Because I style myself as “consultant in technology-based economic development,” I’m often asked my opinion on this or that development in the “tech” world. Sometimes I can answer, but sometimes not, because “tech” is not what I’m primarily about. To me, the word “technology” means the full range of practical arts enabled by advanced scientific knowledge and engineering skill. When I use the word, I’m pretty certain I mean something different from what the general public and the media now mean by “tech.”1

Back in the dot-com boom, the public and the investment community began using the word “technology” as a shortcut for what was really just “information technology,” and “technology” soon shortened further to just “tech.” Actually, in Silicon Valley, “tech” seems to have a broader meaning than here, because there it encompasses not just the big Web successes like eBay, Facebook and Yahoo, but also a broad range of firms that actually manufacture materials, systems, and devices based on a wide array of modern technologies (think Intel, Cisco, or even Tesla Motors). But here in the Big Apple, because our local venture capitalists have rightly perceived that our economy’s comparative advantage lies in those technologies that hold potential to “disrupt” our world-beating advertising, media, financial, and fashion sectors, “tech” has come to mean largely “soft” technology: Web 2.0, social media, and now, above all, mobile apps. In a word, software.

All this raises some points I’ve wanted to make about New York City mayor Michael Bloomberg’s “applied sciences” initiative, which I’ll write up in a subsequent blog post some time before he leaves office, but I before I do, I need to clear some linguistic underbrush. As a long-ago undergraduate historian of science, I have a stake in clarity.2

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  1. Of course: “You keep using that word. I do not think it means what you think it means.” []
  2. Oh, and that headline for this post is a kludge/joke: apparently you can’t put HTML character codes like ≠ into WordPress headlines, so I borrowed the “bang-equals” symbol from software coding which requires no special characters. []

The National Research Council has made available a pre-print of the forthcoming report of its Committee on The Mathematical Sciences in 2025, chaired by Caltech EE/applied physics professor Thomas Everhart. Like all NRC publications, it’s a long and dense document, but the summary remains fully accessible to the general reader. Though it makes all the usual pleas for funding of basic research without undue hope for immediate practical application, the report also starkly underlines what should now be obvious connections between mathematical knowledge and rapidly accumulating advances in a wide array of other disciplines and real-world applications. Even within mathematics itself, the report argues, boundaries between sub-disciplines are breaking down, and mathematicians who would formerly have seemed past their prime years of creativity can now still make important discoveries because it pays increasingly to have long experience of these interconnections.

What I found remarkable was how hard this committee came down on the core discipline itself, calling mathematicians generally “incognizant” (fighting word!) of the expanding role that the mathematical sciences now play in other realms of theory and practice. “It is easy,” the authors write, “to point to work in theoretical physics or theoretical computer science that is indistinguishable from research done by mathematicians, and similar overlap occurs with theoretical ecology, mathematical biology, bioinformatics, and an increasing number of fields.” By implication, the authors are calling their colleagues insufficiently appreciative of these connections. And in practical fields, it seems that everyone — biotechnologists, communication-system engineers, and financial-market “quants,” to take just a few examples — has proved more aware of these interdependencies than mathematicians themselves.
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The data on the national R&D enterprise that are gathered and published annually by the National Science Foundation are so dimensionally rich that the implications are actually difficult to absorb. In the SlideShare presentation below, I’ve taken a try at teasing out some observations that may be of interest to people interested in the innovation system. Some of the findings are obvious; some not. Your comments are welcome. [By the way, the “print/pdf” button will not print the SlideShare deck; instead, click on the “SlideShare” icon or link and download from there.]