In recent years, artificial intelligence (AI) and machine learning (ML) are
reshaping society's production methods and productivity, and also changing the
paradigm of scientific research. Among them, the AI language model represented
by ChatGPT has made great progress. Such large language models (LLMs) serve
people in the form of AI-generated content (AIGC) and are widely used in
consulting, healthcare, and education. However, it is difficult to guarantee
the authenticity and reliability of AIGC learning data. In addition, there are
also hidden dangers of privacy disclosure in distributed AI training. Moreover,
the content generated by LLMs is difficult to identify and trace, and it is
difficult to cross-platform mutual recognition. The above information security
issues in the coming era of AI powered by LLMs will be infinitely amplified and
affect everyone's life. Therefore, we consider empowering LLMs using blockchain
technology with superior security features to propose a vision for trusted AI.
This paper mainly introduces the motivation and technical route of blockchain
for LLM (BC4LLM), including reliable learning corpus, secure training process,
and identifiable generated content. Meanwhile, this paper also reviews the
potential applications and future challenges, especially in the frontier
communication networks field, including network resource allocation, dynamic
spectrum sharing, and semantic communication. Based on the above work combined
and the prospect of blockchain and LLMs, it is expected to help the early
realization of trusted AI and provide guidance for the academic community.

利用区块链技术赋能大型语言模型以构建可信赖的人工智能，主要包括可靠的学习语料库、安全的训练过程和可识别的生成内容，同时探讨了在通信网络领域的潜在应用和未来挑战。

BC4LLM：当区块链遇见大型语言模型时的可信人工智能

BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large  Language Models

ChatGPT is an AI language model developed by OpenAI that can understand and
generate human-like text. It can be used for a variety of use cases such as
language generation, question answering, text summarization, chatbot
development, language translation, sentiment analysis, content creation,
personalization, text completion, and storytelling. While ChatGPT has garnered
significant positive attention, it has also generated a sense of apprehension
and uncertainty in academic circles. There is concern that students may
leverage ChatGPT to complete take-home assignments and exams and obtain
favorable grades without genuinely acquiring knowledge. This paper adopts a
quantitative approach to demonstrate ChatGPT's high degree of unreliability in
answering a diverse range of questions pertaining to topics in undergraduate
computer science. Our analysis shows that students may risk self-sabotage by
blindly depending on ChatGPT to complete assignments and exams. We build upon
this analysis to provide constructive recommendations to both students and
instructors.

本文采用定量方法，展示 ChatGPT 在回答涉及本科计算机科学课程相关主题的不同类型的问题时高度不可靠，揭示学生盲目依赖 ChatGPT 完成作业和考试可能面临自我破坏。同时提出对学生和教师的建设性建议。