Can AI file your taxes? Not yet. Calculating US personal income taxes is a task that requires building an understanding of vast amounts of English text and using that knowledge to carefully compute results. We propose TaxCalcBench, a benchmark for determining models' abilities to calculate personal income tax returns given all of the necessary information. Our experiment shows that state-of-the-art models succeed in calculating less than a third of federal income tax returns even on this simplified sample set. Our analysis concludes that models consistently misuse tax tables, make errors in tax calculation, and incorrectly determine eligibility. Our findings point to the need for additional infrastructure to apply LLMs to the personal income tax calculation task.

The use of Artificial Intelligence (AI) in public administration is expanding rapidly, moving from automating routine tasks to deploying generative and agentic systems that autonomously act on goals. While AI promises greater efficiency and responsiveness, its integration into government functions raises concerns about fairness, transparency, and accountability. This article applies principal-agent theory (PAT) to conceptualize AI adoption as a special case of delegation, highlighting three core tensions: assessability (can decisions be understood?), dependency (can the delegation be reversed?), and contestability (can decisions be challenged?). These structural challenges may lead to a "failure-by-success" dynamic, where early functional gains obscure long-term risks to democratic legitimacy. To test this framework, we conducted a pre-registered factorial survey experiment across tax, welfare, and law enforcement domains. Our findings show that although efficiency gains initially bolster trust, they simultaneously reduce citizens' perceived control. When the structural risks come to the foreground, institutional trust and perceived control both drop sharply, suggesting that hidden costs of AI adoption significantly shape public attitudes. The study demonstrates that PAT offers a powerful lens for understanding the institutional and political implications of AI in government, emphasizing the need for policymakers to address delegation risks transparently to maintain public trust.

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.

Due to the ever-increasing complexity of income tax laws in the United States, the number of US taxpayers filing their taxes using tax preparation software (henceforth, tax software) continues to increase. According to the U.S. Internal Revenue Service (IRS), in FY22, nearly 50% of taxpayers filed their individual income taxes using tax software. Given the legal consequences of incorrectly filing taxes for the taxpayer, ensuring the correctness of tax software is of paramount importance. Metamorphic testing has emerged as a leading solution to test and debug legal-critical tax software due to the absence of correctness requirements and trustworthy datasets. The key idea behind metamorphic testing is to express the properties of a system in terms of the relationship between one input and its slightly metamorphosed twinned input. Extracting metamorphic properties from IRS tax publications is a tedious and time-consuming process. As a response, this paper formulates the task of generating metamorphic specifications as a translation task between properties extracted from tax documents - expressed in natural language - to a contrastive first-order logic form. We perform a systematic analysis on the potential and limitations of in-context learning with Large Language Models(LLMs) for this task, and outline a research agenda towards automating the generation of metamorphic specifications for tax preparation software.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. For years leading up to 2020, I warned that the next national emergency -- like the '08 financial crisis -- would lead to billions in fraud losses. When COVID-19 hit, my warnings became our reality. Hundreds of billions of dollars were plundered from the coffers of vital government programs -- rent relief, unemployment benefits, SNAP benefits and PPP loans became piggy banks for thousands of domestic and transnational cybercriminals.

What is an NFT? (34%) Non-fungible tokens (NFTs) are generally digital art pieces or music that can be bought or traded online. These are unique computer files encrypted with an artist's signature. As a result, they cannot be replicated, acting as a digital certificate of ownership and authenticity. In other words, buying an NFT is almost like the more traditional purchasing of fine art - except in a digital form. Artists can sell pieces that may be tricky to advertise otherwise, such as digital stickers.

ISLAMABAD: A meeting on broadening of tax base was informed that the Federal Board of Revenue (FBR) has provided 14 million records of financial transactions of citizens to the National Database and Registration Authority (NADRA) to compute indicative income and tax liability of non-filers by use of artificial intelligence. The meeting was presided over by Adviser to the Prime Minister on Finance Shaukat Tarin on Monday. The FBR chairman and his team gave a detailed presentation on the progress on readiness for potential taxpayer outreach initiative to boost the revenue growth and resource mobilisation. The FBR chairman apprised the adviser that steps have been initiated for compilation of data, with the support of the NADRA, which would be available to potential and current taxpayers in a presentable and comprehensible manner through a web portal. According to Business Recorder, the 14 million financial records included property transactions, vehicle purchases, registration of cars with provincial excise departments, buying/selling of movable and immovable properties, utility bills, foreign travels, and other heavy expenditures.

Register for free or grab a discounted VIP pass today. Tax compliance platform Blue Dot (previously VatBox) today announced it has raised $32 million, bringing its total raised to over $96 million. The firm says it will put the funds toward product R&D and expanding the size of its globlal workforce. The tax compliance burden for enterprises can be significant. In 2019, half of companies responding to an EY Americas survey indicated that their biggest compliance challenge would be staying current on legislative and regulatory developments.

There could also be a number of challenges that tax authorities in India may face when using artificial intelligence. These can include the need to balance centralisation of tax assessment with on-ground experience, uncertainties around being able to develop models which deliver a positive impact on performance, the varying range of choices in AI solutions, and the need for skills to leverage those advanced solutions. India may soon become the first country to use artificial intelligence and machine learning in the tax assessment process. Finance Minister Nirmala Sitharaman has announced that the government will deploy a faceless assessment system based on AI and ML, starting October 2019. The overall process will increase the accuracy and transparency of India's tax assessment process, thereby improving the tax base and compliance.

We work with many Metropolitan NYC business owners, so that means that the April 15th deadline doesn't carry quite the same "relief" that it does for many firms who work primarily with individual tax returns. Which is one of the reasons why you still see me posting a strategy note here this week. Another reason is that word on the street is that there are many Metropolitan NYC taxpayers who aren't very happy with their tax return. From what I can gather, many of these people are W-2 employees, and not business owners. But just because your accountant somehow qualified you for the §199A deduction, it doesn't mean that he/she covered all your tax bases.