SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866916262482804736 |
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| author | Reddy, Revanth Gangi Lee, Daniel Fung, Yi R. Nguyen, Khanh Duy Zeng, Qi Li, Manling Wang, Ziqi Voss, Clare Ji, Heng |
| author_facet | Reddy, Revanth Gangi Lee, Daniel Fung, Yi R. Nguyen, Khanh Duy Zeng, Qi Li, Manling Wang, Ziqi Voss, Clare Ji, Heng |
| contents | Timely and comprehensive understanding of emerging events is crucial for effective decision-making; automating situation report generation can significantly reduce the time, effort, and cost for intelligence analysts. In this work, we identify intelligence analysts' practices and preferences for AI assistance in situation report generation to guide the design strategies for an effective, trust-building interface that aligns with their thought processes and needs. Next, we introduce SmartBook, an automated framework designed to generate situation reports from large volumes of news data, creating structured reports by automatically discovering event-related strategic questions. These reports include multiple hypotheses (claims), summarized and grounded to sources with factual evidence, to promote in-depth situation understanding. Our comprehensive evaluation of SmartBook, encompassing a user study alongside a content review with an editing study, reveals SmartBook's effectiveness in generating accurate and relevant situation reports. Qualitative evaluations indicate over 80% of questions probe for strategic information, and over 90% of summaries produce tactically useful content, being consistently favored over summaries from a large language model integrated with web search. The editing study reveals that minimal information is removed from the generated text (under 2.5%), suggesting that SmartBook provides analysts with a valuable foundation for situation reports |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_14337 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts Reddy, Revanth Gangi Lee, Daniel Fung, Yi R. Nguyen, Khanh Duy Zeng, Qi Li, Manling Wang, Ziqi Voss, Clare Ji, Heng Computation and Language Timely and comprehensive understanding of emerging events is crucial for effective decision-making; automating situation report generation can significantly reduce the time, effort, and cost for intelligence analysts. In this work, we identify intelligence analysts' practices and preferences for AI assistance in situation report generation to guide the design strategies for an effective, trust-building interface that aligns with their thought processes and needs. Next, we introduce SmartBook, an automated framework designed to generate situation reports from large volumes of news data, creating structured reports by automatically discovering event-related strategic questions. These reports include multiple hypotheses (claims), summarized and grounded to sources with factual evidence, to promote in-depth situation understanding. Our comprehensive evaluation of SmartBook, encompassing a user study alongside a content review with an editing study, reveals SmartBook's effectiveness in generating accurate and relevant situation reports. Qualitative evaluations indicate over 80% of questions probe for strategic information, and over 90% of summaries produce tactically useful content, being consistently favored over summaries from a large language model integrated with web search. The editing study reveals that minimal information is removed from the generated text (under 2.5%), suggesting that SmartBook provides analysts with a valuable foundation for situation reports |
| title | SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2303.14337 |