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Artificial intelligence in information systems: State of the art and research roadmap. Communications Of The Association For Information Systems (Cais), 50. https://doi.org/10.17705/1CAIS.05017
. (2022). 
A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis. Mobile Networks And Applications, 25, 1075–1083. https://doi.org/10.1007/s11036-020-01530-6
. (2020). Competing with Robots: Firm-Level Evidence from France. Aea Papers And Proceedings, 110, 383–388. https://doi.org/10.1257/pandp.20201003
. (2020). . (2020).
Engaged to a Robot? The Role of AI in Service. Journal Of Service Research. https://doi.org/10.1177/1094670520902266
. (2020). Feminist economic geography and the future of work. Epa: Economy And Space, 1–12. https://doi.org/10.1177/0308518X20947101
. (2020). Implementation of Artificial Intelligence (AI): A Roadmap for Business Model Innovation. Ai, 1, 180–191. https://doi.org/10.3390/ai1020011
. (2020). Learning occupational task-shares dynamics for the future of work. In AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (36–42). https://doi.org/10.1145/3375627.3375826
. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information And Management, 57, 103174. https://doi.org/10.1016/j.im.2019.103174
. (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
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Artificial intelligence and the future of labor demand. https://doi.org/10.3386/w25682
. (2019). Automation and new tasks: How technology displaces and reinstates labor. https://doi.org/10.3386/w25684
. (2019). Consider the human work experience when integrating robotics in the workplace. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (75 - 84). https://doi.org/10.1109/HRI.2019.8673139
. (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). The future of the work in America. In McKinsey Global Institute. Retrieved de https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow
. (2019). Global commission on the future of work. In Work for a brighter future. Retrieved de https://www.ilo.org/global/topics/future-of-work/WCMS_569528/lang--en/index.htm
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