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. (2024). Mutual learning in human-AI interaction. In Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference. Presented at the Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference, Honolulu, HI.
TREW_Workshop_Paper_2024.pdf (392.26 KB). (2024). Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy. Citizen Science: Theory And Practice, 9(1), 42. https://doi.org/10.5334/cstp.738
. (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
. (2022). 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
Artificial Intelligence in Information Systems State of the Art.pdf (1 MB). (2020). AI feel you: customer experience assessment via chatbot interviews. Journal Of Service Management. https://doi.org/10.1108/JOSM-11-2019-0341
. (2020). Artificial intelligence and the world of work, a co-constitutive relationship. Journal Of The Association For Information Science And Technology. https://doi.org/10.1002/asi.24388
. (2020). Automation and Radiology—Part 1. In Academic Radiology (pp. 147–149). https://doi.org/10.1016/j.acra.2019.10.026
. (2020). The benefits of eHRM and AI for talent acquisition. Journal Of Tourism Futures. https://doi.org/10.1108/JTF-02-2020-0013
. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719
Social_Construction_of_ML_in_GS_HICCS2020.pdf (124.3 KB). (2020). Industrial robots, employment growth, and labor cost: A simultaneous equation analysis. Technological Forecasting And Social Change, 159, 120202. https://doi.org/10.1016/j.techfore.2020.120202
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2019). Algorithms at War: The Promise, Peril, and Limits of Artificial Intelligence. International Studies Review. https://doi.org/10.1093/isr/viz025
. (2019). Artificial intelligence in workplaces and how it will affect employment in Latvia. Environment. Technology. Resources. Proceedings Of The International Scientific And Practical Conference, 2, 154. https://doi.org/10.17770/etr2019vol2.4151
. (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). 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 digital work force: Robotic process automation (RPA). Journal Of Information Systems And Technology Management, 16. https://doi.org/10.4301/S1807-1775201916001
. (2019). How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany (). In Electronic Government (pp. 233-247). https://doi.org/10.1007/978-3-030-27325-5
. (2019). In the age of the smart artificial intelligence: AI’s dual capacities for automating and informating work. Business Information Review, 026638211988399. https://doi.org/10.1177/0266382119883999
In the Age of the Smart Artificial Intelligence AI’s Dual Capacities for Automating and Informating.pdf (317.68 KB)