Towards Effective Management of Verbal Probability Expressions Using a Co-Learning Approach

Domain experts are one of the most important knowledge sources when building a knowledge base. However, communication about uncertain states and events is prone to misinterpretations and misunderstandings, because people prefer to convey probability estimations by verbal probability expressions (VPEs) which have a high between-subject variability. Additionally, several biases exist when expressing uncertainty verbally. Nevertheless, the application of VPEs might be necessary. Therefore, means must be identified to manage VPEs and to translate them into numeric values appropriately. In this paper, we propose a co-learning approach with example to efficiently and effectively communicate (subjective) probabilities of states and events in teams where human and AI team members are familiarized with the translation between VPEs and numeric values until both parties are capable of using solely numeric values.