Development and AI-Assisted Validation of the Human-AI Symbiotic Theory (HAIST)
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Authors
Chick, John
Morello, Laura
Issue Date
2026-04-17
Type
Other
Language
en_US
Keywords
Artificial intelligence , Researchers , Human - Artificial Intelligence Research
Alternative Title
Abstract
The integration of artificial intelligence into academic research represents a profound paradigm shift, yet current approaches too often treat AI as either a mere tool or a threat to academic agency. While more than 75% of researchers report regular interaction with AI systems (NSF, 2024), fewer than 30% feel adequately prepared for meaningful human-AI partnership—and no comprehensive theoretical framework previously existed to guide this collaboration. This study has two interconnected aims: Propose the Human-AI Symbiotic Theory (HAIST), the first comprehensive framework designed to guide authentic human-AI collaboration in scholarly research, synthesizing five theoretical domains into seven actionable principles. Demonstrate an innovative AI-assisted validation protocol integrating traditional expert assessment with large language model evaluation for scalable, rigorous theory validation.
Research Questions:
RQ1: What theoretical principles should guide effective, ethical human-AI collaboration in academic research?
RQ2: How can traditional and AI-based evaluation methods be integrated to validate the rigor and utility of a comprehensive framework for human-AI research symbiosis?
Description
UB Rise 2026
College of Engineering, Business, and Education