研究人員對大型語言模型 (LLM) 中的意識形態偏見表示擔憂

這些模型廣泛用於摘要和問答等任務，反映了其創建者的世界觀。根特大學的一項新研究表明，法學碩士如何根據語言、地區和培訓數據持有不同的意識形態立場。

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.

大型語言模型 (LLM) 是功能強大的工具，可用於從總結文本到回答問題等各種任務。然而，根特大學最近的一項研究表明，法學碩士也可能存在偏見，反映了其創建者的意識形態世界觀。

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.

該研究考察了英語和漢語法碩士回答中的意識形態差異。研究人員要求模型描述歷史人物，然後分析每個答案中的道德判斷。他們發現法學碩士根據語言和地理訓練的不同做出了不同的反應。這在西方和非西方方法論碩士如何處理全球衝突和政治人物的描述中顯而易見。

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 執行長 Paolo Ardoino 在最近的一篇文章中表達了對此問題的擔憂。他強調了使用者對人工智慧模式的控制的重要性，並對大型科技公司的影響力表示警惕，他說這些公司可能會被用來塑造大眾的思想。

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.

在盧加諾 Plan B 活動中，Ardoino 紹介紹了 Tether 的本地 AI 開發套件作為解決方案。該套件以隱私為重點，利用點對點（P2P）技術為大型技術控制的人工智慧模型提供替代方案。

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

我們需要控制我們執行和依賴的模型。

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

不要讓大型科技霸主強迫和控制我們的思想。

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

解決方案 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 具有高度模組化和適應性，允許開發人員在各種設備上使用它，從廉價手機到高級電腦。此開源套件支援不同的模型，例如 Marian 和 LLaMA，並允許用戶以 P2P 結構儲存資料以增強隱私。這種去中心化的方法提供了執行人工智慧應用程式的本地和私有方法。

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.

根特大學的研究也發現法學碩士處理歷史和政治事件的方式有差異。西方模型在描述中傾向於與西方意識形態保持一致，而非西方模型則以不同的方式處理這些主題，凸顯了敘事視角的分歧。這些發現強調了建構「中立」人工智慧系統的挑戰。

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 的去中心化人工智慧平台倡議符合科技業追求更大隱私的更廣泛趨勢。隨著 Tether 的本地人工智慧套件正在接受測試，它展示了一種由用戶控制的模組化人工智慧的新興途徑。這種方法可能會解決隱私問題，並減少對人工智慧需求的大型技術的依賴。

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