Collaborative Research: DASS: Assessing Accountability of Tax Preparation Software Systems

合作研究：DASS：评估报税软件系统的责任

• 批准号: 2317207
• 负责人: Ashutosh Trivedi
• 金额: $ 22万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2317207&HistoricalAwards=false
• 关键词: Collaborative; Research; DASS; Assessing; Accountability

As the U.S. tax law frequently changes, decision-support software plays a crucial role in helping taxpayers, professionals, and the Internal Revenue Service (IRS) navigate its complexities. The use of tax preparation software has witnessed a significant increase, with over 72 million people utilizing it in 2020. However, there has been limited independent research conducted to assess the accountability of tax software. This project takes on two main challenges: i) ensuring the software's compliance, accuracy, and fairness based on tax law and experts' perspectives, and ii) enhancing scalability and precision in testing, debugging, and patching tax software. The project specifically focuses on exemptions, credits, and deductions for low-income taxpayers, with the aim of ensuring that all taxpayers, including those from vulnerable communities, pay all and only the taxes that tax law prescribes.While it is expected that software with legal and social implications should be fair and compliant with the law, the absence of formal specifications regarding expected behaviors in legal-critical domains like tax software poses significant challenges in ensuring accountability. Since U.S. tax law adheres to the legal doctrine of precedent (stare decisis), this project proposes that these specifications naturally exist as metamorphic relationships between individuals who are considered similar within a given context. The project team plans to 1) explicate metamorphic relations from a large set of challenging requirements in U.S. tax law, 2) automate the extraction of such metamorphic relations by leveraging principles from the psychology of perception pertaining to relateness, 3) develop artifacts for assessing tax software that leverages those relations using formal verification techniques, and 4) experimentally compare the tax software's accuracy and perception of procedural justice to that of human tax experts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

由于美国税法经常发生变化，决策支持软件在帮助纳税人、专业人士和国税局 (IRS) 应对其复杂性方面发挥着至关重要的作用。报税软件的使用量显着增加，2020 年使用人数超过 7200 万人。然而，评估报税软件责任的独立研究却很有限。该项目面临两个主要挑战：i）根据税法和专家的观点确保软件的合规性、准确性和公平性；ii）提高测试、调试和修补税务软件的可扩展性和精度。该项目特别关注低收入纳税人的免税、抵免和扣除，旨在确保所有纳税人，包括来自弱势群体的纳税人，缴纳且仅缴纳税法规定的全部税款。法律和社会影响应该公平且符合法律，但税务软件等法律关键领域的预期行为缺乏正式规范，这给确保问责制带来了重大挑战。由于美国税法遵循先例（遵循先例）的法律原则，因此该项目提出，这些规范自然地作为在给定背景下被认为相似的个人之间的变形关系而存在。项目团队计划 1) 从美国税法中大量具有挑战性的要求中解释变质关系，2) 通过利用与相关性相关的感知心理学原理，自动提取此类变质关系，3) 开发用于评估税收的工件使用形式验证技术利用这些关系的软件，以及 4) 通过实验将税务软件的准确性和程序公正性感知与人类税务专家进行比较。该奖项反映了 NSF 的法定使命，并被视为值得通过使用基金会的智力优点和更广泛的影响审查标准进行评估来支持。