Theory of Knowledge - Course Companion for Students Marija Uzunova Dang Arvin Singh Uzunov Dang

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spread of knowledge. The losses from suchthecan be incalculable and irrecoverable.incidentsthis reason, the Internet Archive has partialForof itself in several physical locations acrosscopiesgeopolitical contexts. What can we learndifferentthis project both for preserving humanfromas well as decentralizing the controlknowledgeknowledge? Is decentralizing the control ofofethos of the Internet Archive is that in mattersTheknowledge, access drives preservation. In otherofthe best way to preserve knowledge is towords,that it is accessible and in use. Inversely,ensuresays, “If you take things away from aKahleit’s as if it doesn’t exist”. His work isgeneration,not on a secure vault for safekeeping,modelledon a public library that is designed for use.butare potential barriers to use, and thereforeWhatto access, in a repository of humanbarriersproject’s goal is bold: universal access toTheknowledge. The Internet Archive is not justallthe internet, but digitizing books,backing-upand movies as well as recording over 100musicchannels 24 hours a day. The technologytelevisiondigitize recorded material already exists, but istoon the internet worth preserving, justeverythingwe are able to? How can we anticipate,becausewhat knowledge will be useful in thecorrectly,And can technologies to search andfuture?digital culture is an intensely visualToday'sPeople appear in photos produced onculture.own devices, tagged by friends, capturedtheirsecurity cameras, in the backgroundbyor otherwise) in the photos of(intentionallyin public spaces—all of which getstrangersinto streams of data. When these getsiphonedwith powerful face-detection technology,coupleddigital technologies see muchHowever,than physical appearance. They includemoreinsights into our likes, uses ofbehaviouraland reactions, interactions andlanguagealgorithms in criminal justice that calculateoflikelihood an accused will reoffend (calledtherisk): this risk score feeds into otherrecidivismthat suggest the length of the prisonalgorithmsThe tragic irony is that longer prisonsentence.have been shown to increase the ratessentencesrecidivism. And so, technology in the USofsystem has been shown to discriminateprisonethnic and economic class lines. People ofalongtend to receive a higher recidivism riskcolourwhich means they tend to be given longerscore,sentences, which, due to the internalizedprisonof prison, means they have fewerexperienceonce released and contribute toopportunitiesrecidivism risk scores for others in theirhigherThis vicious feedback loop isneighbourhood.of many that has resulted in the grosslyoneincarceration of black men in thedisproportionateStates. To dive deeper into this example,Unitedthe link to Cathy O’Neil's talk at Googlefollow“Weapons of Math Destruction”. Sheaboutrecidivism risk specifically from 28:40.discussesterms: Cathy O’NeilSearchof Math Destruction”“Weaponsterms: ProPublicaSearchbias riskMachinethe link to the article Machine Bias:FollowAssessments in Criminal Sentencing”RiskPredictive knowledge produced by1.models has limitations andcomputeras does predictive knowledgecaveats,by humans. How can we knowproducedmachine predictions are more orwhetherreliable than human ones?lessWhat kind of knowledge is necessary2.be able to evaluate the validity andtoWho should decide what assumptions a3.like this should be based on?modelIII. Methods and toolsIII. Methods and toolsknowledge a desirable thing?knowledge such as the Internet Archive?YouTubeFor discussionMachine biascatalogue such a vast collection keepup?assessmentsIII.3 Using data to know humansand consider the following questions.individuals have good reason forconcern.neutrality of risk assessment algorithms?relationships. Consider, for instance, the use71

2013 a team of researchers published resultsInthey could predict personality traitssuggestingFacebook Likes. Their method—calledusingmodelling—laid the foundationpsychographicwhat has been called microtargetingforwith in depth in Chapter 2, IV.2). The(dealtKosinski, Stillwell, Graepel andresearchers,summarized their findings as follows.Youyoureligious and political views, personalityethnicity,intelligence, happiness, use of addictivetraits,parental separation, age, and gender.substances,model correctly discriminates betweenTheand heterosexual men in 88% ofhomosexualAfrican Americans and Caucasian Americanscases,95% of cases, and between Democrat andinin 85% of cases ...RepublicanPercentiles3.7 shows that the personality traitsFigureage of Facebook users is associated withandthey Like on Facebook. For example, thewhatof users who Liked “The Colbertextraversionbasic premise was that individualsTheirbe profiled from their FacebookcouldFigure3.8 shows how accurately theLikes.claim to be able to predict commonresearcherscharacteristics. They tested thepersonalof their predictions by comparing itaccuracyusers’ self-reported personality assessments,tofound that their model predicted genderandrace with over 90% accuracy. It predictedanddetails such as sexual orientation,otheraffiliation and religion with overpolitical80%accuracy.the lengths to which this thesisGivenbeen implicated in alleged politicalhasit is worth considering themanipulation,and methodology behind it.assumptionsscience was fairly straightforward; whatTherevolutionary were the massive amountswas3III. Methods and toolsCase studyDigital technology, social networksand psychometricsaccessible digital records of behavior,…EasilyLikes, can be used to automaticallyFacebookaccurately predict a range of highly sensitiveandattributes including: sexual orientation,personalReport” was relatively low.(Kosinski et al 2013)of data the researchers could use to discernOpenness Conscientiousness Extraversion Agreeableness Stability Age100100100100100100Mitt RomneyMitt RomneyThe ColbertReportNicki Minaj909090909090Mitt RomneyCampingCamping808080808080The ColbertBarackReportBarack ObamaReportObama7070Barack Obama70Nicki Minaj70Cuddling7070CuddlingThe Colbert6050Hello KittyCamping6050CuddlingReport60506050Barack ObamaReport6050Cuddling6050CuddlingNicki MinajHello KittyHello Kitty404040404040Nicki Minaj303030303030Hello KittyHello Kitty202020202020Mitt RomneyReport101010101010000000Figure 3.7 Personality traits, age and Likes on Facebook72

2013 a team of researchers published results

In

they could predict personality traits

suggesting

Facebook Likes. Their method—called

using

modelling—laid the foundation

psychographic

what has been called microtargeting

for

with in depth in Chapter 2, IV.2). The

(dealt

Kosinski, Stillwell, Graepel and

researchers,

summarized their findings as follows.

Youyou

religious and political views, personality

ethnicity,

intelligence, happiness, use of addictive

traits,

parental separation, age, and gender.

substances,

model correctly discriminates between

The

and heterosexual men in 88% of

homosexual

African Americans and Caucasian Americans

cases,

95% of cases, and between Democrat and

in

in 85% of cases ...

Republican

Percentiles

3.7 shows that the personality traits

Figure

age of Facebook users is associated with

and

they Like on Facebook. For example, the

what

of users who Liked “The Colbert

extraversion

basic premise was that individuals

Their

be profiled from their Facebook

could

Figure3.8 shows how accurately the

Likes.

claim to be able to predict common

researchers

characteristics. They tested the

personal

of their predictions by comparing it

accuracy

users’ self-reported personality assessments,

to

found that their model predicted gender

and

race with over 90% accuracy. It predicted

and

details such as sexual orientation,

other

affiliation and religion with over

political

80%accuracy.

the lengths to which this thesis

Given

been implicated in alleged political

has

it is worth considering the

manipulation,

and methodology behind it.

assumptions

science was fairly straightforward; what

The

revolutionary were the massive amounts

was

3III. Methods and tools

Case study

Digital technology, social networks

and psychometrics

accessible digital records of behavior,

…Easily

Likes, can be used to automatically

Facebook

accurately predict a range of highly sensitive

and

attributes including: sexual orientation,

personal

Report” was relatively low.

(Kosinski et al 2013)

of data the researchers could use to discern

Openness Conscientiousness Extraversion Agreeableness Stability Age

100

100

100

100

100

100

Mitt Romney

Mitt Romney

The Colbert

Report

Nicki Minaj

90

90

90

90

90

90

Mitt Romney

Camping

Camping

80

80

80

80

80

80

The Colbert

Barack

Report

Barack Obama

Report

Obama

70

70

Barack Obama

70

Nicki Minaj

70

Cuddling

70

70

Cuddling

The Colbert

60

50

Hello Kitty

Camping

60

50

Cuddling

Report

60

50

60

50

Barack Obama

Report

60

50

Cuddling

60

50

Cuddling

Nicki Minaj

Hello Kitty

Hello Kitty

40

40

40

40

40

40

Nicki Minaj

30

30

30

30

30

30

Hello Kitty

Hello Kitty

20

20

20

20

20

20

Mitt Romney

Report

10

10

10

10

10

10

0

0

0

0

0

0

Figure 3.7 Personality traits, age and Likes on Facebook

72

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