The following profile is part of an ongoing CS News series that highlights the work of Cornell Computer Science faculty by sharing some details about their research initiatives and teaching practice. For this session, Assistant Professor Nika Haghtalab spoke with Leslie Morris for Ezra magazine.
NIKA HAGHTALAB: At Work Using Technology for Societal Good
How can we use technology to create a force for societal good? Nika Haghtalab, assistant professor of computer science, explores this question – in particular, how machine learning algorithms can actually encourage people to invest in better lives.
“Can we think about the technological assessment systems we are building as a way to encourage society to be healthier, individuals to become better citizens, students to become better learners?” she asks. “Our systems have a dual role and responsibility in both assessing and defining qualifications.”
Coming to Cornell after receiving her doctorate from Carnegie Mellon and nearly a year as a postdoctoral researcher at Microsoft Research, Haghtalab chose Ithaca and the Faculty of Computing and Information Science because it is a pioneer in understanding human interactions in computing.
“Cornell had a vision of information science and computer science faculty collaborating way before any other universities were putting their money and efforts into weaving these two fields together,” she says, noting that this encompasses her particular research interests.
Originally intrigued by how computer software could learn about people, Haghtalab was also drawn to machine learning by its interdisciplinary nature. “Machine learning draws from many fields – theory of computation, statistics, artificial intelligence,” she says.
Known as a leader in the field of “tech fairness” and ethics, Cornell CIS is a good fit for Haghtalab, whose postdoctoral research focused on fairness and diversity as they relate to recruiting candidates through machine learning.
“The right search criteria can be used to recruit more diverse candidates in college admission and hiring,” she says. “The criteria that are currently used in practice mirror society’s unconscious and historic biases. The system we propose uses machine learning to look in the space of all attributes and suggest alternative criteria that accept more diverse qualified candidates.
“This is cool because our system automatically suggests criteria for increasing diversity that in some cases lawmakers and consultants had to spend months looking at the data to figure out.”
“What I really value about Cornell,” she adds, “is how it advocates building a theory with practical applications in mind. I work on machine learning problems that are motivated by real life, but I build a theoretical foundation for understanding them with provable guarantees.”
– Leslie Morris
Read about other new Cornell faculty, including Wendy Ju, an assistant professor of Information Science at the Jacobs-Technion-Cornell Institute at Cornell Tech.