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Abstract

Because we live in a “Scientific and Technical Age, we like to think that our decisions and actions are based on scientific findings and technological rationality. But the human mind does not always obey the dictates of science and reason; instead, ”human hardware“ — engrained emotions, likes and dislikes, fears and hopes — sometimes lead people to disregard the scientific evidence, thereby creating difficulties.

Problems arising from disregard of the human element in the man-machine relationship can be found in the organization of work as the Industrial Revolution advanced. Near the beginning of this century, Henry Ford’s moving assembly-line decreased costs, and Frederick W. Taylor’s “Scientific Manage­ment” gave rise to the field of Industrial Engineering by breaking down each operation to its simplest form, so that the worker could perform his task speedily and without great skill. In brief, it treated the worker as a machine. However, Elton Mayo’s experiments showed that production would increase if management treated the works as human beings, giving consideration to their thoughts and feelings.

While automation has great potential for improving quality and productivity in both manufacturing and service trades, robotic machines do not eliminate skilled workers. Indeed, to enable the robots to work most efficiently, highly-trained technical personnel are needed to oversee and back up the machines. Only if information and software systems take into consideration human feelings and capabilities — the “human hardware” — can they capitalize fully on the computer’s growing informational and analytical capacity.

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References

  • Beniger, J. R., 1986, The Control Revolution, Harvard University Press, Cambridge, Mass.

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  • Smith, A., 1937, The Wealth of Nations, Random House (reprint ), New York.

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  • Zuboff, S., 1988, In the Age of the Smart Machine: The Future of Work and Power,Basic Books, New York.

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© 1990 Plenum Press, New York

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Kranzberg, M. (1990). Software for Human Hardware?. In: Zunde, P., Hocking, D. (eds) Empirical Foundations of Information and Software Science V. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5862-6_1

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  • DOI: https://doi.org/10.1007/978-1-4684-5862-6_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-5864-0

  • Online ISBN: 978-1-4684-5862-6

  • eBook Packages: Springer Book Archive

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