Director’s Blog Post 1

By | Director's Blog

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MIDAS Challenge Award lead Dr. Stephanie Teasley and collaborator Dr. Kelly discuss learning analytics, higher education and employment

By | News, Research

Based on an NSF-funded workshop, Drs. Teasley (School of Information) and Kelly discuss learning analytics goals and research priorities for the coming decade.  They report on a research agenda that would strengthen the connection between learning analytics and recognition of learner competencies. This could have a transformative impact on the relationship between higher education and employment.  The agenda will also generate significant new research questions leading to insights about learning and the data science techniques for analyzing learning.

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A MIDAS Challenge Award team, led by Stuart Soroka (Communication and Media & Political Science), works with CNN on a Sentiment Analysis about the 2020 election candidates

By | News, Research

A MIDAS Challenge Award team, led by Stuart Soroka, professor of Communication and Media & Political Science, works with CNN on a Sentiment Analysis of recalled news about the candidates for the U.S. 2020 election. The analysis shows Net Sentiment for all respondents, then each of the Democratic, Independent and Republican respondents.

Data scientists and artists team up to demonstrate “fair representation”

By | News, Research

Depictions of people in museum visual arts collections often reflect the histories of inclusion and exclusion. For example, museum collections in the 1920s likely reflect much less the lives of African Americans than those in the 1960s. U-M Museum of Art’s (UMMA) entire collection of ~24,000 pieces of artwork, spanning 150 years, has been digitized.  A group of data scientists and artists will apply algorithms to recognize faces and to examine how art collections can (mis)represent humanity and how that representation changes with time.  

The project team includes: 

This project, funded by the U-M Arts Initiative, is the result of months of discussion about how data science and arts can give each other a stronger voice to promote social justice.

The issue of fair and unbiased representation looms large as Big Data and Artificial Intelligence (AI) are impacting many aspects of our society, from political messaging to targeted marketing, from parole granting to hiring practices.   With biased data, algorithms will reach superficially compelling but ultimately false conclusions and amplify the biases and the injustices that exist in the data.  This project will illustrate this point by generating a collection of composite representations of human faces from the UMMA dataset, and presenting these representations through an art installation, interactive digital displays and narratives.  Through this new way to communicate research that is understandable, meaningful, and impactful to the public, this project highlights the caveats that lie beneath Big Data and AI applications and inspire the public to participate in shaping our transition into a data-driven society.

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MIDAS Challenge Award team collaborates with CNN and provides polling expertise

By | News, Research

Drs. Josh Pasek (LSA Communication and Media), Michael Traugott (LSA Political Science), Ceren Budak (School of Information) and Stuart Soroka (LSA Communication and Media), along with their Georgetown colleagues, have been collaborating with CNN to improve survey questions and carry out data analysis.  This work is partly an extension of the Challenge Award project that MIDAS has funded.  Read more: