Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing ID Raji, A Smart, RN White, M Mitchell, T Gebru, B Hutchinson, ... Proceedings of the 2020 conference on fairness, accountability, and …, 2020 | 695 | 2020 |
Listen to the noise: noise is beneficial for cognitive performance in ADHD G Söderlund, S Sikström, A Smart Journal of Child Psychology and Psychiatry 48 (8), 840-847, 2007 | 351 | 2007 |
Towards a critical race methodology in algorithmic fairness A Hanna, E Denton, A Smart, J Smith-Loud Proceedings of the 2020 conference on fairness, accountability, and …, 2020 | 324 | 2020 |
Towards accountability for machine learning datasets: Practices from software engineering and infrastructure B Hutchinson, A Smart, A Hanna, E Denton, C Greer, O Kjartansson, ... Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021 | 277 | 2021 |
On the genealogy of machine learning datasets: A critical history of ImageNet E Denton, A Hanna, R Amironesei, A Smart, H Nicole Big Data & Society 8 (2), 20539517211035955, 2021 | 147 | 2021 |
The use and misuse of counterfactuals in ethical machine learning A Kasirzadeh, A Smart Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021 | 101 | 2021 |
Bringing the people back in: Contesting benchmark machine learning datasets E Denton, A Hanna, R Amironesei, A Smart, H Nicole, MK Scheuerman arXiv preprint arXiv:2007.07399, 2020 | 93 | 2020 |
Semantics vs. world knowledge in prefrontal cortex L Pylkkänen, B Oliveri, AJ Smart Language and Cognitive Processes 24 (9), 1313-1334, 2009 | 75 | 2009 |
Participatory problem formulation for fairer machine learning through community based system dynamics D Martin Jr, V Prabhakaran, J Kuhlberg, A Smart, WS Isaac arXiv preprint arXiv:2005.07572, 2020 | 72 | 2020 |
The anterior midline field: Coercion or decision making? L Pylkkänen, AE Martin, B McElree, A Smart Brain and language 108 (3), 184-190, 2009 | 72 | 2009 |
Sociotechnical harms of algorithmic systems: Scoping a taxonomy for harm reduction R Shelby, S Rismani, K Henne, AJ Moon, N Rostamzadeh, P Nicholas, ... Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 723-741, 2023 | 66 | 2023 |
Touch screen having adaptive input parameter S Whitlow, W Rogers, J Lancaster, E Robert, A Smart US Patent App. 12/699,591, 2011 | 48 | 2011 |
Healthsheet: development of a transparency artifact for health datasets N Rostamzadeh, D Mincu, S Roy, A Smart, L Wilcox, M Pushkarna, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 38 | 2022 |
Extending the machine learning abstraction boundary: A Complex systems approach to incorporate societal context D Martin Jr, V Prabhakaran, J Kuhlberg, A Smart, WS Isaac arXiv preprint arXiv:2006.09663, 2020 | 28 | 2020 |
El arte y la ciencia de no hacer nada AJ Smart Clave Intelectual, 2014 | 17 | 2014 |
Cognitive efficacy estimation system and method S Mathan, PM Ververs, A Smart US Patent App. 12/953,763, 2012 | 17 | 2012 |
Towards an index of cognitive efficacy EEG-based estimation of cognitive load among individuals experiencing cancer-related cognitive decline S Mathan, A Smart, T Ververs, M Feuerstein 2010 Annual International Conference of the IEEE Engineering in Medicine and …, 2010 | 17 | 2010 |
& Barnes, P.(2020, January). Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing ID Raji, A Smart, RN White, M Mitchell, T Gebru, B Hutchinson Proceedings of the 2020 conference on fairness, accountability, and …, 0 | 17 | |
Autopilot: The Art & Science of Doing Nothing A Smart OR Books, 2013 | 15 | 2013 |
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML S Rismani, R Shelby, A Smart, E Jatho, J Kroll, AJ Moon, N Rostamzadeh Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023 | 13 | 2023 |