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5,2,2:QuestiQn fQr literary studi,.§,<br />

In c?ntra,st <strong>to</strong>.. our vast knowledge ofhow science and logical reasoning proceeds, we know<br />

precious little In anyformalsense about how <strong>to</strong> makegoods<strong>to</strong>ries.18 (Jerome Bruner)<br />

While the interest of AI researchers in the study and generatiQn of (prose) narratives is<br />

understandable, the question arises which insights, if any, experiments such as T ALE­<br />

SPIN can offer literary researchers, Many of the areas it examines and analyses it carries<br />

out seem after all <strong>to</strong> merely repeat, albeit on a more sophisticated level, research in<strong>to</strong> the<br />

structure ofnarratives which have been carried out under similar assumptions in formalist<br />

and structuralist studies ofnarrative.<br />

One motif for the study of computer-generated literature is the hope <strong>to</strong> obtain further<br />

insight in<strong>to</strong> the nature and structure ofpQetry and prose; Ryan's suggestions, for example,<br />

are based on the strong mechanistic beliefthat the element of"tellability" ofany narrative<br />

is qualifiable and quantifiable and that<br />

the creation of {literary} meaning is not a mysterious brains<strong>to</strong>rm caused by a random<br />

meeting of circumstances - a unique individual in an ephemeral state of mind,<br />

nurtured <strong>to</strong> some immeasurable extent by a culture whose boundaries remain fuzzy,<br />

and bringing <strong>to</strong> the text a deeply private experience ofthe world - but the predictable<br />

output ofdefinable prQcesses operating on a variable input.v<br />

Millc exhibits a less optimistic attitude <strong>to</strong> the ability of the computer <strong>to</strong> imitate creative<br />

acts of humans and believes that through work on prQse genera<strong>to</strong>rs and their outputs one<br />

can not only learn about literary structures (Ryan's argument) but more impQrtantl:g<br />

through the observation of the shortcomings of those genera<strong>to</strong>rs, obtain a greater<br />

appreciation Qf the work of authors. He argues that his work on Era<strong>to</strong>, a poetry prQgram<br />

he created, "doesn't weaken our appreciation for poets. On the contrary, it deepens it<br />

because we see hQW much easier they do what the prQgrammer and machine are trying <strong>to</strong><br />

dQ,"ZO<br />

Far from being a supporter of a romantic vision of the creative genius (he does believe<br />

that the computer could eventually achieve the sophistication ofa human crea<strong>to</strong>r) he does<br />

acknowledge that fac<strong>to</strong>rs which are very difficult <strong>to</strong> compute do playa role in the writing<br />

process, some of which he hopes tQ discover and pinpoint further through his work on<br />

18Jerome Bruner, Actual Minds, Possible Worlds (Cambridge, MA and London: Harvard UP, 1986), P·14, .<br />

'9 Ryan, Possible Worlds, P.5-6, Which, in consequence, turns literary studies in<strong>to</strong> an a-his<strong>to</strong>rical and highly<br />

formalist discipline,<br />

10 McKean, "Computers, Fiction and Poetry", P,51 •<br />

Chapter 5 - page 184

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