5 citations · 18 across the 12 of their papers we have counts for
13 papers
What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research
Wesley Hanwen Deng, Agathe Balayn, Andrew Selbst +6
Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implement, and sustain RAI work direct…
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn +7
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly…
From Stem to Stern: Contestability Along AI Value Chains
Agathe Balayn, Yulu Pi, David Gray Widder +9
This workshop will grow and consolidate a community of interdisciplinary CSCW researchers focusing on the topic of contestable AI. As an outcome of the workshop, we will synthesize…
Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Agathe Balayn, Lorenzo Corti, Fanny Rancourt +2
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. Existing works fall short of accounting for t…
An Empirical Exploration of Trust Dynamics in LLM Supply Chains
Agathe Balayn, Mireia Yurrita, Fanny Rancourt +2
With the widespread proliferation of AI systems, trust in AI is an important and timely topic to navigate. Researchers so far have largely employed a myopic view of this relationsh…
Generating Process-Centric Explanations to Enable Contestability in Algorithmic Decision-Making: Challenges and Opportunities
Mireia Yurrita, Agathe Balayn, Ujwal Gadiraju
Human-AI decision making is becoming increasingly ubiquitous, and explanations have been proposed to facilitate better Human-AI interactions. Recent research has investigated the p…
Hear Me Out: A Study on the Use of the Voice Modality for Crowdsourced Relevance Assessments
Nirmal Roy, Agathe Balayn, David Maxwell +1
The creation of relevance assessments by human assessors (often nowadays crowdworkers) is a vital step when building IR test collections. Prior works have investigated assessor qua…
Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UK
Luca Nannini, Agathe Balayn, Adam Leon Smith
Public attention towards explainability of artificial intelligence (AI) systems has been rising in recent years to offer methodologies for human oversight. This has translated into…
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities
Andrea Tocchetti, Lorenzo Corti, Agathe Balayn +4
Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustne…
Towards a multi-stakeholder value-based assessment framework for algorithmic systems
Mireia Yurrita, Dave Murray-Rust, Agathe Balayn +1
In an effort to regulate Machine Learning-driven (ML) systems, current auditing processes mostly focus on detecting harmful algorithmic biases. While these strategies have proven t…
Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision
Agathe Balayn, Bogdan Kulynych, Seda Guerses
Researchers have identified datasets used for training computer vision (CV) models as an important source of hazardous outcomes, and continue to examine popular CV datasets to expo…
Designing Evaluations of Machine Learning Models for Subjective Inference: The Case of Sentence Toxicity
Agathe Balayn, Alessandro Bozzon
Machine Learning (ML) is increasingly applied in real-life scenarios, raising concerns about bias in automatic decision making. We focus on bias as a notion of opinion exclusion, t…
Unfairness towards subjective opinions in Machine Learning
Agathe Balayn, Alessandro Bozzon, Zoltan Szlavik
Despite the high interest for Machine Learning (ML) in academia and industry, many issues related to the application of ML to real-life problems are yet to be addressed. Here we pu…