arxiv.org Thanks to their generative capabilities, large language models (LLMs) have become an invaluable tool for creative processes. These models have the capacity to produce hundreds and thousands of visual and textual outputs, offering abundant inspiration for creative endeavors. But … Continued
From the perspective of someone who feels like an impostor, the main takeaway of this model is: view yourself as learning. Your main job is to learn. That doesn’t necessarily mean studying in a classroom or from textbooks; often it … Continued
Media disagreements about science can blur distinctions between experts and non-experts, potentially eroding public trust in scientific claims. We explore how trust in scientific claims and experts is affected by the expertise and vested interests of dissenting voices, and scientific … Continued
Natural language is a vital source of evidence for the social sciences. Yet quantifying large volumes of text rigorously and precisely is extremely difficult, and automated methods have struggled to match the “gold standard” of human coding. The present work … Continued
The true potential of human-AI collaboration lies in exploiting the complementary capabilities of humans and AI to achieve a joint performance superior to that of the individual AI or human, i.e., to achieve complementary team performance (CTP). To realize this … Continued
The popularity and promise of mixed reality (MR) technologies, such as virtual (VR) and augmented (AR) reality, have advanced many applications focusing on training and skill development. If successfully deployed, these technologies could prove extremely valuable for high-impact professional training … Continued
This paper assesses the potential for the large language models (LLMs) GPT-4 and GPT-3.5 to aid in deriving insight from education feedback surveys. Exploration of LLM use cases in education has focused on teaching and learning, with less exploration of … Continued
As conversational agents powered by large language models become more human-like, users are starting to view them as companions rather than mere assistants. Our study explores how changes to a person’s mental model of an AI system affects their interaction … Continued
To effectively communicate and collaborate with others, we must monitor not only other people’s cognitive states (e.g., what someone thinks or believes), but also their metacognitive states (e.g., how confident they are in their beliefs). Confidence is however rarely communicated … Continued
Heightened AI expectations facilitate performance in human-AI interactions through placebo effects. While lowering expectations to control for placebo effects is advisable, overly negative expectations could induce nocebo effects. In a letter discrimination task, we informed participants that an AI would … Continued