With Student Interest Soaring, Berkeley Creates New Data-Sciences Division

The University of California at Berkeley today announced a new Division of Data Science and Information. It is the university’s largest program change in decades and helps secure its status among the country’s top data-science research and training hubs.

“The division will enable students and researchers to tackle not just the scientific challenges opened up by pervasive data, but the societal, economic, and environmental impacts as well,” the university said.

Berkeley is in an elite group with Carnegie Mellon University, MIT, Stanford, and the University of Washington in the caliber and scope of its data-science program, said Oren Etzioni, chief executive of the Allen Institute for Artificial Intelligence, a computer-science professor at the University of Washington, and a tech entrepreneur. In creating the new division, Berkeley is responding to two issues, Etzioni said. The first is a large, chronic shortage of well-trained data scientists. The second is what value a university can add when technical courses are widely available through platforms like Coursera and Udacity. In emphasizing interdisciplinary training among scientists, engineers, social scientists, and humanists, Berkeley firmly integrates data sciences into its prestigious academic offerings, he said.

Berkeley’s move follows MIT’s announcement last month that it was investing $1 billion in a new college of artificial intelligence. But leaders at Berkeley say their disclosure of the division today was driven by an imminent international search for a director, who will hold the title of associate provost, putting the program on an institutional par with Berkeley’s colleges and schools. They explain that in creating a division rather than a new college, they are reflecting the way data science has become woven into every discipline.

Berkeley has been planning the division for four years, said David Culler, interim dean for data sciences, and has been rolling it out incrementally through a new data-sciences major approved last year, and corresponding growth in data-science courses. Enrollment in “Foundations of Data Science” has soared from 100 in 2015 to 1,300 in 2018. Enrollment in the upper-level “Principles and Techniques of Data Science” has grown from 100 in 2016 to 800 students. The emerging program has served as a “pilot” for the division, which is now set to evolve under a new director.

Paul Alivisatos, Berkeley’s executive vice chancellor and provost, said that the university will not enroll more undergraduates because of the new division in itself. But undergraduate enrollment, which is 30,574, has been increasing already, and student demand for data sciences, he said, is “enormous,” with some 1,000 students already declaring their intent to major in it.

Alivisatos said there are 11 data-science-related faculty searches in the works — nearly one-quarter of Berkeley’s open searches — although those will include hires in sociology, public health, and other fields with strong data-science components. The data-science division, with ties to the College of Engineering, the College of Letters and Science, and the School of Information, has been in temporary quarters around campus, but Berkeley plans to build a new data-sciences building. On whether major gifts will be involved in that, Alivisatos said, “We are working in that space but not ready to make an announcement today.” He and Culler said it’s impossible to put a price on the division because it is tied into departments across campus, with myriad cross-appointments and collaborations.

The core of the data-science curriculum, said Culler, is computer science and statistics, with additional depth courses in optimization and visualization. But students will also be required to have a “domain emphasis” that would most likely synthesize material from various other departments. For instance, a data-science student’s exploration of social inequality might include courses in sociology, ethnic studies, economics, and philosophy.

The division’s planners say that data and algorithms are key to banks’ fraud detection and credit scoring; retailers’ supply chains; the health-care industry’s drug prescriptions and diagnoses; and remote sensing and imagery showing climate trends, poverty and migration patterns, and energy use. But such applications raise questions about the use of, say, facial-recognition technology, privacy concerns, and predictive policing, so ethics will be a crucial element of the new division.

The Rise of Data Science

Data science became high profile between 2010 and 2012, Culler said, with computer science, machine learning, and distributed systems (computers linked by networks) being increasingly integrated into business models and research across disciplines.

In tandem with that, Etzioni said, the last two decades have seen something like a thousandfold increase in processing power and speed. Accompanying that have been vast boosts in network and memory capacity. Moreover, within the last five years, deep-learning algorithms have “really exploded in their ability,” enabling functions like Apple’s Siri and Amazon’s Alexa.

All that has created an enormous demand for employees trained in data sciences and their applications to a vast range of other fields. Berkeley cites a Gallup poll for the Business-Higher Education Forum that showed “that by 2021, 69 percent of employers expect candidates with data science skills to get preference for jobs in their organizations, while only 23 percent of college and university leaders say their graduates will have those skills.”

But if tech companies compete for recent graduates, Etzioni said, they also compete for potential data-science faculty members. There is also, he said, a “friendly but real” competition for talent between the Bay Area and metropolitan Seattle.

Culler compares Berkeley’s data-science initiative to the university’s 1980s merging of 19 or 20 departments into a new biotech-driven Division of Biological Sciences.

“It is certainly,” he said, “a once in a generation change.”

Alexander C. Kafka is a Chronicle senior editor. Follow him on Twitter @AlexanderKafka, or email him at alexander.kafka@chronicle.com.