Museum Visitor Experience and the Responsible Use of AI to Communicate Colonial Collections

博物馆和遗产机构（MHI）越来越多地使用机器学习、自然语言处理和机器视觉等人工智能工具来增强游客与其藏品的互动。人工智能的一个公认问题是偏见，包括人工智能算法如何重现倾斜的基础数据。面部识别AI在应用于有色人种时的不准确性是众所周知的例子。对于MHI来说，负责任地使用人工智能的挑战在于博物馆藏品中的潜在偏见，例如那些植根于殖民知识和权力的偏见，如何通过人工智能数据处理和输出来复制。当寻求公开交流他们的收藏的故事时，当使用殖民地收藏作为促进这一点的人工智能机制的“数据”时，MHI的“负责任的人工智能”可能是什么样子？负责任的人工智能可能带来哪些影响、挑战和机遇？该项目是与该项目的外部合作伙伴皇家军械库协商开发的。皇家军械库是英国国家收藏的武器和盔甲，也是世界上最古老的博物馆之一。博物馆对战争历史的关注形成了一个解释的背景，包括科学和技术，政治，法律，艺术和诗歌，以及更广泛的人类经验。这项合作与军械库正在进行的工作有关，这些工作与其藏品的殖民特征有关，并为游客提供数字化服务。该项目将与该合作伙伴和其他MHI利益相关者合作，以确保知识成果具有广泛的适用性。该项目的目标是：1）范围的背景和应用的地形：映射人工智能如何以及可以用于增强游客体验;考虑许多博物馆收藏中的殖民形式和基础数据的起源;了解参与者、利益相关者、利益，以及与使用人工智能交流殖民地博物馆收藏有关的权力关系。探索如何在环境和应用中定义负责任的人工智能：如何使用人工智能博物馆殖民地收藏的基础数据带来挑战和机遇;探索人工智能的使用如何在游客体验中重现但也使殖民形式的知识复杂化。与更广泛的MHI和行业利益相关者社区合作，评估现有的负责任人工智能方法是否可以用于或开发，以应对特定的挑战和机遇。与这些社区合作，在必要时开发和提出新的负责任的人工智能工具和实践，以帮助MHI使用人工智能。该项目将产生一个工具包，一份报告和一篇学术期刊文章（详见下文）。这项研究将使所有正在考虑利用人工智能来交流殖民地收藏品的MHI受益，并产生与更广泛的部门相关的知识成果，涉及如何在利用人工智能时导航收藏品和档案中的偏见。该项目将展示具体的知识成果，鼓励在博物馆环境中负责任地开发人工智能工具，帮助MHI解决藏品的特征和来源，并更有效地讲述他们的许多故事。

Museums and heritage institutions (MHIs) are increasingly using AI tools such as Machine Learning, Natural Language Processing, and Machine Vision to enhance visitor interaction with their collections. A well-established problem with AI is bias, including how AI algorithms reproduce skewed underlying data. The inaccuracy of facial recognition AI when applied to people of colour is well known example. For MHIs, a challenge for responsible AI use lies in how underlying biases in museum collections, such as those rooted in colonial knowledge and power, are reproduced through AI data processing and outputs. When seeking to publicly communicate stories of, from, and through their collections, and when using colonial collections as the 'data' for AI mechanisms that facilitate this, what might 'responsible AI' look like for MHIs? What might be the implications, challenges, and opportunities for responsible AI?The project has been developed in consultation with The Royal Armouries, the project's external partner. The Royal Armouries are the UK's national collection of arms and armour and one of the oldest museums in the world. The museum's focus on the history of war forms a backdrop for interpretations encompassing science and technology, politics, law, art and poetry, and the wider human experience. The collaboration connects to ongoing work The Armouries are undertaking that relates to the colonial character of their collections, and to transform their digital offering for visitors. The project will work with this partner and other MHI stakeholders to ensure knowledge outcomes have wide applicability.The project's objectives are to:1) Scope the terrain of the context and application: map how AI has and could be used to enhance visitor experience; consider the colonial form and origin of underlying data within many museum collections; generate understandings of the actors, stakeholders, interests, and power relations that are relevant to the use of AI to communicate colonial museum collections.2) Explore how responsible AI can be defined in the setting and application: how using underlying data from a museum's colonial collection in AI presents challenges and opportunities; explore how AI use might reproduce but also complicate colonial forms of knowledge within visitor experiences.3) Engage with a wider community of MHIs and industry stakeholders to assess whether existing approaches to responsible AI can be used or developed for the particular challenges and opportunities of the context and application.4) Work with these communities to develop and propose novel responsible AI tools and practices where necessary to assist MHI use of AI.The project will yield a Toolkit, a report, and an academic journal article (detailed below). The research will benefit all MHIs who are considering utilising AI to communicate colonial collections and also yield knowledge outcomes relevant to the broader sector regarding how to navigate bias within collections and archives when utilising AI. The project will present concrete knowledge outcomes encouraging responsible development of AI tools in a museum setting, helping MHIs address the character and origin of collections and more effectively tell their many stories.