研究人员对大型语言模型 (LLM) 中的意识形态偏见表示担忧

这些模型广泛用于摘要和问答等任务，反映了其创建者的世界观。根特大学的一项新研究表明，法学硕士如何根据语言、地区和培训数据持有不同的意识形态立场。

Large language models (LLMs) are powerful tools that can be used for a wide variety of tasks, from summarizing text to answering questions. However, a recent study from Ghent University has shown that LLMs can also be biased, reflecting the ideological worldviews of their creators.

大型语言模型 (LLM) 是功能强大的工具，可用于从总结文本到回答问题等各种任务。然而，根特大学最近的一项研究表明，法学硕士也可能存在偏见，反映了其创建者的意识形态世界观。

The study examined ideological differences in LLM responses in English and Chinese. The researchers asked the models to describe historical figures, and then analyzed the moral judgments in each response. They found that LLMs responded differently based on language and geographic training. This was evident in how Western and non-Western LLMs handled descriptions of global conflicts and political figures.

该研究考察了英语和汉语法学硕士回答中的意识形态差异。研究人员要求模型描述历史人物，然后分析每个回答中的道德判断。他们发现法学硕士根据语言和地理培训的不同做出了不同的反应。这在西方和非西方法学硕士如何处理全球冲突和政治人物的描述中显而易见。

Paolo Ardoino, CEO of Tether, raised concerns about this issue in a recent post. He highlighted the importance of user control over AI models, and expressed wariness about the influence of large tech companies, which he said could be used to shape public thoughts.

Tether 首席执行官 Paolo Ardoino 在最近的一篇文章中表达了对此问题的担忧。他强调了用户对人工智能模型的控制的重要性，并对大型科技公司的影响力表示警惕，他说这些公司可能会被用来塑造公众的想法。

At the Lugano Plan B event, Ardoinoを紹介ed Tether’s Local AI development kit as a solution. The privacy-focused kit utilizes peer-to-peer (P2P) technology to offer an alternative to big tech-controlled AI models.

在卢加诺 Plan B 活动中，Ardoino 绍介绍了 Tether 的本地 AI 开发套件作为解决方案。该套件以隐私为重点，利用点对点（P2P）技术为大型技术控制的人工智能模型提供替代方案。

We need to control the models we execute and rely on.

我们需要控制我们执行和依赖的模型。

And not let big tech overlords to force and control our thoughts.

不要让大型科技霸主强迫和控制我们的思想。

A solution https://t.co/1MyRIUXwit

解决方案 https://t.co/1MyRIUXwit

The Tether AI SDK is highly modular and adaptable, allowing developers to use it across various devices, ranging from budget phones to advanced computers. The open-source kit supports different models, such as Marian and LLaMA, and enables users to store data in P2P structures for enhanced privacy. This decentralized approach provides a local and private method of executing AI applications.

Tether AI SDK 具有高度模块化和适应性，允许开发人员在各种设备上使用它，从廉价手机到高级计算机。该开源套件支持不同的模型，例如 Marian 和 LLaMA，并允许用户以 P2P 结构存储数据以增强隐私。这种去中心化的方法提供了执行人工智能应用程序的本地和私有方法。

The Ghent University study also found differences in how LLMs addressed historical and political events. Western models tended to align with Western ideologies in their descriptions, while non-Western models approached these topics differently, highlighting a divide in narrative perspectives. These findings underscore the challenges in constructing "neutral" AI systems.

根特大学的研究还发现法学硕士处理历史和政治事件的方式存在差异。西方模型在描述中倾向于与西方意识形态保持一致，而非西方模型则以不同的方式处理这些主题，凸显了叙事视角的分歧。这些发现强调了构建“中立”人工智能系统的挑战。

Ardoino’s initiative for a decentralized AI platform aligns with a broader trend in the tech industry toward greater privacy. As Tether’s Local AI kit is being tested, it showcases an emerging avenue for modular AI that is controlled by the user. This approach could potentially address privacy concerns and reduce dependence on big tech for AI needs.

Ardoino 的去中心化人工智能平台倡议符合科技行业追求更大隐私的更广泛趋势。随着 Tether 的本地人工智能套件正在接受测试，它展示了一种由用户控制的模块化人工智能的新兴途径。这种方法可能会解决隐私问题，并减少对人工智能需求的大型技术的依赖。

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