Human Like
Research on "human-like" qualities in artificial intelligence focuses on developing models that exhibit behaviors and cognitive abilities resembling those of humans, aiming to improve AI's interaction with and understanding of humans. Current research emphasizes evaluating and enhancing aspects like reasoning, language understanding, and emotional intelligence in large language models (LLMs) and other AI architectures, often employing techniques like cognitive prompting, psychometric analysis, and imitation learning. This work is significant for advancing AI safety and trustworthiness, improving human-computer interaction, and providing novel tools for psychological and cognitive science research.
Papers
Large Language Models on the Chessboard: A Study on ChatGPT's Formal Language Comprehension and Complex Reasoning Skills
Mu-Tien Kuo, Chih-Chung Hsueh, Richard Tzong-Han Tsai
Large language models converge toward human-like concept organization
Mathias Lykke Gammelgaard, Jonathan Gabel Christiansen, Anders Søgaard