Papers
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. (2024). Artificial Intelligence and the Future of Citizen Science. Citizen Science: Theory And Practice, 9(1), 32. https://doi.org/10.5334/cstp.812
. (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). ReelFramer: Human-AI Co-Creation for News-to-Video Translation. In CHI '24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems (1 - 20). https://doi.org/10.1145/3613904.3642868
. (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
. (2020). AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings. Telecommunications Policy, 44, 101976. https://doi.org/10.1016/j.telpol.2020.101976
. (2020). AI in operations management: applications, challenges and opportunities. Journal Of Data, Information And Management, 2, 67–74. https://doi.org/10.1007/s42488-020-00023-1
. (2020). Algorithms at work: The new contested terrain of control. Academy Of Management Annals, 14(1), 366 - 410. https://doi.org/10.5465/annals.2018.0174
. (2020). Cities of the Future? The Potential Impact of Artificial Intelligence. Ai, 1, 192–197. https://doi.org/10.3390/ai1020012
. (2020). Explainable AI under contract and tort law: legal incentives and technical challenges. Artificial Intelligence And Law. https://doi.org/10.1007/s10506-020-09260-6
. (2020). Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators. In Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020 (82–86). https://doi.org/10.1109/ComSDS49898.2020.9101238
. (2020). Machine learning-based clinical prediction modeling – A practical guide for clinicians. Artificial Intelligence In Precision Health, 257–278. https://doi.org/10.1016/b978-0-12-817133-2.00011-2
. (2020). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users' expectations. Technological Forecasting And Social Change, 151, 119794. https://doi.org/10.1016/j.techfore.2019.119794
. (2020). Similarity Learning Networks for Animal Individual Re-Identification-Beyond the Capabilities of a Human Observer. In Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020 (479, 44–52). https://doi.org/10.1109/WACVW50321.2020.9096925
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213
. (2020). Understanding the Impact of Artificial Intelligence on Services. In International Conference on Exploring Services Science (1, 202–213). https://doi.org/10.1007/978-3-030-38724-2
. (2020). A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective. Computer Law & Security Review: The International Journal Of Technology Law And Practice, 38, 105429. https://doi.org/10.1016/j.clsr.2020.105429