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Found 4 papers, 1 papers with code
Designing for Meaningful Human Control in Military Human-Machine Teams
We propose methods for analysis, design, and evaluation of Meaningful Human Control (MHC) for defense technologies from the perspective of military human-machine teaming (HMT).
Teaming up with information agents
Despite the intricacies involved in designing a computer as a teampartner, we can observe patterns in team behavior which allow us to describe at a general level how AI systems are to collaborate with humans.
Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences
There is therefore a need for transparency of machine learning models.
Contrastive Explanations with Local Foil Trees
Recent advances in interpretable Machine Learning (iML) and eXplainable AI (XAI) construct explanations based on the importance of features in classification tasks.
Explainable Artificial Intelligence (XAI)
General Classification
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