分析生成式AI在内容创作中的技术表现与伦理风险
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation
- 对比GPT-4o、DALL-E 3在创意、多样性、准确率上的表现
- 发现模型输出常携带训练数据偏见，存在伪造与滥用风险
- 提出行业可用的伦理规范，助力技术负责任落地
GPT-4o和DALL-E 3等生成式AI正重塑数字内容创作，为各行业提供高效且富有创意的文本与图像生成工具。本文探究这些模型在创意流程中的能力与挑战。尽管其在创造性、多样性、准确性及计算效率方面表现优异，但仍引发显著伦理问题，尤其涉及偏见、真实性及潜在滥用。通过一系列结构化实验，我们评估了模型的技术性能与输出的伦理影响，揭示其虽提升创作效率，却常反映训练数据中的偏见，并存在伦理漏洞，亟需审慎监管。研究提出一套伦理指南，旨在推动生成式AI在产业实践中实现创新与伦理平衡。
原文摘要 · Abstract (English)
Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering industries tools to generate diverse and sophisticated text and images with remarkable creativity and efficiency. This paper examines both the capabilities and challenges of these models within creative workflows. While they deliver high performance in generating content with creativity, diversity, and technical precision, they also raise significant ethical concerns. Our study addresses two key research questions: (a) how these models perform in terms of creativity, diversity, accuracy, and computational efficiency, and (b) the ethical risks they present, particularly concerning bias, authenticity, and potential misuse. Through a structured series of experiments, we analyze their technical performance and assess the ethical implications of their outputs, revealing that although generative models enhance creative processes, they often reflect biases from their training data and carry ethical vulnerabilities that require careful oversight. This research proposes ethical guidelines to support responsible AI integration into industry practices, fostering a balance between innovation and ethical integrity.
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