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Astrobiology in the Time of Artificial IntelligenceThe Viking missions showcased multiple spaceflight technologies representing state-of-the-art capabilities: from digital line-scan imaging to the operation of complex onboard laboratories and software-controlled process autonomy. Since Viking, there have been extraordinary, and still accelerating, advancements in computing technology impacting science, society, and exploration. These developments have occurred in both hardware and software, resulting in increasingly capable devices, advanced programming tools, and algorithmic innovations. The subset of artificial intelligence known as machine learning has emerged as one of the most transformative of these developments, with major implications for space exploration and for improvements to the search for evidence of life beyond the Earth. Those improvements include the integration of data across different scales and increased sensitivity to complex features in data, as well as the generation of adaptive strategies for sampling environments. In this paper, the present and future nature of space exploration and astrobiological research is examined through the contextual lens of Viking, and through the history and possible future of artificial intelligence.
Document ID
20260005626
Acquisition Source
Ames Research Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Caleb Scharf ORCID
(Ames Research Center Mountain View, United States)
Date Acquired
June 22, 2026
Publication Date
June 20, 2026
Publication Information
Publication: Astrobiology
Publisher: SAGE Publishing (United States)
ISSN: 1531-1074
e-ISSN: 1557-8070
Subject Category
Exobiology
Cybernetics, Artificial Intelligence and Robotics
Funding Number(s)
WBS: 811073.02.55.01.40
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
External Peer Committee
Keywords
Viking
AI
machine learning
astrobiology
life detection
artificial intelligence
viking mission
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