AI's social sciences deficit. - Mona Sloane; Emanuel Moss (Nat. Mach. Intell., 2019)

Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. - Desmond Upton Patton; William R. Frey; Kyle A. McGregor; Fei-Tzin Lee; Kathleen R. McKeown; Emanuel Moss (AIES, 2020)

Positionality-aware machine learning: translation tutorial. - Christine Kaeser-Chen; Elizabeth Dubois; Friederike Schuur; Emanuel Moss (FAT*, 2020)

AI reflections in 2019. - Alexander S. Rich; Cynthia Rudin; David M. P. Jacoby; Robin Freeman; Oliver R. Wearn; Henry Shevlin; Kanta Dihal; Seán S. ÓhÉigeartaigh; James Butcher; Marco Lippi 001; Przemyslaw Palka; Paolo Torroni; et al. (Nat. Mach. Intell., 2020)

High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response. - Emanuel Moss; Jacob Metcalf (Patterns, 2020)

Governing Algorithmic Systems with Impact Assessments: Six Observations. - Elizabeth Anne Watkins; Emanuel Moss; Jacob Metcalf; Ranjit Singh 001; Madeleine Clare Elish (AIES, 2021)

Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts. - Jacob Metcalf; Emanuel Moss; Elizabeth Anne Watkins; Ranjit Singh 001; Madeleine Clare Elish (FAccT, 2021)

The Objective Function: Science and Society in the Age of Machine Intelligence. - Emanuel Moss (2021)

Excavating awareness and power in data science: A manifesto for trustworthy pervasive data research. - Katie Shilton; Emanuel Moss; Sarah A. Gilbert; Matthew J. Bietz; Casey Fiesler; Jacob Metcalf; Jessica Vitak; Michael Zimmer 004 (Big Data Soc., 2021)

Participation Is not a Design Fix for Machine Learning. - Mona Sloane; Emanuel Moss; Olaitan Awomolo; Laura Forlano 001 (EAAMO, 2022)

Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. - A. Feder Cooper; Emanuel Moss; Benjamin Laufer; Helen Nissenbaum (FAccT, 2022)

A relationship and not a thing: A relational approach to algorithmic accountability and assessment documentation. - Jacob Metcalf; Emanuel Moss; Ranjit Singh 001; Emnet Tafese; Elizabeth Anne Watkins (CoRR, 2022)

The Objective Function: Science and Society in the Age of Machine Intelligence. - Emanuel Moss (CoRR, 2022)

Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians. - Daniel A. Adler; Emily Tseng; Khatiya C. Moon; John Q. Young; John M. Kane 001; Emanuel Moss; David C. Mohr; Tanzeem Choudhury (Proc. ACM Hum. Comput. Interact., 2022)

Obligations to assess: Recent trends in AI accountability regulations. - Serena Oduro; Emanuel Moss; Jacob Metcalf (Patterns, 2022)

A Silicon Valley love triangle: Hiring algorithms, pseudo-science, and the quest for auditability. - Mona Sloane; Emanuel Moss; Rumman Chowdhury (Patterns, 2022)

Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability. - Jacob Metcalf; Ranjit Singh 001; Emanuel Moss; Emnet Tafesse; Elizabeth Anne Watkins (FAccT, 2023)

Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society. - Emanuel Moss (Commun. ACM, 2023)

The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology. - Emma Harvey; Hauke Sandhaus; Abigail Z. Jacobs; Emanuel Moss; Mona Sloane (CHI, 2024)

Practicing Inclusivity in AI: Stakeholder Engagement Policy in Action. - Tina M. Park; Adriana Alvarado Garcia; Juana Catalina Becerra Sandoval; Jiyoo Chang; Bill Curtis-Davidson; Remi Denton; Seeta Peña Gangadharan; Lara Groves; Jerremy Holland; Kenneth Holstein; Tamara Kneese; Jacob Metcalf; et al. (CSCW Companion, 2024)

Introducing v0.5 of the AI Safety Benchmark from MLCommons. - Bertie Vidgen; Adarsh Agrawal; Ahmed M. Ahmed 004; Victor Akinwande; Namir Al-Nuaimi; Najla Alfaraj; Elie Alhajjar; Lora Aroyo; Trupti Bavalatti; Borhane Blili-Hamelin; Kurt D. Bollacker; Rishi Bomassani; et al. (CoRR, 2024)

Tackling AI Hyping. - Mona Sloane; David Danks; Emanuel Moss (AI Ethics, 2024)

Materiality and risk in the age of pervasive AI sensors. - Mona Sloane; Emanuel Moss; Susan Kennedy; Matthew Stewart; Pete Warden; Brian Plancher; Vijay Janapa Reddi (Nat. Mac. Intell., 2025)

What's So Human about Human-AI Collaboration, Anyway? Generative AI and Human-Computer Interaction. - Elizabeth Anne Watkins; Emanuel Moss; Giuseppe Raffa; Lama Nachman (CoRR, 2025)

ACE, Action and Control via Explanations: A Proposal for LLMs to Provide Human-Centered Explainability for Multimodal AI Assistants. - Elizabeth Anne Watkins; Emanuel Moss; Ramesh Manuvinakurike; Meng Shi; Richard Beckwith 001; Giuseppe Raffa (CoRR, 2025)

Thoughts without Thinking: Reconsidering the Explanatory Value of Chain-of-Thought Reasoning in LLMs through Agentic Pipelines. - Ramesh Manuvinakurike; Emanuel Moss; Elizabeth Anne Watkins; Saurav Sahay; Giuseppe Raffa; Lama Nachman (CoRR, 2025)

Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains. - Emanuel Moss; Elizabeth Anne Watkins; Christopher Persaud; Passant Karunaratne; Dawn Nafus (CoRR, 2025)