Papers
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. (In Press). Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users. Academy Of Management Review. https://doi.org/10.5465/amr.2023.0117
. (2024). Artificial Intelligence and the Future of Citizen Science. Citizen Science: Theory And Practice, 9(1), 32. https://doi.org/10.5334/cstp.812
. (2023). AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3580907
. (2020). Automation Technologies and Employment at Risk : The Case of Mexico. Banco de México.
. (2020). Does AI qualify for the job? A bidirectional model mapping labour and AI intensities. In AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (94–100). https://doi.org/10.1145/3375627.3375831
. (2020). Frameworks for collective intelligence: A systematic literature review. In ACM Computing Surveys (pp. 1–36). https://doi.org/10.1145/3368986
. (2020). The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation. Iza Discussion Paper Series. Retrieved de www.iza.org
. (2020). The Future of Work: Meeting the Global Challenge of Demographic Change and Automation. International Labour Review, 1–28. https://doi.org/10.1111/ilr.12168
. (2020). Replaced by a Robot: Service Implications in the Age of the Machine. Journal Of Service Research. https://doi.org/10.1177/1094670520933354
. (2020). The robo-apocalypse plays out in the quality, not in the quantity of work. In Journal of Information Technology. https://doi.org/10.1177/0268396220923677
. (2020). The Role of Discretion in the Age of Automation. Computer Supported Cooperative Work: Cscw: An International Journal, 29, 303–333. https://doi.org/10.1007/s10606-020-09371-3
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2019). Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice. Journal Of The Association Of Physicians Of India ■ Vol. 67 . Retrieved de https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933
. (2019). Behavioural artificial intelligence: An agenda for systematic empirical studies of artificial inference. Ai & Society. https://doi.org/10.1007/s00146-019-00928-5
. (2019). Can nurses remain relevant in a technologically advanced future?. International Journal Of Nursing Sciences, 6(1), 106 - 110. https://doi.org/10.1016/j.ijnss.2018.09.013
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Does automation influence career decisions among South African students? (). In the South African Institute of Computer Scientists and Information Technologists 2019Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 on ZZZ - SAICSIT '19 (1 - 10). https://doi.org/10.1145/335110810.1145/3351108.3351137
. (2019). The fourth industrial revolution: Trends and impacts on the world of work (pp. 177 - 194; ). In (pp. 177 - 194). https://doi.org/10.1007/978-3-319-94532-3_115