{"title":"协调人工智能系统中的创造力和伦理","authors":"Joffrey Baeyaert","doi":"10.1007/s43681-025-00766-w","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence is increasingly embedded in the creative industries—not only augmenting but originating cultural artefacts. Yet while generative systems expand access and productivity, they also raise complex ethical challenges around authorship, representation, transparency, and environmental cost. Generic AI-ethics frameworks built on fairness, accountability, transparency, and privacy remain too abstract to address the sector-specific tensions of AI-mediated creativity. This paper proposes the multi-dimensional ethics framework (MDEF), a normative and operational architecture that integrates five ethical dimensions—originality, cultural sensitivity, bias, transparency, and sustainability—across the creative pipeline. Drawing on interdisciplinary research, regulatory gaps, and real-world platform case studies, the MDEF embeds concrete instruments such as provenance pipelines, entropy-based bias audits, co-creation logs, carbon dashboards, and cultural veto protocols. It further introduces six quantitative metrics, including the cultural coverage index, transparency compliance index, and energy intensity score, each with calibrated governance thresholds for automated or human-in-the-loop intervention. The framework is designed for modular deployment, participatory oversight, and iterative refinement, ensuring adaptability across regulatory contexts and creative subfields. Pilots and prototypes already demonstrate feasibility, including increased trust through authenticity badging and reduced representational harm via participatory audits. In contrast to static principle-based codes, the MDEF offers a living, verifiable approach to aligning AI-driven creativity with moral rights, epistemic accountability, and cultural plurality.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 5","pages":"5191 - 5211"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Harmonizing creativity and ethics in AI systems\",\"authors\":\"Joffrey Baeyaert\",\"doi\":\"10.1007/s43681-025-00766-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence is increasingly embedded in the creative industries—not only augmenting but originating cultural artefacts. Yet while generative systems expand access and productivity, they also raise complex ethical challenges around authorship, representation, transparency, and environmental cost. Generic AI-ethics frameworks built on fairness, accountability, transparency, and privacy remain too abstract to address the sector-specific tensions of AI-mediated creativity. This paper proposes the multi-dimensional ethics framework (MDEF), a normative and operational architecture that integrates five ethical dimensions—originality, cultural sensitivity, bias, transparency, and sustainability—across the creative pipeline. Drawing on interdisciplinary research, regulatory gaps, and real-world platform case studies, the MDEF embeds concrete instruments such as provenance pipelines, entropy-based bias audits, co-creation logs, carbon dashboards, and cultural veto protocols. It further introduces six quantitative metrics, including the cultural coverage index, transparency compliance index, and energy intensity score, each with calibrated governance thresholds for automated or human-in-the-loop intervention. The framework is designed for modular deployment, participatory oversight, and iterative refinement, ensuring adaptability across regulatory contexts and creative subfields. Pilots and prototypes already demonstrate feasibility, including increased trust through authenticity badging and reduced representational harm via participatory audits. In contrast to static principle-based codes, the MDEF offers a living, verifiable approach to aligning AI-driven creativity with moral rights, epistemic accountability, and cultural plurality.</p></div>\",\"PeriodicalId\":72137,\"journal\":{\"name\":\"AI and ethics\",\"volume\":\"5 5\",\"pages\":\"5191 - 5211\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AI and ethics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s43681-025-00766-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AI and ethics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s43681-025-00766-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial intelligence is increasingly embedded in the creative industries—not only augmenting but originating cultural artefacts. Yet while generative systems expand access and productivity, they also raise complex ethical challenges around authorship, representation, transparency, and environmental cost. Generic AI-ethics frameworks built on fairness, accountability, transparency, and privacy remain too abstract to address the sector-specific tensions of AI-mediated creativity. This paper proposes the multi-dimensional ethics framework (MDEF), a normative and operational architecture that integrates five ethical dimensions—originality, cultural sensitivity, bias, transparency, and sustainability—across the creative pipeline. Drawing on interdisciplinary research, regulatory gaps, and real-world platform case studies, the MDEF embeds concrete instruments such as provenance pipelines, entropy-based bias audits, co-creation logs, carbon dashboards, and cultural veto protocols. It further introduces six quantitative metrics, including the cultural coverage index, transparency compliance index, and energy intensity score, each with calibrated governance thresholds for automated or human-in-the-loop intervention. The framework is designed for modular deployment, participatory oversight, and iterative refinement, ensuring adaptability across regulatory contexts and creative subfields. Pilots and prototypes already demonstrate feasibility, including increased trust through authenticity badging and reduced representational harm via participatory audits. In contrast to static principle-based codes, the MDEF offers a living, verifiable approach to aligning AI-driven creativity with moral rights, epistemic accountability, and cultural plurality.