Human Judgment
Human judgment, a cornerstone of cognitive science, is being rigorously investigated through its comparison with the outputs of increasingly sophisticated artificial intelligence models, particularly large language models (LLMs). Current research focuses on understanding and mitigating biases in human evaluations of AI-generated content, analyzing the alignment between human and AI judgments across diverse tasks (e.g., text generation, image captioning, question answering), and developing new metrics to better capture the nuances of human perception. These studies are crucial for improving the reliability and trustworthiness of AI systems and for fostering more effective human-AI collaboration in various fields.
Papers
Aligning a medium-size GPT model in English to a small closed domain in Spanish
Oscar R. Navarrete-Parra, Victor Uc-Cetina, Jorge Reyes-Magana
Humans in Humans Out: On GPT Converging Toward Common Sense in both Success and Failure
Philipp Koralus, Vincent Wang-Maścianica
A View From Somewhere: Human-Centric Face Representations
Jerone T. A. Andrews, Przemyslaw Joniak, Alice Xiang