118 research outputs found

    Blockchain : a global infrastructure for distributed governance and local manufacturing.

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    International audienceWhile most of these blockchain-based organizations have been—thus far—developed mostly to facilitate the coordination of individuals in the digital world, the possibilities provided by these new organisational structures can also be found in the physical world. Cities, municipalities and local communities can leverage the power of blockchain technology in order to increase transparency and accountability in many sectors of activities, while providing new opportunities for anyone to engage and participate in the local economy. Enabling local processes of production to reduce the impact of the current industrial globalisation is crucial, but enabling mechanisms to incentivise, accelerate and scale this process is fundamental and urgent. This is where blockchain technology could come at hand by creating an open platform and decentralized incentivization scheme that can be articulated between multiple stakeholders

    Three-Strikes Response to Copyright Infringement: The Case of HADOPI

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    International audienceAnother notable example of how copyright enforcement has moved well beyond addressing specific infringing content or individuals into Internet governance-based infrastructural enforcement is the graduated response method, terminating the Internet access of individuals that (allegedly and) repeatedly violate copyright. The case of the French Hadopi (Haute AutoritĂ© pour la Diffusion des ƒuvres et la Protection des droits sur Internet), law first, agency next, both highly controversial, illustrates this strategy of dubious effectiveness for the purpose it is meant for, but of high disruptive potential for Internet users and access rights – and potentially affecting other, perfectly legitimate activities as a collateral effect. In this paper, we will describe the unexpected and perverse effects of this law using the notion of legislative serendipity to explain why this law has never reached the target it was intended for

    Decentralized Autonomous Organization

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    A DAO is a blockchain-based system that enables people to coordinate and govern themselves mediated by a set of self-executing rules deployed on a public blockchain, and whose governance is decentralised (i.e., independent from central control)

    Join Co-Authors Aaron Wright and Primavera DE Filippi for the Launch of Blockchain and the Law: The Rule of Code

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    https://larc.cardozo.yu.edu/event-invitations-2018/1041/thumbnail.jp

    Vers un droit collectif sur les données de santé

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    International audienc

    La transparence des algorithmes face à l'Open Data : Quel statut pour les données d'apprentissage ?

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    International audienceCet article s'intĂ©resse aux problĂ©matiques liĂ©es Ă  l’application d’algorithmes dans les dĂ©cisions administratives, et plus particuliĂšrement aux donnĂ©es et mĂ©thodes utilisĂ©es dans ces applications. Le lĂ©gislateur s’est jusqu’à prĂ©sent focalisĂ© sur la transparence de la “dĂ©cision” qui n’est qu’un certain type de traitement de donnĂ©es. Mais rien n’est prĂ©cisĂ© sur les donnĂ©es qui vont influencer ces algorithmes, c’est Ă  dire les donnĂ©es qui se trouvent en amont de la dĂ©cision. On fait l’hypothĂšse dans cet article que ce droit Ă  l’explication devrait porter aussi sur les donnĂ©es utilisĂ©es pour entraĂźner ces algorithmes.On fera d’abord un rappel de l’évolution des politiques d’Open data, puis on parlera des nouvelles tendances vers l’algorithmisation du droit et de l’administration dans le contexte du gouvernement ouvert et le rĂŽle jouĂ© par les donnĂ©es au sein de ces nouveaux processus dĂ©cisionnels. Enfin, on analysera la difficultĂ© d’assurer une rĂ©elle transparence pour de nouveaux types d’algorithmes (e.g. les algorithmes d’apprentissage automatique) qui seront de plus en plus utilisĂ©s au sein de l’administration. Nous soulignerons notamment la nĂ©cessitĂ© - actuellement encore peu explorĂ©e - de garantir non seulement l’accĂšs au code source de ces algorithmes, mais aussi l’accĂšs aux bases de donnĂ©es qui les ont entraĂźnĂ©s, ainsi qu’aux critĂšres de sĂ©lection utilisĂ©s pour construire ces base d’apprentissage
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