Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based Explanations and Weight of Evidence
<|reference_start|>Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based Explanations and Weight of Evidence: This paper presents Visual Evaluative AI, a decision aid that provides positive and negative evidence from image data for a given hypothesis. This tool finds high-level human concepts in an image and generates the Weight of Evidence (WoE) for each hypothesis in the decision-making process. We apply and evaluate this tool in the skin cancer domain by building a web-based application that allows users to upload a dermatoscopic image, select a hypothesis and analyse their decisions by evaluating the provided evidence. Further, we demonstrate the effectiveness of Visual Evaluative AI on different concept-based explanation approaches.<|reference_end|>
@article{le2024visual,
    title={Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based
  Explanations and Weight of Evidence},
    author={Thao Le, Tim Miller, Ruihan Zhang, Liz Sonenberg, Ronal Singh},
    journal={arXiv preprint arXiv:2407.04710},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.04710},
    primaryClass={cs.CV cs.AI cs.HC}
}