The Promise of Data Science for the Technosignatures Field

TL;DR

This paper discusses how recent advances in computer science, especially machine learning and deep learning, can significantly enhance the search for extraterrestrial technosignatures, supported by case studies and future prospects.

Contribution

It highlights the potential of integrating modern AI techniques into technosignatures research and presents case studies demonstrating successful implementation.

Findings

Successful application of machine learning in large research programs

Potential for unprecedented growth in technosignatures searches

Data from all-sky observations can be effectively analyzed using AI

Abstract

This paper outlines some of the possible advancements for the technosignatures searches using the new methods currently rapidly developing in computer science, such as machine learning and deep learning. It also showcases a couple of case studies of large research programs where such methods have been already successfully implemented with notable results. We consider that the availability of data from all sky, all the time observations paired with the latest developments in computational capabilities and algorithms currently used in artificial intelligence, including automation, will spur an unprecedented development of the technosignatures search efforts.