Taxonomy of Risks posed by Language Models

Laura Weidinger, Jonathan Uesato, Maribeth Rauh, +20

2022 ACM Conference on Fairness, Accountability, and Transparency

Computer EthicEngineeringInformation SecurityRisk AnalysisDigital Ethic +17

The Values Encoded in Machine Learning Research

Abeba Birhane, Pratyusha Kalluri, Dallas Card, +3

2022 ACM Conference on Fairness, Accountability, and Transparency

Artificial IntelligenceData AnnotationEngineeringMachine LearningMachine Learning Tool +19

The Fallacy of AI Functionality

Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, +1

2022 ACM Conference on Fairness, Accountability, and Transparency

Measuring the Carbon Intensity of AI in Cloud Instances

Jesse Dodge, Taylor Prewitt, Rémi Tachet des Combes, +7

2022 ACM Conference on Fairness, Accountability, and Transparency

Artificial IntelligenceEnvironmental MonitoringMachine LearningEngineeringCloud Computing Architecture +17

Predictability and Surprise in Large Generative Models

Deep Ganguli, Danny Hernandez, Liane Lovitt, +27

2022 ACM Conference on Fairness, Accountability, and Transparency

Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI

Mahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson

2022 ACM Conference on Fairness, Accountability, and Transparency

Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem

Sasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini

2022 ACM Conference on Fairness, Accountability, and Transparency

What Does it Mean for a Language Model to Preserve Privacy?

Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, +2

2022 ACM Conference on Fairness, Accountability, and Transparency

Privacy ProtectionEngineeringInformation SecurityInformation PrivacyCommunication +20

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

Lukas Struppek, Dominik Hintersdorf, Daniel Neider, +1

2022 ACM Conference on Fairness, Accountability, and Transparency

How Explainability Contributes to Trust in AI

Andrea Ferrario, Michele Loi

2022 ACM Conference on Fairness, Accountability, and Transparency