论文标题
研究对准研究：无监督分析
Researching Alignment Research: Unsupervised Analysis
论文作者
论文摘要
AI一致性研究是致力于确保人工智能（AI）受益于人类的研究领域。随着机器智能的提高，这项研究变得越来越重要。该领域的研究人员在不同媒体上共享想法，以加快信息交换。但是，这种关注速度意味着研究格局不透明，使年轻的研究人员很难进入该领域。在这个项目中，我们收集并分析了现有的AI对齐研究。我们发现该领域正在迅速增长，并平行出现了几个子场。我们查看了子场，并确定了著名的研究人员，反复出现的主题以及各种沟通方式。此外，我们发现，经过AI对齐研究文章培训的分类器可以检测到我们最初不包含数据集中的相关文章。我们正在与研究社区共享数据集，并希望将来开发工具，以帮助成熟的研究人员和年轻研究人员更多地参与该领域。
AI alignment research is the field of study dedicated to ensuring that artificial intelligence (AI) benefits humans. As machine intelligence gets more advanced, this research is becoming increasingly important. Researchers in the field share ideas across different media to speed up the exchange of information. However, this focus on speed means that the research landscape is opaque, making it difficult for young researchers to enter the field. In this project, we collected and analyzed existing AI alignment research. We found that the field is growing quickly, with several subfields emerging in parallel. We looked at the subfields and identified the prominent researchers, recurring topics, and different modes of communication in each. Furthermore, we found that a classifier trained on AI alignment research articles can detect relevant articles that we did not originally include in the dataset. We are sharing the dataset with the research community and hope to develop tools in the future that will help both established researchers and young researchers get more involved in the field.
