  In recent years, machine learning (ML) methods have remarkably improved how
cosmologists can interpret data. The next decade will bring new opportunities
for data-driven cosmological discovery, but will also present new challenges
for adopting ML methodologies and understanding the results. ML could transform
our field, but this transformation will require the astronomy community to both
foster and promote interdisciplinary research endeavors.
