The focus of the study is new approaches toward the search for intelligent life elsewhere in the Universe. Such a discovery would have profound scientific, cultural and societal impact. In the era of the rapid advances in exoplanet studies, including searches for biomarkers, and the exponential growth of data, the time is right to revisit this challenge using a fresh, data-driven approach that would minimize the existing anthropocentric and cultural biases as much as possible.
We will explore the possible paths for a systematic exploration of observable parameter spaces derived from the modern sky surveys, using machine learning and other computational tools. To this effect, we will address specific methods to conduct objective and unbiased searches for sources or signals that would appear anomalous in some well-defined way, and investigate the possible ways of separating those of possible artificial origins from the natural, albeit rare physical phenomena.
The outcome of this study would be an evaluation of the possible technical approaches to this problem that can be applied on the existing and forthcoming data sets and streams from large sky surveys, and the recommendations for the observing strategies that may increase the chances of the success. These can be used as a basis for the larger proposals for the future studies.
As an added benefit, this study would also sharpen our methodology to look for the rare and/or as yet unknown natural phenomena that may be hidden in these vast data sets.