标题： 一个共同的未来在数字社会中 显示英文标题

标题： Un avenir commun au sein de la société numérique

摘要： 如今，在机器的全球网络中，数据和信息已成为过量的资源，这些机器以接近光速的速度交换信号。 在这样一个高度饱和的环境中，通信已成为最核心的互动形式，得到了迅速发展的技术基础设施的支持。 这些新的通信工具创造出了信息的过度盈余，以至于没有人能够处理所有信息。 作为回应，Facebook、YouTube 和 Google 等平台使用算法来过滤和推荐内容。 这些算法充当排序机制，减少信息噪音，并向用户展示符合其习惯和偏好的内容。 然而，通过在用户和数据之间建立自己，这些平台获得了对用户所见内容的控制权，从而塑造了用户的偏好和行为。 从物理角度来看，我们可以说它们像信息系统中的选择性过滤器或控制闸门，引导信息流并形成反馈回路。 随着时间的推移，这可能导致一种信息惯性，用户越来越受到算法影响，失去独立判断的能力。 这一过程反映了 Bernard Stiegler 所描述的一种更广泛的趋势，即一种新型的无产阶级化，个体失去了被数字系统吸收和自动化的知识和技能。 借用物理学的概念，我们将此视为向更高熵的转变。 然而，Wikipedia 和 arXiv 等平台展示了数字工具如何在不导致认知退化的情况下支持集体知识。 受 Elinor Ostrom 关于公地的研究启发，我们提出了一种数字公地经济模型，其中信息被共同分享和管理，有助于恢复我们数字环境中熵与组织之间的平衡。 显示英文摘要

摘要： Today, data and information have become overabundant resources within a global network of machines that exchange signals at speeds approaching that of light. In this highly saturated environment, communication has emerged as the most central form of interaction, supported by a rapidly evolving technical infrastructure. These new communication tools have created an overwhelming surplus of information so much so that no human could process it all. In response, platforms like Facebook, YouTube, and Google use algorithms to filter and suggest content. These algorithms act as sorting mechanisms, reducing the informational noise and presenting users with content tailored to their habits and preferences. However, by placing themselves between users and data, these platforms gain control over what users see and, in doing so, shape their preferences and behaviors. In physical terms, we might say they function like selective filters or control gates in an information system directing flows and creating feedback loops. Over time, this can lead to a kind of informational inertia, where users become increasingly shaped by algorithmic influence and lose the ability to form independent judgments. This process reflects a broader trend that Bernard Stiegler describes as a new kind of proletarianization where individuals lose the knowledge and skills that are absorbed and automated by digital systems. Borrowing from physics, we study this as a shift toward higher entropy. However, platforms like Wikipedia and arXiv demonstrate how digital tools can support collective knowledge without leading to cognitive degradation. Inspired by Elinor Ostrom work on commons, we propose a model for a digital commons economy where information is shared and governed collaboratively, helping to restore a balance between entropy and organization in our digital environments.