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Accelerated Knowledge Discovery: A Vision for NASA ScienceThis paper introduces the sixth paradigm of scientific discovery: accelerated knowledge discovery (AKD). This paradigm is defined by the full integration of AI into the research workflow as a tool augmenting cognitive capabilities of human scientists. AKD emerges from the convergence of advanced AI models, autonomous agentic systems, and human-AI collaboration.

AKD accelerates the research cycle by reducing the time from conceptualization to discovery. It automates labor-intensive tasks such as literature review, hypothesis generation, experimental design, data analysis, modeling, simulation, and manuscript drafting. In well-defined domains, AKD can transform the scientific method into a continuously adaptive cycle, where outputs from each phase inform the next. These closed-loop scientific workflows shorten discovery timelines and reduce overhead. In addition to the scientific speed up, AKD targets an increase in the quality of research allowing for more systematic discovery of knowledge.

However, AKD's success depends on principled, trustworthy design. This requires a holistic approach that emphasizes explainability, reproducibility, robustness, adaptability, and transparency. Key requirements include alignment with open science principles, required human oversight, scientific accountability, and rigorous provenance tracking. Human researchers must remain ultimately responsible for scientific integrity, ethical reasoning, and interpretation, with AI serving as an augmentative partner.

Although the proposed approach applies to any domain focused on scientific discovery, this paper highlights AKD’s potential to advance NASA’s science mission, given the agency’s vast data assets, complex objectives, and interdisciplinary challenges. By integrating NASA’s data, foundation models, scalable computing, and knowledge frameworks, AKD can accelerate discovery and foster innovation across its scientific portfolio.
Document ID
20250011673
Acquisition Source
Marshall Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Rahul Ramachandran
(Marshall Space Flight Center Redstone Arsenal, United States)
Kaylin Bugbee
(Marshall Space Flight Center Redstone Arsenal, United States)
Juan Bernabe-Moreno
(IBM Research - Ireland Dublin, Ireland)
Date Acquired
December 22, 2025
Publication Date
January 5, 2026
Publication Information
Publication: Earth and Space Science
Publisher: Wiley
e-ISSN: 2333-5084
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Funding Number(s)
WBS: 182939.05.02.01.22
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
Single Expert
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