Leverage white-collar workers with AI
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Author (Corporation)
Publication date
2019
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Collections
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04B - Conference paper
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Parent work
Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019)
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Place of publication / Event location
Palo Alto
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Abstract
Based on the example of automated meeting minutes taking, the paper highlights the potential of optimizing the allocation of tasks between humans and machines to take the particular strengths and weaknesses of both into account. In order to combine the functionality of supervised and unsupervised machine learning with rule-based AI or traditionally programmed software components, the capabilities of AI-based system actors need to be incorporated into the system design process as early as possible.
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Event
AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019)
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Conference start date
25.03.2019
Conference end date
27.03.2019
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Language
English
Created during FHNW affiliation
Yes
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Publication status
Published
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Open access category
Diamond
Citation
Jüngling, S., & Hofer, A. (2019). Leverage white-collar workers with AI. In A. Martin, K. Hinkelmann, A. Gerber, D. Lenat, & P. Clark (Eds.), Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019). https://doi.org/10.26041/fhnw-6456