Looking Back and Ahead: The U.S. Scientific and Technical Workforce
Asking the provocative question, “How we will recognize a shortage or surplus in the scientific and technical workforce?” the recently-published proceedings of a conference held last December highlight the second half of the conference’s theme, “improving the data system for decisionmaking.”
Since Sputnik, there has been continuing controversy about whether the United States will have a sufficient number of scientifically and technically trained workers to maintain our country’s position in the world economy. A two-day conference organized by the RAND Corporation for the OSTP and the Alfred P. Sloan Foundation explored the relationship between data projections and policy making. While there was disagreement among the 25 attending researchers, federal S&T policymakers and statistical agency officials about future projections, there was agreement that there are significant shortfalls in collected data on the S&T workforce.
The conference proceedings were compiled in a 114-page report available at http://www.rand.org/publications/CF/CF194 . The eight-page Introduction neatly summarizes the range of opinions on whether there might be S&T workforce shortfalls. On one hand, “evidence for these periodically anticipated shortages in the general STEM [scientific, technical, engineering and mathematics] workforce has been hard to find. Indications of resulting national crises have, so far, been even less evident.” Yet “the failure of previously anticipated STEM workforce shortages to materialize should not be grounds for complacency.”
The “Rapporteur’s Summary” by William P. Butz well summarizes the conference:
“Again and again, the conference discussion returned to the connection between data and decisionmaking and reiterated the basic point that decisionmaking does not grind to a halt in the absence of adequate data. It simply proceeds with inadequate data. Employers and managers who lack a credible information base produced by statistical experts may base decisions on information and analyses that they themselves have produced, often on the fly, or that are produced by others lacking statistical expertise. Administrators of science funding agencies who lack such information may base funding allocations across scientific disciplines on judgments about where the science is most exciting or where other support is lacking, to the detriment of students encouraged toward fields, however exciting, without waiting jobs. Moreover, without understanding key decision points for STEM students and workers, universities and their science funders cannot efficiently design interventions to affect such decisions. Among all these decisionmakers, students and workers are the most disadvantaged, for they typically command insufficient resources to uncover any but the most rudimentary information about trends in potentially interesting fields. And yet, ironically, it is they who bear the largest burden of mistaken decisions – lengthy training and uncertain outcomes, job insecurity, and potential disillusionment with the scientific enterprise.”
