Emanuel Moss

According to our database, Emanuel Moss authored at least 27 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, June, 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, May, 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, Giuseppe Raffa

CoRR, March, 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, March, 2025

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

2024

Tackling AI Hyping.

Mona Sloane, David Danks, Emanuel Moss

AI Ethics, August, 2024

Introducing v0.5 of the AI Safety Benchmark from MLCommons.

Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt D. Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin N. Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren

CoRR, 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, Emanuel Moss, Wilneida Negrón, Afsaneh Rigot, Lauren Wilcox

Proceedings of the Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing, 2024

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

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2023

Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society.

Emanuel Moss

Commun. ACM, June, 2023

Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability.

Jacob Metcalf, Ranjit Singh, Emanuel Moss, Emnet Tafesse, Elizabeth Anne Watkins

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

A Silicon Valley love triangle: Hiring algorithms, pseudo-science, and the quest for auditability.

Mona Sloane, Emanuel Moss, Rumman Chowdhury

Patterns, 2022

Obligations to assess: Recent trends in AI accountability regulations.

Serena Oduro, Emanuel Moss, Jacob Metcalf

Patterns, 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, Emanuel Moss, David C. Mohr, Tanzeem Choudhury

Proc. ACM Hum. Comput. Interact., 2022

The Objective Function: Science and Society in the Age of Machine Intelligence.

Emanuel Moss

CoRR, 2022

A relationship and not a thing: A relational approach to algorithmic accountability and assessment documentation.

Jacob Metcalf, Emanuel Moss, Ranjit Singh, Emnet Tafese, Elizabeth Anne Watkins

CoRR, 2022

Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning.

A. Feder Cooper, Emanuel Moss, Benjamin Laufer, Helen Nissenbaum

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Participation Is not a Design Fix for Machine Learning.

Mona Sloane, Emanuel Moss, Olaitan Awomolo, Laura Forlano

Proceedings of the Equity and Access in Algorithms, Mechanisms, and Optimization, 2022

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

Big Data Soc., July, 2021

The Objective Function: Science and Society in the Age of Machine Intelligence.

Emanuel Moss

PhD thesis, 2021

Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts.

Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Governing Algorithmic Systems with Impact Assessments: Six Observations.

Elizabeth Anne Watkins, Emanuel Moss, Jacob Metcalf, Ranjit Singh, Madeleine Clare Elish

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response.

Emanuel Moss, Jacob Metcalf

Patterns, 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, Przemyslaw Palka, Paolo Torroni, Shannon Wongvibulsin, Edmon Begoli, Gisbert Schneider, Stephen Cave, Mona Sloane, Emanuel Moss, Iyad Rahwan, Ken Goldberg, David Howard, Luciano Floridi, Jack Stilgoe

Nat. Mach. Intell., 2020

Positionality-aware machine learning: translation tutorial.

Christine Kaeser-Chen, Elizabeth Dubois, Friederike Schuur, Emanuel Moss

Proceedings of the FAT* '20: Conference on Fairness, 2020

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

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

AI's social sciences deficit.

Mona Sloane, Emanuel Moss

Nat. Mach. Intell., 2019