ChatGPT调查:人工智能生成的内容、挑战和解决方案

Yuntao Wang;Yanghe Pan;Miao Yan;Zhou Su;Tom H. Luan
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引用次数: 12

摘要

随着ChatGPT等大型人工智能(AI)模型的广泛使用,人工智能生成内容(AIGC)越来越受到关注,并正在引领内容创作和知识表达的范式转变。AIGC使用生成型大型人工智能算法,根据用户提供的提示,帮助或取代人类以更快的速度和更低的成本创建大规模、高质量、类似人类的内容。尽管AIGC最近取得了重大进展,但安全、隐私、道德和法律挑战仍需解决。本文对AIGC范式的工作原理、安全和隐私威胁、最先进的解决方案以及未来的挑战进行了深入调查。具体而言,我们首先探讨了AIGC的使能技术、通用架构,并讨论了其工作模式和关键特性。然后,我们研究了AIGC的安全和隐私威胁分类,并强调了GPT和AIGC技术的伦理和社会影响。此外,我们还回顾了关于AIGC模型及其生成内容的可调节AIGC范式的最先进的AIGC水印方法。最后,我们确定了与AIGC相关的未来挑战和开放的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on ChatGPT: AI–Generated Contents, Challenges, and Solutions
With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.
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CiteScore
12.60
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