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

2022年底，随着ChatGPT的发布，生成式人工智能（GenAI）突然进入了大众的想象。ChatGPT是一种聊天代理，不仅非常受欢迎，而且标志着技术能力的重大飞跃。ChatGPT只是近年来出现的几种GenAI技术之一；其他人可以生成（或改变）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。迫切需要研究这些工具在创造性工作的特定背景下的影响，在创造性工作中，技术介导的工人不稳定性是一个持续但日益严重的问题。最近美国作家协会（Writers Guild of America）的工业行动表明，工人的抵制突显出，这种影响不仅仅是“取代”或获得工作的机会，还可能影响到既有作者身份的概念，同时也会影响到工人的自由裁量权和尊严。创意部门处于人工智能转型的风口浪尖，新兴技术可能在物质上（工资）和社会上（对贡献的认可）使劳动力贬值。我们对GenAI在创造性工作中的变革性影响的理解仍在兴起，但已经存在；那些生命和生计日益受到这些新技术威胁的人的经验和观点没有被适当地纳入人工智能政策规划和变革。我们需要的是使人们认识到这些观点能够影响数据驱动技术领域的劳工政策。为了实现这一目标，需要建立新的架构，以弥合经验和应用之间的鸿沟，并通过建立英国劳动法的力量来促进参与，类似斯堪的纳维亚参与式设计的历史先例，以及最近转向参与式算法影响评估。算法影响评估有望成为问责工具，它可以揭示数据驱动技术影响的核心问题，同时指出缓解这些问题的治理策略。如果影响评估的目的是突出受新兴技术影响的人们的声音，那么它们也可以作为框架，使反映技术介导的生活的实际经验的观点浮出表面并具体化，从而可以将其引导到政策指导中。在这个项目中，我们汇集了两种领先的相关影响评估方法：人工智能系统的人权、民主和法治保障框架（HUDERIA）和良好工作算法影响评估（GWAIA）。《全球工人尊严法》之所以被选为协调中心，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。我们将与HUDERIA的见解进行交叉参考，HUDERIA为个人与公共和私营技术生产商之间的关系构建问责制提供了具体的见解。这些工具共有的一个核心特征是参与式参与模式，即通过借鉴工人自己的经验、证词和想法，揭示、评估和减轻工人面临的个人和集体风险。

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.