Analyzing human language for social good

Can the use of language on social media reveal information about a patient’s mental health? Can human language, with all its ambiguities and complexities, be analyzed to identify behavioral issues? And what’s the boundary, ethically, of tapping into language sources? In this episode, Dr. Gordon Moore speaks with Philip Resnik, PhD, Professor of Linguistics at the University of Maryland, about the intersection of machine learning, natural language processing and mental health. Dr. Resnik details the work he and other researchers are doing to research human language connections by building a secure cloud enclave of language data where scientists are granted access, allowing them to collaborate and work at a scale that, until now, has been unimaginable.  
 
"What's really important is to recognize that the goal is not to have fully automated technology, the goal is to get the job done in the right way... A lot of the time, the right way to do that is to have an effective combination of what the machine can do and what people can do."
— Philip Resnik, PhD

Resources

NORC at the University of Chicago

Fairness, Accountability, and Transparency in Machine Learning

Podcast Episode Transcript