档案的综合性：一种基于现代人工智能的方法来构建全面共享的文化遗产
Comprehensiveness of Archives: A Modern AI-enabled Approach to Build Comprehensive Shared Cultural Heritage
摘要：
档案在社会的建设和进步中起着至关重要的作用。人类非常信任档案，并依赖它们来制定公共政策，保护语言、文化、自我认同、观点和价值观。然而，在目前的记录和档案分类和可追溯性进程中，有些声音和观点仍然难以捉摸。在本文中，我们探讨了集中的，正当程序的档案系统对边缘化社区的影响和后果。有强有力的证据证明，在追求全面、公平和公正的同时，需要进行渐进式设计和技术创新。当涉及到改进档案实践以及当今社会的进步和繁荣能力时，意向性和全面性是我们最大的机会。意向性和全面性是在技术和我们今天生活的信息时代的支持下实现的。在档案过程中重新开放，质疑和/或有目的地包括其他声音是我们在本文中提出的意图。我们提供了边缘化社区的例子，他们继续领导“社区档案”运动，努力恢复和保护他们的文化身份、知识、观点和未来。总之，我们提供了设计和人工智能主导的技术考虑因素，值得进一步研究，以弥合系统性差距并建立强大的归档流程。
英文摘要：
Archives play a crucial role in the construction and advancement of society. Humans place a great deal of trust in archives and depend on them to craft public policies and to preserve languages, cultures, self-identity, views and values. Yet, there are certain voices and viewpoints that remain elusive in the current processes deployed in the classification and discoverability of records and archives. In this paper, we explore the ramifications and effects of centralized, due process archival systems on marginalized communities. There is strong evidence to prove the need for progressive design and technological innovation while in the pursuit of comprehensiveness, equity and justice. Intentionality and comprehensiveness is our greatest opportunity when it comes to improving archival practices and for the advancement and thrive-ability of societies at large today. Intentionality and comprehensiveness is achievable with the support of technology and the Information Age we live in today. Reopening, questioning and/or purposefully including others voices in archival processes is the intention we present in our paper. We provide examples of marginalized communities who continue to lead "community archive" movements in efforts to reclaim and protect their cultural identity, knowledge, views and futures. In conclusion, we offer design and AI-dominant technological considerations worth further investigation in efforts to bridge systemic gaps and build robust archival processes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
