生成式人工智慧中的統計方法

摘要

生成式人工智慧正逐漸成為一項重要技術，有望在多個領域帶來變革性影響。然而，生成式AI技術基於從概率模型中採樣，預設情況下並不保證其正確性、安全性、公平性或其他屬性。統計方法為提升生成式AI技術的可靠性提供了一種具有潛力的途徑。此外，統計方法在提升AI評估的品質與效率，以及設計AI干預措施和實驗方面也展現出良好前景。本文回顧了這些主題上的現有研究，既闡述了所採用的通用統計技術，也探討了它們在生成式AI中的應用。同時，我們也討論了當前方法的局限性以及未來可能的研究方向。

English

Generative Artificial Intelligence is emerging as an important technology, promising to be transformative in many areas. At the same time, generative AI techniques are based on sampling from probabilistic models, and by default, they come with no guarantees about correctness, safety, fairness, or other properties. Statistical methods offer a promising potential approach to improve the reliability of generative AI techniques. In addition, statistical methods are also promising for improving the quality and efficiency of AI evaluation, as well as for designing interventions and experiments in AI. In this paper, we review some of the existing work on these topics, explaining both the general statistical techniques used, as well as their applications to generative AI. We also discuss limitations and potential future directions.

生成式人工智慧中的統計方法

Statistical Methods in Generative AI

摘要

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