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The Rise of Smart Machines: The Unique Peril of Intelligent Software Agents in Defense and Intelligence

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The Palgrave Handbook of Security, Risk and Intelligence

Abstract

As computer processing power and cyber connectivity has increased, states have turned to intelligent software agents (ISA) as a potential means to extend the reach of their militaries and the analytical capacity of their intelligence agencies. Intelligent software agents (ISA) are computer programs that have the ability to learn, cooperate, and act independently of humans. The development of technologies that can operate autonomously has generated nearly as much anxiety as it has excitement, often to the detriment of clear eyed analysis. The path to acquiring and fully implementing ISA is farther away, and more complex than its advocates and detractors will admit. In addition to this, while ISAs could afford new capabilities for information analysis and battlefield risk reduction, they simultaneously introduce their own unique risks in implementation.

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Notes

  1. 1.

    Many thanks to the scholars and practitioners who took the time to assist me in formulating the thoughts contained herein. Special thanks to Lt. Col. Paul Brister Ph.D. U.S. Air Force, computer software engineer and research associate Tad Masek Naval Postgraduate School, Assistant Professor of Computer Science, USAFA Dr. Andrew Sellers, and CISO Eric J. Smith at Bucknell University. Any errors in fact or interpretation are entirely mine.

  2. 2.

    While there are well-established theories regarding the probability of smart technologies outpacing the intelligence and control of humans (a term generally known as technological singularity), this chapter does not address this debate. For more on this see: Kurzweil, Ray (2005), ‘The Singularity is Near: When Humans Transcend Biology’, New York: Viking.

  3. 3.

    This abstract categorization is an adapted version of Nwana and Azarmi’s ISA typology which is an extension of Wooldridge and Jennings.

  4. 4.

    The design architecture of information ISAs are generally categorized into supervised and unsupervised learning. For more see Chapter 2 of: Dua, Sumeet and Xian Du. 2011. Data mining and machine learning in cybersecurity. Boca Raton: Auerbach Publications.

  5. 5.

    This collection of multifaceted data has simultaneously given rise to a research niche sometimes known as ISS – intelligent software surveillance.

  6. 6.

    This is particularly true of military organizations that compete across and within services. See: Posen, Barry. 1984. Sources of military doctrine. Ithaca, NY: Cornell University Press.

  7. 7.

    The research niche most commonly cited in this work is the literature on human robot interaction (HRI).

  8. 8.

    As Arkin also notes, the potential for a single lethal robot to exhibit unanticipated behaviors is not necessarily unique to robots – humans can also do this, although the mechanisms are likely different.

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Author information

Authors and Affiliations

  1. Government, Franklin and Marshall College, Lancaster, PA 17604, USA

    Nina A. Kollars

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  1. Nina A. Kollars
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Correspondence to Nina A. Kollars .

Editor information

Editors and Affiliations

  1. Politics and International Relations, University of Leicester, Leicester, United Kingdom

    Robert Dover

  2. Department of War Studies, King's College London, London, United Kingdom

    Huw Dylan

  3. Department of War Studies, King's College London, London, United Kingdom

    Michael S. Goodman

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Kollars, N.A. (2017). The Rise of Smart Machines: The Unique Peril of Intelligent Software Agents in Defense and Intelligence. In: Dover, R., Dylan, H., Goodman, M. (eds) The Palgrave Handbook of Security, Risk and Intelligence. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-53675-4_11

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