ARPHA Conference Abstracts :
Conference Abstract
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Corresponding author: Michael Steven Phillips (michael.phillips@jhuapl.edu)
Received: 19 Jun 2023 | Published: 17 Oct 2023
© 2023 Michael Phillips
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Phillips MS (2023) Using AI to Fine Tune the Search for Life. ARPHA Conference Abstracts 6: e108253. https://doi.org/10.3897/aca.6.e108253
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Astrobiologists seek to find life beyond Earth. The “Holy Grail” of Astrobiology research is to discover evidence of a second genesis of life – an origin of life that was independent from life’s origin on Earth. No formal consensus on the possibility for a second genesis of life exists, and opinions about the probability range from near zero to near unity. An extra-terrestrial example of life would help answer this question and settle the quandary of whether life is common in the Universe or exceedingly rare. Quantifying the “ordinariness” of life has far reaching philosophical implications that could even inform us about the future of intelligent, technology-wielding life on Earth (
Life on Mars, one of our closest planetary neighbors, was considered a forgone conclusion as recently as the mid 20th century. What else besides an advanced civilization cultivating crops could have been responsible for the telescopically observed network of “canals” scarring its red surface? The “Advanced Martian Civilization” hypothesis had support from preeminent scientists, such as Giovanni Schiaparelli and Percival Lowell, but was relegated to the realm of pseudoscience when data from the Mariner spacecrafts in the 1970s failed to reveal any evidence for such civilizations. There is still no convincing evidence for life on Mars; however, several studies have at least raised one or two eyebrows (
The Mariner missions ushered in the era of modern space exploration at Mars, and with it an earnest search for life. In 1976, shortly after the Mariner missions, the Viking I & II landers delivered “positive” results from their Labeled Release (LR) experiments. Oxidants in the martian regolith are the generally accepted explanation for these results, but some argue that life is the most parsimonious explanation for the Viking data (
The problems we face in the search for life on Mars today mirror those that confronted Schiaparelli and Lowell: we do not have data of sufficient quality to answer the question definitively. One major difference is that Schiaparelli and Lowell had their prior probability for the expectation of life on Mars set at what must have been a fairly high value. By contrast, decades of null results for evidence of life on Mars have tuned our expectations such that all abiogenic explanations for any piece of would-be-evidence-for-life must be rigorously rejected before biotic explanations can be considered (e.g.,
NASA developed a strategic exploration arc to hone in on the most likely places to find evidence of life on Mars. The strategy goes:
The “Follow the water” theme characterized missions from Mars Global Surveyor in 1996 to the Mars Atmospheric and Volatile EvolutioN orbiter in 2013. “Explore habitability” and “Seek signs of life” have overlapped, beginning in 2007 with the Phoenix lander and persisting to the present with the Perseverance rover at the Jezero Crater delta.
Despite technological and philosophical advances in Astrobiology and the overarching principles guiding NASA missions, a coherent and standard strategy for quantifying the probability of finding life in an arbitrarily chosen environment does not exist. For example, when we land in a deltaic system on Mars we do not know, and in fact do not have a strategy for knowing, which specific outcrop, or rocks within in an outcrop, will have the highest probability of containing signs of past life. What would such a “signs of life search strategy” look like?
In our recent paper (
Astrobiology; Artificial Intelligence
Michael Phillips
ISEB-ISSM 2023
The Johns Hopkins University Applied Physics Laboratory