Taxation on individuals based on data usage

Abstract

As digital technologies increasingly shape modern life, traditional taxation systems have not yet adapted to address the growing consumption of data by people. This capstone project studies the feasibility, design, and implications of a progressive tax on individual internet data consumption. In the context of an increasing acknowledgment of data as an economic asset, the project examines whether user-level consumption of data can serve as an ethical and implementable basis for a system of taxation that encourages responsible engagement with the digital world without violating privacy or exacerbating socioeconomic inequality. The research employed a mixed-methods design using both primary data from a survey administered to 121 students at Ahmedabad University plus structured qualitative interviews and secondary literature reviews and policy comparisons. The survey examined engagement across social media, streaming, e-commerce, video conferencing, web browsing, and email. While spending a significant amount of time engaged on social media and streaming platforms, students reported high levels of digital engagement around smartphones, with most respondents consuming data between 1-4GB per day. This consumption pattern shows an interaction that is habitual and the implications for personal health and well-being are of concern, including Digital Eye Strain and mental fatigue documented in secondary literature.The theoretical framework comprises economic, psychological, ethical, and behavioral dimensions. Key topics include progressive taxation, status quo bias, psychological distance, and context to evaluate students' behavioral ecology of data usage. The proposed policy is a multi-tier tax structure which recognizes personal from commercial usage of data. Personal usage below a defined threshold will not be taxed, while usage above that threshold, and monetized usage, will be taxed proportionally. Tax liability will be enforced through ISPs, digital platforms, and self-reporting, with appropriate privacy protections in the form of anonymized reporting and blockchain technology. The tax revenues can be used to build capacity in digital literacy, infrastructure, and welfare access to bridge the digital divide and foster social inclusiveness. Case studies from around the world (Hungary, Italy, Kenya, Canada) and developing frameworks (e.g. the OECD’s DST framework) were employed to contextualize the Indian situation and assess feasibility. The model intends to complement existing sources of tax, avoid regressive implications and reward good corporate behaviour of using data ethically over time. Psychological interviews reinforced that, while digital behavior is often automatic, habitual and dictated by social norms and convenience, there is conditional openness to change, particularly in desirable and rewarding circumstances. Gifford's concept of the "Dragons of Inaction", as well as psychologies related to hyperbolic discounting and status quo bias, inform resistance to behavioral taxation about digital usage. Ultimately, this project has demonstrated that a model of taxation related to data usage, if developed with and for the public, with the elements of transparency, inclusivity and recognizably ethical objectives can fundamentally align fiscal tax structures with the realities of digital practice in the 21st century, with the potential to encourage greater responsible digital use and accountability for data monetization companies, together with moving towards a national objective of digital equality and economic sustainability.