Explainable AI: The Effect of Contradictory Decisions and Explanations on Users’ Acceptance of AI Systems

Author:

Ebermann Carolin1,Selisky Matthias1,Weibelzahl Stephan1

Affiliation:

1. Business Psychology, PFH Private University of Applied Sciences, Göttingen, Germany

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics

Reference151 articles.

1. Trends and Trajectories for Explainable, Accountable and Intelligible Systems

2. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

3. Agrawal, A., Gans, J., Goldfarb, A. (2016, October 7). Managing the machines. Data Science Association. Retrieved October 16, 2020, from http://www.datascienceassn.org/sites/default/files/Managing%20the%20Machines%20-%20AI%20is%20Making%20Prediction%20Cheap,%20Posing%20New%20Challenges%20for%20Managers.pdf

4. Agrawal, A., Gans, J., Goldfarb, A. (2017). What to expect from artificial intelligence. MIT Sloan Management Review. Retrieved October 16, 2020, from https://static1.squarespace.com/static/578cf5ace58c62ac649ec9ce/t/589a5c99440243b575aaedaa/1486511270947/What+to+Expect+From+Artificial+Intelligence.pdf

5. Assessing accounting students’ performance in “cognitive misfit” condition

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