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Who Owns the Intellectual Fruits of Job Guarantee Labor?

  • Rohan Grey
Chapter
Part of the Binzagr Institute for Sustainable Prosperity book series (BISP)

Abstract

This chapter explores the relationship between intellectual property law and the job guarantee ("JG") in the context of the twenty-first-century economy.

Today, any information capable of digital expression—manuals, books, songs, poems, pictures, software—can be infinitely reproduced and shared at near-zero marginal cost. Moreover, with the rise of big data analytics and remix culture, it is becoming clear that there is no intrinsic correlation between the short-term demands of "the market" and the long-term social value of information, knowledge and cultural production. These developments have profound implications for the ongoing debate over the productive and price-stabilizing potential of a job guarantee-based approach to macroeconomic policy. At the same time, a data-driven, open knowledge-oriented approach to JG implementation raises a number of legal and economic questions of its own.

This article explores one such question of topical relevance: who owns the intellectual output produced by JG labor? It begins by introducing the arguments for and against the establishment and granting of intellectual property rights, before critiquing the present state of the copyright and patent debates based on the insights of the school of macroeconomic thought known as "Modern Monetary Theory," or "MMT." It then articulates a proposal for a copyleft-inspired, knowledge-oriented JG model, drawing inspiration from previously enacted cultural, educational and scientific job creation programs, as well as recent policy proposals for encouraging open-access scientific research and cultural production. Finally, it concludes by emphasizing the importance of further exploration of the relationship between law, modern money and the digital economy.

Keywords

Intellectual Property Public Investment Creative Work Intellectual Property Protection Creative Production 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© The Author(s) 2017

Authors and Affiliations

  • Rohan Grey
    • 1
  1. 1.Research FellowBinzagr Institute for Sustainable ProsperityGranvilleUSA

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