TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Oelke, Daniela
A1  - Keim, Daniel A.
A1  - Chau, Polo
A1  - Endert, Alex
T1  - Interactive Visualization for Fostering Trust in AI
T2  - Dagstuhl Reports
N2  - Artificial intelligence (AI), and in particular machine learning algorithms, are of increasing importance in many application areas but interpretability and understandability as well as responsibility, accountability, and fairness of the algorithms' results, all crucial for increasing the humans' trust into the systems, are still largely missing. Big industrial players, including Google, Microsoft, and Apple, have become aware of this gap and recently published their own guidelines for the use of AI in order to promote fairness, trust, interpretability, and other goals. Interactive visualization is one of the technologies that may help to increase trust in AI systems. During the seminar, we discussed the requirements for trustworthy AI systems as well as the technological possibilities provided by interactive visualizations to increase human trust in AI.
KW  - accountability
KW  - artificial intelligence
KW  - explainability
KW  - fairness
KW  - interactive visualization
KW  - machine learning
KW  - responsibility
KW  - trust
KW  - understandability
Y1  - 2021
SN  - 2192-5283
SS  - 2192-5283
U6  - https://doi.org/10.4230/DagRep.10.4.37
DO  - https://doi.org/10.4230/DagRep.10.4.37
VL  - 10
IS  - 4
SP  - 37
EP  - 42
PB  - Schloss-Dagstuhl - Leibniz Zentrum für Informatik
ER  -