Papers by Dan Schumacher
Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI (2026.findings-acl)
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| Challenge: | Artificial intelligence (AI) is rapidly transforming healthcare but can also introduce risks, including bias, privacy violations, and unequal access. |
| Approach: | They propose a framework that generates speculative user stories and supports multi-agent discussions to help people reflect on potential benefits and harms of healthcare AI before deployment. |
| Outcome: | The framework generates speculative user stories and supports multi-agent discussions to help people reflect on potential benefits and harms of healthcare AI before deployment. |
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations (2025.coling-main)
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| Challenge: | Existing evaluation methods rely on human judgment to assess data accuracy and visual communication, which is costly and unscalable. |
| Approach: | They propose a framework that leverages Visual Question Answering (VQA) models to automate the evaluation of LLM-generated data visualizations. |
| Outcome: | The proposed framework assesses data representation quality and communicative clarity of charts using two leading VQA benchmark datasets, ChartQA and PlotQA, with visualizations generated by OpenAI’s GPT-3.5 Turbo and Meta’s Llama 3.1 70B-Instruct models. |