In recent years, research involving human participants has been critical to advances in artificial intelligence (AI) and machine learning (ML), particularly in the areas of conversational, human-compatible, and cooperative AI. For example, around 12% and 6% of publications at recent … Continued
Abstract Leveraging a scientific infrastructure for exploring how students learn, we have developed cognitive and statistical models of skill acquisition and used them to understand fundamental similarities and differences across learners. Our primary question was why do some students learn … Continued
Research and application have used human-AI teaming (HAT) as a new paradigm to develop AI systems. HAT recognizes that AI will function as a teammate instead of simply a tool in collaboration with humans. Effective human-AI teams need to be … Continued
Many real-world tasks involve a mixed-initiative setup, wherein humans and AI systems collaboratively perform a task. While significant work has been conducted towards enabling humans to specify, through language, exactly how an agent should complete a task (i.e., low-level specification), … Continued
This study investigates the impact of ChatGPT — a generative AI-based tool — on undergraduate students’ software development experiences. Through a three-month project involving seven undergraduate students, ChatGPT was employed as a supporting tool, and their experiences were systematically surveyed … Continued
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