01:33:41

FAccT '24 Town Hall

01:10:21

FAcct '24 Keynote: Sanmi Koyejo, Stanford University "The measure and mismeasure of AI"

01:08:49

FAccT '24: Keynote: Stephanie Nguyen, U.S. Federal Trade Commission

01:03:47

FAccT '24: Community Keynote: Polinho Mota

01:10:34

FAccT '24 Keynote: Seeta Peña Gangadharan, London School of Economics

01:07:00

Technodiversity & digital practices in Brazil: Joaquim Melo, Nina da Hora, Alexsandro Mesquita

01:14:41

FAccT '24 Keynote: Virgilio Almeida

01:12:04

FAccT'23 Community Keynote: Productivity Monitoring, Surveillance, Automation, and Big Tech Harms

10:08

Welfarist Moral Grounding for Transparent Artificial Intelligence

05:21

Machine Explanations and Human Understanding

09:58

Honor ethics: The Challenge of Globalizing Value Alignment in AI

09:44

Bias as Boundary Object: Critiquing An Algorithm For Austerity Using Bias Frameworks

08:44

Stronger Together: Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML

09:49

Trustworthy AI and the Logics of Intersectional Resistance

09:56

Reconciling Individual Probability Forecasts

10:51

Algorithmic decisions, Desire for Control, & the Preference for Human Review over Algorithmic Review

09:56

How online behavioral advertising harms people

08:51

Preventing Discriminatory Decision-making in Evolving Data Stream

09:39

Broadening AI Ethics Narratives: An Indic Art View

12:02

Multi-dimensional discrimination in Law and Machine Learning - A comparative overview

10:14

How Biased are Your Features?Computing Fairness Influence Functions with Global Sensitivity Analysis

10:01

Disparities in Text-to-Image Model Concept Possession Across Languages

10:41

Representation Online Matters Practical End-to-end Diversification in Search and Recommender Systems

10:00

On The Impact of Machine Learning Randomness on Group Fairness

09:31

Humans, AI, and Context: Understanding End-Users’ Trust in a Real-World Computer Vision Application

09:32

WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?

09:57

Skin Deep Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets

15:03

Fairness in machine learning from the perspective of sociology of statistics

10:25

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification

08:55

Harms from Increasingly Agentic Algorithmic Systems

10:01

Using Supervised Learning to Estimate Inequality in the Size and Persistence of Income Shocks

09:22

The Gradient of Generative AI Release: Methods and Considerations

09:08

Achieving diversity in counterfactual explanations: a review and a discussion

12:40

Two Reasons for Subjecting Medical AI Systems to Lower Standards than Humans

09:57

Discrimination through Image Choice by Job Advertisers on Facebook

08:43

How to Explain and Justify Almost Any Decision

10:01

‘We are adults and deserve control of our phones’

10:01

Arbitrary Decisions are a Hidden Cost of Differentially-Private Training

07:45

Detection and Mitigation of Algorithmic Bias via Predictive Parity

09:49

On the Praxes and Politics of AI Speech Emotion Recognition

10:27

Algorithmic Transparency from the South: Examining the state of algorithmic transparency in Chile...

07:25

On the Independence of Association Bias and Empirical Fairness in Language Models

09:28

In her Shoes: Gendered Labelling in Crowdsourced Safety Perceptions Data from India

08:18

The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions

09:55

Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument

09:58

The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending...

09:53

Affordances for Machine Learning

10:01

Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study

09:30

Saliency Cards: A Framework to Characterize and Compare Saliency Methods

09:59

Algorithmic Transparency and Accountability through Crowdsourcing

09:56

"I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models

13:38

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice

10:04

The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices

07:41

Fairness Auditing of Urban Decisions using LP-based Data Combination

11:47

Cross-Institutional Transfer Learning for Educational Models

09:56

Capturing Humans' Mental Models of AI: An Item Response Theory Approach

10:00

Interrogating the T in FAccT

10:49

Simplicity Bias Leads to Amplified Performance Disparities

09:06

Who Should Pay When Machines Cause Harm?

09:09

Envisioning Equitable Speech Technologies for Black Older Adults