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）方面起着至关重要的作用。税务准备软件的使用已大幅增长，在2020年使用了超过7200万人使用它。但是，进行了有限的独立研究来评估税收软件的问责制。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，调试和修补税收软件的可扩展性和精度。该项目特别关注低收入纳税人的豁免，信用和扣除额，以确保所有纳税人（包括来自脆弱社区的纳税人）支付所有税收的税款，而税法处方的全部和唯一的税款则应与法律和社会构成诸如法律范围的范围较大的范围，以实施税务行为，以实施税务范围，以实现正式的行为，并在法律上构成诸如法律范围的范围。问责制。由于美国税法遵守先例法律学说（Decisis），因此该项目建议这些规范自然存在是在给定背景下被认为相似的个体之间的变质关系。项目团队计划1）从美国税法中的一系列挑战性要求中解释变态关系，2）通过利用与相关性有关的感知心理学的原则来自动提取这种变态关系，3）人类税务专家。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估的。