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Artificial Intelligence and Robotics in the World of Taxation

The use of artificial intelligence (AI) and robotics in taxation is not a new concept. In fact, it dates back to the early 1970s when Thorne McCarty, an assistant professor at Harvard University, developed a program called Taxman. This program focused on group reorganizations under the US Internal Revenue Code, applying “rule based reasoning” to analyze corporate tax. McCarty recognized that corporate tax had lost much of its real-world context and believed that AI could provide a solution.

In recent years, AI and robotics have become integral to revenue administrations’ plans for risk assessment and customer service. These technologies have proven useful in understanding vast amounts of data, detecting patterns of fraud, and answering taxpayers’ questions through chatbots. However, the advent of advanced language models, such as ChatGPT, has brought forth new challenges concerning the legal and ethical frameworks required to regulate their use.

The potential benefits of AI in taxation are considerable. Revenue authorities have successfully used AI to identify fraudulent VAT refund claims, uncover phoenix activities, trace money flows from data leaks, and detect aggressive or illicit tax practices. Additionally, businesses and revenue authorities alike can leverage AI for error detection in data analysis, real-time analytics, understanding tax implications in documents, and gaining insights into different tax codes globally.

AI could also play a crucial role in applying the principal purpose test in tax treaties developed as part of the OECD/G20 Base Erosion and Profit Shifting (BEPS) 1.0 initiative.

How AI legalese decoder Can Help

The emergence of AI legalese decoder presents a solution to address the risks associated with AI misuse. This innovative tool can aid in interpreting and understanding legal language, which is often riddled with complexities and nuances. By parsing legal texts, AI legalese decoder can accurately extract relevant information and assist in constructing a robust legal framework around AI technologies in taxation.

For instance, in the aftermath of the Dutch childcare benefits scandal, where racial bias was uncovered in an AI system used for fraud detection, the implementation of AI legalese decoder could have helped identify and rectify the biased algorithms. Such a tool enables policymakers and tax administrations to ensure that AI systems are developed and used in an ethical manner.

In line with the ethical practices adopted by the Australian Taxation Office (ATO), AI legalese decoder promotes transparency and accountability. It allows decision-makers and taxpayers to understand the reasoning behind AI-driven decisions, ensuring that they are not arbitrary or discriminatory. By piloting the use of AI across a smaller population and progressively expanding it, potential biases can be detected and addressed early on.

Furthermore, AI legalese decoder can contribute to protecting privacy rights. Its ability to navigate through vast datasets while respecting privacy concerns ensures that sensitive taxpayer information remains secure. Through robust security measures and encryption protocols, this tool minimizes the risk of data breaches in the context of taxation, where privacy is of utmost importance.

AI, when used responsibly and ethically, can help combat biases in taxation. As Harvard Professor Cass Sunstein suggests, algorithms and AI can assist in correcting cognitive biases present in existing systems. Through unbiased data analysis, AI legalese decoder paves the way for fairer and more accurate decision-making, reducing the impact of human biases.

Embracing an Ethical Framework

While the potential benefits of AI in taxation are significant, it is crucial to place AI within an ethical framework. The adoption of strong ethical practices, as exemplified by the Australian Taxation Office, can prevent the misuse of AI systems and uphold public trust.

An essential aspect of this framework is the rapid rectification of incorrect decisions made by AI. Continuous human supervision and regular testing for biases, such as confusion between correlation and causation, are necessary to ensure AI operates in a fair and unbiased manner.

Ultimately, the responsible and ethical use of AI in taxation requires a balance between its advantages and potential risks. By embracing AI legalese decoder and similar tools, policymakers and tax administrations can harness the power of AI while mitigating adverse outcomes. The future of AI in taxation holds both promise and concern, and it is our collective responsibility to navigate this path wisely.

About the Author

Grant Wardell-Johnson is KPMG’s Global Tax Policy Leader.

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