ChatGPT 说 "不":ChatGPT 推出后 Twitter 讨论中的代理、信任和指责

Dan Heaton, Elena Nichele, Jeremie Clos, Joel E. Fischer
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摘要

ChatGPT是使用GPT-n系列大型语言模型的聊天机器人,它提供对话、帮助和娱乐功能,受到了广泛的欢迎。这引发了人们对其机构的质疑,以及由此对信任和指责的影响,尤其是在Twitter等社交媒体平台上对其的描述。理解信任和指责对于衡量公众对ChatGPT等人工智能驱动工具的看法、依赖和采用至关重要。为了探索ChatGPT作为算法社会行动者的感知地位,并通过代理和及物性揭示信任和指责的含义,我们使用语料库语言学和批评话语分析,以社会行动者代表为基础,研究了在2022年11月至2023年3月的“炒作期”发布的关于ChatGPT的88,058条推文。值得注意的是,ChatGPT在推特中有87%的情况下是作为社会行动者出现的,使用个性化和代理隐喻来强调其在内容创作、信息传播和影响力方面的作用。然而,动态呈现,在创造性社会行动者和信息源之间摇摆,反映了用户对其能力的不确定性,因此,责备归因发生了。在13%的情况下,ChatGPT是通过背景和排除被动呈现的。在这里,ChatGPT在通知和影响方面的作用强调了交互者对它的信息依赖,这对信息传播和对人工智能生成内容的信任产生了影响。因此,本研究有助于理解决策算法的感知社会代理及其对信任和指责的影响,这对人工智能开发者和政策制定者来说很有价值,对于理解和处理当今人工智能时代的权力动态具有重要意义。
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“ChatGPT says no”: agency, trust, and blame in Twitter discourses after the launch of ChatGPT

ChatGPT, a chatbot using the GPT-n series large language model, has surged in popularity by providing conversation, assistance, and entertainment. This has raised questions about its agency and resulting implications on trust and blame, particularly when concerning its portrayal on social media platforms like Twitter. Understanding trust and blame is crucial for gauging public perception, reliance on, and adoption of AI-driven tools like ChatGPT. To explore ChatGPT’s perceived status as an algorithmic social actor and uncover implications for trust and blame through agency and transitivity, we examined 88,058 tweets about ChatGPT, published in a ‘hype period’ between November 2022 and March 2023, using Corpus Linguistics and Critical Discourse Analysis, underpinned by Social Actor Representation. Notably, ChatGPT was presented in tweets as a social actor on 87% of occasions, using personalisation and agency metaphor to emphasise its role in content creation, information dissemination, and influence. However, a dynamic presentation, oscillating between a creative social actor and an information source, reflected users’ uncertainty regarding its capabilities and, thus, blame attribution occurred. On 13% of occasions, ChatGPT was presented passively through backgrounding and exclusion. Here, the emphasis on ChatGPT’s role in informing and influencing underscores interactors’ reliance on it for information, bearing implications for information dissemination and trust in AI-generated content. Therefore, this study contributes to understanding the perceived social agency of decision-making algorithms and their implications on trust and blame, valuable to AI developers and policymakers and relevant in comprehending and dealing with power dynamics in today’s age of AI.

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