Summary of Explainers’ Mental Representations Of Explainees’ Needs in Everyday Explanations, by Michael Erol Schaffer et al.
Explainers’ Mental Representations of Explainees’ Needs in Everyday Explanations
by Michael Erol Schaffer, Lutz Terfloth, Carsten Schulte, Heike M. Buhl
First submitted to arxiv on: 13 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel investigation into the mental representations of explainers is proposed to advance XAI capabilities. The study aims to understand how explainers adapt and customize explanations based on their perception of the explainee’s developing knowledge and shifting interests. By analyzing everyday explanations of technological artifacts, the researchers aim to identify the key aspects that explainers consider when determining whether an explanation is effective. The findings suggest that explainers initially assume a strong focus on “Architecture” (observable features) but adapt to address both “Architecture” and “Relevance” (interpretable aspects) as the explanation progresses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this study, researchers explored how people who explain things to others think about the person they’re explaining to. They found that these “explainers” start with a simple understanding of what the person needs to know, but then adjust their explanation based on how much the person knows and cares about the topic. The results show that explainers initially focus on making things clear (Architecture) but adapt to include more details as they realize the person is interested in both the “how” (Architecture) and “why” (Relevance). This study has practical implications for creating systems that can help people understand complex information. |
