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Emanuel Moss
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2020 – today
- 2024
- [j9]Mona Sloane
, David Danks
Tackling AI Hyping. AI Ethics 4(3): 669-677 (2024) - [c9]Emma Harvey
The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology. CHI 2024: 768:1-768:23 - [c8]Tina M. Park
Practicing Inclusivity in AI: Stakeholder Engagement Policy in Action. CSCW Companion 2024: 748-751 - [i8]Emma Harvey
The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology. CoRR abs/2401.10877 (2024) - [i7]Matthew Stewart, Emanuel Moss, Pete Warden, Brian Plancher, Susan Kennedy, Mona Sloane, Vijay Janapa Reddi:
Materiality and Risk in the Age of Pervasive AI Sensors. CoRR abs/2402.11183 (2024) - [i6]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
Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR abs/2404.12241 (2024) - 2023
- [j8]Emanuel Moss:
Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society. Commun. ACM 66(6): 42-44 (2023) - [c7]Jacob Metcalf
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability. FAccT 2023: 1450-1462 - 2022
- [j7]Daniel A. Adler
Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-48 (2022) - [j6]Mona Sloane
A Silicon Valley love triangle: Hiring algorithms, pseudo-science, and the quest for auditability. Patterns 3(2): 100425 (2022) - [j5]Serena Oduro, Emanuel Moss, Jacob Metcalf
Obligations to assess: Recent trends in AI accountability regulations. Patterns 3(11): 100608 (2022) - [c6]Mona Sloane, Emanuel Moss, Olaitan Awomolo, Laura Forlano:
Participation Is not a Design Fix for Machine Learning. EAAMO 2022: 1:1-1:6 - [c5]A. Feder Cooper, Emanuel Moss, Benjamin Laufer, Helen Nissenbaum:
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. FAccT 2022: 864-876 - [i5]A. Feder Cooper, Benjamin Laufer, Emanuel Moss, Helen Nissenbaum:
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. CoRR abs/2202.05338 (2022) - [i4]Jacob Metcalf, Emanuel Moss, Ranjit Singh, Emnet Tafese, Elizabeth Anne Watkins:
A relationship and not a thing: A relational approach to algorithmic accountability and assessment documentation. CoRR abs/2203.01455 (2022) - [i3]Emanuel Moss:
The Objective Function: Science and Society in the Age of Machine Intelligence. CoRR abs/2209.10418 (2022) - 2021
- [b1]Emanuel Moss:
The Objective Function: Science and Society in the Age of Machine Intelligence. City University of New York, USA, 2021 - [j4]Katie Shilton
Excavating awareness and power in data science: A manifesto for trustworthy pervasive data research. Big Data Soc. 8(2): 205395172110407 (2021) - [c4]Elizabeth Anne Watkins
Governing Algorithmic Systems with Impact Assessments: Six Observations. AIES 2021: 1010-1022 - [c3]Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins
Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts. FAccT 2021: 735-746 - [i2]Mona Sloane, Emanuel Moss, Rumman Chowdhury:
A Silicon Valley Love Triangle: Hiring Algorithms, Pseudo-Science, and the Quest for Auditability. CoRR abs/2106.12403 (2021) - 2020
- [j3]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
AI reflections in 2019. Nat. Mach. Intell. 2(1): 2-9 (2020) - [j2]Emanuel Moss
High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response. Patterns 1(7): 100102 (2020) - [c2]Desmond Upton Patton, William R. Frey, Kyle A. McGregor, Fei-Tzin Lee, Kathleen R. McKeown, Emanuel Moss:
Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. AIES 2020: 337-342 - [c1]Christine Kaeser-Chen, Elizabeth Dubois, Friederike Schuur, Emanuel Moss:
Positionality-aware machine learning: translation tutorial. FAT* 2020: 704 - [i1]Mona Sloane, Emanuel Moss, Olaitan Awomolo, Laura Forlano:
Participation is not a Design Fix for Machine Learning. CoRR abs/2007.02423 (2020)
2010 – 2019
- 2019
- [j1]Mona Sloane, Emanuel Moss:
AI's social sciences deficit. Nat. Mach. Intell. 1(8): 330-331 (2019)
Coauthor Index
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