I see those biases a lot, and use finding my own sloppy patches as keys to where I'll discover new things. One exceptionally common bias of current interest is the tendency of scientists to ignore the time lags between cause and effect, that when not ignored lead to the discovery of the independent developmental process that are functional necessities in the occurrence of the response. An example? Any process of entropy, seems to requires the local development of individual self-organizing complex systems to carry it out, and when you look you find them. I've been reading 'Linked' by Barabasi, and thoroughly enjoying his insightful discoveries of telling structural patterns in the topology of networks, and how the distribution of densely connected hubs changes network behaviors entirely, among other things. What's totally remarkable is that despite observing that this 'scale free' distribution of connections, as it has become called, develops as the network adds and then abandons links (branching followed by selection) to produce the final form, he attributes no causal contribution to the direct process by which system producing the network develops, i.e. to what happens. Instead he extremely consistently phrases the cause of the pattern as being the benchmark indicator of having an inverse square distribution of nodes with high degrees of connection, a statistical property discovered after the fact. I'm going page after page after page wondering when is he ever going to credit the evolutionary process by which the pattern develops in the overall causal scheme of things,... and the answer seems to be, well, never!! It's stunning how so many hugely productive insights are so obviously being looked at squarely and then skipped over again and again and again, evidently just not fitting the question and purpose of his otherwise brilliantly observant examination of the facts! I'm wondering if the blind spot this exposes is embedded in our tools, since he obviously sees the actual behaviors producing the patterns and is very creative in identifying the resultant patterns associated with them, but is just not drawn to studying them. If used for the purpose, these same patterns would lead us to investigate how the direct causal mechanisms do actually operate, in detail, but he keeps consistently declaring the resultant pattern to be the cause and the behavior to not exist. Just g.d. remarkable! Could it be that our forbearers were just so totally obsessed with control, that our traditional tools were built in a way that can't describe anything else?
Phil Henshaw ¸¸¸¸.·´ ¯ `·.¸¸¸¸ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com <http://www.synapse9.com/> -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Roger Critchlow Sent: Sunday, August 05, 2007 12:47 PM To: The Friday Morning Applied Complexity Coffee Group Subject: [FRIAM] The Verifier Here's an article about a kind of meta-analysis that looks for cognitive biases among groups of researchers. http://www.nytimes.com/2007/08/05/business/yourmoney/05frame.html?ref=bu siness <http://www.nytimes.com/2007/08/05/business/yourmoney/05frame.html?ref=b usiness> -- rec --
============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
