Author: rwatkins

The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas Large Language Models (LLMs) have shown promise in accelerating the scientific research pipeline. A key capability for this process is the ability to generate novel research ideas, and prior studies have found settings in which LLM-generated research ideas were judged as more novel than […]

Background: Systematic and meta-analytic reviews provide gold-standard evidence but are static and outdate quickly. Here we provide performance data on a new software platform that uses artificial intelligence technologies to (1) accelerate screening of titles and abstracts from library literature searches, and (2) provide a software solution for enabling Living Systematic Reviews by maintaining a […]

Despite the wide application of message stimuli in communication experiments, creating effective stimuli is often challenging and costly. However, the advent of generative artificial intelligence (AI) and large language models (LLMs) suggests great potential to facilitate this process. To advance AI-assisted communication research, we examined the performance of ChatGPT (powered by GPT-4) in generating message […]

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 article introduces Cognitio Emergens (CE), a framework addressing critical limitations in existing models that focus […]

Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advancement of large language models affect the practice of science? For this opinion piece, we have invited four diverse groups of scientists to reflect on this query, sharing their […]

The rapid evolution of scientific inquiry highlights an urgent need for groundbreaking methodologies that transcend the limitations of traditional research. Conventional approaches, bogged down by manual processes and siloed expertise, struggle to keep pace with the demands of modern discovery. We envision an autonomous generalist scientist (AGS) system-a fusion of agentic AI and embodied robotics-that […]

Surveys are a widespread method for collecting data at scale, but their rigid structure often limits the depth of qualitative insights obtained. While interviews naturally yield richer responses, they are challenging to conduct across diverse locations and large participant pools. To partially bridge this gap, we investigate the potential of using LLM-based chatbots to support […]

Recent advancements have positioned AI, and particularly Large Language Models (LLMs), as transformative tools for scientific research, capable of addressing complex tasks that require reasoning, problem-solving, and decision-making. Their exceptional capabilities suggest their potential as scientific research assistants but also highlight the need for holistic, rigorous, and domain-specific evaluation to assess effectiveness in real-world scientific […]