In a study titled “Does GPT-4 Pass the Turing Test?” by University of California, San Diego researchers Cameron R. Jones and Benjamin K. Bergen where they explored the performance of various AI models, including ELIZA, GPT-3.5, and GPT-4, alongside human participants in imitating human conversation, they ended up highlighting several factors that contributed to ELIZA's surprising performance. First factor was its conservative response style that minimized the risk of providing misleading or incorrect information that could have exposed that it's a machine since ELIZA was processed to build its response around a single keyword from users which meant that its accuracy was limited to syntactic response built upon predefined patterns. Further, researchers observed an absence of characteristic traits that were found in modern AI - such as helpfulness or excessive verbosity - that led them to view ELIZA as an uncooperative human. Ultimately, the researchers, Cameron R. Jones and Benjamin K. Bergen from UC San Diego, pointed out how the Turing Test that led to ELIZA's roar need to be critically reevaluated in the light of findings about both current and historical AI systems as ELIZA's role in the case of ongoing conversation seems to be relevant only because of the parameters put forward by the Turing Test in 1949 which was initially thought of as an experiment and not an actual test. In the same research, they - Cameron R. Jones and Benjamin K. Bergen from UC San Diego - also observed how ELIZA ignores grammatical structure and the context of the sentence. This causes an issue as ELIZA suffers from the inability to parse sentence structures that leads to less meaningful responses. This could also stem from its knowledge gap about the topic being discussed. Unlike modern models, due to this ELIZA could not put things into a broader context. ELIZA's responsiveness is scripted and seems rigid and the reason is rooted in its underlying design, thus, changing its programming would not change its response patterns and sentence handling, rather would add more to its complexity as seen in the information shared by University of Birmingham’s excerpt What ELIZA lacks that say when a user states “Computers worry me,” ELIZA cannot relate this to any broader context, and often can generalize between the previous statement and “I’m not worried much by computers”. This calls for an AI capable of meaningful guidance.
in A StuDy titlEd “DOes gpT-4 pasS the turinG test?” bY uniVErsIty of califOrnIA, SaN dieGO reSearchErs cameRON R. jonEs And benjamIN k. berGeN where they explored the performaNce Of vArioUs aI modelS, incluDing elIZa, gPt-3.5, aNd gPt-4, aloNGSIde human ParticIPantS in ImiTaTing HumAn conVersATiOn, thEy endeD up HIGhliGhting seVEral factoRs that CoNtrIButed to eliza's suRprisinG PerfoRmanCE. FirSt factor wAS Its conserVatiVE response styLe that MInImized the risk oF provIdINg MISLeADIng oR inCorreCT iNformAtIon tHat coulD haVE exPosEd that it'S a MaChIne SINCe eliZa was prOCeSsed to build its rESPonse ArouNd a single keywOrd from Users WHicH meant thAt its aCcuRaCy was LIMited to syNTactIc response BuiLt upoN PReDeFIned pattERns. furthEr, REsearcheRS observED an AbsencE oF characteristiC trAIts that WERe fouND in Modern aI - suCh as helPfULNess or ExCEssIve vErBOSity - tHat lEd thEm To vieW Eliza as an uncooperative humaN. UltiMAtely, The ResearchErs, caMeron r. jOnes ANd benjamiN k. beRGen fRom uc san diegO, pOINTED oUt hOw tHe turInG teSt thaT led TO elIza's roar need tO be cRitIcallY REEVaLUatEd in ThE light of FindIngS ABoUt both current and hIstorICal Ai SysTeMS As elizA's rOle iN tHe case of onGoing converSation sEeMs To bE relEVAnt only BecaUsE of thE ParaMEters puT ForwarD BY tHe turIng tesT in 1949 whicH Was InItiallY thOught Of as aN expErImeNT anD not an actual teSt. iN thE sAme rEseaRch, tHeY - CAmEron r. jones AND BEnjaMin k. bergeN FroM uC SAn DIeGo - AlSo obServed how EliZa ignOReS grammAtical StruCtuRe and tHe contExt oF thE SenTeNCe. this cAUseS an issUe as eliZa suFfErS From the inabiLitY To parse senTeNCE stRUCTUrEs THat LEadS To lEss meANInGfUl reSponses. tHis couLd aLSo stEM fRoM its knoWLedGe gap abOUt The topiC beIng DiscUsSed. uNLiKe MoDeRn mODels, DuE tO ThIS eliZA cOuld NoT put thInGs intO a brOaDer CoNteXT. ELizA's ResponsIvEness iS scRIpTed And SeemS rigiD ANd THe ReasoN Is rOoted IN Its UndeRlYING deSiGn, tHus, cHAnGInG ItS PrOGrAmMiNG wOUld nOt ChanGe its reSponse PAtternS AnD SeNtEnCe handling, Rather would aDd MoRe To Its coMplExitY as seeN In tHe InformAtioN shAREd by uniVERsity Of birmiNgham’s exCerpt WhAT ElIZA lacks That say when a user sTates “CompuTers wOrry me,” ELIZA cANnoT rElAtE tHiS TO aNy BroAdeR coNtext, anD OfTEN can GENerAlIZe betWeEn the pREviOuS sTAteMent ANd “I’m Not worRiEd muCh by cOmPutErS”. thiS calls for an aI capable OF meaningful GUidance.