Yejin emphasizes the importance of transparency in AI research, advocating for open access to knowledge graphs and norm repositories. She highlights the limitations of large language models, noting that while they accumulate vast knowledge, they often do so indirectly, leading to issues like hallucinations and a lack of common sense. The focus on direct learning objectives is crucial for developing reliable AI systems that reflect diverse norms and values.
