risks introducing additional biases, and collecting attributes can carry legal risks. Besides, categ…
Ethical Considerations for Responsible Data Curation
Jerone T. A. Andrews, Dora Zhao, William Thong +3
Human-centric computer vision (HCCV) data curation practices often neglect privacy and bias concerns, leading to dataset retractions and unfair models. HCCV datasets constructed th…
Men Also Do Laundry: Multi-Attribute Bias Amplification
Dora Zhao, Jerone T. A. Andrews, Alice Xiang
As computer vision systems become more widely deployed, there is increasing concern from both the research community and the public that these systems are not only reproducing but…
Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users
Ana Lucic, Sheeraz Ahmad, Amanda Furtado Brinhosa +7
When using medical images for diagnosis, either by clinicians or artificial intelligence (AI) systems, it is important that the images are of high quality. When an image is of low…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA
Rui-Jie Yew, Alice Xiang
Harms resulting from the development and deployment of facial processing technologies (FPT) have been met with increasing controversy. Several states and cities in the U.S. have ba…
Promises and Challenges of Causality for Ethical Machine Learning
Aida Rahmattalabi, Alice Xiang
In recent years, there has been increasing interest in causal reasoning for designing fair decision-making systems due to its compatibility with legal frameworks, interpretability…
On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
Riccardo Fogliato, Alice Xiang, Zachary Lipton +2
The risk of re-offense is considered in decision-making at many stages of the criminal justice system, from pre-trial, to sentencing, to parole. To aid decision makers in their ass…