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Doctoral Dissertation Research: Recovering the Polyvalent Genealogies of Machine Learning, 1948 - 2017

Machine learning techniques currently make "high-stakes" judgments in areas as diverse as criminal justice, credit risk, social welfare, hiring, and congressional redistricting. Such techniques make these decisions using patterns learned from historical social data. Emphasis on prediction rather than the circumstances of dataset creation have led to machine learning systems that preferentially target vulnerable populations for disparately adverse social judgments while making it more difficult for those subject to these decisions to protest unfair treatment.

Matthew L. Jones

James R. Barker Professor of Contemporary Civilization

The Freedom of Information Archive

The FOIArchive makes it possible to explore millions of declassified government records. The project aggregates collections that are currently scattered across virtual archives, extracts unique metadata, and makes all of it available through web-based interactive tools. This extension also will make these data and tools compatible with Columbia Library systems and software. Users worldwide will be able to get an aggregate view of entire archives, filter subsets of metadata, and see the specific words that produced a single data point.

The Emergence of Symbolic Notation and Data Visualization in Algebra and Chemistry

This award supports doctoral dissertation research in history of science that focuses on the use of mathematical and chemical symbolism. Such notation is currently regarded as essential to scientific work. By contrast, for much of Western European history, the use of symbols in science was not regarded as a suitable approach. However, by the nineteenth century, symbolic notation had become ubiquitous. This project's objective is to explain why European scientists came to see symbolic notation as credible during the early modern period.

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