Nima Mesgarani’s Team Will Use Data Science to Solve Societal Problems
The Data Science Institute (DSI) awarded Seeds Fund Grants to five research teams whose proposed projects will use state-of-the-art data science to solve seemingly intractable societal problems in the fields of cancer research, medical science, transportation and technology.
Each team will receive up to $100,000 for one year and be eligible for a second year of funding.
“In awarding these grants, the DSI review committee selected projects that brought together teams of scholars who aspire to push the state-of-the-art in data science by conducting novel, ethical and socially beneficial research,” said Jeannette M.Wing, Avanessians Director of the Data Science Institute. “The five winning teams combine data-science experts with domain experts who’ll work together to transform several fields throughout the university.”
The inaugural DSI Seeds Fund Program supports collaborations between faculty members and researchers from various disciplines, departments and schools throughout Columbia University. DSI received several excellent proposals from faculty, which shows a growing and enthusiastic interest in data-science research at Columbia, added Wing.
The seed program is just one of many initiatives that Wing has spearheaded since the summer of 2017, when she was named director of DSI, a world-leading institution in field of data science. The other initiatives include founding a Post-doctoral Fellows Program; a Faculty Recruiting Program; and an Undergraduate Research Program.
What follows is a brief description of Prof. Mesgarani’s winning project.
p(true): Distilling Truth by Community Rating of Claims on the Web
The team: Nikolaus Kriegeskorte, Professor, Psychology and Director of Cognitive Imaging, Zuckerman’s Institute; Chris Wiggins, Associate Professor, Department of Applied Physics and Applied Mathematics, Columbia Engineering; Nima Mesgarani, Assistant Professor, Electrical Engineering Department, Columbia Engineering; Trenton Jerde, Lecturer, Applied Analytics Program, School of Professional Studies.
The social web is driven by feedback mechanisms, or “likes,” which emotionalize the sharing culture and may contribute to the formation of echo chambers and political polarization, according to this team. In their p(true) project, the team will thus build a complementary mechanism for web-based sharing of reasoned judgments, so as to bring rationality to the social web.
Websites such as Wikipedia and Stack Overflow are surprisingly successful at providing a reliable representation of uncontroversial textbook knowledge, the team says. But the web doesn’t work well in distilling the probability of contentious claims. The question the team seeks to answer is this: How can the web best be used to enable people to share their judgments and work together to find the truth?
The web gives users amazing power to communicate and collaborate, but users have yet to learn how to use that power to distill the truth, the team says. Web users can access content, share it with others, and give instant feedback on claims. But those actions end up boosting certain claims while blocking others, which amounts to a powerful mechanism of amplification and filtering. If the web is to help people think well together, then the mechanism that determines what information is amplified, the team maintains, should be based on rational judgment, rather than emotional responses as communicated by “likes” and other emoticons.
The team’s goal is to build a website, called p(true), that enables people to rate and discuss claims (e.g., a New York Times headline) on the web. The team’s method will enable the community to debunk falsehoods and lend support to solid claims. It’s also a way to share reasoned judgments, pose questions to the community and start conversations.
Original article can be found here.