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

“CREAATIF：对人工智能和技术影响的未来进行响应式评估”

• 批准号: AH/Z505584/1
• 负责人: David Leslie
• 金额: $ 28.04万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=AH%2FZ505584%2F1
• 关键词: CREAATIF; Crafting; Responsive; Assessments; AI

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.

Generative AI（Genai）在2022年末发行了Chatgpt（Chatgpt）的聊天代理，这不仅是非常受欢迎的，而且还表示技术能力的重大飞跃。 Chatgpt只是近年来进入现场的几种Genai技术之一。其他人可以生成（或更改）视频，图像，音乐，对话和计算机代码。这些事态发展有可能改变许多人的工作性质，包括以前被认为是从技术中受到直接竞争的工人的影响。在创造性工作的特定背景下，紧迫地研究这些工具的影响，技术上介导的工人的卑鄙是一种持续但越来越严重的关注。美国作家协会最近的工业行动所举例说明了工人的抵抗力，强调了影响的影响超出了工作或获得工作的“流离失所”，并且可能影响既定的作者概念，同时也影响工人的酌处权和尊严。创意部门处于Genai转型的煤层中，其中新兴技术可能会贬值（工资）和社会（认识贡献）。这些新技术越来越受到生活和生计受到威胁的人的经验和观点尚未被适当地纳入AI政策计划和变革中。需要的是将这些观点带入观察它们可以在数据驱动技术领域影响劳动政策的地方。要实现这一目标，需要建立新的体系结构，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，可比较的历史先例，例如斯堪的纳维亚参与性设计，而促进参与的参与式算法影响评估。对核心影响评估作为核心对核心的责任心构成对这些策略的责任感，这些工具对这些策略进行了对数据的影响。 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良好的工作算法影响评估（GWAIA）。 GWAIA因其在工人尊严问题上的特定应用而被选为焦点。它的当前设计与“常规”就业环境中的算法管理工具有关。我们将与Huderia的见解交叉引用，该见解为个人与技术生产者，公共和私人关系之间的关系带来了特定的见解。这些工具共享的主要功能是通过借鉴工人本身的经验，证词和思想来表面表面，评估和减轻个人和集体风险的参与式参与模型。