TY - JOUR
T1 - A Survey on ChatGPT
T2 - AI-Generated Contents, Challenges, and Solutions
AU - Wang, Yuntao
AU - Pan, Yanghe
AU - Yan, Miao
AU - Su, Zhou
AU - Luan, Tom H.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - AIGC
KW - ChatGPT
KW - and privacy
KW - generative AI
KW - security
UR - https://www.scopus.com/pages/publications/85168262902
U2 - 10.1109/OJCS.2023.3300321
DO - 10.1109/OJCS.2023.3300321
M3 - 文章
AN - SCOPUS:85168262902
SN - 2644-1268
VL - 4
SP - 280
EP - 302
JO - IEEE Open Journal of the Computer Society
JF - IEEE Open Journal of the Computer Society
ER -