By Prospero I mean a thought experiment that David Hays and I proposed back in 1976 in a review article, Computational Linguistics and the Humanist, we published in Computers and the Humanities. Sometime in the last decade or so, when I began thinking about doing a book on naturalist criticism, I took that old idea, of a computer program capable of a non-trivial simulation of a reader of Shakespeare, and elaborated it more or less as a stand-alone piece. In particular, I contextualized it with some remarks Stanley Fish had made about stylistic analysis in Is There as Text in This Class? I posted that piece about half a year ago, then revised and reposted it about a month ago.
I’ve now done yet another revision, this time incorporating the notion of a tabula rasa interpretation from Alan Liu’s article, “The Meaning of the Digital Humanities” (PMLA 128, 2013, 409-423). I’ve posted that version at my SSRN (Social Sciences Research Network) page. I’ve appended the abstract to this post.
Why yet another revision?
It would seem that this notion, this Prospero, has become a touchstone, something through which I gauge the state of my thinking on certain possibilities of literary analysis. But that’s not quite what it was when Hays and I advanced it almost 40 decades ago. Then it was a way of conveying something to an audience we presumed to be unfamiliar with current ideas in computational linguistics.
At that time, the mid-1970s, semantics was the Big New Thing. Computational linguistics was born in the early 1950s under the rubric of machine translation. The US Federal Government needed to translate a lot of Russian documents into English. Perhaps that could be done with computers?
And so a variety of investigators went to work recasting phonology, morphology, and syntax into computational form appropriate to machine translation. By the late 1960s it became apparent, both in computational linguistics and artificial intelligence, that it would be necessary to tackle meaning. Thus was born the computational semantics of natural language.
THAT’s what Hays was interested in when I began working with him in the spring of 1974. That’s what everyone was interested in. By the time we wrote that essay I’d completed and published preliminary work on Shakespeare’s sonnet “The Expense of Spirit”, which we discussed in the article. But we couldn’t go into any of the details in that article. So, to give our readers some sense of what that work portended we concocted Prospero.
The idea was straightforward: Code the Elizabethan worldview into a computer using formalisms then being developed, have a computer “read” a Shakespeare play, and then examine what it did in the process. For bonus points you could also program the computer with the knowledge needed to crank out Freudian, Marxist, feminist, and other interpretations. Who wouldn’t be excited at the prospect of working on such a project, even if it were a long-term (decades) project?
I don’t know what Hays thought about the real possibility of such a thing – he’d already lived through the institutional collapse of machine translation when it failed to deliver on some rather extravagant promises – but I figured that I’d be working on Prospero in my lifetime. Certainly not in the near-term future, but 20, 30 years out...?
It didn’t happen. Nor is there any immediate prospect of such a thing. IBM’s Watson is the state of the art, and it’s nowhere near the capability needed to implement Prospero.
What would it take to implement Prospero? I don’t know.
Oh, sure, it’s easy enough to say that it would require a good model of how the human brain operates, including conversation with others. But what would THAT require? We don’t know.
By way of comparison, the folks who want to send a manned mission to Mars know a great deal about what that would require. After all, we’ve already sent humans to the moon and brought them back. And we’ve sent probes that have landed on Mars and beamed back information about what’s there. All that’s directly relevant to the task of a manned mission to Mars. It may not be sufficient – it doesn’t tell us how the human body will adapt to months of weightlessness in transit, nor the mind to those months being bound to a very small group – but it IS a lot.
It is much more than we know about simulating the human brain or coding up the Elizabethan worldview.
So, if Prospero is not possible, then why think about it at all?
Let me put that more personally. What can you learn from me by reading about Prospero? To some extent that depends on what you already know about things such as cognitive science, AI, and computational linguistics, and how much you are willing to trust my knowledge of such things. And what could I learn from you through conversing about Prospero? And that depends on what you already know and on my willingness to trust in your knowledge.
That is to say, Prospero is a set of ideas for organizing a conversation, a conversation about what computers bring to the study of literature.
For example, in one of the essays in Is There a Text in This Class? (1980) Stanley Fish asserts that Michael Halliday, a linguist, is one of many lured on by “the promise of an automatic interpretive procedure” (p. 78). Though I can’t be sure of this, I rather doubt that Halliday himself had any such idea, certainly not as Fish attributes it to him. The idea’s a straw man. Thinking about Prospero is a way of thinking about why the idea IS a straw man. It may even get you to the edge of thinking about why Stanley Fish posits such a thing.
I suppose what Fish had in mind was that you “feed” your text into “the automatic interpretive procedure” and it “spits out an interpretation.” Given such a device, why should you trust the interpretation? Wouldn’t you have to know what it does? And if you know that, do you need the device?
Prospero is useful for thinking about that. So, we’ve got Prospero and we feed it, say, Much Ado About Nothing. How do we know that Prospero understood the play in some meaningful way? Of course we could ask: Did you understand it? But what would we know once Prospero answers Yes? Not much. And if Prospero were to tell us that, no, he didn’t understanding the play, would THAT tell us anything useful? We could ask Prospero questions about the play: Who is Hero? What’s her relationship to Beatrice? And when Prospero answers correctly (or not) then what do we know?
As I say in my various versions of this little thought experiment, what’s important is that knowledge that goes into building Prospero. But Prospero could give reasonable answers to those questions without understanding much about the play, no? After all, aren’t there students like that?
I’ve also said that, given that Prospero is a reasonable simulation (as determined by some as yet unspecified set of procedures), what we really want to do is examine what Prospero does internally in the process of reading a play. That, surely, would tell us a lot.
And now we’ve got a problem, one I’ve been aware of but chose not to bring up. Assume that Prospero IS a fairly robust simulation of a human mind. Isn’t there an ethical problem in opening it/her/him up and examining what happens while reading? Don’t we have to ask permission and, if permission is not granted, go no farther?
If I was aware of this issue, why didn’t I bring it up? I don’t quite know. The matter seems both obvious and beside the point. It exists in some other thought-world, one that impinges on the Prospero world, but that’s outside the actual business of creating a Prospero machine.
Perhaps that’s what Prospero is, a boundary marker, or a guardian spirit.
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Revision 3, May 2014
Abstract: Prospero is a thought experiment, a computer program powerful enough to simulate, in an interesting way, the reading of a literary text. To do that it must simulate a reader. Which reader? Prospero would also simulate literary criticism, and controversies among critics. The point of Prospero, if we could build it, is the knowledge required to build it. If we had it, we could examine its activities as it reads and comments on texts. But our knowledge of Prospero is of a different kind and order from our knowledge of the world and of life, though those things are central to literary texts. The point of this thought experiment is to clarify that difference, for that is what we will have to do to build a naturalist literary criticism grounded in the neuro-, cognitive, and evolutionary psychologies. Though contemplation of this experiment we can see that, whatever computing promises literary study, it will not yield automatic interpretive procedures.