Data Science Lecture: Is Machine Learning Good or Bad for Science?

In this distinguished lecture hosted by the Research Network Data Science @ Uni Vienna, our guest speaker David W. Hogg from ‪@newyorkuniversity‬ explores the different possible roles for machine learning in science using some examples from his own field of astrophysics. He discusses the various roles that machine learning can play in science and examines the epistemological and ontological implications of using this approach. He also considers the effects on measurement precision and understanding. The talk offers insight into the ways in which machine learning is being applied in the field of science and the potential consequences of its use.
David W. Hogg is an astrophysicist and a leader of the Astronomical Data Group at the Flatiron Institute in New York. His research has covered a wide range of topics in astrophysics, including galaxy formation, the Milky Way's stellar dynamics, and exoplanet discovery. He has also worked on instrument calibration, data analysis, and statistical inference in his research. Hogg is a developer of open-source software and an advocate for open data initiatives.
This lecture was recorded on 7 July 2022 @ Urania Rooftop Hall
Find out more information about this lecture:
👉 datascience.un...
Find out more about the research network Data Science @ Uni Vienna:
👉 datascience.un...