Artificial Intelligence (AI) systems have historically been used as tools that execute narrowly defined tasks. Yet recent advances in AI have unlocked possibilities for a new class of models that genuinely collaborate with humans in complex reasoning, from conceptualizing problems … Continued
Using AI to create autonomous researchers has the potential to accelerate scientific discovery. A prerequisite for this vision is understanding how well an AI model can identify the underlying structure of a black-box system from its behavior. In this paper, … Continued
There is significant discussion about the opportunities and issues associated with the use of artificial intelligence in higher education. However, issues, such as academic integrity and privacy, continue to dominate the conversation. This has limited how well instructors and higher … Continued
AI writing assistants powered by Large Language Models (LLMs) are increasingly used to make autocomplete suggestions to people as they write text. Can these AI writing assistants impact people’s attitudes in this process? In two large-scale preregistered experiments (N=2,582), we … Continued
Providing personalized, detailed feedback at scale in large undergraduate STEM courses remains a persistent challenge. We present an empirically evaluated practice exam system that integrates AI generated feedback with targeted textbook references, deployed in a large introductory biology course. Our … Continued
This study critically distinguishes between AI Agents and Agentic AI, offering a structured conceptual taxonomy, application mapping, and challenge analysis to clarify their divergent design philosophies and capabilities. We begin by outlining the search strategy and foundational definitions, characterizing AI … Continued
Culturally Relevant Pedagogy (CRP) is vital in K-12 education, yet teachers struggle to implement CRP into practice due to time, training, and resource gaps. This study explores how Large Language Models (LLMs) can address these barriers by introducing CulturAIEd, an … Continued
Chain-of-thought (CoT) offers a potential boon for AI safety as it allows monitoring a model’s CoT to try to understand its intentions and reasoning processes. However, the effectiveness of such monitoring hinges on CoTs faithfully representing models’ actual reasoning processes. … Continued
Scientific knowledge creation is fundamentally transforming as humans and AI systems evolve beyond tool-user relationships into co-evolutionary epistemic partnerships. When AlphaFold revolutionized protein structure prediction, researchers described engaging with an epistemic partner that reshaped how they conceptualized fundamental relationships. This … Continued
Current AI evaluation paradigms that rely on static, model-only tests fail to capture harms that emerge through sustained human-AI interaction. As interactive AI systems, such as AI companions, proliferate in daily life, this mismatch between evaluation methods and real-world use … Continued