Dr. Brian Nord
CASE associate, Department of Astronomy and Astrophysics
The University of Chicago
Through the combination of large experiments, big data sets, and powerful algorithms, we have an opportunity to imagine new avenues for improving scientific discovery. For example, artificial intelligence
(AI) has begun to have an impact on almost all fields of physics – on critical tasks like simulation, analysis, and even decision-making. In looking to the future, there is potential to use AI and related algorithms to further automate the full loop of the scientific method – from hypothesis generation to data acquisition and analysis. Closing the scientific loop creates opportunities for more efficient planning of experiments and exploration of new physics. However, this leaves us with multiple critical questions to address: how does this affect the role of scientists, who will have access to tools like this, how will we interpret the results of automated scientific pipelines?
Dr. Nord will discuss the potential of this approach in the context of recent work in cosmology and astronomy, showing progress and challenges in each major element of the scientific method as well as the roles and responsibilities of scientists in creating algorithmic tools that have implications and uses in society.