Creating a Dynamic Archive of Responsible Ecosystems in the Context of Creative AI

在创造性人工智能应用程序的背景下，确定利益相关者并划定生态系统的边界尤其具有挑战性，因为这些应用程序的用户，包括艺术家、公共机构、地方当局或国家机构，通常不参与它们的开发。然而，确定边界和利益相关者很重要，因为如果边界划得太窄或太宽，适用不同的RAI考虑因素；划出狭窄的边界可能会将相关利益攸关方排除在这些生态系统之外。绘制边界可能会导致RAI变得过于复杂而无法应用或识别。该项目的一个关键目标是建立一个动态档案的结构，可以用来在创造性人工智能的背景下识别这些生态系统中的利益相关者。一个平行的目标是使用存档的数据来突出每个项目中需要解决的RAI考虑因素，并比较这些人工智能生态系统的边界。这将产生对如何更好地理解人工智能生态系统本身的责任的更深层次的洞察。该项目将通过使用在特定研究项目中已经收集的自下而上的证据，为在创造性人工智能的背景下绘制RAI生态系统图奠定基础。我们将人工智能生态系统解读为相互关联的生态系统，由不同的个体行为者和群体以复杂的方式相互作用，并与人工智能应用程序相互作用。当这些生态系统密切关注RAI UK研究确定的责任挑战时，它们就是负责任的人工智能生态系统。该项目将分为两个阶段：1)严格分析Digiscore(https://digiscore.github.io/pages/aboutus/Creative)和CAT Royale(https://www.blasttheory.co.uk/projects/cat-royale)，前者使用人工智能为残疾音乐家创作音乐，后者使用人工智能与宠物互动；2)对至少5个额外项目进行不那么深入的分析。由此将产生新的和创新的见解，即什么可能真正构成负责任的创造性人工智能，它的特征和特点，它的限制和风险。例如，我们的分析将涉及审查创造力、真实性和责任概念之间产生的伦理和道德紧张，并将探索与此背景相关的不同类型的责任，例如道德、法律、角色或美德。创造性人工智能提供了一种扩展和丰富基于人类的创造力的方式，其中人工智能成为一个良性的合作者，使人类能够打破既定实践的限制。从这个角度来看，人工智能的数据管理员成为人工智能生态系统中的关键创造性角色。这个项目将提供一个范围研究，在这个竞争激烈和紧急的领域，什么可能构成负责任的人工智能实践。这一特定背景很重要，因为创意产业在经济和社会上都很重要，而创意本身是由一系列伦理和认识论因素支撑的，这些因素直接影响到任何负责任的人工智能概念：我们不能简单地引入为银行或金融服务等其他部门创造的责任方法。或许同样重要的是，要做到这一点，时间已经不多了：斯坦福大学最近的一项研究发现，所有行业的领先人工智能模型中，没有一家接近于符合欧盟人工智能法案草案。

Identifying stakeholders and delineating boundaries of ecosystems is especially challenging in the context of Creative AI applications as users of these applications including artists, the public, local authorities or national institutions, do not typically participate in their development. However, defining boundaries and stakeholders is important because different RAI considerations apply if the boundaries are drawn narrowly or widely; drawing narrow boundaries risks excluding relevant stakeholders from these ecosystems. Drawing boundaries widely risks any considerations of RAI becoming too complex to apply or identify. A key objective of this project is to develop the structure of a dynamic archive that can be used to identify the stakeholders in these ecosystems in the context of Creative AI. A parallel objective is to use the archived data to highlight the RAI considerations that need to be addressed in each project and to compare the boundaries of these AI ecosystems. This will generate deeper insight into how responsibility within AI ecosystems itself can be better understood.This project will lay the foundation work for mapping RAI ecosystems in the context of Creative AI by using bottom-up evidence already collected in specific research projects. We interpret AI ecosystems as interlinked ecosystems consisting of different individual actors and groups interacting in complex ways with one another and with AI applications. These ecosystems are Responsible AI Ecosystems when they pay close attention to responsibility challenges as identified by RAI UK research. The project will have two stages: 1) a rigorous analysis of Digiscore (https://digiscore.github.io/pages/aboutus/Creative) which uses AI to create music for disabled musicians and CAT Royale (https://www.blasttheory.co.uk/projects/cat-royale) which uses AI to interact with pet animals and 2) a less intensive analysis of at least 5 additional projects. From this will emerge new and innovative insight into what might actually constitute responsible creative AI, its characteristics and features, its limitations and risks. For example, our analysis will involve examining the ethical and moral tension arising between the concepts of creativity, authenticity and responsibility, and will explore the different types of responsibility e.g. moral, legal, role or virtue attaching to this context.Creative AI offers a way of extending and enriching human-based creativity, where AI becomes a benign collaborator enabling humans to break the constraints of established practice. From this perspective, the data curator for the AI becomes a key creative role within the AI ecosystem. This project will provide a scoping study of what might constitute responsible AI practice in this highly contested and emergent area. This specific context is important because creative industries are important economically and societally while creativity itself is underpinned by a range of ethical and epistemological considerations which impinge directly on any notion of responsible AI: we cannot simply import approaches to responsibility created for other sectors such as banking or financial services. Perhaps equally importantly, time is running out to get this right: a recent study by Stanford University found that none of the leading AI models in all sectors came close to being compliant with the draft European Union AI Act.