用AI识别税收漏洞，辅助制定更公平的政策。
Can AI expose tax loopholes? Towards a new generation of legal policy assistants
- 结合自然语言与领域专用语言，构建法律政策助手原型。
- 案例研究验证可系统发现税收漏洞与避税方案。
- 适合政策制定者、税务机构及法律科技研究者参考。
立法过程是建立在稳固制度之上的国家的基石。然而，由于法律本身——尤其是税法——的复杂性，政策可能导致不平等和社会矛盾。本研究提出一种新型原型系统，旨在解决税收漏洞与避税问题。该混合解决方案将自然语言接口与专用于规划的领域特定语言相结合。通过案例研究，展示了如何揭示税收漏洞与避税策略。研究结论表明，该原型系统有助于通过系统性识别和应对由漏洞引发的税收缺口，提升社会福利。
原文摘要 · Abstract (English)
The legislative process is the backbone of a state built on solid institutions. Yet, due to the complexity of laws -- particularly tax law -- policies may lead to inequality and social tensions. In this study, we introduce a novel prototype system designed to address the issues of tax loopholes and tax avoidance. Our hybrid solution integrates a natural language interface with a domain-specific language tailored for planning. We demonstrate on a case study how tax loopholes and avoidance schemes can be exposed. We conclude that our prototype can help enhance social welfare by systematically identifying and addressing tax gaps stemming from loopholes.
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