We present EKILA; a decentralized framework that enables creatives to receive recognition and reward for their contributions to generative AI (GenAI). EKILA proposes a robust visual attribution technique and combines this with an emerging content provenance standard (C2PA) to address the problem of synthetic image provenance -- determining the generative model and training data responsible for an AI-generated image. Furthermore, EKILA extends the non-fungible token (NFT) ecosystem to introduce a tokenized representation for rights, enabling a triangular relationship between the asset's Ownership, Rights, and Attribution (ORA). Leveraging the ORA relationship enables creators to express agency over training consent and, through our attribution model, to receive apportioned credit, including royalty payments for the use of their assets in GenAI.

翻译：我们提出EKILA——一个去中心化框架，使创作者能够因其对生成式人工智能（GenAI）的贡献而获得认可与奖励。EKILA提出了一种鲁棒的视觉归属技术，并将其与新兴的内容溯源标准（C2PA）相结合，以解决合成图像溯源问题——即确定生成某AI图像的模型及训练数据来源。此外，EKILA扩展了非同质化代币（NFT）生态，引入了一种代币化权利表示，从而建立了资产所有权、使用权与归属（ORA）之间的三角关系。通过利用ORA关系，创作者能够对训练许可行使自主权，并借助我们的归属模型获得按比例分配的权益，包括因其资产在GenAI中被使用而获得的版税支付。