In the wake of the OECD’s BEPS project, there has been an explosion of interest in the closely related question of how tax systems ought to deal with highly mobile individual taxpayers.  The most obvious example of such a taxpayer is a high net-worth individual (HNWI) who can move easily between jurisdictions and whose choice of jurisdiction may be affected by tax rates, reliefs and administrative arrangements, amongst other considerations.  Yet we should not lose sight of taxpayers at the other end of the spectrum such as low-paid migrant workers, who may be paying considerable amounts of tax to their host jurisdiction without the capacity to make informed tax-efficient choices, or who, conversely, might be forced into the informal sector with few realistic opportunities to comply with their formal tax obligations.    

Either way, and as illustrated by recent debates surrounding the abolition of the UK’s preferential regime for non-domiciled individuals, individual mobility creates important challenges for democracy.  Contrary to the US Revolutionary slogan “no taxation without representation”, mobility can amplify the voice of at least some HNWIs even at the expense of revenue-generation (“reduce my tax liability or I shall leave”) at the same time as denying voice to others (“refugees must pay tax but cannot vote”).  In other words, it leads to potentially serious mismatches between taxation and representation.  Nor does citizenship provide any easy answers, despite its importance in signifying membership of political communities.  Citizenship has never been identical to subjection to the tax system (children, for example, are taxable but do not enjoy the full range of citizenship benefits), but in the context of ever-increasing individual mobility it is more difficult than ever to treat it even as a rough proxy for those who ought to be subjected to tax liabilities.  Indeed, tax systems can be expected to have to cope with increasing numbers of non-citizen taxpayers as well as non-taxpaying citizens.

Whether states ought to respond to these challenges with lower expectations of “no taxation without representation”, by making citizenship easier to obtain, by widening the franchise to include a wider range of non-citizens, or in some other way, raises an eye-wateringly complex series of questions that demand attention not only from lawyers but from a myriad of other disciplines.  It is hardly surprising, then, either that there has been a significant upswing in literature dealing with these topics, or that this literature has not yet settled on any consistent recommendations.   The Fiscal Citizenship Project, whose members are represented in the present volume, is perhaps driving the most systematic attempt to build a common vocabulary between disciplines, but it remains at a relatively early stage.

The present volume does not even attempt to compete as a systematic project.  On the contrary, it is gloriously various, representing the complexity of the problems involved as well as the sheer range of insights that are emerging across different jurisdictions and academic backgrounds. This approach is backed up by tolerant editorship that allows authors to speak for themselves rather than repeating an “editorial line”, which seems particularly well-judged in a young research area where the literature is still finding its way.  It encourages, instead of restricting or channelling, the growth of ideas.  All the same, variety is not the same as incoherence, and indeed the editors do an excellent job of drawing together the different strands and ensuring that the volume provides a meaningful and useful experience, whether read from the beginning to the end or dipped into. In this connexion, it is worth noting that both Lind’s introductory chapter and Brøgger and Björklund Larsen’s closing chapter focus on boundaries.  This is hardly a coincidence: the volume is all about boundaries, be they disciplinary, geographical, membership or tax conceptual. 

This neat bracketing of the issues is complemented by the exceptional clarity with which Bamford sets out many of the most relevant political philosophical questions in Chapter 2, which will be helpful for anyone working in this area but could equally be understood by the most recalcitrant first-year undergraduate.  In the following chapters, we read about a proposal for a more sophisticated concept of tax residency that would account for a wider range of life circumstances (Shanan and Narotzki); a new way of conceptualising fiscal citizenship (Schmidt and Matthaei); a proposal for increasing the relevance of tax payments to citizenship applications (Ramos Obando); an analysis of whether distinctions between citizens and non-citizens, if used carefully, might help states to respond to the challenges of taxpayer mobility (Lindsay); a discussion of the citizenship position of corporates (Scherer); the treatment of non-citizens within automated tax risk-management systems (More and Schenke); the importance, and misuse, of taxpayer status in defining political communities (Davis); the anomalous and potentially pointed exemption of agricultural workers in the US from certain fiscal obligations (Sarkar); the different status of taxpayers in the Canadian and Chinese tax systems (Li); and the scope, design and operation of cooperative compliance programmes in Norway and Sweden (Brøgger and Björklund Larsen).

I greatly enjoyed reading this book and would heartily recommend it to anyone who is or who might conceivably be interested in this emerging area of research.  In common with many if not most edited collections, the volume is not entirely even, either in quality or relevance to the topic.  Without wishing to single out any particular author, I sympathised with the attempts to develop theoretical and philosophical frameworks but felt that some were more successful than others.  I also thought that some of the boundary issues, in a field of study replete with boundaries, were presented by authors in a rather over-simplified or at least stylised way; still useful, but perhaps a starting-point for further discussion rather than a destination.   Finally, there is some evidence of “shoehorning” of topics into the scope of the volume, though, in balance, one of my most valuable experiences was realising that the final chapter on cooperative compliance is not at all shoehorned but instead highlights the themes of the book in a new and (for me) unexpected way.

These minor reservations, ironically, highlight one of the things that I enjoyed most about reading this volume, which is its exploratory quality.  It provides a coherent overall experience, as would be expected from editors of this calibre, but it is not overly tidied.  It is suggestive of directions rather than attempting to close down possibilities.  This, in turn, indicates a field of enquiry that is on its way up rather than one that has been answered and is exhausted of inspiration.  This sense of excitement and newness is more than captured in the volume and is one of its real strengths.  Apart from anything, it is fun to read, full of insights and inclusive.  It invites the reader to join in, and it is to be hoped that this invitation is accepted widely.

Tax researchers are increasingly focusing on the impacts of digital technologies on tax authorities and taxpayers. In June 2023, Benita Rose Mathew^[1] of the Surrey Institute for People-Centred Artificial Intelligence spearheaded a workshop on digital innovation in tax administration with participants from universities, tax authorities, companies, and NGOs from around the world.^[2]  A similar mix of participants gathered in Antwerp in June 2024 for the 9th International Conference on Taxpayer Rights. Convened by the Center for Taxpayer Rights and hosted by the DigiTax Centre at the University of Antwerp.  The focus was “Towards a Digital Taxpayer Bill of Rights^[3].”

About four dozen experts participated in about a dozen sessions over three days in Antwerp. Discussions centred on taxpayer rights to transparency, fair treatment, and human intervention, particularly in the context of AI blackboxes, data collection and accuracy, and the incomparable speed and scale at which digitized systems can inflict harm. The following are a few points that struck me as especially interesting.   

GDPR and the AI Act 

Within the EU,^[4] digitalization implicates both the GDPR and the recent AI Act. As taxation is an important objective of public interest, the GDPR permits a state to limit the rights of data subjects and the obligations of a tax authority (as a data controller) , provided any limitation of rights is necessary and proportionate and the essence of the data subject’s fundamental freedoms and rights remain protected. Philip Baker^[5] explained that the meaning of this power to limit rights and obligations in tax administration is  unclear as key issues have yet to be addressed by the EU Court of Justice.

The EU AI Act, now coming into force, imposes different levels of regulations based on a classification of AI applications.  Applications classified as “high risk” are subject to the most regulation.  The Act includes a list of AI uses that will be classified as high risk.   For example, AI used to determine eligibility for public benefits or used for  criminal law enforcement or that uses biometric data is considered “high risk” and thus subject to the most regulation.  Sylvie De Raedt^[6] highlighted that, although tax administration is not explicitly listed as high risk, it may be in specific situations For example,  tax authorities using biometric data or determining eligibility for public benefits would be high risk.

Baker questioned whether, under European Convention on Human Rights criteria the risk of administrative penalties, not just prison time, means much of tax administration should be classed as law enforcement, and, thus, high risk.

The deeper issue regarding the extent to which tax authorities should be limited by non-tax laws is what sets tax authorities apart as exceptional. Is it that taxes are the lifeblood of government?  Historically, this has been the US approach, Nina Olson explained.^[7] This leads to fewer limitations on tax authorities.  Conversely, Baker argued that tax authorities are exceptional because they collect, hold, and process the most personal data on the most persons.  Thus, he argued, tax authorities involve the riskiest data activities, and their AI and data uses should be subjected to more, not fewer data protection and human rights safeguards.

Privacy and history

National histories should be expected to influence the politics of how tax authorities use AI.  Magnus Kristoffersson^[8]described the traditional openness of  records held by Swedish authorities, including parts of personal tax records that taxpayers in many other nations would expect to be confidential. Baker speculated that the US and UK governments have lagged in developing data and AI protections because, unlike much of Europe neither experienced invasion or dictatorship in the 20th century. He attributed the EU’s lead in data protection to living memories of invasion, dictatorship, and the misuse of government-held information for persecution.

Glitches and incremental steps

Lotta Larsen^[9] reminded us that digitized systems will always have bugs and glitches, and system designers will struggle to keep up with societal changes. Keeping up with technological changes continues to prove difficult for some tax authorities, such as the IRS. David Padrino, the IRS Chief Transformation Officer, cited new funding aimed at modernizing the IRS. He said there is no IRS-wide digital transformation strategy.  The focus is on incremental projects. One such project is the introduction of “Direct File,” enabling taxpayers to file returns directly with the IRS. His pride in the success of this program, even though he acknowledged that taxpayers elsewhere have long been able to file directly with their tax authorities, underscored how far the IRS is from the type of digital revolution the AI salesforces hype. 

Cautionary tales

Dirk Van Rooy^[10] presented the Australian Robodebt scandal and David Hadwick^[11] discussed the Dutch childcare benefits scandal as cautionary tales for tax authorities. The Robodebt scandal arose from automating processes to recover overpaid welfare benefits.  Robodebt compared welfare recipients’ reported income with their tax data held by the Australian Tax Office, but it used averages of the tax data, which generated inaccurate debt calculations for those with fluctuating incomes.  The beneficiaries targeted for collection were not informed as to how their alleged debts were calculated; there was no process to challenge the alleged debts; and there was little human oversight.  A half million alleged debts had to be recalculated by hand. In a class action settlement, the government paid $1.2 billion.   In addition to the obvious process deficiencies, Van Rooy identified ideological assumptions about welfare recipients as critical to the flawed design of the system.

Hadwick highlighted the role of mistaken assumptions in the Dutch childcare benefits scandal in which non-Dutch recipients were disproportionately targeted. The problem was human bias against the non-Dutch resulted in sampling biases in the data used for machine learning. This led to discrimination against the non-Dutch as a feature rather than a bug of the automated system. Exacerbating problems for those targeted was a decision to require reimbursements not based on individual misconduct but rather a “hunch” about the percentage of individuals who would be non-compliant if they had certain social relationships (e.g., parents of children served by a childcare-provider previously connected to fraud). Hadwick’s message was that the scandal was not caused by artificial intelligence but rather politically motivated instead of data-based theorizing. Hadwick emphasized that humans must not be removed from automated-decision making processes, that is, there should always be a “human-in-the-loop” but that this is insufficient; the humans must be subject to a duty of care (e.g., to use data rather than hunches when building the system).

Developing countries 

Rhoda Nyamongo^[12] addressed the challenges faced by tax authorities in developing countries implementing AI systems.  One is the shortage of personnel who are trained in data science or taxpayer rights.  Like Hadwick, she emphasized that humans-in-the-loop are not sufficient.  What is needed are humans who understand what they are doing and what the AI system is doing and work carefully. A second challenge is that many developing countries are in the early stages of AI and data protection regulation.  A third is that tax authorities in developing countries often are locked-into using off-the-shelf software that they are unable to improve.  A fourth challenge is corruption, which means taxpayers in some developing countries may trust an AI-generated decision more than that of a tax agent.

Personal involvement 

The role of tax agents in digitized tax administration was a recurring topic. De Raedt noted that digitization reduces human contact between taxpayers and tax authorities. Vincent Vercauteren^[13] lamented how already tax agents do not become personally acquainted with the taxpayer being audited but rely exclusively on e-mailed demands for the taxpayer’s digitized books and records, which leads to worse results for both the agency and the taxpayer.  Nina Olson^[14] worried that one ultimate effect of digitization will be to exacerbate inequities with high income individuals and corporate taxpayers receiving more human interaction while others will be forced to rely exclusively on AI-delivered services.

Data from third parties 

Tax authorities will increasingly rely on third parties to provide data for AI analysis. Alessia Tomo^[15] argued that transparency as to what the government is doing is a cornerstone of democracy, which means that taxpayers have the right to know that tax authorities are engaged in web-scraping, for example.  She argued that, not only is the re-use of this data practically and legally problematic, it also does nothing to improve voluntary compliance.  If the agency’s goal is improving compliance rather than merely detecting tax cheats, this is an inadequate strategy as taxpayer compliance is unaffected if taxpayers do not know what information is being collected.  

Bigger picture

Several speakers suggested the importance of tax researchers considering the bigger picture. Raffaele Russo^[16]characterized much of the discussion at the conference as simply talking about AI doing what tax agents have done for 50 years.   Instead, he characterized this as a moment for thinking outside the box, thinking how radically different not only tax administration but substantive tax law could be. Diana van Hout^[17] suggested considering whether substantive tax law should be reformed to reduce the need for sensitive personal data (e.g., medical expense information).  Larsen encouraged pondering who ultimately will control the data (a handful of multi-national corporations)?

Digital Taxpayer Bill of Rights

The goal of the conference was producing recommendations for a Digital Taxpayer Bill of Rights.  It is expected to be published around the New Year.  Materials and recordings will soon be available at the Center for Taxpayer Rights site.