The special issue on “Machine Learning for Science and Society” showcases machine
learning work with influence on our current and future society. These papers address …

Machine-learning algorithms have become deeply embedded in contemporary society. As
such, ample attention has been paid to the contents, biases, and underlying assumptions of …

Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings
prior, in this report we outline the relevance of community engagement and infrastructure …

Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

MIT presents a concise primer on machine learning—computer programs that learn from
data and the basis of applications like voice recognition and driverless cars. No in-depth …

Much of current machine learning (ML) research has lost its connection to problems of
import to the larger world of science and society. From this perspective, there exist glaring …

As machine learning increasingly affects people and society, it is important that we strive for
a comprehensive and unified understanding of how and why unwanted consequences …

Three pitfalls to avoid in machine learning Skip to main content Thank you for visiting nature.com.
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We humans are curious animals. While other animals generally live in balance with their
respective ecosystems, we almost seem to go out of our way to tip that balance in our favor …

Machine learning is a field at the intersection of statistics and computer science that uses
algorithms to extract information and knowledge from data. Its applications increasingly find …