Missy Cummings gets recruited for jobs outside of academia a lot. But she always says no.
Cummings, a professor in the department of mechanical engineering and material science (aka robotics) at Duke University, has consulted for many autonomous drive programs for automakers and Silicon Valley companies, but she said it's better for everyone if she just stays where she is for her full-time gig.
"I've had many offers to leave academia, but I'm doing everyone a favor by staying in academia," she said. "I am very persnickety about data and evidence and I would drive these companies crazy."
As companies such as Google race to bring autonomous cars to market, the cultural divide between academic types and corporate types is surfacing publicly. Academics, known for taking long, methodical approaches to problems, appear to be uncomfortable with the pace at which Silicon Valley companies are pushing ahead with autonomous cars.
"The mindset of the Silicon Valley approach is to want to go fast, to be agile, to fail quickly," said Ryan Eustice, a University of Michigan robotics professor who was hired this year by the Toyota Research Institute in Ann Arbor, Mich., to work on autonomous vehicle research.
The different approaches have worked well until recently, when companies have entered the final stretch of producing autonomous cars for real consumers, rather than for testing and research. Solving the problems needed to create a successful end product may simply be less fun for big-name academics, who are accustomed to thinking big thoughts and running large-scale research projects. The issues now at hand -- such as refining how the cars drive -- can be worked on by basic systems engineers.
