Vocabularies
https://docs.google.com/forms/d/e/1FAIpQLScZfT6HKtxlv-fDC6HBr67YdWfLzl996-FV3aFVD71Ts_5Kyg/viewform?usp=sf_link
https://docs.google.com/spreadsheets/d/1pCwJE0YUl0HzzWqIEJ3I1aYfsopmXpN7RFDA7LhPPKc/edit?usp=sharing
Enter proposed terms in the appropriate form (terms should be domain specific and representative of domain knowledge)
This vocabulary captures the essence of knowledge representation (as an established scientific discipline) in relation to AI and Machine Learning in the consideration of how explicit KR can help to mitigate known AI risks and challenges (accountability, transparency, auditability, explainbility, reliabilty, replicability etc).
The vocabulary is going to be published as a community resource and It is intended to complement and extend the concepts and terms in use in existing resources, such as:
Please follow the guidelines
1. Evaluate the relevance and centrality to AI KR of the term you are proposing in the light of AI state of the art risks and challenges, explain the relevance and centrality of the proposed term and how the terms concept they point to contributes to mitigate the risks and challenges for AI/ML
2. Check if the term you are proposing is already included in existing standards or other resources, and only add it here if it is not defined elsewhere and/or if you intend to propose an alternate definition
3. Cite the source of the definition and possibly add justification/use case
Eventually we can transform the vocabulary into some concept map
DEPRECATED (No longer in use)