Review of Falling Behind? Boom, Bust, and the Global Race for Scientific Talent

Falling Behind?
Boom, Bust, and the Global Race for Scientific Talent
by Michael S. Teitelbaum
Princeton University Press
March 30, 2014

Introduction

Falling Behind? is a recent (March 2014) book by Michael Teitelbaum of the Sloan Foundation, a demographer and long time critic of STEM (Science, Technology, Engineering and Mathematics) shortage claims. Falling Behind? is an excellent book with a wealth of data and information on the history of booms and busts in science and engineering employment since World War II, STEM shortage claims in general, and lobbying for “high-skilled” immigration “reform”. Although I have been a student of these issues for many years, I encountered many facts and insights that I did not know or had not thought of. Nonetheless the book has a number of weakenesses which readers should keep in mind.

The “core findings” of the book are summarized forthrightly on page three of the Kindle edition:

The evidence assembled in this book leads inescapably to three core findings:

o First, that the alarms about widespread shortages or shortfalls in the number of U.S. scientists and engineers are quite inconsistent with nearly all available evidence;

o Second, that similar claims of the past were politically successful but resulted in a series of booms and busts that did harm to the U.S. science and engineering enterprise and made careers in these fields increasingly unattractive; and

o Third, that the clear signs of malaise in the U.S. science and engineering workforce are structural in origin and cannot be cured simply by providing additional funding. To the contrary, recent efforts of this kind have proved to be destabilizing, and advocates should be careful what they wish for.

Teitelbaum, Michael S. (2014-03-30). Falling Behind?: Boom, Bust, and the Global Race for Scientific Talent (p. 3). Princeton University Press. Kindle Edition.

A Long History of Alarms, Booms, and Busts

Teitelbaum identifies and gives a detailed history of a series of alarms, booms and busts in science and engineering training and employment dating back at least to the end of World War II. World War II was followed by a sharp increase in training of physicists for the nascent Cold War, the development of nuclear and thermonuclear (fusion) bombs, and related activities. Teitelbaum shows that this immediate post-war boom was starting to falter in 1956 and 1957, but the dramatic surprise launch of Sputnik (October 4, 1957) followed by the launch of Sputnik 2 (November 3, 1957), a satellite large enough to deliver a nuclear or even thermonuclear weapon anywhere in the world, triggered massive investments in physics and other STEM fields, including the multi-billion dollar Apollo program and the less public development of Intercontinental Ballistic Missiles (ICBMs).

Drawing in part on MIT historian and physicist David Kaiser’s research, he discusses the subsequent bust in physics and STEM employment in the late 1960’s and early 1970’s. He then covers the cycle of alarm, boom in physics and some other STEM fields during the 1980’s followed by the 1992-1993 bust as the Cold War ended, projects such as the Super Conducting Supercollider (SSC) were cancelled, and numerous freshly minted Ph.D.’s discovered (once again) a paucity of actual jobs for physicists and many other Cold War fueled STEM professions.

Teitelbaum moves on to discuss two post Cold War alarm/boom/bust cycles: The now famous or infamous “Internet/Telecom Bubble” of the late 1990’s and early 00’s and the molecular biology/biotech bubble of 1998-2005 fueled by the rapid doubling of the budget of the National Insitutes of Health (NIH) in these years. All in all, he identifies five major alarm/boom/bust cycles since World War II. He also discusses a number of smaller booms and busts in energy research and development and other fields. He says little about the current mobile/social/search boom.

Since the end of the Cold War, the alarm/boom/bust cycles have become intertwined with immigration policy in general and the controversial H1-B visa program in particular. Much of the book discusses the role of industry and leading research universities in both promoting alarms over alleged shortages of scientists and engineers, alarms over the quality of K-12 (Kindergarten through 12th grade) education in the United States, and heavy lobbying for increases in or the complete elimination of immigration quotas for “high-skilled” immigrants on temporary guest-worker visas, although as Teitelbaum points out several times the H1-B program only requires a bachelor’s degree or equivalent.

Teitelbaum makes the important point that the reported high dropout rate of college students expressing an interest in a science or engineering degree may reflect poor teaching at the college level rather than inadequate preparation due to poor K-12 education. Not surprisingly, the presidents and other representatives of research universities who comprise around half the membership of the “Blue Ribbon” committees such as the National Research Council’s “Rising Above the Gathering Storm” report committee (2005) might consciously or unconsciously wish to focus attention on K-12 education rather than lousy teaching by professional researchers at research universities. K-12 teachers and actual students at any level — K-12, college, or graduate school — are never represented on these committees.

One of the book’s strengths is detailed information on the lobbying organizations such as Compete America involved in STEM shortage claims and their activities. The discussion of lobbyist Jack Abramoff and his relationship with Microsoft is particularly titillating and, as Teitelbaum points out, almost never mentioned in the “mainstream media” despite easily available information on numerous web sites and specialty publications.

Those Missing Fact Checkers

One of the minor themes of the book is the frequency of both omissions of important facts and factually inaccurate information in “mainstream” reporting on both STEM shortage claims in general and also “high-skilled” immigration, particularly the controversial H1-B visa program. He notes, for example, that the H1-B visa program is often described as requiring an unsuccessful search for a skilled American to fill a position before an H1-B visa applicant or holder can be hired, which is not the case. One of the many sources of confusion in this topic is that a permanent resident or “Green Card” visa does require such a search but the H1-B does not.

The Bipartisan Consensus

Teitelbaum spends a substantial number of pages rightly discussing how the seeming Left/Right polarization of American politics does not apply to STEM shortage claims and related issues. He cites a number of specific examples of “politics makes curious bedfellows” in which ostensibly left-wing and right-wing groups have joined forces on STEM shortage and related immigration issues. Similarly, opposition to STEM shortage claims does not follow a clear left/right ideological axis with both some labor unions (think tanks associated with the AFL-CIO such as the Economic Policy Institute, for example) and some right wing groups questioning or strongly attacking the claims and associated policies.

Indeed, there was little difference between Al Gore and George W. Bush on these issues in the 2000 presidential election. President Obama has largely continued the same policies in this area as George W. Bush, recently touting executive action on “high-skilled” immigration. President Obama was famously embarassed by questions about the H1-B visa program and STEM shortage claims by Jennifer Wedel, the wife of a then unemployed semiconductor engineer, Darin Wedel, in a Google Plus chat session in 2012.

In this generally excellent discussion, we encounter one of the weaknesses of Falling Behind?. Like most Americans, Teitelbaum appears to take the Left/Right axis in American politics at face value or mostly face value. In fact, both the Republican and Democratic parties and many self-identified “Conservatives” and “Liberals” in both parties have a long history of pursuing the same or almost the same policies in many areas, not just STEM policy, while often attacking each other as extremist nutjob Communists or Fascists.

A notable recent example is the bank bailout of 2008, supported by both the Democratic candidate Barack Obama and the Republican candidate John McCain and a large fraction of both Republican and Democratic Senators and Representatives. The revolving door between the US government and major financial institutions is well documented (see, for example, this report by the Project on Government Oversight) to include many leading Republicans and many leading Democrats without much regard to either party affiliation or purported ideology.

A Number of Weaknesses

Overall, Falling Behind? is an excellent book. It does however have a number of significant weaknesses. This is a large and complex topic filled with confusing and rapidly shifting terminology and claims, making it difficult even for a highly experienced researcher such as Teitelbaum to fully address the issues. Teitelbaum does not appear to have much experience or direct knowledge of the Silicon Valley. He seems more familiar with academia and federally funded research than with the private computer industry and its curious hiring practices.

Purple Squirrels and Mutant Supermen

In academia and federally funded research, mostly the same thing today, a Ph.D. is specific hands-on training for a specific discipline. It is now well documented that many federally funded Ph.D. programs produce far more Ph.D.’s than actual permanent or long term positions in the discipline exist or will exist. In many STEM disciplines, such as particle physics (my Ph.D. is in experimental particle physics), large majorities of Ph.D.’s cannot find work and must eventually leave the discipline, often becoming software engineers of some sort. Eventually means immediately after receiving a Ph.D. or after a first “postdoc,” typically lasting 2-3 years. A minority of Ph.D.’s who fail to get a tenure track position, typically an assistant professor, hang on in a series of “postdoc” or “staff” positions, most leaving their field of specialization. In most fields, a large majority of Ph.D.’s leave the field by the time they are thirty-five. See the references section at the end of this review for more details.

There is no credible case for a shortage of people with specific as opposed to general skills in most academic research fields. There is also no credible case for a shortage of people with skills taught at the K-12 level such as basic arithmetic, algebra or simple “Hello World” level “coding” in most academic research fields. Academic, federally funded research is the area that Teitelbaum writes about most clearly and effectively.

In the computer industry (a large fraction of STEM degree holders at all levels end up working for the computer industry regardless of their original plans), one often hears claims of a shortage of engineers or programmers “with special skills” or “qualified” in some way. There is tremendous confusion over what this means. In many cases the claims are quickly followed with complaints about the poor quality of K-12 education in the United States (and almost never over the quality of college or university education). This seems to imply a shortage of engineers or programmers with K-12 STEM skills such as basic arithmetic, algebra, calculus, or introductory “Hello World” coding skills such as taught in AP Computer Science classes.

It is easy to understand why computer companies cannot hire applicants lacking such basic skills and cannot realistically provide on-the-job training for new hires who again lack such basic skills such as reading, writing, and arithmetic.

In fact, computer companies are usually seeking applicants with at least three years of paid, industry experience in not one but usually dozens of specific, often new “technologies”. In general, this must be paid “industry” experience. College or school work does not count. Paid work for universities or government labs usually does not count. A typical job description is often something like:

Senior IOS Game Developer at Cool SOMA (South of Market Neighborhood in San Francisco) Startup

REQUIRED

o 3-5 years of IOS programming using XCode and clang compiler (the GNU gcc compiler won’t cut it)
o 3-5 years of Unity (game development system) on IOS 8 (IOS 7 won’t do)
o 3-5 years of OpenGL (3D graphics API) experience
o 3-5 years of Python experience
o 3-5 years of Java experience
o 3-5 years of Hadoop database experience
o 3-5 years experience with modern C++ (C++11 and at least some C++14)
o 3-5 years of Agile development
o 3-5 years of Git (version control system), Gerrit code review system, in a commerical collaborative team environment
o at least three apps in the iPhone app store
o B.S. degree (MS preferred) from top computer science program (e.g. Stanford, CMU)

Note also that 3-5 years of experience in a closely related “technology” is generally not acceptable as a substitute. So, for example, C++, Java, and Microsoft’s C# (“C-sharp”) are all very similar programming languages with most of the same English-derived keywords, but 3-5 years of C# or C++ alone would not be an acceptable substitute for the 3-5 years of Java experience in the example above.

The term “technology” is used in a peculiar way in the computer industry, especially with respect to hiring practices. If programming tools were automobiles, in many cases it would be like saying a Volvo and a Subaru are two different “technologies” even though both use a gasoline-based internal combustion engine and most of the same standard automobile components.

Many of these lists of requirements are so extensive and picky that it is doubtful even a single “qualified” engineer actually exists, even among highly experienced IOS game developers (for example). These elusive, often non-existent candidates are known as “purple squirrels” in the human resources field. Companies frequently cite these “purple squirrel” requirements when explaining decisions to turn down seemingly highly qualified applicants.

Yet it is common for companies to turn down or not even interview candidates in the rare cases that they actually match all the Purple Squirrel requirements. This raises many questions about how real these job requirements are and also what the actual hiring criteria may be. When challenged about this, employers often start talking about “cultural fit.”

Computer companies also often claim to be seeking “the very best” engineers or programmers: “A players” or even “A+ players”, “superprogrammers”, “10X” or even “100X” programmers. It is not clear what this in practice refers to. It is often vaguely defined. Computer companies often seem to be saying that a small minority of programmers have some special “superprogrammer” gene that inherently makes them much better than the typical or median engineer or programmer with a degree from Stanford, MIT, or some other top university and twin 800 scores on the SAT exam. 🙂

These mysterious superbeings are elusive and rarely identified by name. Fabrice Bellard and John Carmack are sometimes cited as specific examples.

In some respects, the super-programmers and super-engineers bear a resemblance to Marvel Comics outcast mutant supermen the X-Men, complete with real world “superpowers,” a term that appears in code.org’s famous inspirational “What Most Schools Don’t Teach” video on coding for example. The X-Men and other comic book super-heroes are popular with many in the computer industry, although basing hiring practices on comic books seems rather questionable.

Many Silicon Valley employers claim to be convinced that while these mutant supermen and women (they seem to be mostly men for some reason, possibly the “superprogrammer” gene is linked to the Y chromosome) are remarkably hard to find in the United States there are more than 65,000 (the current H1-B visa cap) produced every year in India and China clamoring to move to the United States on a risky temporary guest-worker visa rather than use their mutant superpowers to found their own Google in Bangalore or Shenzen. 🙂

The United States has a special, “genius” visa, the “O-1 Visa: Individuals with Extraordinary Ability or Achievement,” which is rarely mentioned in debates on “high-skilled” immigration and, unlike the H1-B visa, appears to require actual evidence that the visa applicant is a mutant superman (or woman).

It should be noted also that the Purple Squirrels and Mutant Supermen are often conflated. Jean Grey must not only have world-destroying psychokinetic powers but also at least three years of paid professional experience incinerating alien planets for a cool Silicon Valley company, preferably Google. Working for a non-profit educational institution such as Professor Xavier’s School for Gifted Youngsters just won’t cut it. 🙂

Teitelbaum doesn’t get the Silicon Valley’s paradoxical hiring practices explicitly wrong in Falling Behind? but a full analysis of the STEM shortage claims emanating from the computer industry and the Silicon Valley requires a detailed investigation and explanation of the Purple Squirrel job requirements and the Mutant Superman theory of science and engineering which is lacking.

An Independent Agency to Evaluate STEM Shortage Claims?

Falling Behind? ends with a chapter “Making Things Work Better” which presents a number of suggested public policy changes to improve the system, reduce or eliminate the boom/bust cycle, and make STEM professions more appealing to talented young (or old) people. Teitelbaum gives little advice for STEM students or workers on how to cope with the current system nor arguments addressed to employers on how and why to change their current hiring practices. He is primarily concerned with government policy. One of Teitelbaum’s main suggestions is to establish an independent commission or agency, perhaps similar to the Migration Advisory Committee (MAC) in the United Kingdom, to evaluate the STEM labor market and current and future STEM shortage claims specifically.

This idea will probably fail even if adopted. Teitelbaum documents several cases of government agencies, presumably or clearly in response to employer pressures and lobbying, producing reports and analyses of highly questionable quality and accuracy asserting either a current shortage of STEM workers or predicting a shortage or shortfall in the future that never occurred (instead a glut, a bust, actually occurred). An agency or commission such as Teitelbaum suggests would almost certainly become the target of sustained lobbying and pressure to produce the same sort of flawed analyses that have repeatedly occurred since World War II.

Are the Booms and Busts Bad for America or the World?

The greatest weakness of the book is that Teitelbaum fails to make a strong or convincing case that the alarm/boom/bust cycle and related policies is bad for the United States, the World, or businesses. That it is bad for many STEM workers, scientists and engineers is obvious. That it discourages many talented people from pursuing STEM careers is also obvious. Many people simply do not want to take such risks or cannot take such risks. However, Teitelbaum argues in several places that the American research and development system has produced many positive results and in many respects worked well since World War II. For better or worse, the alarm/boom/bust system that he critiques has produced: nuclear weapons and power plants, thermonuclear weapons, ICBM’s, the successful landing on the Moon, lasers, iPhones, successful heart transplants, Lithium Polymer super-batteries, fracking, and many other technological marvels.

Now, I personally believe that the alarm/boom/bust system that Teitelbaum critiques has been bad for the United States, the human race as a whole, and many businesses. As a STEM worker, I am obviously biased.

My personal argument is that, in fact, there has been a marked slowdown in scientific and technological progress in many fields since World War II and especially since about 1970, with some areas of computers and electronics an obvious exception. This is partly due to the alarm/boom/bust system, but also due to the marked tendency of government funded research programs to lock onto a single theory or paradigm, such as superstrings for many years in theoretical particle physics, to the exclusion of other competing theories or paradigms and without good reason or supporting evidence. The glut of STEM Ph.D.’s in academic research creates an environment in which questioning or challenging the reigning paradigm, the “one true way,” is usually career suicide. This is a major contributing factor to the lock-in on a single paradigm or theory.

Since World War II private businesses have come to rely heavily on federally funded research programs for the basic research underlying and enabling most of their products, goods and services. Hence the flaws of the federally funded research and development system have propagated through the entire modern economy.

We see this slowdown most noticeably in power and propulsion technology despite some advances such as better batteries and perhaps hydraulic fracturing, “fracking,” in oil and natural gas drilling. This slowdown in progress in power and propulsion technology has contributed heavily to the serious economic problems experienced on a global scale over the last decade and also to violent and counterproductive conflicts — Iraq, Afghanistan, the Global War on Terror, mysterious “terrorist” incidents — in recent years.

In power and propulsion, there are several examples of New Manhattan Projects such as tokamaks for nuclear fusion (culminating in ITER), inertial confinement fusion (culminating in the National Ignition Facility), and gigantic accelerator projects such as the Super Conducting Super Collider (SSC) and the Large Hadron Collider (LHC) that have crowded out other possibilities while failing to produce practical results despite heavy funding — far exceeding pre-World War II R&D budgets.

Crude Oil Prices Since 1861

Inflation Adjusted Crude Oil Prices Since 1861 (Red Line) — Wikipedia

But belief is not proof, nor are general, hand-waving arguments. In Falling Behind?, Teitelbaum fails to show that the current system is bad for the United States or the world. I think he clearly believes this and I agree with him if he does. A more specific argument and detailed data is needed to make the case to a skeptical audience with a strong short-term interest in the current system.

Conclusion

Falling Behind? is an excellent book and well worth reading if you have an interest in STEM policy or STEM shortage claims, “high-skilled” immigration, or science and engineering policy and economics in general. Many STEM workers and employers would benefit from reading the book — as well as policy makers.

For STEM workers, the one clear takeaway is to expect and plan for the booms and busts. As Joseph advised the Pharaoh, save during the seven fat years to survive the seven lean years. Don’t buy the “new economy/this time is different” hype that often accompanies the booms.

For STEM employers, Teitelbaum recounts how major high tech companies invested millions of dollars and many hours of executive time on lobbying for an increase in the H1-B visa cap during the Internet Bubble only to finally get their increase just as the bubble collapsed, surely a waste of time and money in retrospect. While it may take years to change policies in Washington or fail outright, high tech employers have direct and immediate control over their own hiring practices, working conditions and salaries. In this arena, employers have many immediate options including (but not limited to):

o reducing or eliminating the long lists of required specialized skills in Purple Squirrel job descriptions either by using “Preferred” instead of “Required” or simply requiring only some of the list of desired skills instead of all.

o establishing apprenticeship or training programs to enable successful on-boarding of employees without the exact “right skills”

o switching to blind coding and technical tests scored by computers or by human evaluators who know nothing about the candidate other than the answers — as is now the case with standardized tests such as the SAT or Advanced Placement (AP) tests to eliminate bias. One could argue that federal anti-discrimination statutes and common law actually require this anyway 🙂

o simply taking a hard look at many common beliefs and practices of high tech employers that appear to be based on verbal folklore and frequent repetition rather than hard evidence.

We can hope that Michael Teitelbaum will follow up Falling Behind? with another book addressing these and other issues that were not covered in his current book.

© 2015 John F. McGowan

About the Author

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing video compression and speech recognition technologies. He has extensive experience developing software in C, C++, Visual Basic, Mathematica, MATLAB, and many other programming languages. He is probably best known for his AVI Overview, an Internet FAQ (Frequently Asked Questions) on the Microsoft AVI (Audio Video Interleave) file format. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech). He can be reached at jmcgowan11@earthlink.net.

References and Suggested Reading

“U.S. Pushes for more scientists, but the jobs aren’t there,” by Brian Vastag, Washington Post, July 7, 2012

“A Career in Science Will Cost You Your Firstborn,” by John Skylar, Blog Post, Jan 7, 2015

“The Scientific Century:securing our future prosperity” by the Royal Society (UK), March 2010, Figure 1.6: careers in and outside science, page 14

CareerProspectUK2010

“Survivor: theoretical physics,” by Steve Hsu, Blog Post, September 24, 2008

Particle Theory Job Market
Posted on January 29, 2010
Blog Post, Not Even Wrong, by Peter Woit

“What Scientist Shortage? The Johnny-can’t-do-science myth damages US research” by Beryl Lieff Benderly, Columbia Journalism Review, January 17, 2012

Does the U.S. Produce Too Many Scientists?
American science education lags behind that of many other nations, right? So why does it produce so many talented young researchers who cannot find a job in their chosen field of study?
By Beryl Lieff Benderly
Scientific American, February 22, 2010

“What Scientist Shortage?” by Daniel S. Greenberg, Washington Post, Wednesday, May 19, 2004; Page A23

Mathematicians and the Market
Geoff Davis, Mathematics Department, Dartmouth College
Notices of the American Mathematical Society, Vol. 44, No. 10, pp. 1307-1315, 1997.

The disposable academic
Why doing a PhD is often a waste of time

The Economist
Dec 16th 2010

What to do about overproduction of PhDs?
Aug 19 2010, Blog Post, Published by galacticinteractions under Academia, Rant, about the author’s experience with the Physics Bust of the Early 1990’s

Stop Admitting Ph.D. Students
Inside Higher Ed
August 18, 2010
Monica J. Harris

The Overproduction of PhDs Was Recognized Over a Decade Ago
Posted on February 1, 2013, Mike The Mad Biologist Blog

Scientist shortage? Maybe not
By Greg Toppo and Dan Vergano, USA TODAY
Updated 7/9/2009 2:29 AM

How and Why Government, Universities, and Industry Create Domestic Labor Shortages of Scientists and High-Tech Workers
By Eric Weinstein (1998)
(Working Draft)
National Bureau of Economic Research

Is There a Shortage of Scientists and Engineers? How Would We Know?
by William Butz, Gabrielle Bloom, Mihal Gross, K. Kelly, Aaron Kofner, Helga Rippen
RAND Corporation 2003

Toil, Trouble, and the Cold War Bubble: Physics and the Academy since World War II
Speaker(s): David Kaiser
Presentation at Perimeter Institute
Date: 10/09/2008 – 2:00 pm

Bridges to Independence: Fostering the Independence of New Investigators in Biomedical Research (National Research Council 2005)

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3 Comments

  1. Jake January 14, 2015
  2. Rob Corte January 22, 2015
  3. John F. McGowan, Ph.D. July 2, 2015

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