While the science underlying the still-nascent field of quantum information science (QIS) is well established, timelines for other key milestones in the development of QIS remain big question marks – with none bigger than the development of a QIS tech workforce that can meet increased demand for the technology in the coming years.
That was the message from Terrill Frantz, Professor of eBusiness and Cybersecurity at Harrisburg University of Science and Technology, who spoke about CIS workforce training at ATARC’s virtual Quantum Workforce Development Webinar on Oct. 27.
Comparing QIS development with the decades it took for “classical” computing to mature, Frantz said, “we are in the really early days with quantum … but we are reaching the point where we can turn some crazy ideas into reality.”
What points to a much faster maturity cycle for QIS versus classical computing, Frantz said, is all of the “serial” development that was required for the latter – including the laborious development of hardware and software. “In quantum, however … the hardware, the software, the workforce, even on the demand side of quantum computing and technologies … are all being developed in the same parallel,” he said.
Where the task of workforce development becomes more difficult, Frantz said, is “trying to be in the right place at the right time” with a workforce trained to create the kind of QIS services that the market demands. The problem, he said, is that specific market demands several years from now remain unclear – and by necessity so do workforce training strategies.
“Engineers are trying to get things developed as fast as possible … but when it comes to the workforce, we are trying to predict where the engineering will be five, eight, ten years from now,” he said. “And we are trying to figure out where the software algorithms will be” in fields that will demand QIS services, such as finance, and biology, Frantz added.
“We are trying to see where the demand is going to be,” Frantz said, while at the same time “we are trying to develop educational and training systems for a workforce that doesn’t exist.”
He said the QIS workforce is “mostly a PhD-level workforce now,” but in masters, undergraduate and high school levels “we are trying to develop an educational system for a workforce that we don’t even know what it needs to know.”
“The main thing that we don’t want to get wrong … is have a mismatch of supply and demand,” Frantz said. “If we train people too early … people will find other things to do.” And that uncertain timeline, he said, makes it difficult for universities to ramp up QIS programs with confidence.
Speaking at the same event, NIST Deputy Director Carl Williams said QIS workforce training is also being helped by private-sector companies that are creating internal projects to target their own QIS demands. Those include companies in the finance and airline industries, he said.
QIS tech training, he said, may also evolve to focus on specific applications rather than the underlying science “where optimization is the key piece.” Under that scenario, people “don’t have to fully understand what is going on in the back end … but they do have to understand that something special is going on there.”
“There are going to be layers” of understanding of QIS, Williams predicted. “You may not have to understand the quantum algorithms in order to use them.”