Thank you. I recommend reading this article to go a bit deeper into that reasoning. I think it's a really important one.

There’s a useful high-tech concept called the Technology Readiness Level that helps explain why Uber pounced when it did. NASA came up with this scale to gauge the maturity of a given field of applied science. At Level 1, an area of scientific inquiry is so new that nobody understands its basic principles. At Level 9, the related technology is so mature it’s ready to be used in commercial products. ‘‘Basically, 1 is like Newton figuring out the laws of gravity, and 9 is you’ve been launching rockets into space, constantly and reliably,’’ says Jeff Legault, the director of strategic business development at the National Robotics Engineering Center.

Today’s early-stage inquiry — so-called basic research, the Level 1 work, where scientists are still puzzling over fundamental questions — is financed almost exclusively by the federal government. It’s too far out, too speculative, to attract much investment; it isn’t clear if anyone will make any money on it. This wasn’t always the case. Decades ago, corporations were more willing to engage in Level 1, moonshot research. Bell Labs supported the work that led to the transistor when it was far from clear that there would be a market for it; Xerox supported research into the ‘‘windows’’ style of computing years before the market existed for such an interface. But in the last few decades, the vista of corporate R.& D. has shrunk as markets and executives have focused more on short-term profit, says Marc Kastner, an M.I.T. physicist. The far-off research questions have been left to university labs, though they struggle, too: The percentage of the federal budget devoted to basic research is about half of what it was in 1968.

These days, private industry gets involved mostly when a field of research has matured to the midpoint of the NASA scale. In the ’90s and early ’00s this happened to ‘‘machine learning,’’ the science of getting machines to recognize patterns. It had long been an academic concern. But once online firms like Google began grappling with ‘‘big data’’ — search-engine requests, social-network behavior, email — the field became suddenly lucrative, and Silicon Valley started frantically hiring experts away from Stanford.

I think the fact tax dollars are paying for all Level 1 research makes a pretty clear case tax payers should see an ROI.