The Consciousness’ Drive: Information Need and the Search for Meaning

241 Pages·2018·13.581 MB·English

by  Charles Cole

Charles Cole
The Consciousness’
Drive
Information Need and the Search
for Meaning
’
The Consciousness Drive
Charles Cole
’
The Consciousness Drive
Information Need and the Search for Meaning
CharlesCole
McGillUniversity
Montreal,QC,Canada
ISBN978-3-319-92455-7 ISBN978-3-319-92457-1 (eBook)
https://doi.org/10.1007/978-3-319-92457-1
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Preface
Needinginformationandsearchingforthatinformationarethingswedoconstantly
everydayofourwakingandsleepinglives.Wehavealwaysdonethisasaspecies:
needing,finding,andusinginformationtogoaboutourbusiness,togetthroughlife
relatively intact. With Google and mobile phone technology, this sort of low-level
informationsearch—thelocationofournextappointment,theweatherforecast—has
becomemoresystematized.Wehavetoclearlyformulateourinformationneedinto
aquery,thenselectwhichsourceintheresultslististhemostrelevant.Butthereisa
difference with the advent of this systemization of information search. The infor-
mation economy is, with the ubiquity of high-level information at our finger tips,
transitioningintotheartificialintelligence(AI)economywiththeemphasisonnew
knowledgesearchingandproduction.Googlenowallowsustoexploreinformation
whenweneedtoproducenewknowledge.Wehavetoconstructthenewknowledge
from the information but the effect of the search is the new knowledge production
insideourheads.
Thesecanbesmallknowledgeproductioneventslikeidentifyingaproblematthe
office.Butthesenewknowledgeproductioneventscanbeimportantlikediscover-
ingcancerdrugsorsolvingarocketproblemsowecangotoMars.
Theproblemwithusinginformationsearchtoproducenewknowledge,bothona
small,day-to-daybasis,andforthemuchlargermoreimportantissues,isthatweas
humansdon’tknowourreal,deep-levelinformationneedinthesesituations,sowe
havetomakedowithacompromised-leveloftheneed,wherewehavetoguessat
whatwedon’tknowbutneedtoknow.
Ibegantolinkinformationneedlevelsandknowledgeproductioninmyprevious
book(Cole2012).Butthatbookhadmanyreferencestopreviousresearchandwas
aimedatthescholarcommunity.
In this book, I wanted to make the writing more conversational for a broader
readership, keeping my references to research material to the bare minimum.
I copied the structure of a detective novel, building my argument to a climax in
Chap. 16. For our video game, video-on-demand times, I visualized the ideas that
form the structure of the book’s thesis or argument in over 90 original diagrams.
v
vi Preface
Butaboveall,Isetthelinkbetweeninformationneedandknowledgeproductionin
evolutionarypsychology,aperspectivepeoplearereadingandtalkingabout.Istep
back from the minutiae of cognition togo as big-picture as humanly possible. In a
way, it is a return to our sources: how we humans naturally think, and why we
naturallysearchfornewinformationbecauseourconsciousnessdrivesustoneedit.
There isanotherreason for mychange inemphasis betweenthe2012book and
this one, an intervening factor: the rise of artificial intelligence (AI) as a topic of
general discussion in the newspapers. The New York Times predicts that in a little
over a decade from now up to a third of US jobs will be transformed by AI (Lohr
2017). AI-equipped devices or machines can now learn to respond to new stimuli
they find in the environment, for which they haven’t been programmed for in
advance, by collecting large quantities of environmental data and ascertaining
patterns from those data. We will soon be in theworldof 2001: A Space Odyssey,
director Stanley Kubrick’s prescient 1968 prediction of Hal, a super knowing
AI-equippedcomputer,takingcontrolofthespaceship.
What became evident to me is that the sciences involved in information search
(computer science and information science, as well as cognitive science and psy-
chology)mustreallylookathowhumansrelatetotheworld,theirconsciousness,to
distinguish human thinking from the computational thinking of the AI-equipped
machinesthatwillsoonbelivingandworkingamongstus.
I asked myself: what is the uniquely human factor in finding and using new
information to produce new knowledge. I’m thinking about big knowledge events
underlying discovery, inventions and creativity. What is this exceptional human
factorthatcan’tbeimitatedbyAIalgorithms?Isthereinfactanunderlyingaspectof
ourthinkingthatcan’tbeimitatedbythesemachines?
Humans actually ignore a great deal of data around them when they think. We
knowwhatinformationisgenerallyrelevanttoourtask,andignoretherest.Thatis
whywearesoefficient,soabletomakedecisions,usuallythecorrectone,quickly
and without fuss. AI can certainly do this, and eventually it will make these
calculations about what is relevant and what is not relevant faster and more effi-
cientlythanwecan.IexaminethisinPartIIofthisbook.Butthatisonlyhalfofour
humanexceptionality.Whatistheotherhalf?
The other half of our consciousness’ exceptionality is why we need new infor-
mation,whyweareconstantlysearchingforit,notjusttogetby,buttoproducenew
knowledge.Weneedinformationtoperformtaskswehavealreadydone.Machines
candothis.Butwehumansalsoseemtoneedinformationforthingswedon’thave
animmediateorevenapotentialusefor.Thisisthemoremysteriousx-factorinour
human species makeup that cannot be imitated by AI algorithms. It is something
aboutourconsciousness,itsdriveorintentioninseekingoutnewinformationinthe
world around us that makes us an exceptional species. Somehow, the same world
we’velivedinfor hundredsofthousandsofyears, changes.Nottheworld, butthe
way we see it. We see different information. We can not only recognize this new
information, but we can bring it inside us where we use it to construct new
knowledge.
Preface vii
Search engines must be designed in consequence in our new knowledge econ-
omy,shiftingthesearcher’ssearchfromwhatshealreadyknowstowhatshedoesn’t
yetknowbutneedstoknow.Thisisthetruegenesisofnewknowledgeproduction,
notthepatternrecognitionlearningofAI-equippedrobots.
That is the perspective on information need, information search, and search
enginedesigntakeninthisbook.
* * *
Thebookisstructuredinthreeparts,witheachpartcontaininganIntroductionand
Conclusionthatrelatesthetheoriesandmodelsofthebooktotherealconditionsofa
searcherconductinganinformationsearchusingasearchengine:
(cid:129) Part I defines the exceptionality of human consciousness and its need for new
information, how we frame our intersection with the world unlike any other
species.
(cid:129) Part II investigates the problem of finding our real Q1-level information need
duringinformationsearch:howweareblockedfromfindingitbyourexceptional
abilityatframingourintersectionwiththeworld.
(cid:129) PartIIIelaboratesthebook’ssolutiontothisframingproblemanditsoperational
implications for search engine design for searchers whose objective is the pro-
ductionofnewknowledge.
Therehavebeenmanyinfluences inmy25-yearcareer asaninformationscien-
tist.IwouldliketoacknowledgeTDWilson,CarolKuhlthau,BrendaDervin,Tefko
Saracevic, Nicholas Belkin, Amanda Spink, and Marcia Bates. And there were
professorsduringmyMcGillundergraduatedaysIwouldalsoliketoacknowledge,
astheirteachings,whichIdidn’tunderstandatthetime,haveunconsciouslyguided
meinmyresearch:PeterHoffmann(Germanhistory)andCharlesTaylor(philoso-
phy).
Montreal,QC,Canada CharlesCole
Contents
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
PartI HumanExceptionality
2 HumanExceptionality:HowWeSeeOurselvesinRelation
totheWorld. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3 Framing:LessonsfromVermeer. . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4 EpisodicMemory:LessonsfromtheScrubJays. . . . . . . . . . . . . . . 35
5 EpisodicMemory:SubjectiveTime-Travel. . . . . . . . . . . . . . . . . . . 43
6 Episodic-to-MimeticTransition. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
7 Framing:TheMimetic-to-MythicTransition. . . . . . . . . . . . . . . . . . 65
8 Framing:TheMythic-to-TheoreticTransition. . . . . . . . . . . . . . . . . 81
PartI Conclusion
PartII TheFramingProblem
9 ProblemSetup:Minsky’sFrameTheory. . . . . . . . . . . . . . . . . . . . . 109
10 IndividualFrameLevel:Meno’sParadox. . . . . . . . . . . . . . . . . . . . 121
11 GroupFrameLevel:InformationAvoidance. . . . . . . . . . . . . . . . . 129
12 NationFrameLevel:TheDarkSide. . . . . . . . . . . . . . . . . . . . . . . . 143
PartII Conclusion
ix
x Contents
PartIII TheFramingSolution
13 Solution:OpeningtheInformationLoop:Constructing
InformationChannels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
14 Solution:Belief-Begets-Knowledge—Definitions. . . . . . . . . . . . . . . 181
15 Belief-BasedInformationSearch. . . . . . . . . . . . . . . . . . . . . . . . . . . 193
16 TheModeloftheConsciousness’Drive:InformationNeed
andtheSearchforMeaning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
17 ConclusiontoBook:TheSearchforMeaning
andtheOpen-EndedQuestion. . .. . . .. . . .. . . .. . . .. . . . .. . . .. 223
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235
ProperNamesIndex. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
SubjectIndex. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Chapter 1
Introduction
Wetaketheconsciousnessapproachtoinformationneedandinformationsearchin
this book. The opposite is the computational approach, which is artificial intelli-
gence’s(AI)viewthatitcanimitatehumanthinking.TheAIviewasksandanswers
in the affirmative: How do humans think and can it be put into a machine that
imitateshumanthinking?
AI research began in 1936 when Alan Turing (1936–1937) investigated the
possibility of developing a machine that could imitate human intelligence, “a
thinking machine,” later called the universal Turing machine. Turing envisaged
that one day computers would in fact be able to perfectly imitate human thinking.
In fact, he even developed a test that would establish this eventuality, called the
Turing (1950) test, which he described in his famous article written for the
journalMind.
TheTuringtestplacesahumanquestionerinanisolatedroom;inasecondroom
are a human and a Turing-type machine. Can the questioner tell whether it is the
machineorthehumanthathasansweredherquestions?Ifshecannot,themachine
passes theTuring test. The machine so perfectly imitates how humans think that it
canbesaidtothinkthesamewayasahuman.Thephysicist-mathematicianRoger
Penrose (1997) asked: Are we humans just computational thinkers similar to a
Turing-typemachineorishumanthinkingsomethingelse?
We diagram a computational-thinking approach to human thinking in Fig. 1.1.
Themachine/humanisprogrammedwithinstructiontablestorecognizeallpossible
expected stimuli from the outside world, and the machine must compute the most
appropriateresponse,probablythemostefficientresponse,whichiscontrolledbya
completesetofrulesofconductorbehaviorforeachpredictedstimulus.InFig.1.1,
weusetheexampleofatrafficaccident.Soforthestimulus:
IfEventC—“trafficaccident,”
themachinecomputestheresponse:
ThenResponseC—“trafficaccident:mostefficientresponsebehavior.”
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C.Cole,TheConsciousness’Drive,https://doi.org/10.1007/978-3-319-92457-1_1