The expansive whiteness of the ice and snow at the Antarctic seems the same as more than a century ago when explorers first started traversing the continent. But scientists monitoring the continent have noticed rapid changes in the mass and reach of ice sheets, whose collapse can impact sea levels all over the world. Climate change has raised…

Machine learning technologies are increasingly being used to analyze complex, ambiguous situations such as the spread of diseases or financial markets, but some of these algorithms falter when they encounter new data, an altered environment, or have hidden biases that come to the surface.

In machine learning, the term “robustness”…

In the last quarter of this year, news organizations have been reporting that the United Kingdom is headed toward a recession, with economists saying that Brexit, the economic decoupling of the United Kingdom and the European Union, is a major factor.

The economic downturn has not been a surprise to many economists. In fact, in 2017,…

In recent years, scientists have noticed that conclusions in some published research that heavily use machine learning cannot be reproduced.

To uncover why this is happening, Sayash Kapoor, a computer science doctoral student affiliated with the Center for Information Technology Policy (CITP), and Arvind Narayanan, professor of computer science, a participating faculty member of the Center for Statistics and Machine Learning (CSML) and CITP associated faculty, published the paper, “Leakage and the Reproducibility Crisis in ML-based Science.”