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: 2317206
• 负责人: Saeid Tizpaz-Niari
• 金额: $ 53万
• 依托单位: University of Texas at El Paso
• 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=2317206&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.

随着美国税法的频繁变化，决策支持软件在帮助纳税人、专业人士和美国国税局(IRS)驾驭其复杂性方面发挥着至关重要的作用。纳税筹划软件的使用显著增加，2020年超过7200万人使用该软件。然而，评估税务软件问责制的独立研究有限。该项目面临两个主要挑战：i)基于税法和专家的观点，确保软件的合规性、准确性和公平性；ii)提高税务软件测试、调试和修补的可扩展性和精确度。该项目特别关注低收入纳税人的免税、抵免和扣减，目的是确保所有纳税人，包括来自弱势群体的纳税人，缴纳税法规定的所有且仅限于税法规定的税款。虽然预期具有法律和社会影响的软件应该是公平和合规的，但对于税务软件等法律关键领域的预期行为缺乏正式规范，在确保问责方面构成了巨大挑战。由于美国税法遵循先例的法律原则(STARE PROCESION)，本项目提出，这些规范自然作为在给定背景下被视为相似的个人之间的变形关系而存在。该项目团队计划1)从美国税法中一大套具有挑战性的要求中阐明变质关系，2)通过利用与相关性相关的感知心理学中的原理来自动提取这种变质关系，3)开发利用这些关系的人工制品来使用正式验证技术来评估税务软件，以及4)通过实验比较税务软件的准确性和对程序正义的看法与人类税务专家的看法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。