TY - GEN
T1 - EASY-AI: SEmantic and compoSable glYphs for representing AI systems
T2 - 3rd International Conference on Hybrid Human-Artificial Intelligence, HHAI 2024
AU - Ellis, Alexis
AU - Dave, Brandon
AU - Salehi, Hugh
AU - Ganapathy, Subhashini
AU - Shimizu, Cogan
N1 - Publisher Copyright:
© 2024 The Authors.
PY - 2024/6/5
Y1 - 2024/6/5
N2 - Despite the rapid integration of artificial intelligence (AI) into various research domains and the lives of everyday people, challenges with communicating and understanding these AI systems arise. The lack of a consistent method of communication highlights the need for a transdisciplinary approach to explain the inner workings of AI systems in a cohesive and accessible manner. We thus propose an ontological visual framework using semantically-enhanced, symbols, providing a symbolic language for conveying the structure, purpose, and characteristics of AI systems. The framework encompasses a generalizable glyph set of various AI system components, ensuring both common and obscure architectures can be represented. In this paper, we present the underlying logical formalisms that dictate the behavior of this visual framework as a means to significantly enhance the comprehensibility and understandability of AI system behaviors.
AB - Despite the rapid integration of artificial intelligence (AI) into various research domains and the lives of everyday people, challenges with communicating and understanding these AI systems arise. The lack of a consistent method of communication highlights the need for a transdisciplinary approach to explain the inner workings of AI systems in a cohesive and accessible manner. We thus propose an ontological visual framework using semantically-enhanced, symbols, providing a symbolic language for conveying the structure, purpose, and characteristics of AI systems. The framework encompasses a generalizable glyph set of various AI system components, ensuring both common and obscure architectures can be represented. In this paper, we present the underlying logical formalisms that dictate the behavior of this visual framework as a means to significantly enhance the comprehensibility and understandability of AI system behaviors.
KW - Human-Computer Interaction
KW - Ontology
KW - Semantics
KW - Symbology
UR - https://corescholar.libraries.wright.edu/cse/697
UR - https://www.scopus.com/pages/publications/85198725779
UR - https://www.scopus.com/pages/publications/85198725779#tab=citedBy
U2 - 10.3233/FAIA240187
DO - 10.3233/FAIA240187
M3 - Conference contribution
AN - SCOPUS:85198725779
T3 - Frontiers in Artificial Intelligence and Applications
SP - 105
EP - 113
BT - HHAI 2024: Hybrid Human AI Systems for the Social Good - Proceedings of the 3rd International Conference on Hybrid Human-Artificial Intelligence
A2 - Lorig, Fabian
A2 - Tucker, Jason
A2 - Lindstrom, Adam Dahlgren
A2 - Dignum, Frank
A2 - Murukannaiah, Pradeep
A2 - Theodorou, Andreas
A2 - Yolum, Pinar
PB - IOS Press BV
Y2 - 10 June 2024 through 14 June 2024
ER -