Moore’s Law at 50

Thomas Friedman interviewed Gordon Moore on the occasion of the 50th anniversary of Moore’s 1965 article predicting that computing power would exponentially increase at little additional cost. Moore’s ten-year prediction for the doubling rate of the numbers of transistors on microchips held up, and has now, with small adjustments, guided investments and expectations in electronics for five decades.

Friedman makes an especially important point, saying:

But let’s remember that it [Moore’s Law] was enabled by a group of remarkable scientists and engineers, in an America that did not just brag about being exceptional, but invested in the infrastructure and basic scientific research, and set the audacious goals, to make it so. If we want to create more Moore’s Law-like technologies, we need to invest in the building blocks that produced that America.”

These kinds of calls for investments in infrastructure and basic research, for new audacious goals, and for more Moore’s Law-like technologies are, of course, some of the primary and recurring themes of this blog (here, here, here, and here) and presentations and publications of the last several years. For instance, Miller and O’Leary’s (2007) close study of how Moore’s Law has aligned and coordinated investments in the electronics industry has been extrapolated into the education context (Fisher, 2012; Fisher & Stenner, 2011).

Education already has had over 60 years experience with a close parallel to Moore’s Law in reading measurement. Stenner’s Law retrospectively predicts exactly the same doubling period for the increasing numbers from 1960 to 2010 of children’s reading abilities measured in a common (or equatable) unit with known uncertainty and personalized consistency indicators. Knowledge of this kind has enabled manufacturers, suppliers, marketers, customers, and other stakeholders in the electronics industry to plan five and ten years into the future, preparing products and markets to take advantage of increased power and speed at the same or lower cost. Similarly, that same kind of knowledge could be used in education, health care, social services, and natural resource management to define the rules, roles, and responsibilities of actors and institutions involved in literacy, health, community, and natural capital markets.

Reading instruction, for example, requires text complexities to be matched to reader abilities at a comprehension rate that challenges but does not discourage the reader. Uniform grade-level textbooks are often too easy for a third of a given classroom, and too hard for another third. Individualized instruction by teachers in classrooms of 25 and more students is too cumbersome to implement. Connecting classroom reading assessments with known text complexity measures informed by judicious teacher input sets the stage for the realization of new potentials in educational outcomes. Electronic resources tapping existing text complexity measures for millions of articles and books connect individual students’ high stakes and classroom assessments in a common instructional framework (for instance, see here for an offering from Pearson). As the numbers of student reading measures made in a common unit continues to grow exponentially, capacities for connecting readers to texts, and for communicating about what works and what doesn’t in education, will grow as well.

This model is exactly the kind of infrastructure, basic scientific research, and audacious goal setting that’s needed if we are to succeed in creating more Moore’s Law-like technologies. If we as a society made the decision to invest deliberately, intentionally, and massively in infrastructure of this kind across education, health care, social services, and natural resource management, who knows what kinds of powerful results might be attained?

References

Fisher, W. P., Jr. (2012). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-734.

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