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Taking race into account when developing tools to predict a patient’s risk of colorectal cancer leads to more accurate predictions when compared with race-blind algorithms, researchers find.
While many medical researchers have argued that race should be removed as a factor from clinical algorithms that predict disease risks, a new study finds that, at least for colorectal cancer, including race can help correct a data issue – inaccurate recording of family history for Black patients.
The U.S. National Science Foundation (NSF) has awarded $12 million to a multi-institutional team of researchers that includes Cornell Tech Assistant Professor Udit Gupta for an initiative to establish new standards for carbon accounting in the computing industry.
In an examination of thousands of human-written college admissions essays and those generated by AI, researchers found that the AI-generated essays are most similar to essays authored by students who are males, with higher socioeconomic status and higher levels of social privilege.
Faculty and researchers invited to request time to run research projects on new AI tool
A multidisciplinary team aims to build a more inclusive AI shaped by global cultures and knowledge – one of three projects that make up Cornell’s new Global Grand Challenge: The Future.
Happening every Friday from 4-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans. Earlier this spring, New York State and six academic partners,...
A new program at Cornell will tackle critical environmental challenges by integrating advanced artificial intelligence (AI) tools with sustainability research across the campus, thanks to a grant from the National Science Foundation’s Research Traineeship Program.
“Cultural prompting” – asking an AI model to perform a task like someone from another part of the world – resulted in reduced bias in responses for the vast majority of the more than 100 countries tested by a Cornell-led research group.
