Why do we do astrophysics?

TL;DR

This paper discusses the evolving role of large language models in astrophysics, examining their implications, benefits, and policy considerations, emphasizing the importance of balanced approaches to AI integration in scientific research.

Contribution

It provides a comprehensive analysis of the philosophical, practical, and policy issues surrounding AI use in astrophysics, advocating for moderate, well-considered policies.

Findings

LLMs can assist in designing and executing astrophysical research.

Potential benefits include scientific advancement, educational growth, and societal impact.

Risks involve policy challenges and ethical considerations.

Abstract

At time of writing, large language models (LLMs) are beginning to obtain the ability to design, execute, write up, and referee scientific projects on the data-science side of astrophysics. What implications does this have for our profession? In this white paper, I list - and argue for - a set of facts or "points of agreement" about what astrophysics is, or should be; these include considerations of novelty, people-centrism, trust, and (the lack of) clinical value. I then list and discuss every possible benefit that astrophysics can be seen as bringing to us, and to science, and to universities, and to the world; these include considerations of love, weaponry, and personal (and personnel) development. I conclude with a discussion of two possible (extreme and bad) policy recommendations related to the use of LLMs in astrophysics, dubbed "let-them-cook" and "ban-and-punish." I argue strongly against both of these; it is not going to be easy to develop or adopt good moderate policies.