A pre-registered experiment found that an AI providing only pro and con evidence, without recommendations, did not improve decision performance and was used shallowly by participants.
Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based Explanations and Weight of Evidence
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abstract
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.
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cs.HC 1years
2024 1verdicts
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An Empirical Examination of the Evaluative AI Framework
A pre-registered experiment found that an AI providing only pro and con evidence, without recommendations, did not improve decision performance and was used shallowly by participants.