"CREAATIF: Crafting Responsive Assessments of AI and Tech-Impacted Futures"

2022年末，随着聊天代理ChatGPT的发布，生成性人工智能(GenAI)突然进入了大众的想象。事实证明，ChatGPT不仅非常受欢迎，而且标志着技术能力的重大飞跃。ChatGPT只是近年来进入该领域的几种GenAI技术之一；其他技术可以生成(或更改)视频、图像、音乐、对话和计算机代码。这些发展有可能改变许多人的工作性质，包括以前被认为不受技术直接竞争影响的工人。迫切需要在创造性工作的特定背景下研究这些工具的影响，在创造性工作中，技术中介的工人早产是一个持续但日益尖锐的问题。美国作家工会最近的劳工行动就是工人抵抗的例证，这突显出其影响不仅仅是工作岗位被取代或获得，还可能冲击既定的作者身份观念，同时也影响到工人的自由裁量权和尊严。创意行业处于GenAI转型的聚集地，在这种转型中，新兴技术可能会使劳动力在物质上(工资)和社会上(对贡献的认可)贬值。我们对GenAI在创意工作中的变革性影响的理解仍在形成中，但存在；那些其生活和生计日益受到这些新技术威胁的人的经验和观点尚未适当地纳入人工智能政策规划和变化中。我们需要的是让这些观点进入人们的视野，使它们能够影响数据驱动技术领域的劳工政策。要实现这一点，需要构建新的架构，以弥合体验和应用之间的鸿沟，并通过建立在英国劳动法、斯堪的纳维亚参与式设计等可比历史先例以及最近转向参与式算法影响评估的基础上来促进参与。算法影响评估有望成为问责工具，可以表达对数据驱动技术影响的核心担忧，同时指向缓解这些担忧的治理战略。在影响评估的设计中，旨在突出受新兴技术影响的人的声音，它们也可以作为框架，用于浮出和具体化反映技术中介生活的生活经验的观点，这些经验反过来可以被引导到政策指导中。在这个项目中，我们将两种领先和相关的影响评估方法结合在一起：人工智能系统的人权、民主和法治保障框架(HUDERIA)，以及Good Work算法影响评估(GWAIA)。GWAIA之所以被选为一个协调中心，是因为它具体适用于工人尊严问题。它目前的设计与“传统”就业环境中的算法管理工具相关。我们将把这一点与HUDERIA的见解相互参照，HUDERIA的见解带来了关于构建个人与技术生产者(公共和私人)之间的责任结构的具体见解。这些工具共有的一个核心特征是参与式参与模式，即通过利用工人本身的经验、证词和想法来浮出水面、评估和减轻对工人的个人和集体风险。

Generative AI (GenAI) burst into the popular imagination in late 2022 with the release of ChatGPT - a chat agent that has proven not only to be very popular but also signifies a major leap forward in technological capabilities. ChatGPT is just one of several GenAI technologies that has entered the scene in recent years; others can generate (or alter) video, images, music, dialogue, and computer code. These developments have the potential to change the nature of work for many, including for workers previously deemed immune to direct competition from technology.There is urgency to studying the impact of these tools in the specific context of creative work, in which technologically-mediated worker precarity is an ongoing but increasingly acute concern. Worker resistance, as exemplified by recent industrial action by the Writers Guild of America, highlights that impacts go beyond 'displacement' of or access to work, and can impact established notions of authorship while also affecting worker discretion and dignity. The creative sector is at the coalface of the GenAI transformation in which emerging technologies potentially devalue labour materially (wages) and socially (recognition of contribution).Our understanding of the transformative effects of GenAI in creative work is still emerging but present; the experience and perspective of those whose lives and livelihoods are increasingly threatened by these new technologies have not been properly factored into AI policy planning and change. What is needed is to bring these perspectives into view where they can influence labour policy in the area of data-driven technologies. To achieve this requires the building of new architectures that bridge this divide between experience and application and which promote involvement by building on the strength of UK labour law, comparable historical precedents like Scandinavian participatory design, and recent turns toward participatory algorithmic impact assessments.Algorithmic impact assessments hold promise as accountability tools that can surface core concerns about the effects of data-driven technologies while pointing towards governance strategies for mitigating those concerns. Where impact assessments are designed to foreground the voices of people affected by emerging technologies, they can also serve as frameworks for surfacing and crystalising perspectives that reflect the lived experience of technology-mediated lives, which in turn can be channelled into policy guidance.In this project, we bring together two leading and relevant methods of impact assessment: the Human Rights, Democracy, and the Rule of Law Assurance Framework for AI Systems (HUDERIA), and the Good Work Algorithmic Impact Assessment (GWAIA). The GWAIA has been selected as a focal point because of its specific application to questions of worker dignity. Its current design is relevant to algorithmic management tools within a 'conventional' employment context. We will cross-reference this with insights from HUDERIA, which brings specific insights with regards to structuring accountability in the relationship between individuals and technology producers, public and private. A central feature these tools share is the participatory engagement model of surfacing, assessing, and mitigating individual and collective risks to workers by drawing on the experiences, testimony, and ideas of workers themselves.