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JACIII Vol.15 No.7 pp. 786-792
doi: 10.20965/jaciii.2011.p0786
(2011)

Paper:

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The Omnipresent Computing Menace to Information Society

Alfons Schuster* and Daniel Berrar**

*Laboratory for Dynamics of Emergent Intelligence, RIKEN Brain Science Institute, Wako-shi, Saitama 351-0198, Japan

**Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, G3-45, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan

Received:
February 21, 2011
Accepted:
May 27, 2011
Published:
September 20, 2011
Creative Commons License
Keywords:
intelligent computing, carbon-based computing, information society, information ethics
Abstract
Computers have evolved from mere number crunchers to systems demonstrating an astonishing degree of sophistication, decision-making ability, and autonomy. Silicon is no longer the only substrate facilitating information processing. Despite these progresses, machine intelligence is still far from rivaling human intelligence. Nonetheless, we might be all too ready to rely on inferior agents for decision making, to give away sensitive information without fully understanding the consequences involved, or to tinker with genetic code to program carbon-based machines without fully appreciating the risks. This article explores the potentials and risks that information societies may face in the wake of current and emerging intelligent computing paradigms.
Cite this article as:
A. Schuster and D. Berrar, “The Omnipresent Computing Menace to Information Society,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.7, pp. 786-792, 2011.
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References
  1. [1] A. Kent, “Too damned quiet?”
    Available at: http://arxiv.org/abs/1104.0624, accessed May 16, 2011.
  2. [2] A. Schuster and Y. Yamaguchi, “From foundational issues in artificial intelligence to intelligent memristive nano-devices,” Int. J. Mach. Learn. & Cyber.,
    DOI 10.1007/s13042-011-0016-1, 2011.
  3. [3] M. Schmidt and H. Lipson, “Distilling free-form natural laws from experimental data,” Science, Vol.324, No.5923, pp. 81-85, 2009.
  4. [4] D. Berrar, M. Granzow, and W. Dubitzky, “Introduction to genomic and proteomic data analysis,” In W. Dubitzky, M. Granzow, and D. Berrar (Eds.), Fundamentals of Data Mining in Genomics and Proteomics, Springer, pp. 1-37, 2007.
  5. [5] D. F. Ransohoff, “Bias as a threat to the validity of cancer molecular-marker research,” Nature Reviews Cancer, Vol.5, No.2, pp. 142-149, 2005.
  6. [6] J. Cohen, “Chance, skill, and luck: The psychology of guessing and gambling,” Baltimore, MD: Penguin Books, 1960.
  7. [7] S. Goodman, “A dirty dozen: Twelve p-value misconceptions,” Seminars in Hematology, Vol.45, No.3, pp. 135-140, 2008.
  8. [8] S. Goodman, “p values, hypothesis tests, and likelihood: Implications for epidemiology of a neglected historical debate,” American J. of Epidemiology, Vol.137, No.5, pp. 485-496, 1993.
  9. [9] J. P. A. Ioannidis, “Why most published research findings are false,” PLoS Medicine, Vol.2, No.8, p. e124, 2005.
  10. [10] D. H. Johnson, “The insignificance of statistical significance testing,” J. of Wildlife Management, Vol.63, No.3, pp. 763-772, 1999.
  11. [11] D. N.McClosky and S. T. Ziliak, “The unreasonable ineffectiveness of Fisherian “tests” in biology, and especially in medicine,” Biological Theory, Vol.4, No.1, pp. 44-53, 2009.
  12. [12] C. Poole, “Beyond the confidence interval,” American J. of Public Health, Vol.77, No.2, pp. 195-199, 1987.
  13. [13] A. Isaksson, M. Wallman, H. Gransson, and M. G. Gustafsson, “Cross-validation and bootstrapping are unreliable in small sample classification,” Pattern Recognition Letters, Vol.29, No.14, pp. 1960-1965, 2008.
  14. [14] D. Hambling, “Surveillance robots know when to hide,” New Scientist, Vol.209, No.2804, p. 25, March 2011.
  15. [15] A. R. Wagner and R. C. Arkin, “Acting deceptively: providing robots with the capacity for deception,” Int. J. of Social Robotics, Vol.3, No.1, pp. 5-26, 2011.
  16. [16] C. Heeney, N. Hawkins, J. de Vries, P. Boddington, and J. Kayeb, “Assessing the privacy risks of data sharing in genomics,” Public Health Genomics, Vol.14, No.1, pp. 17-25, 2010.
  17. [17] J. Du and M. Gerstein, “Genomic anonymity: Have we already lost it?,” The American J. of Bioethics, Vol.8, No.10, pp. 71-81, 2010.
  18. [18] A. Schuster (Ed.), “Robust intelligent systems,” Springer-Verlag, London, 2008.
  19. [19] P. Vytelingum, T. D. Voice, S. D. Ramchurn, A. Rogers, and N. R. Jennings, “Agent-based micro-storage management for the smart grid,” Proc. 9th Int. Conf. on Autonomous Agents and Multiagent Systems, pp. 39-46, 2010.
  20. [20] J. Bohannon, “News Focus: IEEE International Conference On Computational Intelligence And Games, Game-miners grapple with massive data,” Science, Vol.330, No.6000, pp. 30-31, 2010.
  21. [21] I. S. Kotchetkov, B. Y. Hwang, G. Appelboom, C. P. Kellner, E. S. Connolly, Jr., “Brain-computer interfaces: Military, neurosurgical, and ethical perspective,” Neurosurg Focus, Vol.28, No.5, 2010.
  22. [22] P. Lin, K. Abney, and G. Bekey, “Robot ethics: Mapping the issues for a mechanized world,” Artificial Intelligence,
    doi:10.1016/j.artint.2010.11.026, 2011.
  23. [23] J. Giles, “Fake tweets by socialbot fool hundreds of followers,” New Scientist, Vol.209, No.2804, p. 28, March 2011.
  24. [24] Y. Benenson, T. Paz-Elizur, R. Adar, E. Keinan, Z. Livneh, and E. Shapiro, “Programmable and autonomous computing machine made of biomolecules,” Nature, Vol.414, No.6862, pp. 430-434, 2001.
  25. [25] Y. Benenson, B. Gil, U. Ben-Dor, R. Adar, and E. Shapiro, “An autonomous molecular computer for logical control of gene expression,” Nature, Vol.429, No.6990, pp. 423-429, 2004.
  26. [26] A. Tamsir, J. J. Tabor, and C. A. Voigt “Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’,” Nature, Vol.469, pp. 212-215, 2010.
  27. [27] D. G. Gibson, J. I. Glass, C. Lartigue et al., “Creation of a bacterial cell controlled by a chemically synthesized genome,” Science, Vol.329, No.5987, pp. 52-56, 2010.
  28. [28] A. Levskaya, A. A. Chevalier, J. J. Tabor et al., “Synthetic biology: engineering Escherichia coli to see light,” Nature, Vol.438, No.7067, pp. 441-442, 2005.
  29. [29] R. D. Berg, “The indigenous gastrointestinal microflora,” Trends in Microbiology, Vol.4, No.11, pp. 430-435, 1996.
  30. [30] M. B. Miller and B. L. Bassler, “Quorum sensing in bacteria,” Annual Review of Microbiology, Vol.55, pp. 165-199, 2001.
  31. [31] H. Breithaupt, “The engineer’s approach to biology,” EMBO Rep., Vol.7, No.1, pp. 21-23, 2006.
  32. [32] A. M. Turing, “Intelligent machinery, a heretical theory,” Philosophia Mathematica, Vol.4, No.3, pp. 256-260, 1996.
  33. [33] A. M. Turing, “The chemical basis of morphogenesis,” Philosophical Trans. of the Royal Society of London B, Vol.237, No.641, pp. 37-72, 1952.
  34. [34] D. Berrar, N. Sato, and A. Schuster, “Quo vadis, artificial intelligence?,” Advances in Artificial Intelligence,
    doi:10.1155/2010/629869, 2010.
  35. [35] C. A. Lowery, T. J. Dickerson, and K. D. Janda, “Interspecies and interkingdom communication mediated by bacterial quorum sensing,” Chem Soc Rev. Vol.37, No.7, pp. 1337-1346, 2008.
  36. [36] J. Cello, A. V. Paul, and E. Wimmer, “Chemical synthesis of poliovirus cDNA: generation of infectious virus in the absence of natural template,” Science, Vol.297, pp. 1016-1018, 2002.

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