解决生成式人工智能产出的多手问题:归功框架

Donal Khosrowi, Finola Finn, Elinor Clark
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摘要

最近的一波生成式人工智能(GenAI)系统,如Stable Diffusion或ChatGPT,可以从人类提示中生成图像、文本和代码,引发了关于创作、原创性、创造力和版权的争议性问题。这篇论文的重点是创造者:谁在GenAI的帮助下创造了产出,谁应该被归功于他?目前围绕这些问题存在着重大的道德、法律和监管不确定性。我们开发了一个新的框架,称为CCC(以集体为中心的创造),它有助于解决这种不确定性。根据CCC的说法,GenAI的产出首先是由集体创造的。对创造者的主张有不同程度,并取决于所涉及的各种代理人和实体,包括用户、GenAI系统、开发人员、培训数据生产者和其他人所作的个人贡献的性质和意义。我们展示了CCC如何帮助解决围绕负责任的GenAI技术开发和部署的一系列持续争议,并帮助更准确地将功劳归于应有的地方。
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Engaging the many-hands problem of generative-AI outputs: a framework for attributing credit

The recent wave of generative AI (GenAI) systems like Stable Diffusion or ChatGPT that can produce images, text and code from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GenAI? There is currently significant moral, legal and regulatory uncertainty around these questions. We develop a novel framework, called CCC (collective-centered creation), that helps resolve this uncertainty. According to CCC, GenAI outputs are created by collectives in the first instance. Claims to creatorship come in degrees and depend on the nature and significance of individual contributions made by the various agents and entities involved, including users, GenAI systems, developers, producers of training data and others. We demonstrate how CCC can help navigate a range of ongoing controversies around the responsible development and deployment of GenAI technologies and help more accurately attribute credit where it is due.

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