Confusing surveillance systems

 

Simple surveillance systems can be easily attracted, confused and distracted from our brothers and sisters by blogging and spreading nonsensical stories using keywords that trigger these systems on social notworks.

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And …

… more “sophisticated” surveillance systems are not so easily fooled. I have not looked inside these systems but I would not be surprised if Bayesian systems are used. Just an additional challenge.

The greatest vulnerabilities of such systems are 1) their inability to separate ignorance from disbelief and 2) assuming their approach provides a universal logic of induction and *** theirs is IT *** of course. Heh!

Exploiting Bayesian vulnerabilities for confusing surveillance systems

  • Create fragments of inductive logic that represent ignorance (evidential neutrality).
  • Use competing systems of inductive logic.
  • Use inductive logic of indeterministic systems for which the probability calculus fails.
  • Use inductive inferences that are warranted by facts that prevail locally.

Background information

  • Cosmic Confusions: Not Supporting versus Supporting Not-“. Philosophy of Science. 77 (2010), pp. 501-23., this manuscript is an extensively revised version of “Cosmology and Inductive Inference: A Bayesian Failure,” Prepared for “Philosophy of Cosmology: Characterising Science and Beyond” St. Anne’s College, Oxford, September 20-22, 2009
  • “Challenges to Bayesian Confirmation Theory,” Prepared for Prasanta S. Bandyopadhyay and Malcolm Forster (eds.), Philosophy of Statistics: Vol. 7 Handbook of the Philosophy of Science. Elsevier. Download final.
  • “Probability Disassembled” British Journal for the Philosophy of Science, 58 (2007), pp. 141-171. Download preprint.
  • “There are No Universal Rules for Induction,” Philosophy of Science, 77 (2010) pp. 765-77. Download.
  • “Ignorance and Indifference.” Philosophy of Science, 75 (2008), pp. 45-68. Download final version.

 


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