Vox Populi, Vox ChatGPT: Large Language Models, Education and Democracy
- URL: http://arxiv.org/abs/2311.06207v1
- Date: Fri, 10 Nov 2023 17:47:46 GMT
- Title: Vox Populi, Vox ChatGPT: Large Language Models, Education and Democracy
- Authors: Niina Zuber and Jan Gogoll
- Abstract summary: This paper explores the potential transformative impact of large language models (LLMs) on democratic societies.
The discussion emphasizes the essence of authorship, rooted in the unique human capacity for reason.
We advocate for an emphasis on education as a means to mitigate risks.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: In the era of generative AI and specifically large language models (LLMs),
exemplified by ChatGPT, the intersection of artificial intelligence and human
reasoning has become a focal point of global attention. Unlike conventional
search engines, LLMs go beyond mere information retrieval, entering into the
realm of discourse culture. Its outputs mimic well-considered, independent
opinions or statements of facts, presenting a pretense of wisdom. This paper
explores the potential transformative impact of LLMs on democratic societies.
It delves into the concerns regarding the difficulty in distinguishing
ChatGPT-generated texts from human output. The discussion emphasizes the
essence of authorship, rooted in the unique human capacity for reason - a
quality indispensable for democratic discourse and successful collaboration
within free societies. Highlighting the potential threats to democracy, this
paper presents three arguments: the Substitution argument, the Authenticity
argument, and the Facts argument. These arguments highlight the potential risks
that are associated with an overreliance on LLMs. The central thesis posits
that widespread deployment of LLMs may adversely affect the fabric of a
democracy if not comprehended and addressed proactively and properly. In
proposing a solution, we advocate for an emphasis on education as a means to
mitigate risks. We suggest cultivating thinking skills in children, fostering
coherent thought formulation, and distinguishing between machine-generated
output and genuine, i.e. human, reasoning. The focus should be on responsible
development and usage of LLMs, with the goal of augmenting human capacities in
thinking, deliberating and decision-making rather than substituting them.
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