Columbia University Libraries Journals
Not a member yet
    6467 research outputs found

    Ben Sorer U’moreh: Mishnah or Midrash? That Is The Question

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    What differentiates Midrash from Mishnah? In Midrash, usually a verse is referenced and is interpreted to teach us something, while in Mishnah the rules that we are supposed to follow are debated by the Tannaim and plainly stated. But what is the relationship between Midrash and Mishnah and, further, is it possible that the Mishnah itself engages in the act of ‘midrash?’ This paper will attempt to answer this question, shedding light on the nature of Mishnah and Midrash as religio-legalistic texts in the case of the ‘ben sorer u’moreh.’ &nbsp

    Autism Spectrum Disorder and Face Identity Recognition Deficit across Ages

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    The purpose of this review was to assess the face identity recognition deficit and the developmental difference that manifested in autism spectrum disorder (ASD) compared to their typically developing (TD) peers. Based on the meta-analysis using a random-effect model of 94 studies, with 144 effect sizes, for both adult and pediatric subjects with simultaneous and delayed face identity recognition paradigms, the underperformance in ASD was significant and persistent across ages. In addition, a higher level of deficit was found in adult ASD when performing simultaneous face-matching tasks while other subgroups showed homogenous effect sizes. This suggested a dissociation between the difficulties of the two mechanisms of face recognition: face perception (perceiving identity from the face with minimal memory load required) and face memory (recall of identity from the face that requires memory load), which was only shown in adults but not in children. The result indicated the possibility of using face identity recognition deficit as a diagnostic trait for ASD

    Social, Behavioral, and Academic Ramifications of Video Game Playing in College

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    The purpose of this research project is to determine whether video game usage influences the psychological well-being of college students. This project seeks to understand technology usage habits among students and whether this affects school performance. Previous research suggests video games may be used to treat psychological issues such as anxiety. Self-report studies note video games were helpful in certain populations in coping with stress, developing positive social behaviors, and improving cognitive abilities (Carras et al., 2018; Nuyens et al., 2019; Schuurmans et al., 2018;). Since psychological well-being is a crucial factor in academic performance (Carton & Goodboy, 2015; Punia & Malaviya, 2015), the current study will examine potential relationships between gaming and college GPAs. Poor habits related to technological usage may lead to negative mental health outcomes. A survey examining these factors was completed by college students at Texas Woman’s University. The survey was composed of questions from the Internet Gaming Disorder Scale, Psychological Wellbeing Scale, and Boundary Management Subscale. Data was tested using ANOVAs, a Tukey HSD test as a post hoc test, and Eta squared. The results of the data found gaming tendencies were not significantly associated with GPA but were associated with negative mental health outcomes and increased issues with technology boundary management. The study has marked limitations due to the lack of non-gaming survey participants and most respondents identifying as female. These findings may be useful for clinicians in treating addictive gaming tendencies. Future research should examine more diverse student populations

    Validity Inquiries in Second Language Assessment

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF

    An Exploratory Practice Study on the Use of Film Adaptation in the Tunisian Literature Classroom

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    This exploratory practice study examined the effectiveness of film adaptation in teaching a Shakespearean play, The Merchant of Venice, during the fall semester of 2022 at the Higher Institute of Languages, Gabès. Qualitative and quantitative data from third-year students majoring in English language, literature, and civilization, as well as teachers of English literature were collected through a questionnaire and two interviews. Questionnaire results indicated that the majority of students had a positive view of the film adaptation of the play in question, noting that it helped them overcome their anxiety when reading Shakespearean works and increased their motivation and engagement. The teachers interviewed highlighted the effectiveness of film adaptation in teaching literature, in general, and Shakespearean plays, in particular.&nbsp

    (ART)ificial Intelligence

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    The Portrait of Edmund de Belamy looks like it could almost be framed in a museum. The painting depicts a portly gentleman wearing a dark frock coat and a plain white collar, perhaps the attire of a clergyman. It would be a very dignified composition, except for the fact that the artwork appears unfinished—the facial features are blurred, large swaths of canvas remain unpainted, and up close, the paintwork becomes a grid of mechanical-looking dots, resembling pixels. Even more strangely, in place of the artist’s signature, a cursive script scrawls out what appears to be an algebraic formula (see fig. 1).  Fig. 1. Portrait of Edmond de Belamy. 2018. As one may have guessed, this portrait was not a product of the human mind. Rather, it was created by an artificial intelligence using the formula at the bottom right corner. When the Portrait of Edmond de Belamy went under the hammer in Christie’s Prints & Multiples sale on October 25, 2018, it sold for an incredible 432,500,signalingthearrivalofAIarttotheinternationalauctionstage(“IsArtificialIntelligenceSettoBecomeArt’sNextMedium?:Christie’s”).Thesale,however,sparkedimmediatecontroversy,andartadmirersaroundtheworldallaskedthesamequestion:shouldthePortraitofEdmonddeBelamy,andothercomputer−generatedartwork,beconsideredart?   Toartconnoisseurswhovaluethestirringemotionsbehindeachpaintingoveritstechnicality,theanswerwasno.Trueart—oratleastartworthyofnearlyhalfamilliondollars—isaboutpassionatehumanexpression,epitomizedinthemasterpiecesof“geniuses”likeLeonardoDaVinciandVincentVanGogh.AccordingtoJonathanJones,anartcriticforTheGuardian,“Computerswouldneedtoreplicatehumanconsciousnessbeforetheycouldreplicatethefunnythinghumansdocalled‘art’”(“APortraitCreatedbyAI”).HearguesthatbecauseAIsareincapableofemotion,theycannotmeaningfullyreplicatecertainqualitiesthatoldmasterpieces,suchastheMonaLisa(1503)orStarryNight(1889),dosowell—andthatiftheyeventuallycan,itwouldcertainlymeanthedoomofbothartisticexpressionandhumanity.Suchfearpreventsseriousdiscussion,andwithmanyprofessionalpaintersexpressingtheconcernthatcomputerswillputthemoutofwork,wemightexpectthatcomputer−generatedartwouldonlyreinscribetheestablisheddivisionsbetweenthemechanicalandthecreative.However,inaworldgovernedbythenewaestheticsbornfromdigitalization,technologyhasalreadyrevolutionizedtheartmarketinnumerousways:ithasprovidedartistswithaversatilemediumandawaytogainvisibility,andhasgivenartenthusiastsaccesstoawiderrangeofart,reshapingthewaythepublicinteractswithit.Byallowingtechnologytocontributetoacreativeproductionwithahigherdegreeofautonomy,computer−generatedartnotonlyfurtherblurstheboundariesbetweentechnologyandart,providingnewinsightsintohowtraditionalelementsofvisualartmaytakeforminnewtechnologicalmedia,butalsoenablesanewartisticstylethateschewscategorization,fusingawiderangeofpictorialconventionsintosurprisingnewforms.Contrarytowhatsomeskepticalartcriticsbelieve,AIsthatcreateartaremorethancapableofhavingoriginalartisticvision.Suchalgorithmsarecalledcreativeadversarialnetworks(CANs),atermcoinedbyAhmedElgammal,thedirectoroftheArtandArtificialIntelligenceLaboratoryatRutgersUniversity.CriticssuchasJonesoftenusethefactthatCANsaretrainedondatasetsofexistingartworkstomakethecasethatAIscanonlymimicart,butotherwisedon’thavethecapacitytoproducepowerfulstimuliinartsuchasnoveltyorsurprise.However,thisobjectionisagravemisunderstandingofthenatureofCANsandintelligentmachines.Perhapsnoonewouldbetterenumeratethediversityofcomputerbehaviorthanthefatherofmodern−daycomputerscience,AlanTuring,oneofthefirstscientiststoexplorethepossibilityofcreatingamachinecapableofhuman−likeintelligence.Inhisarticle“ComputingMachineryandIntelligence,”Turingpointsoutthefallaciesintheideathatmachines“can‘neverdoanythingreallynew’...cannever‘takeusbysurprise’”(450).Turingstatesthatthisviewemergesfromthemistakenassumptionthat“assoonasafactispresentedtoamindallconsequencesofthatfactspringintothemindsimultaneouslywithit”(451).Inotherwords,hearguesagainsttheideathattheoutputofaprogramcanalwaysbedeterminedbytheinput.Infact,withintelligentmachines,becauseitisimpossiblefortheprogrammertoknowthestateofthemachineateachmomentofthecomputation,theprogrammoreoftenthannotproducesaresultthatisunintentionalorunpredictable.TheprogrammersofCANstakeadvantageofthisuncertaintytoensurethatthealgorithmsproducenovelty,somethingdifferentfromtheimagesinthetrainingdataset,throughwhatTuringcallsa“randomelement”(459).InthePortraitofEdmonddeBelamy,weseetherandomelementtakeeffectintheindistinctnessofEdmonddeBelamy’sfacialfeatures,portrayingthesubjectinamannerthatdepartsfromtheconventionaldepictionsof18th−centuryportraits.ThereissomethingweirdlycontemporaryinthedeliberatedistortionofEdmond’sface,andtheabstractstylespresentinmanyothercomputer−generatedartworksseemtosuggestthatAIstendtoproduceworksthatmirrorthecourseofarthistory—art’slongprogressionfromfigurationtoabstraction.WhatcriticsfailtounderstandisthatthepurposeofCANsstudyingpatternsinexistingartworksisnottogenerateimagesconsistentwithsuchart,buttosearchforwaystotransposetheimageryfromthemixofinfluencesintonewworkswherecolorandformundergoreassessment.Thegreatestspacefornovelty,forcomputersandhumansalike,liesinthepotentialfuturetrends,intheunseen,andwithAIsseeminglyabletomodelart’strajectoryfromthetraditionaltothenew,it’slikelythatthenextoriginalartisticmovementwillbebornfromcomputer−generatedart.Unfortunately,thenewisoftenseenasathreattotheold,andthePortraitofEdmonddeBelamy,asaproductofartandscienceinconjunction,posesachallengetothetraditionalideaofthe“artisticgenius.”Artisticgeniushaslongbeenbelievedtobeepitomizedbythemasterpiecesofthegreats,whichmanyregardasshiningrepresentationsoftheidealsfromtheirrespectiveperiods,fromtheRenaissancetoRomanticismtoSurrealism.Whilemanyartmovementscoincidedwithsignificantadvancementsinmathematicsandsciencesandoftendrewinspirationfromsuchevents,theemphasisofthesegreatworkstypicallyliesintheirimaginativequalities.Forinstance,Romanticartoftendelvesintotranscendentalthemes,whileSurrealistartfeaturesdreamlikeimagery.Consequently,theconceptsofartandinspirationareoftenspokenofinmysticalterms,elevatedtoastatusbeyondtherealmofscienceandtechnology.Infact,theclaimthatJohannesVermeer,theartistwhofamouslypaintedtheGirlwithAPearlEarring(1665),usedsomesortofopticaldeviceandmirrortechnologytohelpaccuratelyrecreatesceneswithinhispaintingscauseddeepanguishformanyarthistoriansandcritics,whoaccusedtheallegationofbeing“adepressingattempttoreducegeniustoatrick”(Jones,“DIYVermeerDocumentary”).What,then,constitutesthisso−called“genius”? Forcenturiesofarteducation,the“artisticgenius”tropehasalwaysconsistedoftheWesterncanonofartistssuchasLeonardodaVinci,Michelangelo,ClaudeMonet,andJohannesVermeer,anunderstandingsocloselylinkedtotheprivilegesandtraitsassociatedwithwhitenessandmasculinitythatitsuggeststheverynotionof“genius”issociallyconstructed.IanHackingexplainsinhisessay“MakingUpPeople”thatitishumannaturetoclassifythings,thoughtheactofclassificationinmanycases“breedsconceptualconfusion,”referringtohowwehavedifficultygivingjustconsiderationtoobservedbehaviorsthatdonotconformtoourunderstandingofsomething.HelamentsthatinattemptingtomeasuregeniusthroughstatisticalmeanssuchastheIQtest,wehaveinturnabolishedgeniusfromoursociety.Hackingmakesanargumentagainstourclassificationofgenius,yetironically,intheprocess,heimpliesthattruegeniusistobeassociatedwiththegreaterasofart,reaffirmingtheidealizedclassificationof“genius”thatmanycriticsofAIartusetopreventcomputer−generatedartworkfrombeingconsideredart.Theideathatartisticgeniusisavalidclassification,however,directlycontradictsHacking’spointabout“real”and“finite”kinds.HackingbringsupJohnStuartMill’sargumentthata“realkind”isaclassificationinwhichthemembershave“innumerablefeaturesincommon,”whilea“finitekind”isaclassificationinwhichmembershaveverylittleincommon.Forexample,ourspecies,thehomosapiens,isarealkindbecausewesharemanybiologicalfeaturesandcharacteristics,whereasracesarejustfinitekindsbecausemembersofdifferentraceshaveonlytheirraceasacommonality.Uponcloseexamination,theoldmastersregardedasartisticgeniuseshavefewsimilarities;thediverserangeofstylesandexpressivemanifestationsthattheirartworkscontainreflectstheirexistenceassubjectsofdifferentsocialandculturalsettings,artistictraining,andschoolsofthought.“Artisticgenius”isthereforemerelyafinitekind,makingthecurrentdefinitionof“greatness”inartlessabouttheaestheticsoftheworkproducedoreventheintentionsbehindthework,andmoreaboutwhiteness,elitism,maleness,andEurocentricity.Theunderlyingissueisthat“artisticgenius”haslongbeencenteredonthemythosoftheartistsratherthantheartworksthemselves,afactthathasalmostalwaysworkedagainstwomenandartistsofcolorandnowworksagainstartificialintelligences.Anydivergencefromrealityintheartist’sdepictiontendstoholdsignificance,butonlyifthatartistisaman.1Forinstance,thedistortionswithinthePortraitofEdmonddeBelamygreatlyresembleGlennBrown’sart−historicalappropriations(“Biography”),yetwhileGlennBrown’sartispraisedforitstechnicalvirtuosityandpassion,thePortraitofEdmonddeBelamyisunfairlycondemnedtobeapoorpasticheofgenius. Toovercomethisbiasrequiresseismicsocialshifts,areanglingofhowweviewarthistory—asahistoryoftheart,ratherthanoftheartists.In“AutomatingGender,”JackHalberstamencouragesustoconfrontourpre−existingideasregardingWesternsociety’sgrandnarratives,whichinartisthemyththattherearenear−deitiesofcreativewisdom,asuperiorkindofhumanitythatlivesamorerarifiedhumanexperience—white,Europeanmaleartists.Theprevalenceofthismyth,endorsedbyarthistoriansandartcritics,placestheworksof“artisticgeniuses”inthehighestrealmofart,notonlyestablishingthelegitimacyofthesearthistoriansandcriticsasexpertsintheirknowledgeofsuchart,butalsoguaranteeingthestatusoftheartistsofthoseworksasoldmasters,perpetuatingagenderedtautologythattheartisticgeniusismalebecausemenaremostfittobeartisticgeniuses.Throughthelensofpostmodernism,whichHalberstamdefinesasamovement“embeddedwithinthemodernasinterferenceorinterruptionandasacomingtoconsciousnessofasubjectnolongermodeledupontheWesternwhitemale,”HalberstamaffirmsthatquestioningtheinterestsservedbytheperpetuationofsuchgrandnarrativeswillleadtotheconclusionthattheideasofartisticgeniusrelatedtothealluresofthegreatEuropeanartperiodsareunprogressive(446).Fromthepoliticsofartificialityprovidedbypostmodernism,itfollowsthat“genius”isasociallymanipulatedideathatactuallykeepsusfromgettingabetterunderstandingoftheartworksstudiedandfromexploringnewavenuesinart.Historicalemphasismustbereturnedtotheartratherthantheartist.IfwefocusontheartworkcreatedbyCANsratherthanthemechanicalnatureoftheCANsthemselves,perhapswecanseecomputer−generatedartaslessofachallengetotheprestigeofhuman−madeart,andmoreasanewartisticmanifestationthatsubvertscommondistinctionsbetweenartandtechnology,thecreativeandthemechanical,andtheoldandthenew.Inthissense,ifwenolongerfocusonthemindor,particularly,thebodybehindawork,wemightdiscoverthattheartworkscreatedbyCANsarejustasimpactfulasartworkcreatedbyhumans.PerhapsinthiscaseweshouldalsolooktoTuringforinspiration,andreplacethequestionunderconsideration,“Cancomputerscreateart?”,withanother:“Couldacomputercreateartworkthatcouldsuccessfullytrickahumanintothinkingitwascreatedbyanotherhuman?”IfasatisfactoryplayoftheTuringtest,atestdesignedtoseeifanevaluatorcandistinguishbetweenahumanandmachinethroughconversation,isenoughtoarguethatmachineintellectcanbecomparabletoman’s,thenawaytoprovethatcomputer−generatedartiscomparabletohumanart,surely,istoconductakindofvisualTuringtest,toshowtheoutputofthealgorithmstohumanevaluatorsandaskiftheycantellthedifference(seefigs.2−3). Fig.2.Barrat,Robbie.2018. Fig.3.Monet,Claude.PoplarsontheEpte,1891.Infact,AhmedElgammalconductedasurveyamongviewersinagalleryspecificallyarrangedforavisualTuringtest,wherecomputer−generatedartwaspresentedalongsidehumanart.Hefoundthatmanyhadadifficulttimedistinguishingbetweenhumanartandcomputer−generatedart,withseveralevenclaimingtobemoreinspiredbytheartdonebyamachine(“AIisBlurringtheDefinitionofArtist”).Theresultsofthepollaffirmthattheidentityofacreatordoesnotinherentlygrantmorevaluetoawork,andshowthatAIsaremorethancapableofcreatingaestheticandthought−provokingworksofart.Moreover,computer−generatedartworkslikethePortraitofEdmonddeBelamyareinhighdemandbycontemporaryartenthusiasts,asevidencedbythepassionatereceptionoftheportraitandthefinaldealingpriceofnearly5timesthepriceofanAndyWarholprintatthesameauction.Bothfactorsprovethatcomputer−generatedartcanbejustasartisticallyandsociallymeaningfulastraditionalart.ThesuccessofthePortraitofEdmonddeBelamydemonstratesthatthefutureofartisnowintertwinedwiththefutureoftechnology.Newtechnologiesnotonlybenefitartcriticsandarthistorians,forcingthemtoreevaluatetheirpreconceivednotionsof“artisticgenius,”butalsobenefitartandartists,creatingnewtoolsandmodesofexpression.WhatpeoplewhoworrythatAIartisaharbingerofhumanity’sdestructionoftenforgetisthattherearehumansbehindthemachines,acreatorbehindanothercreatorofart.Allcomputer−generatedartistheresultofhumaninvention,softwaredevelopment,andotherkindsofauthorship.Wemustacknowledgethatthehumanisalwaysthecreativeforcebehindtheworkandthatthecomputerisreallyjustahelpfultool,albeitalittlemorecomplicatedthanacanvasandapaintbrush.Butevenifthatwerenottrue—evenifAIscreatedartwithcompleteindependenceandautonomy—thevalueoftheirworkwouldnotchange.Technologicaldevelopmentstimulatessomuchofthecontinuedvitalityofart,andnewAIalgorithmslikeCANsarejustanothermeansbywhichartistscantransformartinpositiveways,justassomanyothertechnologieshaveinthepast. NOTEIt’simportanttonotethattherehavebeenexceptionswithintherealmofhumanartists:exceptionalindividualslikeBasquiatorSofonisba,whoarewidelyregardedas“artisticgeniuses”despitedeviatingfromconventionalartisticnorms,havemadegroundbreakingcontributionstotheworldofart.Therecognitionandappreciationoftheirworkhasenrichedourunderstandingofart,andhighlightstheimportanceofacknowledgingandcelebratingdiversetalentsinart,regardlessofthenatureoftheartists. WORKSCITED“Biography.”GlennBrown,Artlogic,https://glenn−brown.co.uk/biography/. Elgammal,Ahmed.“AIIsBlurringtheDefinitionofArtist.”AmericanScientist,https://www.americanscientist.org/article/ai−is−blurring−the−definition−of−artist. Hacking,Ian.“MakingUpPeople,”LondonReviewofBooks,vol.28,no.16,2006,https://www.lrb.co.uk/the−paper/v28/n16/ian−hacking/making−up−peopleHalberstam,Jack.“AutomatingGender:PostmodernFeminismintheAgeoftheIntelligentMachine,”FeministStudies,vol.17,no.3,1991,pp.439−460,https://www.jstor.org/stable/3178281.Jones,Jonathan.“APortraitCreatedbyAIJustSoldfor432,500, signaling the arrival of AI art to the international auction stage (“Is Artificial Intelligence Set to Become Art’s Next Medium?: Christie’s”). The sale, however, sparked immediate controversy, and art admirers around the world all asked the same question: should the Portrait of Edmond de Belamy, and other computer-generated artwork, be considered art?    To art connoisseurs who value the stirring emotions behind each painting over its technicality, the answer was no. True art—or at least art worthy of nearly half a million dollars—is about passionate human expression, epitomized in the masterpieces of “geniuses” like Leonardo DaVinci and Vincent Van Gogh. According to Jonathan Jones, an art critic for The Guardian, “Computers would need to replicate human consciousness before they could replicate the funny thing humans do called ‘art’” (“A Portrait Created by AI”). He argues that because AIs are incapable of emotion, they cannot meaningfully replicate certain qualities that old masterpieces, such as the Mona Lisa (1503) or Starry Night (1889), do so well—and that if they eventually can, it would certainly mean the doom of both artistic expression and humanity. Such fear prevents serious discussion, and with many professional painters expressing the concern that computers will put them out of work, we might expect that computer-generated art would only reinscribe the established divisions between the mechanical and the creative. However, in a world governed by the new aesthetics born from digitalization, technology has already revolutionized the art market in numerous ways: it has provided artists with a versatile medium and a way to gain visibility, and has given art enthusiasts access to a wider range of art, reshaping the way the public interacts with it. By allowing technology to contribute to a creative production with a higher degree of autonomy, computer-generated art not only further blurs the boundaries between technology and art, providing new insights into how traditional elements of visual art may take form in new technological media, but also enables a new artistic style that eschews categorization, fusing a wide range of pictorial conventions into surprising new forms. Contrary to what some skeptical art critics believe, AIs that create art are more than capable of having original artistic vision. Such algorithms are called creative adversarial networks (CANs), a term coined by Ahmed Elgammal, the director of the Art and Artificial Intelligence Laboratory at Rutgers University. Critics such as Jones often use the fact that CANs are trained on data sets of existing artworks to make the case that AIs can only mimic art, but otherwise don’t have the capacity to produce powerful stimuli in art such as novelty or surprise. However, this objection is a grave misunderstanding of the nature of CANs and intelligent machines. Perhaps no one would better enumerate the diversity of computer behavior than the father of modern-day computer science, Alan Turing, one of the first scientists to explore the possibility of creating a machine capable of human-like intelligence. In his article “Computing Machinery and Intelligence,” Turing points out the fallacies in the idea that machines “can ‘never do anything really new’ . . . can never ‘take us by surprise’” (450). Turing states that this view emerges from the mistaken assumption that “as soon as a fact is presented to a mind all consequences of that fact spring into the mind simultaneously with it” (451). In other words, he argues against the idea that the output of a program can always be determined by the input. In fact, with intelligent machines, because it is impossible for the programmer to know the state of the machine at each moment of the computation, the program more often than not produces a result that is unintentional or unpredictable. The programmers of CANs take advantage of this uncertainty to ensure that the algorithms produce novelty, something different from the images in the training data set, through what Turing calls a “random element” (459). In the Portrait of Edmond de Belamy, we see the random element take effect in the indistinctness of Edmond de Belamy’s facial features, portraying the subject in a manner that departs from the conventional depictions of 18th-century portraits. There is something weirdly contemporary in the deliberate distortion of Edmond’s face, and the abstract styles present in many other computer-generated artworks seem to suggest that AIs tend to produce works that mirror the course of art history—art’s long progression from figuration to abstraction. What critics fail to understand is that the purpose of CANs studying patterns in existing artworks is not to generate images consistent with such art, but to search for ways to transpose the imagery from the mix of influences into new works where color and form undergo reassessment. The greatest space for novelty, for computers and humans alike, lies in the potential future trends, in the unseen, and with AIs seemingly able to model art’s trajectory from the traditional to the new, it’s likely that the next original artistic movement will be born from computer-generated art. Unfortunately, the new is often seen as a threat to the old, and the Portrait of Edmond de Belamy, as a product of art and science in conjunction, poses a challenge to the traditional idea of the “artistic genius.” Artistic genius has long been believed to be epitomized by the masterpieces of the greats, which many regard as shining representations of the ideals from their respective periods, from the Renaissance to Romanticism to Surrealism. While many art movements coincided with significant advancements in mathematics and sciences and often drew inspiration from such events, the emphasis of these great works typically lies in their imaginative qualities. For instance, Romantic art often delves into transcendental themes, while Surrealist art features dreamlike imagery. Consequently, the concepts of art and inspiration are often spoken of in mystical terms, elevated to a status beyond the realm of science and technology. In fact, the claim that Johannes Vermeer, the artist who famously painted the Girl with A Pearl Earring (1665), used some sort of optical device and mirror technology to help accurately recreate scenes within his paintings caused deep anguish for many art historians and critics, who accused the allegation of being “a depressing attempt to reduce genius to a trick” (Jones, “DIY Vermeer Documentary”). What, then, constitutes this so-called “genius”?   For centuries of art education, the “artistic genius” trope has always consisted of the Western canon of artists such as Leonardo da Vinci, Michelangelo, Claude Monet, and Johannes Vermeer, an understanding so closely linked to the privileges and traits associated with whiteness and masculinity that it suggests the very notion of “genius” is socially constructed. Ian Hacking explains in his essay “Making Up People” that it is human nature to classify things, though the act of classification in many cases “breeds conceptual confusion,” referring to how we have difficulty giving just consideration to observed behaviors that do not conform to our understanding of something. He laments that in attempting to measure genius through statistical means such as the IQ test, we have in turn abolished genius from our society. Hacking makes an argument against our classification of genius, yet ironically, in the process, he implies that true genius is to be associated with the great eras of art, reaffirming the idealized classification of “genius” that many critics of AI art use to prevent computer-generated artwork from being considered art. The idea that artistic genius is a valid classification, however, directly contradicts Hacking’s point about “real” and “finite” kinds. Hacking brings up John Stuart Mill’s argument that a “real kind” is a classification in which the members have “innumerable features in common,” while a “finite kind” is a classification in which members have very little in common. For example, our species, the homo sapiens, is a real kind because we share many biological features and characteristics, whereas races are just finite kinds because members of different races have only their race as a commonality. Upon close examination, the old masters regarded as artistic geniuses have few similarities; the diverse range of styles and expressive manifestations that their artworks contain reflects their existence as subjects of different social and cultural settings, artistic training, and schools of thought. “Artistic genius” is therefore merely a finite kind, making the current definition of “greatness” in art less about the aesthetics of the work produced or even the intentions behind the work, and more about whiteness, elitism, maleness, and Eurocentricity. The underlying issue is that “artistic genius” has long been centered on the mythos of the artists rather than the artworks themselves, a fact that has almost always worked against women and artists of color and now works against artificial intelligences. Any divergence from reality in the artist’s depiction tends to hold significance, but only if that artist is a man.1 For instance, the distortions within the Portrait of Edmond de Belamy greatly resemble Glenn Brown’s art-historical appropriations (“Biography”), yet while Glenn Brown’s art is praised for its technical virtuosity and passion, the Portrait of Edmond de Belamy is unfairly condemned to be a poor pastiche of genius.  To overcome this bias requires seismic social shifts, a reangling of how we view art history—as a history of the art, rather than of the artists. In “Automating Gender,” Jack Halberstam encourages us to confront our pre-existing ideas regarding Western society’s grand narratives, which in art is the myth that there are near-deities of creative wisdom, a superior kind of humanity that lives a more rarified human experience—white, European male artists. The prevalence of this myth, endorsed by art historians and art critics, places the works of “artistic geniuses” in the highest realm of art, not only establishing the legitimacy of these art historians and critics as experts in their knowledge of such art, but also guaranteeing the status of the artists of those works as old masters, perpetuating a gendered tautology that the artistic genius is male because men are most fit to be artistic geniuses. Through the lens of postmodernism, which Halberstam defines as a movement “embedded within the modern as interference or interruption and as a coming to consciousness of a subject no longer modeled upon the Western white male,” Halberstam affirms that questioning the interests served by the perpetuation of such grand narratives will lead to the conclusion that the ideas of artistic genius related to the allures of the great European art periods are unprogressive (446). From the politics of artificiality provided by postmodernism, it follows that “genius” is a socially manipulated idea that actually keeps us from getting a better understanding of the artworks studied and from exploring new avenues in art. Historical emphasis must be returned to the art rather than the artist. If we focus on the artwork created by CANs rather than the mechanical nature of the CANs themselves, perhaps we can see computer-generated art as less of a challenge to the prestige of human-made art, and more as a new artistic manifestation that subverts common distinctions between art and technology, the creative and the mechanical, and the old and the new. In this sense, if we no longer focus on the mind or, particularly, the body behind a work, we might discover that the artworks created by CANs are just as impactful as artwork created by humans. Perhaps in this case we should also look to Turing for inspiration, and replace the question under consideration, “Can computers create art?”, with another: “Could a computer create artwork that could successfully trick a human into thinking it was created by another human?” If a satisfactory play of the Turing test, a test designed to see if an evaluator can distinguish between a human and machine through conversation, is enough to argue that machine intellect can be comparable to man’s, then a way to prove that computer-generated art is comparable to human art, surely, is to conduct a kind of visual Turing test, to show the output of the algorithms to human evaluators and ask if they can tell the difference (see figs. 2-3).  Fig. 2. Barrat, Robbie. 2018.  Fig. 3. Monet, Claude. Poplars on the Epte, 1891. In fact, Ahmed Elgammal conducted a survey among viewers in a gallery specifically arranged for a visual Turing test, where computer-generated art was presented alongside human art. He found that many had a difficult time distinguishing between human art and computer-generated art, with several even claiming to be more inspired by the art done by a machine (“AI is Blurring the Definition of Artist”). The results of the poll affirm that the identity of a creator does not inherently grant more value to a work, and show that AIs are more than capable of creating aesthetic and thought-provoking works of art. Moreover, computer-generated artworks like the Portrait of Edmond de Belamy are in high demand by contemporary art enthusiasts, as evidenced by the passionate reception of the portrait and the final dealing price of nearly 5 times the price of an Andy Warhol print at the same auction. Both factors prove that computer-generated art can be just as artistically and socially meaningful as traditional art. The success of the Portrait of Edmond de Belamy demonstrates that the future of art is now intertwined with the future of technology. New technologies not only benefit art critics and art historians, forcing them to reevaluate their preconceived notions of “artistic genius,” but also benefit art and artists, creating new tools and modes of expression. What people who worry that AI art is a harbinger of humanity’s destruction often forget is that there are humans behind the machines, a creator behind another creator of art. All computer-generated art is the result of human invention, software development, and other kinds of authorship. We must acknowledge that the human is always the creative force behind the work and that the computer is really just a helpful tool, albeit a little more complicated than a canvas and a paintbrush. But even if that were not true—even if AIs created art with complete independence and autonomy—the value of their work would not change. Technological development stimulates so much of the continued vitality of art, and new AI algorithms like CANs are just another means by which artists can transform art in positive ways, just as so many other technologies have in the past.   NOTE It’s important to note that there have been exceptions within the realm of human artists: exceptional individuals like Basquiat or Sofonisba, who are widely regarded as “artistic geniuses” despite deviating from conventional artistic norms, have made groundbreaking contributions to the world of art. The recognition and appreciation of their work has enriched our understanding of art, and highlights the importance of acknowledging and celebrating diverse talents in art, regardless of the nature of the artists.   WORKS CITED “Biography.” Glenn Brown, Artlogic, https://glenn-brown.co.uk/biography/.  Elgammal, Ahmed. “AI Is Blurring the Definition of Artist.” American Scientist, https://www.americanscientist.org/article/ai-is-blurring-the-definition-of-artist.  Hacking, Ian. “Making Up People,” London Review of Books, vol. 28, no. 16, 2006, https://www.lrb.co.uk/the-paper/v28/n16/ian-hacking/making-up-people Halberstam, Jack. “Automating Gender: Postmodern Feminism in the Age of the Intelligent Machine,” Feminist Studies, vol. 17, no. 3, 1991, pp. 439-460, https://www.jstor.org/stable/3178281. Jones, Jonathan. “A Portrait Created by AI Just Sold for 432,000. But Is It Really Art?” The Guardian, Guardian News and Media, 26 Oct. 2018, https://www.theguardian.com/artanddesign/shortcuts/2018/oct/26/call-that-art-can-a-computer-be-a-painter.  ‑‑‑. “DIY Vermeer Documentary Utterly Misses the Point about Old Masters.” The Guardian, Guardian News and Media, 28 Jan. 2014, https://www.theguardian.com/artanddesign/jonathanjonesblog/2014/jan/28/tims-vermeer-fails.  “Is Artificial Intelligence Set to Become Art's next Medium?” The First Piece of AI-Generated Art to Come to Auction | Christie's, Christies, 12 Dec. 2018, https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx.  Turing, Alan M. “Computing Machinery and Intelligence,” Mind, vol. 59, no. 236, 1950, pp. 433–460, https://doi.org/10.1093/mind/LIX.236.433

    Presenting a New Model to Support the Secondary-Tertiary Transition to College Calculus: The Secondary Precalculus and Calculus Four Component Instructional Design (SPC 4C/ID) Model

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    No full text
    Although the secondary-tertiary transition has been investigated in mathematics education research with different focuses and theoretical approaches, it remains a major issue for students in the transition. With success in a science, technology, engineering, or mathematics (STEM) major at stake, we investigated a novel approach to support the transition from secondary precalculus or calculus to tertiary calculus. Using the Four Component Instructional Design (4C/ID) model and empirical data from the United States (US) nationally representative FICSMath project, we mapped instructional experiences of students in the transition to theoretical components of the 4C/ID model. From exploratory factor analysis (n=6,140), we found six factors that mapped to the 4C/ID model components and created the new Secondary Precalculus Calculus (SPC) 4C/ID model. In this model, the Learning Task Component represents tasks to engage learners in meaningful problem solving; the Support Component grounds instruction in reasoning and understanding; the Procedure Component integrates group work and graphing calculators to connect concepts to procedures; and the Part-Task Component represents instruction to develop automaticity. The SPC 4C/ID model presents a unique support for precalculus and calculus teachers in the quest of teaching for learning and transfer of learning across the transition

    Notes from the Field Preface

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    No full text

    The Trademark Problem of “TRUMP TOO SMALL”

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    Consider the phrase—and my apologies for asking—“Trump too small.” It comes from the 2016 campaign for the Republican presidential nomination. A back-and-forth between Donald Trump and Florida Senator Marco Rubio culminated in a debate exchange about the size of Trump’s penis. This cultural low prompted one Steve Elster to seek registration of the trademark TRUMP TOO SMALL for use on shirts. The Patent and Trademark Office (“PTO”) refused, relying on section 2(c) of the Lanham Act, which bars registering a mark that “[c]onsists of or comprises a name, portrait, or signature identifying a particular living individual” absent written consent. In re Elster reversed the PTO’s rejection of Elster’s application. The Federal Circuit ruled that applying the section 2(c) bar to TRUMP TOO SMALL would unduly burden Elster’s First Amendment rights. This is nonsense. If we are concerned with burdens on speech, the larger issue is the prospect that registering the mark would create opportunities to limit others’ ability to use the phrase as speech. But it is nonsense well-grounded in recent Supreme Court opinions that use the First Amendment to strike down the Lanham Act’s bars to registering disparaging and scandalous marks. First Amendment implications aside, Elster highlights the bind facing the PTO when presented with low-quality trademarks. TRUMP TOO SMALL is not an effective brand name. When seen on a T-shirt, the phrase will naturally be read as an insulting commentary on the former President, not as a source indicator. But trademark law allows logos and slogans to be protected as merchandise. Even if the TRUMP TOO SMALL application is intended to support a merchandising play, that is not enough reason in and of itself to deny the registration. But apparent merchandising efforts like TRUMP TOO SMALL are different in kind from merchandising related to sports or university paraphernalia, for they lack any pre-existing goodwill to monetize. In effect, many would-be merchandisers are free riders, seeking to reap where they have not sown by capitalizing on cultural moments or other circumstances unconnected to their efforts. Trademark law lacks an effective vocabulary for these situations, placing significant pressure on nebulous doctrines like “failure to function” that may not be able to bear the weight increasingly placed on them to screen out low-quality trademarks. In re Elster thus illustrates a problem relating not to the First Amendment but rather to the choice to make trademark doctrine the vehicle for vindicating markholders’ merchandising interests

    The Case for the CCB: A Defense of the Constitutionality of the Copyright Claims Board

    Author
    Publication venue
    Columbia University Libraries
    Publication date
    Field of study
    Get PDF
    Copyright litigation is expensive. Since copyright is federal law, disputes must be heard in federal court. Federal litigation can be prohibitively costly for creators bringing small claims, essentially leaving them with a right without a remedy against infringement of their work. Congress sought to alleviate this financial burden in 2020 when it passed the Copyright Alternative in Small-Claims Enforcement (“CASE”) Act, thus creating the Copyright Claims Board (“CCB”) to adjudicate small copyright disputes. Opponents raised constitutional concerns about the CCB throughout the legislative process. The concerns included the fact that the CCB officers would wield unreviewable power and that Congress cannot set up non-Article III courts to hear cases involving public rights. Critics renewed their concerns in the aftermath of the Supreme Court’s June 2021 decision in United States v. Arthrex, in which the Court found that the Patent Trial and Appeal Board administrative patent judges (“APJs”) wielded unreviewable authority that violated the appointments clause. Furthermore, a possible challenge to the constitutionality of the CCB could be forthcoming since the CCB is now operational. This Note analyzes the evolution of Appointments Clause and Article III jurisprudence and finds that the CCB is constitutionally constructed. While copyright is likely a private right, the CCB is still constitutionally permitted to hear these claims because the parties voluntarily consent to use the CCB. The voluntary nature of CCB proceedings plus the fact that these small cases are typically not heard by federal courts ease Article III and reviewability concerns. Part I provides background information to the passage of the CASE Act and explores arguments for the necessity of the CCB. Part II outlines the structure of the CCB. Parts III and IV respectively detail relevant Appointments Clause and Article III jurisprudence then apply it to the CCB. Parts V and VI discuss the possible arguments critics may lodge against the CCB in a constitutional challenge and how these invariably fall short. Finally, Part VII takes a practical look at how the Supreme Court as currently constructed might analyze the CCB’s constitutionality

    3,462

    full texts

    6,467

    metadata records
    Updated in last 30 days.
    Columbia University Libraries Journals
    Access Repository Dashboard
    Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇