Excavation is Destruction Digitization: Advances in Archaeological PracticeCH Roosevelt, P Cobb, E Moss, BR Olson, S Ünlüsoy Journal of field archaeology 40 (3), 325-346, 2015 | 242 | 2015 |
| Owning ethics: Corporate logics, silicon valley, and the institutionalization of ethics J Metcalf, E Moss Social Research: An International Quarterly 86 (2), 449-476, 2019 | 229* | 2019 |
| Participation is not a design fix for machine learning M Sloane, E Moss, O Awomolo, L Forlano Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms …, 2022 | 155 | 2022 |
| Algorithmic impact assessments and accountability: The co-construction of impacts J Metcalf, E Moss, EA Watkins, R Singh, MC Elish Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 127 | 2021 |
| AI’s social sciences deficit M Sloane, E Moss Nature Machine Intelligence 1 (8), 330-331, 2019 | 78 | 2019 |
| Accountability in an algorithmic society: relationality, responsibility, and robustness in machine learning AF Cooper, E Moss, B Laufer, H Nissenbaum Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 73 | 2022 |
| Assembling accountability: algorithmic impact assessment for the public interest E Moss, EA Watkins, R Singh, MC Elish, J Metcalf Available at SSRN 3877437, 2021 | 65 | 2021 |
| Contextual analysis of social media: The promise and challenge of eliciting context in social media posts with natural language processing DU Patton, WR Frey, KA McGregor, FT Lee, K McKeown, E Moss Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 337-342, 2020 | 43 | 2020 |
| A Silicon Valley love triangle: Hiring algorithms, pseudo-science, and the quest for auditability M Sloane, E Moss, R Chowdhury Patterns 3 (2), 2022 | 36 | 2022 |
| High tech, high risk: Tech ethics lessons for the COVID-19 pandemic response E Moss, J Metcalf Patterns 1 (7), 2020 | 27 | 2020 |
| Ethics owners: A new model of organizational responsibility in data-driven technology companies E Moss, J Metcalf Data & Society Research Institute, 2020 | 27 | 2020 |
| Resistance and refusal to algorithmic harms: Varieties of ‘knowledge projects’ MI Ganesh, E Moss Media International Australia 183 (1), 90-106, 2022 | 25 | 2022 |
| Excavating awareness and power in data science: A manifesto for trustworthy pervasive data research K Shilton, E Moss, SA Gilbert, MJ Bietz, C Fiesler, J Metcalf, J Vitak, ... Big Data & Society 8 (2), 20539517211040759, 2021 | 24 | 2021 |
| Burnout and the quantified workplace: tensions around personal sensing interventions for stress in resident physicians DA Adler, E Tseng, KC Moon, JQ Young, JM Kane, E Moss, DC Mohr, ... Proceedings of the ACM on Human-computer Interaction 6 (CSCW2), 1-48, 2022 | 22 | 2022 |
| Governing with algorithmic impact assessments: six observations E Moss, EA Watkins, J Metcalf, MC Elish Watkins, Elizabeth and Moss, Emanuel and Metcalf, Jacob and Singh, Ranjit …, 2020 | 21 | 2020 |
| The ethical dilemma at the heart of big tech companies E Moss, J Metcalf Harvard Business Review 14, 2019 | 20 | 2019 |
| AI reflections in 2019 AS Rich, C Rudin, JD MP, R Freeman, OR Wearn, H Shevlin, D Kanta, ... Nature Machine Intelligence 2 (1), 2-9, 2020 | 15 | 2020 |
| Participation is not a design fix for machine learning (pp. 1–7) M Sloan, E Moss, O Awomolo, L Forlano Proceedings of the International Conference on Machine Learning, Vienna, Austria, 2020 | 10 | 2020 |
| Governing algorithmic systems with impact assessments: Six observations EA Watkins, E Moss, J Metcalf, R Singh, MC Elish Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 1010 …, 2021 | 8 | 2021 |
| Positionality-aware machine learning: translation tutorial C Kaeser-Chen, E Dubois, F Schüür, E Moss Proceedings of the 2020 Conference on fairness, accountability, and …, 2020 | 8 | 2020 |
Brandon R. OlsonBoston UniversityVerified email at bu.edu
