Shared Post-Human Imagination: Human-AI Collaboration in Media Creation

共享的后人类想象力：媒体创作中的人机协作

• 批准号: AH/Z50564X/1
• 负责人: Szilvia Ruszev
• 金额: $ 24.54万
• 依托单位: Bournemouth University
• 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%2FZ50564X%2F1
• 关键词: Shared; Post; Human; Imagination; AI

The rapid advancements in AI and ML have revolutionized the media landscape, opening new possibilities for content creation. Generative AI tools (GAIT) for creation and manipulation of text, image and sound such as ChatGPT or Midjourney became accessible for everyone and hold the promise of changing the ways in which media production can be effective and creative. However, these technological breakthroughs have also come with moral, ethical and legal challenges and risks that need to be addressed. Concerns regarding copyright and job security have been amplifying, as the recent strikes in Hollywood show. A rising number of publications and position papers in the UK and internationally strive to address the challenges and risks offered by GAIT. While the public discourse around AI fluctuates between the extremes of enthusiasm and dystopia, questions about bias, transparency, accountability, safety, justice and trustworthiness need to be addressed in their complexity.The proposed research aims to investigate responsible AI(RAI) in the context of media production, focusing on collaboration, creativity and representation. The research outputs seek to foster feedback loops among developers, users and policymakers in order to develop RAI practices. In detail:While AI is not yet on-par with human capabilities, we use AI algorithms as tools. Yet, it is productive to reflect on the implications of a human-AI collaboration in the context of RAI. In other words, we will ask questions such as: Who has access to and who has control over GAIT? Also, how can we create feedback loops to progress not only human media creation processes but the underlying dynamic AI system?Similarly, the notion of creativity has to be re-evaluated in the context of RAI. Questions of extractive database practices, copyright, intellectual property and the displacement of human labour are in the foreground. Yet, technologically aided serendipity offers new creative possibilities.And finally, based on existing studies, we are increasingly aware of the ingrained bias in large databases used to train GAIT. Our research aims to understand how these biases materialise through the use of GAIT. Furthermore, by applying the knowledge and methodologies of media studies research, we will propose ways in which socio-cultural complexities can be productively addressed avoiding the (re)production of stereotypical representations of social categories such as race, class, gender, etc.In order to address these research aims, we will apply a hybrid, practice-theory methodology. In four workshops, we will simulate the process of media production (script-writing, image generation, audio/music generation and post-production), experiment with significant GAIT and subsequently reflect on our experience within the context of our research questions.Research outputs will be:A report with information, analysis and recommendations for best practices of the use of GAIT in media creation in the context of RAI.A draft sci-fi short film created using GAIT reflecting on the research questions. (full version to be completed outside the research time).The outputs will be presented in a closing event to a group of media creators, policy makers and developers to foster dialogue and concrete actions.

AI和ML的快速发展彻底改变了媒体格局，为内容创作开辟了新的可能性。用于创建和操纵文本、图像和声音的生成人工智能工具（GAIT），如ChatGPT或Midjourney，变得人人都可以使用，并有望改变媒体制作的有效性和创造性。然而，这些技术突破也带来了道德、伦理和法律的挑战和风险，需要加以解决。正如最近好莱坞的罢工所显示的那样，对版权和就业保障的担忧一直在加剧。越来越多的出版物和立场文件在英国和国际上努力解决GAIT带来的挑战和风险。虽然围绕人工智能的公众话语在热情和反乌托邦的极端之间波动，但有关偏见，透明度，问责制，安全性，正义和可信度的问题需要在其复杂性中得到解决。拟议的研究旨在调查负责任的人工智能（RAI）在媒体制作的背景下，专注于协作，创造力和代表性。研究成果旨在促进开发者、用户和决策者之间的反馈循环，以制定RAI做法。虽然人工智能还不能与人类的能力相提并论，但我们使用人工智能算法作为工具。然而，在RAI的背景下反思人类与AI合作的影响是富有成效的。换句话说，我们会问这样的问题：谁可以访问GAIT，谁可以控制GAIT？此外，我们如何创建反馈循环，不仅促进人类媒体创作过程，而且促进底层动态AI系统的发展？同样，在RAI的背景下，创造力的概念必须重新评估。采掘数据库做法、版权、知识产权和取代人力劳动的问题处于突出地位。最后，基于现有的研究，我们越来越意识到用于训练GAIT的大型数据库中根深蒂固的偏见。我们的研究旨在了解这些偏见如何通过使用GAIT实现。此外，通过运用媒体研究的知识和方法，我们将提出如何有效地解决社会文化的复杂性，避免（重新）生产的社会类别，如种族，阶级，性别等的刻板印象，为了解决这些研究目标，我们将采用混合，实践理论方法。在四个工作坊中，我们将模拟媒体制作的过程（脚本编写，图像生成，音频/音乐生成和后期制作），实验显著的GAIT，并随后在我们的研究问题的背景下反思我们的经验。研究成果将是：一份报告，其中包含在RAI背景下使用GAIT进行媒体创作的最佳实践的信息，分析和建议。(full将在一次闭幕活动中向媒体创作者、决策者和开发者介绍成果，以促进对话和具体行动。