As artificial intelligence (AI) advances, human-AI collaboration has become increasingly prevalent across both professional and everyday settings. In such collaboration, AI can express its confidence level about its performance, serving as a crucial indicator for humans to evaluate AI’s suggestions. … Continued
In this paper, we introduce the novel concept of pedagogically aligned Large Language Models (LLMs) that signifies a transformative shift in the application of LLMs within educational contexts. Rather than providing direct responses to user queries, pedagogically-aligned LLMs function as … Continued
Humans have the remarkable ability to learn new categories from few examples, but how few examples can we actually learn from? Recent studies suggest it may be possible to learn more novel concepts than the number of examples. Previous approaches … Continued
2023-10-25-JMP-Draft.pdf drive.google.com Abstract: In an era of rapid technological and social change, do universities adapt enough to play their important role in creating knowledge? To examine university adaptation, I extracted the information contained in the course catalogs of over 450 … Continued
Autoregressive language models, which use deep learning to produce human-like texts, have surged in prevalence. Despite advances in these models, concerns arise about their equity across diverse populations. While AI fairness is discussed widely, metrics to measure equity in dialogue … Continued
Complementing human decision-making with AI advice offers substantial advantages. However, humans do not always trust AI advice appropriately and are overly sensitive to incidental AI errors, even in cases with overall good performance. Today’s research still needs to uncover the … Continued
Exposure to large language model output is rapidly increasing. How will seeing AI-generated ideas affect human ideas? We conducted an experiment (800+ participants, 40+ countries) where participants viewed creative ideas that were from ChatGPT or prior experimental participants and then … Continued
Generative artificial intelligence (AI) is poised to reshape the way individuals communicate and interact. While this form of AI has the potential to efficiently make numerous human decisions, there is limited understanding of how individuals respond to its use in … Continued
We propose that individuals mistakenly interpret their success in predicting an event as an indication that they understand the underlying mechanism or process. In four experiments, we demonstrate this prediction-comprehension bias (PCB) and identify three factors that contribute to it: … Continued
osf.io We address the question of how humans select between multiple goals in a temporally-extended context. We probed whether humans engage in the prospec- tive evaluation of goals by estimating which goals are likely to yield future success and choosing … Continued