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[2304.14347] The Dark Side of ChatGPT: Legal and Ethical Challenges from Stochastic Parrots and Hallucination
Summary
The article discusses the legal and ethical challenges posed by Large Language Models (LLMs) like ChatGPT, highlighting issues such as stochastic parrots and hallucination, and the need for evolving regulatory frameworks, particularly in the EU.
Why It Matters
As LLMs become integral to various sectors, understanding their potential risks is crucial for policymakers and developers. This article emphasizes the importance of adapting regulations to address the unique challenges posed by AI technologies, ensuring responsible use and public safety.
Key Takeaways
- LLMs like ChatGPT introduce significant legal and ethical risks.
- Stochastic parrots and hallucination are key challenges that need addressing.
- Current EU regulations may underestimate the risks associated with LLMs.
- The article calls for an evolution of regulatory frameworks to mitigate these risks.
- Awareness and proactive measures are essential for safe AI integration.
Computer Science > Computers and Society arXiv:2304.14347 (cs) [Submitted on 21 Apr 2023 (v1), last revised 24 Feb 2026 (this version, v2)] Title:The Dark Side of ChatGPT: Legal and Ethical Challenges from Stochastic Parrots and Hallucination Authors:Zihao Li View a PDF of the paper titled The Dark Side of ChatGPT: Legal and Ethical Challenges from Stochastic Parrots and Hallucination, by Zihao Li View PDF Abstract:With the launch of ChatGPT, Large Language Models (LLMs) are shaking up our whole society, rapidly altering the way we think, create and live. For instance, the GPT integration in Bing has altered our approach to online searching. While nascent LLMs have many advantages, new legal and ethical risks are also emerging, stemming in particular from stochastic parrots and hallucination. The EU is the first and foremost jurisdiction that has focused on the regulation of AI models. However, the risks posed by the new LLMs are likely to be underestimated by the emerging EU regulatory paradigm. Therefore, this correspondence warns that the European AI regulatory paradigm must evolve further to mitigate such risks. Comments: Subjects: Computers and Society (cs.CY); Computation and Language (cs.CL); Machine Learning (cs.LG) Cite as: arXiv:2304.14347 [cs.CY] (or arXiv:2304.14347v2 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2304.14347 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Nature Machine Intelligence 5 (2023) Related DOI: https...
