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Introduction

Published online by Cambridge University Press:  08 November 2023

By
Louis Tay ,
Sang Eun Woo  and
Tara Behrend
Edited by
Louis Tay ,
Sang Eun Woo  and
Tara Behrend
Louis Tay
Affiliation:
Purdue University, Indiana
Sang Eun Woo
Affiliation:
Purdue University, Indiana
Tara Behrend
Affiliation:
Purdue University, Indiana
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Summary

Technology, that is, the output of human innovation, has always been central to human progress worldwide. Early on, the ancients developed the wheel, concrete, calculus, and paper, which led to advances in transportation, construction, and communication. Today, the incarnation of technology falls in the realm of the digital and computational, and its progress has been rapid, even arguably exponential. In his chapter, “The Law of Accelerating Returns,” Ray Kurzweil writes, “An analysis of the history of technology shows that technological change is exponential, contrary to the common-sense ‘intuitive linear’ view. So we won’t experience 100 years of progress in the 21st century – it will be more like 20,000 years of progress (at today’s rate)” (Kurzweil, 2004, p. 381).

Type
Chapter
Information
Technology and Measurement around the Globe , pp. 1 - 8
Publisher: Cambridge University Press
Print publication year: 2023

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References

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Tay, L., Woo, S. E., Hickman, L., Booth, B. M., & D’Mello, S. (2022). A conceptual framework for investigating and mitigating Machine-Learning Measurement Bias (MLMB) in psychological assessment. Advances in Methods and Practices in Psychological Science, 5(1). https://doi.org/10.1177/25152459211061337CrossRefGoogle Scholar
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