Propertarian justifications of intellectual property postulate the appropriation of various entities, often called patterns, designs, or technologies. These must be immaterial and should not be confused with material structures that embody them. Hence two classes of objects are distinguished. It is convenient to refer to them as types and tokens. The type must involve a condition defining which material structures should be considered its tokens. For an IP regime to be economically meaningful one must necessarily appropriate types in a way (...) which restricts access to wide classes of similar, non-identical material structures. Therefore, type conditions must be general. They must define, with a margin of tolerance, only certain aspects of the structure, leaving others unspecified. Consequently, the relationship between such types and tokens is of many-to-many variety. The recognition of these facts leads to four problems in justifying intellectual property on propertarian grounds. The first problem is to demonstrate possession of the type in the pre-legal situation. The second one is to explain, why boundaries of an appropriated type should be placed in a particular location. The third problem is to avoid claim deadlocks resulting from conflicts of rights generated by separate overlapping types. The fourth problem is to justify why ownership of the type should entail the control over other separate entities—that is tokens. In the propertarian framework grounded in the pre-legal state of nature, satisfactory solutions do not seem to have been proposed for any of these four problems. (shrink)

Property rights of personal data have been advocated for some time. From the perspective of economics of law some argued that they could lower transaction costs for contracts involving personal data. This may be the case, but new transaction costs are introduced by propertization and the issue has not been settled. In this paper, I focus on a different and potentially more important aspect. In the actual situation, data collectors externalize costs and internalize benefits. An ownership regime that enables every (...) citizen to hold a personal data account, like a bank account, and that gives people ownership rights over secondary use of personal data could correct these misallocations. I hope to shed new light on the normative implications of the issue by offering normative justifications for property rights of personal data (Sections 2–4). Secondly, I present fundamental goals and building blocks of a property regime of personal data (Section 5) and, thirdly, I illustrate how income from personal data ownership could for instance contribute to financing pensions under proper regulation (Section 6). (shrink)

The advent of artificial intelligence (AI) challenges political theorists to think about data ownership and policymakers to regulate the collection and use of public data. AI producers benefit from free public data for training their systems while retaining the profits. We argue against the view that the use of public data must be free. The proponents of unconstrained use point out that consuming data does not diminish its quality and that information is in ample supply. Therefore, they suggest, publicly available (...) data should be free. We present two objections. First, allowing free data use promotes unwanted inequality. Second, contributors of information did not and could not anticipate that their contribution would be used to train AI systems. Therefore, charging for extensive data use is pro tanto permissible and desirable. We discuss policy implications and propose a progressive data use tax to counter the inequality arising. (shrink)