I would like to open by paraphrasing Dobzhanzky’s well-known title (1973) and assert that nothing in human psyche and society makes sense except in the light of cultural evolution. Having written the paraphrase I must confess that, alas, I cannot affirm it. The study of cultural evolution will not yet support such an assertion. It is too scattered and incomplete. Yet I believe that such a paraphrase indicates the proper scope for a robust investigation of cultural evolution. Accordingly I’ll offer a few observations on what we must do to move in that direction.

* * * * *

But first I want to deal with a mundane organizational matter. Once I’d committed myself to this post I recalled those many times when I set out to write an easy piece – nothing new, just bang out a couple of thousand quick words on stuff I’ve been chewing on for some time. Before I knew it Quick and Easy had grown into an Ungainly Monster with no end in sight. As this assignment had all the earmarks of such a beast I decided on a preemptive strike in the form of a series of posts at my own blog, New Savanna. The idea was to think things through ahead of time so that: 1) I had at least the ghost of a chance of writing a coherent post for the Forum, and 2) I would have plenty of online back-up material at hand.

I have listed those posts in an appendix and will refer to them as CE1, CE2, CE7, etc. I’ve also gathered those posts, including some comments, into a single PDF document which you can download from the Social Science Research Network (here). I would, of course, be happy to comment on those posts either here or at New Savanna (see URLs in the appendix).

My Slant

While I accept the anthropological view of culture, I tend first to think of such things as literature, music, art, and film. I was trained in English Literature; I am a musician and have published a book about music (Benzon 2001); I like to photograph graffiti [1]; and have developed a deep interest in animation in the last several years. My discussion is thus biased toward those kinds of things.

Thus I will not be discussing one of the most robust research programs in cultural evolution, gene-culture cooevolution. I am willing to take it as given that cultural environments have influenced our biology. But for reasons given in CE1 and CE2 I don’t think gene-cultural cooevolution has much to say about the phenomena that most interest me.

Nor do I intend to say much about memes. The term is a brilliant coinage, and I’ve adopted it myself, but I think the conceptualization that has come with it is unfortunate. The notion that culture consists of homuncular memebots hopping about from brain to brain is uninformative and thus a useless time sink (cf. Benzon 2002).

And yet I believe that Dawkins got something right. As I say in CE3, Dawkins’ key insight is that, in the cultural evolutionary process, selection operates on cultural entities and not on human phenotypes. That is to say, the evolutionary costs and benefits accrue directly to cultural entities, not to the human beings who create and consume them. There are cases where cultural entities seem to thrive at the expense of humans, but this is a secondary matter and, in the large scope, not worth the attention that’s been lavished on them in popular discussions. Most of my preparatory effort has been aimed at working out such a scheme (CE3, CE4, CE5, CE6, and CE8; see also Benzon 1996, Benzon 2001) and I will offer a few remarks on those matters here and there.

A Start: Colin Martindale

Let me set the stage by quoting a passage from the excellent review Tim Lewens (2007) wrote for the Stanford Encyclopedia of Philosophy:

One might fear that in the end cultural change, and the influence of cultural change on other aspects of the human species, are best understood through a series of individual narratives. Our brief examination of memetics illustrated this concern. We gain no real explanatory insight if we are told that ideas spread through populations, some more successfully than others. We want to know what makes some ideas fitter than others. And it is not clear that there will be any general rules that can help us to answer this question. In the biological realm we need detailed accounts of local environmental circumstances, species-specific physiology and anatomy, and so forth, to tell us what makes one organic variant fitter than another. Similarly, in the cultural realm we will need to look at local psychological dispositions to explain why some ideas are more likely to spread than others. So any explanatory value to be had from memetics is parasitic on conventional work done in psychology.

With those caveats in mind, let’s take a quick look at the work of the late Colin Martindale. Like Dawkins, Martindale realizes that cultural selection operates on cultural objects and processes (1990). Unlike Dawkins he has both a theory about those processes and empirical data supporting that theory.

A need for novelty is the driving factor in Martindale’s scheme. Novelty value is what recommends expressive works to their audience. The trouble, of course, is that once one has sufficient experience of the new, it loses its capacity to excite. It has become old. Psychologists call this habituation, and it is a much-studied aspect of neural operation. Martindale argues that art overcomes habituation 1) through the regressive inclusion of more primordial content and 2) through the formal elaboration of content (pp. 34-76) – here’s an entry point for the local psychological dispositions Lewens mentions.

Using his model Martindale argues for cyclic change in aesthetic styles within a given tradition. Basically, an increase in primordial content (novelty) is followed by a relaxation of stylistic rules. That permits stylistic change (novelty) which then allows the use of primordial content to recede as the new style becomes increasingly elaborated. At some point, however, further elaboration becomes pointless and it’s time to up the primordial content. And so on. Given these predictions, Martindale has analyzed long runs of French and British and American poetry, classical music, Gothic architecture, European painting, Japanese prints, and New England grave stones. In all cases he has found cyclic variations in form and content in line with his predictions.

Martindale’s theory is thus fundamentally about audience reception. For all practical purposes we can treat artists – even the most exalted of geniuses – as an anonymous fountain that spews forth works for public consideration. People decide which works they like and it is those preferences that, in the long run, allow selected works to enter the canon. Thus when Martindale is tracking artistic change he is also indirectly tracking changes in the collective psyche.

But how can we conceptualize the collective psyche without falling into hopeless mysticism?

Collective Culture

Let me offer a simple model system, one simple enough that we are probably within range of understanding it at the neural level. I used this example in my book on music, Beethoven’s Anvil, and the following discussion is a paraphrase of that discussion.

Consider the bi-modal clapping that routinely rewards a successful performances—music, drama, circus, etc.—in eastern European communities, but which is less common in western Europe and North America. Z. Néda and colleagues (2000) have investigated this phenomenon, recording applause for a number of performances in Romania and Hungary. The applause would start out randomly and then quickly become strongly synchronized. Synchronized clapping would continue for a short while (one mode) and then disintegrate into random clapping (the other mode), from which synchronized clapping would reemerge, and so forth.

Analysis of the recordings revealed two things:

1. The average noise level was greater during the random clapping than during the synchronized clapping.
2. During random clapping individuals clapped at roughly twice the frequency they used during synchronized clapping.

Clearly the greater volume during random clapping came because individuals were clapping faster. But during this mode, the time between individual claps varied more than when people clapped at the lower rate. That variability made it impossible for the group to synchronize at the higher rate, which also produced a louder sound.

Néda concluded that audience members were caught in a conflict. They can express one value by making as much noise as possible through rapid clapping. If, however, they wish to express another value by synchronizing their clapping, they must clap more slowly, thereby lowering the volume. It is impossible simultaneously to maximize these two aims. The group deals with this conflict by switching back and forth between two different expressive modes.

The investigators assume that the loudness of the clapping reflects the audience members’ enthusiasm for the performance, while synchronous clapping expresses group solidarity, which seems reasonable enough. What is immediately significant, however, is the mechanism by which these two values, whatever they are, were expressed by the group. That mechanism is clearly self-organizing. No one leads audiences in this behavior. It just happens.

Now I want to take a quick look at memes (cf. CE3) by shifting point of view slightly and asking an obvious question: What is audience attending to in this process? That is, what aspects of the sound stream are carrying the expressive messages in these two clapping modes? Obviously, synchrony in one case and volume in the other. We can thus say that those properties are memetically active (CE5).

In my reading, those properties are memes (CE3). They don’t replicate and scatter (the wrong theoretical imagery). Rather, they allow mutual coordination. In my notes I devote considerable attention to a more complex example, so-called Rhythm Changes (CE5, CE6). This complex is named after George Gershwin’s song, “I Got Rhythm,” and refers to the song’s harmonic structure, which spans 32 bars. Gershwin’s song was so popular that by the late 1930s other composers where writing their own melodies on that harmonic foundation. This practice went riot with the emergence of bebop in the early 1940s, with every musician of stature creating one or more tunes on Rhythm Changes. Consequently any reasonably competent jazz musician can recognize Rhythm Changes tunes regardless of the melody and can jam on Rhythm Changes anytime, anyplace.

It is not obvious to me just how one is to characterize such complex patterns in physical terms. In my posts I draw on fairly standard means of musical notation, but that’s pretty far from the sound itself. But if the patterns weren’t physical, musicians couldn’t use them as vehicle for coordination.

What this suggests about memes in general, however, is that various disciplines may already be quite familiar with them under rubrics such as semiotic codes, or what not. I explore this possibility in a discussion of the emic/etic distinction in a comment to John Wilkins in CE3 and in my discussion of language in CE8, including comments made to John Lawler. But this is taking us a bit afield, into perceptual and cognitive psychology. Both are necessary to our study, but I want to return to group behavior.

I want to move beyond the immediacy of post-performance applause. What happens in the days and weeks following, say, the opening of a film? What gives a film legs, as they say? That’s a question investigated by Robert de Vany in Hollywood Economics, a profound and imaginative treatment of the economics of the movie business. De Vany is interested in understanding what happens to movies once they’re released to the public. To that end he has analyzed a ten year run of box office receipts from the 1990s.

Most movies, of course, don’t even break even, much less make a profit – not in theatrical release, though many movies finally break-even or make a profit though DVDs and TV. The deep and ineradicable condition of the business seems to be that there is no reliable way to estimate the market appeal of a movie short of putting it on screens across the country and seeing if people come to watch. What De Vany shows is that that about 3 or 4 weeks into circulation, the trajectory of movie dynamics (that is, people coming to theatres to watch a movie) splits into one of two alternative trajectories (a term of art in the study of dynamical systems). Most movies enter a trajectory that leads to diminishing attendance and no profits. But a few enter a trajectory that leads to continuing attendance and, eventually, a profit. Among these, a very few become block busters.

No matter how the studios and distributors try to manipulate audience behavior through advertising and public relations, the most important factor in movie success is word-of-mouth (pp. 60-63). People sitting together in a theatre influence one another’s experience of the film through remarks to one’s immediate neighbors, but also through sighs, groans, and laughter audible several rows away. When the movie’s over people tell their friends about the film and that, in turn, influences whether or not their friends will go see the film. The studios cannot elicit this behavior, they cannot lead it. It reflects the spontaneous reactions and interactions of people.

In the short term such behavior determines which movies make a profit and what kind of movies the studios will churn out in search of profits. Over the long run such behavior determines what films will have an enduring cultural presence and become canonical cultural works.

Some Examples of Large-Scale Phenomena

During roughly the third quarter of the twentieth century some anthropologists and archaeologists did a great deal of empirical work on cultural complexity, mostly among preliterate societies. This work typically involved large-scale cross-cultural studies. Much of it was directed toward forms of social organization, establishing a sequence going from the hunting-gathering band, to the tribe, the village, the chiefdom, petty-kingdom, and church-state (Hays 1993, chapter 5; Hays 1997; cf. Service 1975). Note that these levels of social organization are all within preliterate cultures. So far as I know such work has not been attempted among literate cultures.

During the 1960s the late Alan Lomax (1968) decided to investigate folk song styles against the background of cultural complexity. Lomax and his colleagues prepared a sample of over 3000 songs, representing 233 cultures from 5 continents plus the Pacific islands, and had judges code the songs on features of style — nature of the performing group, relationship between vocal part and instrumental parts, melodic style, rhythmic style, wordiness, tone quality, tempo, and so on. They correlated style traits with measures of social complexity and found that the simpler the society, the simpler its song lyrics. The simplest societies used a great deal of repetition and nonsense syllables. Similarly, the precision of enunciation varies with social complexity; the more complex the society, the more precise the enunciation. The prevalence of solo singers was also associated with complexity. In the simplest societies, everyone sang; no one was given or took a solo role. It is only in more complex societies, with permanent leaders and social stratification, that we see ensembles divided into a soloist and accompanists.

This is an empirical finding. And, while it may seem intuitively obvious that complex cultures create a collective ambiance that favors expressive forms that different from those of less complex cultures, one would like an explanation for this “fit.” I would expect a robust account of cultural evolution to provide such an explanation.

In a similar vein, John Roberts, Brian Sutton-Smith, and Adam Kendon (1963) were interested in the relationship between child-rearing practices, community size, types of games, and folk tales. In particular, they were interested in what they have called the strategic mode. Strategy plays a minor role in games of physical skill, but a dominant role in games such as chess and poker, which also has strong elements of chance. In folk tales, we can examine how the outcome is achieved, whether through physical skill, chance (guessing, casting lots, magic), or strategy (e.g. evaluating a situation, deception, out-witting an opponent). They discovered that games of strategy are likely to co-occur with folktales having a strong strategic element and that both are more likely in politically complex societies (chiefdoms and above).

Now let us consider a different style of large-scale research. Franco Moretti (2003) has recently published some very interesting work on the origins and course of the novel in Britain, Denmark, India, Japan, Italy, Span, and Nigeria. In this work he is interested in sheer numbers, creating graphs depicting the number of titles published per year over a century or more, starting in the eighteenth century. In most cases – Britain, Denmark, India, Japan, Italy, Spain – he finds that the rise is not a steady one but is marked with declines so long and deep that we must talk of the cyclic rise and fall of the novel.

To my mind, however, Moretti’s most interesting finding concerns the emergence of British novelistic genres between 1750 and 1900. Most generally, he shows that the types of genre shift over time. For example, Gothic novels were strong from 1800-1825, sporting novels seem to run from 1820 to 1860, while imperial romances run from 1850 though 1890, and so on for over 40 genres. What is most interesting, however, is that the genres seem grouped into six periods of creativity and they disappear in clusters as well. Consequently there is an almost complete turn-over in genres every 25 years or so, that is, roughly a generation (p. 80 ff.). Moretti cannot explain that, but it does seem to be a fact about literary history.

How could one explain such a pattern? I find that to be a deep and puzzling question. But it is not just the evolution of the British novel that puzzles me, it is the phenomenon of cultural, and literary, evolution itself. The work of Lomax and of Roberts, Sutton-Smith, and Kendon suggests causal relations between cultural forms and social organization – a game that has been played by legions of Marxist scholars and critics – but the existence of such relations does not itself tell us why, in the long run, such forms evolve.

Sita Sings the Blues

It is time to turn from such empyrean heights – Moretti talks of distant reading – and think about these aesthetic objects in some greater detail and particularity. Thus I would like to consider one specific example, Nina Paley’s animated film, Sita Sings the Blues. Using a variety of visual styles Paley juxtaposes and intertwines two narratives: 1) the breakup of her own marriage and, 2) the story of Rama and Sita from the Ramayana, one of the classic texts of Hinduism. Paley is thus using Hindu tradition to illuminate her life, and her life to reflect back on that tradition.[2]

Paley tells Sita’s story in three different ways: 1) in a series of vignettes set to songs recorded by Annette Hanshaw in the 1920s and which is animated in a very “cartoony” style; 2) in a series of scenes based on paintings Paley did in imitation of 18th Century Rajput miniatures and on collages based on what appears to be calendar and greeting-card art, and 3) through voice-over dialogue among three Indian-Americans talking about the Ramayana and realized on-screen as three Indonesian shadow puppets. The multiplicity of this story, its many sources – which I’ve only hinted at in this brief description – is deliberately built-in to the visual and audio texture of the film.

One could, in fact, organize a course on cultural process around Sita Sings the Blues. As a way of thinking what could go into such a course, imagine a large table. In the first row we list various elements appearing in the film. In the rows below we trace those elements back to their sources, moving further back in time as we move down the table. The incidents in Paley’s own life took place only a few years ago. The Hanshaw recordings date to the 1920s, as do elements of that caroony style. Hanshaw’s singing, in turn, is in a popular tradition that evolved through over two centuries of interplay between Americans of European origin and Americans of African origin. Some of Paley’s art imitates 18th century Indian sources, which, in turn, can be traced back to Persian miniatures. And so forth and so on through a list of 20, 30, 50 or more items.

And then we have the Ramayana itself, the oldest version of which is attributed to Valmiki. The dating, as best I can tell from a bit of googling, is the sort of thing over which learned scholars argue for generations. It’s not quite lost in the mists of time, but it is very old. As Amardeep Singh (2009) has pointed out, the Ramayana exists in multiple versions that are not always mutually consistent, one source of the confusion exhibited by Paley’s three shadow-puppet narrators. And so this putative course must discuss that kind of process and its role in maintaining culture, but also allowing it to change (cf. Whitehouse 2000).

In thinking about this table one must, of course, distinguish between the process by which Paley took up those materials and made a film and the processes by which those materials had become available for her use. The first is individual creativity while the latter are group processes. The distinction is, however, a difficult one to make. For Paley made the film over five years and began posting segments on the internet as she completed them. Thus she was interacting with her audience during the process, and that audience includes fundamentalist Hindus who objected to her work and, in some cases, threatened her.

Finally, the sociology and economics units in this course can examine Paley’s distribution process and her subsequent income streams. Copyright problems made it impossible for Paley to secure normal theatrical distribution, so she put the film into the public domain and put copies on the internet where people can download them free of charge. She’s shown the film at festivals all over the world, won many prizes, and has developed a small merchandising operation based on the film. All of this depends, more or less, on word of mouth.

But enough already. Let us look at the film itself. What does it look like on the screen? How do we describe it? What features are important to the film’s effect, and which are incidental? These are important and difficult questions and I can do no more than indicate what’s entailed.

I want to examine the Agni Pariksha segment, which is unlike anything other segment in the film.[3] In the Ramayana Sita had to prove her fidelity to Rama in a trial by fire. She throws herself into the flames and is rescued by Agni, the fire deity, thereby establishing her purity.

Paley has placed this segment somewhat after the middle of the film at the point immediately after Nina, her alter ego in the film, learns that her husband wants a divorce. On the sound track we hear her heart thumping away while we see it pulsing (a stylized red heart) and finally breaking. At that point Nina screams, the virtual camera zooms into her wide-open mouth, and we’re into the segment, which is basically a solo dance amid flames.

The role of Sita is danced by Reena Shah, who voices Sita and who also sings the lyrics, written in Hindi by her mother, Laxmi Shah. This is the only place in the film where we hear Hindi and the only place where we see live action, sort of. Paley videotaped Shah dancing before a green screen and then hand-traced Shah’s movements into the film.

Rather than attempting to describe the entire three-minute segment, which could easily go on and on – “a picture is worth a thousand words” and this film packs a lot of them into 180 seconds. Instead, I’ll concentrate on a few frames. The following two frames are from the beginning and the end of the segment, respectively. We see Sita in white outline against a black background, but her hair has some color fill (collaged in) in the ending segment, but not the beginning.

In both frames she is holding  a lighted match. She lit the match at the opening of the segment and then dropped it, lighting the fire beneath her. At the end she blows the match out, ending the segment. Thus there is a bit of visual continuity between the opening and ending segments. At the same time the final act, in effect, reverses the opening one. The opening act took Sita into the fire; the closing act brings her out of it and back into the world.

Is this a rite de passage? (Of course it is, of course.) For who? Sita, Nina, us? Of what kind, from what to what?

Now consider these three frames, which come one after the other in the film:

The backgrounds are pretty much the same, which is what you would expect from such closely spaced frames. But look at Sita in the center. Her outline is not quite the same from one frame to the next, for she’s spinning counter-clockwise at a pretty good rate; but her overall visual mass remains in the same position within the frame. The texture filling her form, however, differs radically from one frame to the next. All three body fills are half-tone images magnified to the point where the individual dots are visible, but I can’t make out identity of the material in either the first frame or the third. The second image is the head of a woman.

Paley uses this technique throughout the segment. None of the collage elements is on the screen for more than a fraction of a second. You can identify some of the images, but not most of them. It is obvious that she’s showing lots of different things mostly through Sita’s form, but through other elements of the segment as well.

Now look at Sita in this next frame, to the left. Her outline, in black, is decoupled from the texture-filling forms, one for her hair (yellow-green), one for her body (a warm medium brown) and still others for her eyes. Paley does this for about six seconds. What’s this about?

If you’ve been reading visual neuroscience you may note that fill and outline are handled in different systems, as is motion. So Paley is “manipulating” those systems, which is interesting. But that doesn’t tell us why she’s doing it? Because she can, and it’s interesting? Certainly, but is that all?

Before I hazard a guess I want to state that the most important thing, at this point, is simply to describe what’s going on. Without that description, nothing else can be done.

So, why’s she doing it? Because it’s different from every other segment in the film, including the other segment that also depicts the Agni Pariksha. This segment is set to Annette Hanshaw’s performance of “Mean to Me” and the visual style is Paley’s old-time “cartoony” style, which she uses for all the Hanshaw performances. That is to say, that ritual enactment is not stylistically different from any other events in the Hanshaw version of the Sita story.

Any anthropologist will tell you that rituals are about transformation (e.g. van Gennep 1960); some literary critics will tell you that as well (e.g. Frye 1965, Barber 1959). By making this segment visually different from anything else in the film Paley is giving the film itself a ritual dimension – though the part of me that is a child of the 60s is thinking “altered state of consciousness” (cf. Fischer 1975). She’s not merely showing a ritual, depicting one in the film; she is inviting us to enact a ritual by experiencing the visual world in a way that is radically different from what we experience anywhere else in the film. This segment of the film IS ritual.

Now, if we wish, we can begin thinking about what happens in the nervous system in this segment that is different from every other segment in the film. In the annoying manner of math textbooks, however, I’ll leave that as an exercise for the reader.

The Priority of Description

I want to conclude with a more general discussion of the need for better descriptive work in my home discipline, literary studies.

Let’s consider some work by a great anthropologist, the late Mary Douglas. She spent the last years of her career investigating so-called ring structures in narrative (Douglas 2007). In such stories the narrative will unfold through a series of steps to a mid-point and then trace its way back through the same series of steps, but in reverse, thus:

1 2 3 … X … 3’ 2’ 1’

Douglas has been investigating ring structure in books of the Old Testament, while I have found it in Osamu Tezuka’s graphic novel, Metropolis (Benzon, 2006) and in two episodes of Disney’s Fantasia (Benzon 2010). I would like to know, for each text of interest (all 100, 1000, or 10,000+ of them), whether or not it has a ring structure. If not, what kind of structure does it have – and on that point I am embarrassed to confess that I don’t know what the alternatives are. They may be named in the literature somewhere, but I don’t know that work.

Determining whether or not a narrative has a ring-form is not a deeply difficult and problematic task. It is not neuro-science, nor even rocket science. But it is tedious and time-consuming. And that, I suppose, is one one reason why the work hasn’t been done. Another reason is that we have no theory of narrative cognition that would tell us the role such a form plays in comprehension.

As another example, consider the well-known distinction between story and plot (cf. Shklovsky 1965). Story refers to the intrinsic temporal order of a series of events in some narrative while plot refers to the order in which those events are introduced into a particular narrative. Where plot order and story order are the same, there is no need to make the distinction. But many narratives introduce events in some order other than that intrinsic to those events. Noting this fact and attending to it in fragments of texts is standard practice in narratology. But I am unaware of any effort to systematically map the relationships of story and plot for complete texts. David Herman has done so for a film, Atom Egoyan’s The Sweet Hereafter (Herman 2002, pp. 237-250), and has discovered that the ordering of some events with respect to others is indeterminate. That’s an interesting result. Is this the only narrative where that is so? It seems unlikely, but the work hasn’t been done that would permit us to answer that question.

While I can multiply such examples, there’s no point in that. Such work simply hasn’t been systematically and thoroughly done (see Benzon 2005 for a more complete account of such a descriptive program). We have some useful conceptual tools, but lack an overall intellectual context in which the thorough use of those tools for descriptive purposes is seen as an important matter. It seems to me that the cognitive sciences might provide some of that context, for computation – as a model as well as a metaphor – has been critical in the development of the cognitive sciences. And the matter of serial order is fundamental to both the practice and theory of computation. Computation, real computation, is always resource limited: is there enough time to reach a result, do we have enough memory? Intuitively, a narrative which forces the distinction between plot and story requires more computational resources than one that does not (cf. Benzon 1993). Is there a reason, then, for using a more computationally expensive strategy?

That is one thing. There is another.

Consider the situation of Darwin faced in the 19th century. When he began formulating his ideas on the origin of species he had three bodies of knowledge to work from: prior thought on the topic, his own observations over three decades, and the cumulative results of four centuries of descriptive work in natural history (cf. Ogilvie 2006) to which he had access through books and collections. That descriptive work provided models for his own observation and description. Plants and animals, and their lifeways, are very complex. Which traits and features are the most important to observe and describe? That is not an obvious matter, and it took naturalists decades to arrive at useful descriptive methods (cf. Foucault 1973, pp. 128 ff.). Secondly, it gave him the means to abstract and generalize from his own observations, to explore their implications throughout the natural world, most of which, of course, was beyond his immediate experience.

In short, description was indispensable to Darwin’s enterprise, as it is to biology in general. Though discussions of scientific method accord more cachet to theory-testing, and devotes more effort to debating it, description is no less necessary to objective knowledge. It sets the boundaries of the knowable. If we cannot describe a phenomenon – whether in words, images, or mathematical expressions – then we cannot investigate it, we cannot come to explain it.

How, then, do we gain more effective control over literary texts? I have no easy answer to that question. These are very complex objects, not only literary texts, but other cultural artifacts and processes. They have many properties one could note in a description – for all practical purposes the number of properties is unbounded. How, then can we tell which properties are memetically active?

For one thing, it helps to be . . . no, it is essential that one is familiar with a wide range of examples, and to have worked through many examples in detail. This cannot be done by reading a methods book or two or three or ten or by reading up on the pop neuroscience du jour. It requires total immersion in primary materials.

Given that, I imagine that the statistical techniques developed in corpus linguistics would be useful tools. And such tools represent our only hope of gaining some purchase on the vast number of texts that are our proper province. Then, one day some decades from now, perhaps longer, when we have better descriptive control over literary phenomena, then it will be possible for a Darwin-of-literature to come on the scene and make deeper sense of the distribution and diversity of literary forms. But for now, we must labor in the fields of analysis and description. For us, to quote John Barth, the key to the treasure is the treasure.

Conclusion: All Together Now

In the course of my argument I’ve moved from the emergent behavior of coupled neuro-muscular systems (clapping) and so forth to the apparently mundane business of describing literary texts. The former is properly the domain of the sciences while the latter belongs to literary specialists. These are very different kinds of tasks and require very different methods. To those we can add the work of modeling perceptual and cognitive phenomena, conducting field studies, searching through archives, and simulating phenomena at all scales, from the microscale of neural processes through the macro scale of change over historical time and geographical space. The study of culture encompasses all of that, if not more.

The way is by no means clear. But it is there. Or rather, they are there.

Do we have the will to take those first few steps leading thousands of miles into an intellectual future we cannot foresee in any detail?

Appendix: New Savanna Posts on Cultural Evolution

Cultural Evolution 1: How “Thick” is Culture?
http://new-savanna.blogspot.com/2010/05/cultural-evolution-1-how-thick-is.html

Cultural Evolution 2: A Phenomenological Gut Check on Gene-Culture Coevolution
http://new-savanna.blogspot.com/2010/05/cultural-evolution-2-phenomenological.html

Cultural Evolution 3: Performances and Memes
http://new-savanna.blogspot.com/2010/05/cultural-evolution-3-performances-and.html

Cultural Evolution 4: Rhythm Changes 1
http://new-savanna.blogspot.com/2010/06/cultural-evolution-4-rhythm-changes-1.html

Cultural Evolution 5: Rhythm Changes 2
http://new-savanna.blogspot.com/2010/06/cultural-evolution-5-rhythm-changes-2.html

Cultural Evolution 6: The Problem of Design
http://new-savanna.blogspot.com/2010/06/cultural-evolution-6-problem-of-design.html

Cultural Evolution 7: Where Are We At?
http://new-savanna.blogspot.com/2010/06/cultural-evolution-7-where-are-we-at.html

Cultural Evolution 8: Language Games 1, Speech
http://new-savanna.blogspot.com/2010/06/cultural-evolution-8-language-games-1.html

Cultural Evolution 8A: Addendum on Language as Game
http://new-savanna.blogspot.com/2010/06/cultural-evolution-8a-addendum-on.html

Cultural Evolution 9: Language Games 2, Story Telling
http://new-savanna.blogspot.com/2010/06/cultural-evolution-9-language-games-2.html

These two posts are also useful:

The Busy Bee Brain
http://new-savanna.blogspot.com/2010/05/busy-bee-brain.html

The Sound of Many Hands Clapping: Group Intentionality
http://new-savanna.blogspot.com/2010/06/group-intentionality-collective-mind.html

Notes

[1] I post many of my graffiti photos to a Flickr site, where my user name is STC4blues:

http://www.flickr.com/photos/stc4blues/collections/72157601413328684/

[2] Paley has established a website where you can find information about Sita Sings the Blues, links to interviews and articles, and even links to downloadable copies of the film itself. The Wikipedia entries on the film and on Paley herself are also useful, as is Paley’s own blog.

Sita site: http://www.sitasingstheblues.com/

Nina Paley’s blog: http://blog.ninapaley.com/

Wikipedia, Sita: http://en.wikipedia.org/wiki/Sita_Sings_the_Blues

Wikipedia, Paley: http://en.wikipedia.org/wiki/Nina_Paley

[3] You can view the Agni Pariksha segment online here:

http://www.youtube.com/watch?v=jdG6PySczg0&feature=related

Start at, say, 7:00, to see Nina’s heart get broken; the purification segment itself starts at 7:20.

References

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Benzon, William (2001). Beethoven’s Anvil: Music in Mind and Culture. Basic Books.

Benzon, William (2002). Colorless Green Homunculi. Human Nature Review 2: 454-462, 2002.

Benzon, William (2005). Literary Morphology: Nine Propositions in a Naturalist Theory of Form. PSYART: An Online Journal for the Psychological Study of the Arts, August 2005, Article 060608. URL: http://www.clas.ufl.edu/ipsa/journal/2006_benzon01.shtml
Downloadable PDF: http://ssrn.com/abstract=1503087

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Hays, D. G. (1997). The Measurement of Cultural Evolution in the Non-Literate World: Homage to Raoul Naroll. New York, Metagram Press.

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Lewens, Tim (2007). Cultural Evolution. Stanford Encyclopedia of Philosophy. URL: http://plato.stanford.edu/entries/evolution-cultural/

Lomax, A. (1968). Folk Song Style and Culture. New Brunswick, Transaction Publishers.

Martindale, Colin (1990). The Clockwork Muse: The Predictability of Artistic Change. Basic Books, Inc.

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Néda, Z., E. Ravasz, et al. (2000). “The sound of many hands clapping.” Nature 403: 849-850.

Ogilvie, B. W. (2006). The Science of Describing: Natural History in Renaissance Europe. Chicago, University of Chicago Press.

Roberts, J. M., B. Sutton-Smith, et al. (1963). Strategy in Games and Folk Tales. Mythology. P. Maranda, ed. Harmondsworth, Middlesex, Penguin Books, Ltd.: 194-211.

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Whitehouse, Harvey (2000). Arguments and Icons: Divergent Modes of Religiosity. Oxford.

Creativity and computers: what could these possibly have to do with one another? “Nothing!,” many people would say. The two are simply incompatible.”

Well, I disagree. Computers and creativity make interesting partners with respect to two different projects. One, which interests me the most, is understanding human creativity. The other is trying to produce machine creativity–or anyway, machine “creativity”–in which the computer at least appears to be creative, to some degree.

What is Creativity?

Human creativity is something of a mystery, not to say a paradox. One new idea may be creative, while another is merely new. What’s the difference? And how is creativity possible? Creative ideas are unpredictable. Sometimes, they even seem to be impossible — and yet they happen. How can that be explained?

Before we can hope to explain creativity, we need to know what’s meant by the term. In fact, people use it in rather different ways — so, when discussing it, they can end up talking at cross purposes.

Here, let’s agree that creativity is the ability to come up with ideas or artefacts that are new, surprising, and valuable. “Ideas,” here, includes concepts, poems, musical compositions, scientific theories, cooking recipes, choreography, jokes … and so on. “Artefacts” include paintings, sculpture, steam-engines, vacuum cleaners, pottery, origami, penny-whistles … and more.

Creativity isn’t a special “faculty,” confined to a tiny elite: it’s an aspect of human intelligence in general. Nor is it an all-or-none affair. Rather than asking “Is that idea creative, Yes or No?,” we should ask “Just how creative is it, and in just which way(s)?” Asking that question will help us to see just what sorts of psychological process could have brought the new idea about.

Creative ideas, then, are new. But of course, there’s new–and there’s new. Ask a teacher, for instance. Children can come up with ideas that are new to them, even though they may have been in the textbooks for years. Someone who comes up with a bright idea is not necessarily less creative just because someone else had it before them.

We need to make a distinction between “psychological” creativity and “historical” creativity. (P-creativity and H-creativity, for short.) P-creativity is coming up with a surprising, valuable idea that’s new to the person who comes up with it. It doesn’t matter how many people have had that idea before. But if a new idea is H-creative, that means that (so far as we know) no-one else has had it before: it has arisen for the first time in human history.

Clearly, H-creativity is a special case of P-creativity. For historians of art, science, and technology, H-creativity is what’s important. But for someone who is trying to understand the psychology of creativity, it’s P-creativity which is crucial. Never mind who thought of the idea first: how could anyone manage to come up with it, given that they had never thought of it before?

If “new,” in this context, has two importantly different meanings, “surprising” has three. First, An idea may be surprising because it’s unfamiliar, or even unlikely–like an outsider winning the Derby. This sort of surprise goes against statistics.

The second sort of surprise is more interesting. An unexpected idea may “fit” into a style of thinking that you already had–but you’re surprised because you hadn’t realized that this particular idea was part of it.

And the third sort of surprise is more interesting still. This is the astonishment you feel on encountering an apparently impossible idea. It just couldn’t have entered anyone’s head, you feel–and yet it did. What on earth can be going on?

The Three Roads to Creative Surprise

“What is going on” isn’t magic–and it’s different in each type of case. For creativity can happen in three main ways, which correspond to the three sorts of surprise.

The first involves making unfamiliar combinations of familiar ideas. Examples include poetic imagery, collage in painting or textile art, and analogies. Think of a physicist comparing an atom to the solar system, for instance, or call to mind some examples of creative associations in poetry or in political cartoons.

In all these cases, making–and appreciating–the novel combination requires a rich store of knowledge in the person’s mind, and many different ways of moving around within it. If the new combination is to be valued, it has to have some point. It may or (more usually) may not have been caused by some random process–like shaking marbles in a bag. But the ideas/marbles have to have some intelligible conceptual pathway between them for the combination to “make sense.”

The other two types of creativity are interestingly different from the first. They involve the exploration, and in the most surprising cases the transformation, of conceptual spaces in people’s minds.

Conceptual spaces are structured styles of thought. They aren’t originated by one individual mind, but are picked up from one’s culture, or occasionally borrowed from other cultures. They include ways of writing prose or poetry; styles of sculpture, painting, or music; theories in chemistry or biology; fashions of couture or cooking … in short, any disciplined way of thinking that’s familiar to (and valued by) a certain social group.

Within a given conceptual space, many thoughts are possible, only some of which may have been actually thought. Some spaces have a richer potential than others. Noughts-and-crosses is such a restricted style of game-playing that every possible move has already been made countless times. But that’s not true of chess, where the number of possible moves, though finite, is astronomically large. So is the space of possible sonnets, or screenplays, or fugues.

Someone who comes up with a new idea within a particular thinking-style is being creative in the second, exploratory, sense. If the new idea leads on to others (still within the same space) whose possibility was previously unsuspected, so much the better. Exploratory creativity is valuable partly because it can enable someone to see possibilities they hadn’t glimpsed before. They may even start to ask just what limits, and just what potential, this style of thinking has.

All professional artists and scientists do this sort of thing. Even the most mundane street artists produce new portraits every day. They are exploring their space, though not necessarily in an adventurous way. Occasionally, they may realize that their sketching-style enables them to do something (convey the set of the head, or the hint of a smile) better than they’d been doing before. They add a new trick to their repertoire, but in a real sense it’s something that “fits” their established style: the potential was always there.

What the street-artist–or Picasso, in a similar position–may also do is realize the limitations of their style. Then, they have an opportunity to change it.

The limits of the thinking-style, or of some particular aspect of it, may be slightly pushed, slightly altered, gently tweaked. They may even be changed so decisively that ideas which previously were unthinkable now become possible. The deepest cases of creativity involve someone’s thinking something which, with respect to the conceptual spaces in their minds, they couldn’t have thought before. The supposedly impossible idea can come about only if the creator transforms the pre-existing style in some radical way.

But how can that possibly happen? And how could computers help us to find the answer?

How Can Computers Throw Light on Creativity?

To understand how exploratory or transformational creativity can happen, we must know what conceptual spaces are, and what sorts of mental processes could explore and modify them.

Styles of thinking are studied by literary critics, musicologists, and historians of art, fashion, and science. And they are appreciated by us all. But intuitive appreciation, and even lifelong scholarship, may not make their structure clear. (An architectural historian, for instance, said of Frank Lloyd Wright’s Prairie Houses that their “principle of unity” is “occult”.)

This is the first point where computers are relevant. Conceptual spaces, and ways of exploring and transforming them, can be described by concepts drawn from artificial intelligence (AI).

AI tries to get computers to do the many different sorts of things that minds can do. Indeed, AI-concepts enable us to do psychology in a new way, by allowing us to construct (and test) hypotheses about the structures and processes that may be involved in thought. For instance, the structure of tonal harmony, or the “grammar” of Prairie Houses (no longer “occult”), can be clearly expressed, and specific ways of exploring the space can be tried out. Methods for navigating, and changing, highly-structured spaces can be compared.

Of course, there is always the additional question of whether the suggested structures and processes are actually implemented in people’s heads. And that question isn’t always easy to answer. But the point, here, is that a computational approach gives us a way of formulating clear scientific hypotheses about the rich subtleties of the human mind.

With respect to understanding creativity, computer models can help us because they can be creative. Or rather, they can at least appear to be creative.

Many people would argue that no computer could possibly be genuinely creative, no matter what its performance was like. It might produce theories as ground-breaking as Einstein’s, or music as highly valued as Beethoven’s … but still, for these people, it wouldn’t really be creative.

Several different arguments are commonly given. For instance: it’s the programmer’s creativity that’s at work here, not the machine’s. The machine isn’t conscious, and has no desires or values–so it can’t appreciate or judge what it’s doing. A work of art is an expression/communication of human experience, so machines simply don’t count. And all ideas have meaning, which is lacking in computers.

Perhaps you accept at least one of those reasons for denying creativity to computers? Very well, I won’t argue with you here. Let’s assume, for the purpose of this discussion, that computers can’t really be creative. That doesn’t mean, however, that there’s nothing more of interest to say.

All the objections just listed accept, for the sake of argument, that the imaginary computer’s performance is indeed very like that of human beings. What we need to focus on here is whether it’s true that computers could, in fact, come up with ideas that at least appear to be creative–and, if so, how?

Computer Models of Creativity

Let’s consider combinational creativity first. In one sense, this is easy to model on a computer. For nothing is simpler than picking out two ideas (two data-structures) and putting them alongside each other. A computer could merrily produce novel combinations till Kingdom come.

But would they be of any interest? We saw, above, that combining ideas creatively isn’t like shaking marbles in a bag. There must be some intelligible, though previously unnoticed, link between them that we value because it is interesting in some way. We saw also that combinational creativity typically requires a very rich store of knowledge, and the ability to form links of many different types.

For a computer to make a subtle combinational joke, for example, would require (1) a database with a richness comparable to ours, and (2) methods of link-making (and link-evaluating) comparable in subtlety with ours. In principle, this isn’t impossible. After all, the human mind/brain doesn’t do it by magic. But don’t hold your breath!

The best example of computer-based combinational creativity so far is a program called JAPE, which makes punning jokes of nine general types that are familiar to every ten-year-old. For example: What do you call a depressed train?–A low-comotive, and What’s the difference between leaves and a car?–One you brush and rake, the other you rush and brake. To be able to do this, the program needs a set of templates defining the ’skeleton’ of each type of joke (e.g. What’s the difference between an x and a y?, What kind of x can y?, and What do you get when you cross an x with a y?), plus rules for finding words to fit the chosen template. Those rules, in turn, need access to a large semantic network (of over 30,000 items), with links representing not only meaning, hierarchy, and synonymy but also phonology, spelling, syllabic structure, and grammatical class.

Filling-in a familiar joke-schema is difficult enough. (Try to work out just what was needed to generate the joke about the depressed train.) But making a one-off jest is usually more demanding. Ask yourself, for instance, what Jane Austen had to know in order to write the opening sentence of Pride and Prejudice: “It is a truth universally acknowledged that a single man in possession of a good fortune must be in want of a wife.” (And why, exactly, is it funny?) To put the relevant knowledge into a computer, alongside (so as not to ’cheat’) the many other things that Austen happened to know, would take forever. And to enable the program to originate the countless one-off jokes in the book (in Mr. Collins’ preposterous proposal to Elizabeth, for instance) would in practice be impossible.

In short, computer models of combinational creativity can help us to understand, in general terms, how our own combinations can come about–but they will generate valuable new combinations only rarely.

Exploratory creativity is more promising. Indeed, several programs already exist which can explore a given space in acceptable ways.

One example is Harold Cohen’s AARON, a drawing-program that can generate thousands of line-drawings or coloured images in a certain style. These are pleasing enough to be exhibited in galleries around the world. Another is David Cope’s “Emmy”, which composes music in many different styles (based on human composers such as Bach, Mozart, Stravinsky, and Joplin). Still others include architectural programs that design Palladian villas or Prairie Houses, and programs that can analyse experimental data and find new ways of expressing scientific laws.

A few AI-programs can even transform their conceptual space, by altering their own rules. ”Evolutionary” programs, for instance, can make random changes in their current rules so that new forms of structure result. At each generation, the “best” structures are selected, and used to breed the next generation. Several examples evolve coloured images which, like AARON’s, are exhibited in galleries world-wide. These images often cause the third, deepest, form of surprise. In such cases, one can’t see the relation between the daughter-image and its parent. The one appears to be a radical transformation of the other, or even something entirely different.

Values and Creativity

There’s no major difficulty in getting an (evolutionary) art program to make transformations: that’s relatively easy. What’s difficult is to state our aesthetic values clearly enough to enable the program itself to make the evaluation at each generation. At present, the “natural selection” is done by a human being. (In scientific domains, the value-criteria can often be stated clearly enough to allow the program to apply them automatically. So these techniques are used, for instance, to help biochemists to design new molecules for pharmaceutics.)

One huge problem here has no special relevance to computers, but bedevils discussion of human creativity too. I said earlier that “new” has two meanings, and that “surprising” has three. I didn’t say how many meanings “valuable” has–and nobody could. Our aesthetic values are difficult to recognize, more difficult to put into words, and even more difficult to state really clearly. (For a computer model, of course, they have to be stated really, really clearly.)

Moreover, they change. They vary across cultures. They are often disputed: different subcultures or peer groups value different types of dress, jewellery, or music. And where transformational creativity is concerned, the shock of the new may be so great that even fellow artists or fellow-scientists find it difficult to see value in the novel idea.

Because creativity by definition involves not only novelty but value, and because values are highly variable, it follows that many arguments about creativity are rooted in disagreements about value. This applies to human activities no less than to computer performance. So even if we could identify and program our aesthetic values, so as to enable the computer to inform and monitor its own activities accordingly, there would still be disagreement about whether the computer even appeared to be creative.

The answer to our opening question, then, is that there are many intriguing relations between creativity and computers. Computers can come up with new ideas, and help people to do so. And computer models of creativity, both in their failures and in their successes, help us think more clearly about our own creative powers.

Abstracted from ‘Qualitative experience in machines,’ The Digital Phoenix: How computers are changing philosophy.

1. Many people, perhaps most people, have the idea that, however problematic qualitative experience is for the case of human beings, it is a lot more so for that of machines constructed by human beings.  Few philosophers doubt that human beings’ experiences have qualitative characters, but many doubt or disbelieve outright that robots and computers (much less backhoes and can openers) could ever have qualitative experiences at all.  Often the latter denial is just evinced, as an “intuition,” though occasionally it has been argued.  There are even some philosophers who think that the big problems have been pretty well solved for human beings or can be solved without much further effort, but who also think that machines simply could not be conscious, have qualitative or subjective experiences, etc.; that is the most extreme version of the idea I am considering.

My purpose in this paper is to defend the goose-gander thesis that the disparity here is specious: There is no problem for or objection to qualitative experience in machines that is not equally a quandary for such experience in humans.  It is, I contend, mere human chauvinism or at best fallacy to suppose otherwise.

Just for the record, here are the leading problems regarding the phenomenal character of human experience: Leibniz’-Law objections; the immediacy of our access to qualia; essentialistic and other Kripkean (alleged) modal features of qualia; “zombie”- and “absent-qualia”-type puzzle cases; first-person/third-person asymmetries of several kinds and the perspectivalness of the mental; putative funny facts as claimed by Thomas Nagel and Frank Jackson; qualia in the strict sense, the introspectible monadic properties of apparent phenomenal individuals; the grainlessness or homogeneity of qualitative features, emphasized by Sellars; and Joseph Levine’s now celebrated “explanatory gap.”  That is an impressive array of difficulties for the materialist (1).  It is so impressive, in fact, that it immediately lends support to my goose-gander claim.  For if there is a problem about qualitative experience in machines that is not equally an objection to a materialist view of people, that problem must be additional even to the many and wide-ranging ones I have listed.  It must also be grounded in some substantive difference between machines and human beings.

2. For present purposes, then, we must mean by “machine” something that contrasts interestingly with “human being.”  (In one sense, uncontroversially, human beings are machines.)  Let us mean a kind of artifact, an information-processing device manufactured by people in a laboratory or workshop, out of physical materials that have been obtained without mystery or magic.  A paradigm case would be a robot driven by a present-day supercomputer.  But I want to allow technologically imaginable extensions of that paradigm; a machine need not have von Neumann architecture, or even digital architecture (whatever that means) at all.  And let us idealize a bit:  I shall assume that problems of information storage and retrieval, such as the notorious frame problem, are solved.  (A fairly outrageous assumption, true.  The reason I get to make it is that my chauvinist opponents do not think that their objection could be overcome even if the frame problem and its ilk could be; they think their obstacle arises no matter how good our machine might be at mere information storage and retrieval.)

What, then, are the most obvious differences between machines in the foregoing sense and natural-born human beings, that might support the chauvinist position?  Let us begin by abstracting away from the most obvious deficiency of actual, 1990s machines: that no such thing has a humanoid behavioral repertoire or anything remotely approaching it, because no present-day machine is anywhere nearly as complex as a human being or gifted with a biologic brain’s almost unthinkably vast information-processing capacity.  Here again, my opponents deny that more information processing (per se) would help; no further amount of the same, no matter how large, would convert a mere machine into a sentient creature capable of subjective, qualitative experience.

So let us help ourselves to some futuristic, science-fiction technology, and suppose that such resources have afforded us an expert human simulator.  Elsewhere I have introduced a character called Harry(2), who through amazing miniaturization and cosmetic art is an entirely lifelike android.  He is also a triumphant success of AI: his range of behavior-in-circumstances is equal to that of a fully acculturated and rather talented late 20th-century American adult.  No one would ever guess that he is not an ordinary person.  (Let us further suppose that his internal functional organization is very like ours; his total pattern of information flow is parallel to ours, even though it runs on considerably different hardware.)

But our question is, in the relevant sense, is Harry a person at all?  He is, remember, only a computer with limbs; his humanoid looks are only a brilliant makeup job.  Some philosophers will readily grant that he has beliefs or belief-like states; after all, he stores and deploys information about his environment and about the rest of the world.  But desires are a bit harder; hopes, embarrassments and other conative attitudes still harder.  Yet even those who would award Harry a full range of propositional attitudes might still balk at qualitative experience.  Even if in some sense he thinks, he does not feel in the most immediate sense in which we doso says the chauvinist.

3. Before we go on to look at some further differences between Harry and the rest of us, let us note that there is a heavy presumption in favor of my egalitarian goose-gander claim (3).  First, how do we now tell that any familiar humanoid being is conscious?  Normatively pursued, this is just the Problem of Other Minds.  But we need not take a stand on the best solution to that problem in order to note its origin.  The problem begins with the fact that the ordinary person’s evidence for ascribing mental states, including qualitative states, to another human being is the latter’s behavior, broadly construed, in the circumstances, broadly construed.  How we justify the epistemic move from that behavior to the mental ascription is a topic of notorious controversy, but unless we succumb to global skepticism about other minds, we do not doubt that the mental ascription is justified by our observation of the behavior.  (Of course the justification is defeasible.)

Few readers will have failed to foresee my next move:  By hypothesis, Harry is a flawless human simulator and behaves, in any circumstance, just as a human being might.  So, over time, he provides his viewers with just the same sorts of behavioral evidence for mental ascriptions that you or I doincluding ascriptions of qualitative experience.  So far as we have evidence for ascribing qualitative phenomenal states to each other, we have just as strong prima facie evidence for ascribing them to Harry.  And common sense, at least, counts that evidence as very strong, so strong that we rarely even entertain potential defeaters.

Notice further that in the case of human beings, such behavioral evidence does not require assumptions about the subject’s innards (4).  We mature and educated people do know that other human beings are biologic organisms and we presume that the others’ biology is like theirs, but the standard tacit behavioral reasoning does not depend on that presumption.  1) A child or naïf who did not know those things would be just as well justified in her/his mental ascriptions, or at least very nearly as well justified, as we.  And 2) if we were watching a videotape of humanoid creatures which might be from another planet and might have a biology quite different from ours, then if those beings behaved just like humans, we would still be justified in imputing human mental states to them–indeed, I submit we would not even think about it, unless our philosophical guard were up.

The foregoing points, especially subargument 2), might be thought to beg the question against the chauvinist.  But they do not.  I have granted (and would insist) that the justification conferred by the behavioral evidence is in every case defeasible.  That leaves open the possibility that for machines, or even for aliens, the class of potential defeaters is wider than that which attends mental ascription to human beings, and I have not assumed otherwise.  My present point is only that powerful defeat is required in Harry’s case; the chauvinist is already one–a big one–down.

Here is my second argument for the same conclusion.  (Science fiction again:)  Suppose that Henrietta, a normal human being, requires neurosurgery; indeed her entire CNS is under attack by a virus that will gradually destroy it.  The surgeons start replacing it (and if you like, much of the rest of Henrietta) with prostheses.  First a few neurons are replaced by tiny electronic devices.  These micromachines so sucessfully duplicate the functions of the neurons they replace that Henrietta’s performance is entirely unimpaired.  Then a few more neurons are removed and substituted for; complete success again.

And so on until there is no wetware lefteventually, Henrietta’s behavior is controlled entirely by (micro)machinery, yet her intelligence, personality, poetic abilities, etc., and most importantly her perceptual acuity, sensory judgments and phenomenological reports remain just as always.  Now, a chauvinist must maintain that at some point during the sequence of operations, Henrietta ceased to have qualitative experiences; she has become cold and dead inside and is now no more sentient than a pocket calculator.  One can imagine a particularly boorish chauvinist asserting this to her face.  She would protest, of course, and tell him that her inner life is as rich and vivid as ever, describing it as lyrically as time and his rudeness allow.  It is hard to imagine how the boor, or any other chauvinist, would be able to draw a line and state with assurance that after the nth operation, Henrietta ceased to have a phenomenology (whatever she may think to the contrary).  It is a hard position to defend.

Here again, I do not want to beg the question against the chauvinistor to commit a slippery slope fallacy, either.  For there may be a defeater that cuts in at some point and does override the behavioral evidence; and the “point” may be a vague one to boot (5).  As before, I am not asserting that no such defeater exists, but only emphasizing that the chauvinist bears the burden of coming up with one and that it is a considerably heavier burden than one might think.

4. What, then, are the defeaters specific to machinekind?  I can think of three possibilities.  First:  There is Harry’s origin.  He is an artifact; he was not of woman born, but was cobbled together on a workbench by a group of human beings for purposes of their own.  Perhaps a workshop is not a proper mother (imagine Dame Edith Evans enunciating, “A workshop?”).

I do not think any sound chauvinist argument can be based on that difference.  For suppose we were to synthesize billions of human cells and stick them together, making a biologic humanoid organism.  (We could either make a mature adult straightway or, what is technologically easier, make a fetus and nurture it.)  We might further suppose that the resulting pseudo-humanlet us call him Hubertis a molecular duplicate of a preëxisting human being.  There is little doubt that such a creature would have qualitative experience; at least, if he did not, that would probably not be simply because of his early history (6).  So artifactuality per se seems not to count against having phenomenal states. Our first difference is no defeater (7).

Second: It may be said that Harry is not a living organism.  (Paul Ziff made such an appeal in his well-known article, “The Feelings of Robots” [8].)  If something is not an organism at all, properly speaking, then there does seem to be something odd about ascribing sensations and feelings to it.

Much depends on what is considered criterial for “living organism.”  We have already failed to find reason to think that artifactuality per se precludes qualitative experience.  Parallel reasoning would show that artifactuality per se does not preclude something’s being a living organism either, for surely our synthesized pseudo-human would count as a living organism.  Putting artifactuality aside, then, what constitutes living?  Automotion?  Autonomous growth and regulation of functions?  Reproduction or self-replication?  Metabolism?  Being made of protein?

Whatever.  Some of these things–the first three, at least–could be done by a machine, in which case the machine would be “alive” in the relevant sense and the objection’s minor premise goes false.  Others, very likely the last two, could not be done by machines; but in that case we should ask pointedly why they should be thought germane to consciousness, qualia and the rest.  E.g., why should a thing’s metabolizing or not bear on its psychological faculties in so basic a way as to decide the possibility of qualitative experience?  It is hard to see what the one has to do with the other, or to imagine a plausible argument leading from “no metabolism” to “no qualitative experience.”  And likewise for being made of protein.

Also, remember Henrietta.  She started out as a normal human being but was gradually turned into a machine.  Did she go from being a living organism to being non-living, inanimate?  In that caseif she had been alive and then ceased to liveshe died, and obsequies are in order.  It would be both hard and easy to make her funeral arrangements:  Hard, because we would first have to persuade her that she was dead and that services should be held at all; she might resist that suggestion fairly indignantly, especially when we got around to the question of burial vs. cremation.  But then easier, because we would not have to guess posthumously at her wisheswe could just ask her what hymns she wanted, whether there should be a eulogy or a general sermon, and so forth, right up till the last minute.  I must say I think I would enjoy attending that funeral; I am not so sure that Henrietta would, herself.

Notes

1 As is perhaps surprising and certainly far from well enough known, every one of those problems is resolved in my books Consciousness (Cambridge, MA: Bradford Books / MIT Press, 1987) and Consciousness and Experience (Cambridge, MA: Bradford Books / MIT Press, 1996).

Incidentally, in this paper I shall concentrate only on “feels” in the sense of qualia.  But for explicit defense of the thesis that machines can have feelings in the sense of emotions, see (e.g.), A. Sloman and M. Croucher, “Why Robots will Have Emotions,” in the Proceedings of the 7th International Joint Conference on Artificial Intelligence (Vancouver, B.C., 1981), and N.H. Frijda, “Emotions in Robots,” in H.L. Roitblat and J.-A. Meyer (eds.), Comparative Approaches to Cognitive Science (Cambridge, MA: Bradford Books / MIT Press, 1995).

2 “Abortion and the Civil Rights of Machines,” in N. Potter and M. Timmons (eds.), Morality and Universality (Dordrecht: D. Reidel, 1985), pp. 141ff.; and the Appendix to Consciousness, loc. cit.

3 The following two arguments are reprised from the Appendix to Consciousness, loc. cit., pp. 125-26.  (Hereafter I am going to spare myself typing “loc. cit.” in references to my own works.)

4 This claim is contested by Christopher Hill, in Ch. 9 of Sensations (Cambridge University Press, 1991), and by Andrew Melnyk in “Inference to the Best Explanation and Other Minds,” Australasian Journal of Philosophy 72 (1994): 482-91.  What follows in this paragraph is in part a reply to their objections.

5 Ch. 2 of my Consciousness and Experience defends the claim that the notion of conscious awareness is vague and comes in degrees of richness or fullness.

6 My suggestion about molecular twinning is not meant to suggest that qualiaphenomenal propertiesare “narrow” in the sense of supervening upon molecular constitution.  In Ch. 6 of Consciousness and Experience I argue that they are “wide” and do not.  But there is no reason to think that the external factors needed to determine qualitative character include the circumstances of one’s coming into existence.

7 In fact, I think that discrimination against Harry on the basis of his birthplace and/or his genesis would be almost literally a case of racism.

8 Analysis 19 (1959): 64-68.  In reply, see also J.J.C. Smart, “Professor Ziff on Robots,” Analysis 19 (1959): 117-18, and Hilary Putnam, “Robots: Machines or Artificially Created Life?,” Journal of Philosophy 61 (1964): 668-91.  Interestingly, I have found that young children uniformly resist the anthropomorphizing of computers on the grounds that computers are not alive.

Most researchers agree that there is no reason in principle why we will not eventually develop conscious machines that rival or surpass human intelligence. If we are crossing to a new era of the posthuman, how have we gotten here? And how should we understand the process?

Cultural theorists have addressed the topic of the posthuman singularity and how, if at all, humanity will cross that divide. Most scholars have focused on the rhetorical and discursive practices, the metaphors and narratives, the intermediation of scientific texts, science fiction, electronic texts, film, and other elements of the discursive field enabling the posthuman imaginary. While recognizing that posthumans, cyborgs and other tropes are technological objects as well as discursive formations, the focus has been directed less toward analyzing the material systems and processes of the technologies and more toward the narratives and ideological discourses that empower them. We speak about machines and discourses “co-constituting” one another, but in practice, we tend to favor discursive formations as preceding and to a certain extent breathing life into our machines. The most far-reaching and sustained analysis of the problems has been offered by N. Katherine Hayles in her two recent books, How We Became Posthuman and My Mother Was a Computer. Hayles considers it possible that machines and humans may someday interpenetrate. But she rejects as highly problematic, and in any case not yet proven, that the universe is fundamentally digital, the notion that a Universal Computer generates reality, a claim that is important to the positions staked out by proponents of the posthuman singularity such as Morowitz, Kurzweil, Wolfram and Moravec. For the time being, Hayles argues, human consciousness and perception are essentially analog, and indeed, she argues, currently even the world of digital computation is sandwiched between analog inputs and outputs for human interpreters. How we will become posthuman, Hayles argues, will be through interoperational feedback loops between our current mixed analog-digital reality and widening areas of digital processing. Metaphors, narratives and other interpretive linguistic modes we use for human sense-making of the world around us do the work of conditioning us to behave as if we and the world were digital.

I propose to circumvent the issue of an apocalyptic end of the human and our replacement by a new form of Robo Sapiens by drawing upon the work of anthropologists, philosophers, language theorists, and more recently cognitive scientists shaping the results of their researches into a new argument for the co-evolution of humans and technics, specifically the technics of language and the material media of inscription practices. The general thrust of this line of thinking may best be captured in Andy Clark’s phrase, “We have always been cyborgs.” From the first “human singularity” to our present incarnation, human being has been shaped through a complicated co-evolutionary entanglement with language, technics and communicational media.

Is there any foundation for relating this approach to the biological evolution of human cognition to a theory of signification and the notions of media machines? Terrence Deacon, Merlin Donald and others have pursued this question deep into the structure of symbolic communication and its embodiment in the neural architecture of evolving human brains. Their work on the evolution of language is suggestive for considering the formative power of media technologies in shaping the human and some of the critical issues in current debates about posthumanity. For Deacon and for Donald what truly distinguishes humans from other anthropoids is the ability to make symbolic reference. This is their version of the Singularity; Homo symbolicus, the human singularity. Although language evolution in humans could not have happened without the tightly coupled evolution of physiological, anatomical and neurological structures supporting speech, the crucial driver of these processes, according to Deacon, was outside the brain; namely, human cultural evolution. The first step across the symbolic threshold was most likely taken by an australopithecine with roughly the cognitive capabilities of a modern chimpanzee. Symbolic communication did not spontaneously emerge as a result of steady evolution in size and complexity of hominid brains. Rather symbolic communication emerged as a solution to a cultural problem. To be sure language could not have arisen without a primitive prerequisite level of organization and development of the neurological substrates that support it. But in Deacon’s view those biological developments were more directly driven by the social and cultural pressures to regulate reproductive behavior in order to take advantage of hunting-provisioning strategies available to early stone-tool-using hominids. Deacon argues this required the establishment of alliances, promises and obligations linking reproductive pairs to social (kin) groups of which they were a part. Such relationships could not be handled by systems of animal calls, postures and display behaviors available to apes and other animals and could only be regulated by symbolic means. A contract of this sort has no location in space, no physical form of any kind. It exists only as an idea shared among those committed to honoring and enforcing it. Without symbols, no matter how crude in their early incarnation, that referred publicly and unambiguously to certain abstract social relationships and their future extensions, including reciprocal obligations and prohibitions, hominids could not have taken advantage of the critical resources available to them as habitual hunters. In short, symbolic culture was a response to a reproductive problem that only symbols could solve: the imperative of representing a social contract. What was at stake here was not the creation of social behavior by the social contract as described by Rousseau, but rather the translation of social behavior into symbolic form.

Once the threshold had been crossed to symbolic communication natural selection shifted in dramatic ways. Deacon bases his model on James Mark Baldwin’s original proposals for treating behavioral adaptation and modification as a co-evolutionary force that can affect regular Darwinian selection. Baldwinian evolution treats learning and behavioral flexibility as a force amplifying and biasing natural selection by enabling individuals to modify the context of natural selection that affects their future offspring. Deacon uses Baldwinian evolution in a provocative way to address the question of the co-evolution of language and the brain. Though not itself alive and capable of reproduction, language, Deacon argues, should be regarded as an independent life form that colonizes and parasitizes human brains, using them to reproduce. Although this is at best an analogy—the parasitic model being too extreme—it is useful to note that while the information that constitutes a language is not an organized animate being it is nonetheless capable of being an integrated adaptive entity evolving with respect to human hosts. This point becomes more salient when we think of language as carried by communication systems and examine the effects of media, including electronic media, more broadly.

For Deacon, the most important feature of the adaptation of language to its host to recognize is that languages are social and cultural entities that have evolved with respect to the forces of selection imposed by human users. Deacon argues that the greater computational demands of symbol-use launched selection pressure on increased prefrontalization, more efficient articulatory and auditory capacities, and a suite of ancillary capacities and predispositions which eased the new tools of communication and thought. Each assimilated change added to the selection pressures that led to the restructuring of hominid brains.

In Deacon’s theory evolutionary selection on the prefrontal cortex was crucial in bringing about the construction of the distributed mnemonic architecture that supports learning and analysis of higher-order associative relationships constitutive of symbolic reference. The marked increase in brain size over apes and the beginnings of a stone tool record are the fossil remnant effects of the beginnings of symbol use. Stone tools and symbols were the architects of the Australopithecus-Homo transition and not its consequences.

Symbolic reference is not only the source of human singularity. It is also the source of subject formation in all its varied manifestations. Deacon bases his theory of reference on (arguably a modified version of) Charles Sanders Peirce’s semiotics. Peirce made the distinction between iconic, indexical and symbolic forms of reference; where icons are mediated by similarity between sign and object, indices are mediated by some physical or temporal connection between sign and object, and symbols are composed of relations between indices and mediated by formal or conventional links rather than by more direct neurological connection between sign and object.

Supported by the evidence of contemporary neuroscience on the plasticity of the neocortex and its capacity to adapt to intricate challenges of a changing cognitive environment, Deacon argues that rather than being rigidly hardwired to structures inside the brain, symbolic communication created a mode of extrabiological inheritance with a powerful and complex character, and with an autonomous life of its own. The individual mind is a hybrid product, partly biological and partly ecological in origin, shaped by a distributed external network whose properties are constantly changing. The leap to the symbolizing mind did not depend on a built-in hard-wired tendency to symbolize reality. The direction of flow was from culture to the individual mind, from outside-to-inside. A number of theorists, including Andy Clark and Kate Hayles have been interested in expanding this analysis to include media other than speech and writing, especially technologically mediated and computer based forms of communication. It is to that argument I want to turn now.

In several books and pathbreaking articles Andy Clark has developed a compelling thesis about what he calls “extended mind” that provides the perfect bridge between Deacon’s work on the evolution of symbolic reference and our considerations of media in the posthuman singularity. In the Extended model of cognition thinking and cognition depend directly and noninstrumentally upon the ongoing work of the body and/the extraorganismic environment. According to Clark:

According to EXTENDED, the actual local operations that realize certain forms of human cognizing include inextricable tangles of feedback, feed-forward, and feed-around loops: loops that promiscuously crisscross the boundaries of brain, body, and world. The local mechanisms of mind, if this is correct, are not all in the head. Cognition leaks out into body and the world.

In discussing the parity principle at the basis of their important paper on the extended mind Clark and David Chalmers argue when the human organism is linked with an external entity creating a two-way interaction, the coupled system consisting of components both external and internal to the brain should be seen as a cognitive system in its own right. All the components, including the external components, play an active causal role and jointly govern behavior in the same way that cognition usually does. If by removing the external component the behavioral competence of the system drops, the external component should be viewed as much a causal factor in the cognitive process whether or not it is wholly in the head. In Clark and Chalmers’ vision of cognition the boundary between external and internal perception and action disappears, so that iPhones, calculators, computational aids and less exotic cultural props such as the tray of letters in a game of Scrabble become components of the extended mind. In the years since they first published their paper (1998) Chalmers has become convinced that the extended mind is most likely even more widely extended than to the domain of beliefs and specifically cognitive processes. What about extended desires, extended reasoning, extended perception, imagination and emotions?

I think there is no principled reason why the physical basis of consciousness could not be extended in a similar way. It is probably so extended in some possible worlds: one could imagine that some of the neuronal correlates of consciousness are replaced by a module on one’s belt, for example. There may even be worlds where what is perceived in the environment is itself a direct element of consciousness.

Brain-machine interfaces such as cochlear implants, artificial prosthetic hippocampus chips, retinal implants and DARPA’s “brain-in-the-loop” imaging systems for its Cognitive Threat Awareness Program are all examples of where the extended mind might be heading.

The Extended Mind treatment of language in terms of hybrid representational forms, coordination dynamics and complementarity between biological and artifactual contributions provides a supportive framework for Hayles’ theory of intermediation described above by offering an account of how the transactions between bodies and our inscription practices might take place and how to understand the “entanglement” Hayles describes of media with the formation of human subjects. The key point in Clark’s model is that language is fundamentally an external resource, and even processes of internal thought, silent rehearsal, and other forms of “off-line” linguaform representation for problem-solving are internal recapitulations of the relevant external vehicles. Of course, there are internal representations in this model, but Clark-Chalmers part company with defenders of neural mentalese (Churchland) or a hardwired language of thought (Fodor). Stressing hybrid representational forms and coordination dynamics of a brain that is fundamentally a pattern-completing engine, the proposal is that external artifactual resources of the symbolic environment are co-opted without being replicated by special biological structures or translated into another internal code. Exposure to external material symbols and epistemic artifacts does not result in the installation of new internal representational forms in the brain, or as Dennett proposed by installing a new virtual serial machine via “myriad microsettings in the plasticity of the brain.”

What then about the posthuman? Are we transitioning to some new form of self adapted to our environment of ubiquitous computing technology, and if so, how is this self assembled and transformed by the machinic processes of our technoscientific milieu? Since the rise of Homo Sapiens between 200,000 to 100,000 years ago, there has been little change in brain size or, as far as can be determined, in brain structure. A critical contributing factor to the rapid cultural evolution that took off with Sapiens and has continued at an ever increasing pace since is the development of supplements to individual internal biological memory in the form of visuographic systems and external memory media, especially written records and other forms of symbolic storage. Rather than being limited by our neural architecture these external material supports have only enhanced the symbolizing power of the mind. In a sense, the recent development of the internet and distributed forms of electronic communication only further accelerate a process that has defined and shaped human being since that first singularity. From the perspective of the work in evolutionary cognitive science we have discussed, any change in the way information gets processed and represented inevitably constitutes a change in the cognitive economy of the subject, a difference in psychic architecture and ultimately of consciousness itself.

In a panel discussion at the 1998 “Bookends” conference at SUNY Albany, Jacques Derrida spoke of Internet initiatives under way by his younger colleagues in France at the time. The first thing they would do, he said, is set up editorial boards, appoint in-house grant writers, and establish closed review processes – effectively replicating the foundations of recent print practice in the  new media.

At the time, I may have allowed myself a moment of self-congratulation since I had done no such thing in the journal I’d founded four years previously, www.electronicbookreview.com [ebr], a DIY literary critical enterprise. Today, I’m not so confident; and I recognize how many institutional inheritances I depended on, not least the collegiality that let me work with and attract contributions from scholars like myself, and also programmers and designers interested in print/screen transformations. Certainly the Internet prior to the Telecommunications Act of 1996 was less dominated by commercial content and instrumental constraints, and it was easy enough to take advantage of a medium created, by scientists, for purposes of freely sharing documents among colleagues working at a distance from one another.

I won’t address here the commercialization of content on the Internet and the neoliberal capitalist turn in academic life. (That was critiqued, as it was happening, notably by Marc Bousquet and Katherine Wills in their ebr thread, Technocapitalism, and the accompanying Alt-X Critical E-Book, The Politics of Informatics [2003].) Instead, I want to look at the way institutional practices can be transformed, if Humanities scholars can make consistent, collaborative, and (not least) frugal use of the affordances of network technology in gathering literary works and forming conversations around them. My recent experience reading 300 works of electronic literature for preservation on the Wayback machine at archiveit.org, an initiative co-sponsored by the Electronic Literature Organization and the Library of Congress, suggests that the oft-noted “obsolescence” of works published in perpetually “new” media is an institutional and cognitive problem as much as a technological challenge. Capturing works on the Internet at stages of their development is technologically feasible. What is hard is finding the works worth preserving, defining their literary qualities, and establishing incentives for readers to go back, for more.

Whatever transformations the Humanities undergo in new media, a condition for the field’s possibility has to be the ability to re-read, and the freedom to cite, the work of peers and precursors. This is the task of editorial boards and granting institutions in online environments: those who vet works need to look at, not only what an author has accomplished, but at what the work might become, as it circulates among other works and, over time, collects comments from readers as well as its initial peer reviewers. In print, the credentialing process ends when the contract is signed; in e-media, the work is vetted continuously (or could be) and lives or dies depending on the readings it attracts, the re-writings it inspires, and how these are presented. That trail of commentary, not number of objects sold, constitutes popularity and presence in electronic environments (though business models will need to emerge, in university presses or other not exclusively commercial enterprises that can recognize this processual aspect of the digital literary object).

The conditions that matter to current research in the Humanities are constrained (though one hopes not pre-determined) by the collective creation of a “Semantic Web” or “Web 2.0” under the direction of Tim Berners Lee, the original architect of the World Wide Web. To some extent, this development answers the need to locate, identify, and re-circulate, information produced and found in electronic environments. The ability to “tag” material conceptually, rather than to search character strings, is of course attractive – one might even say, seductive – for literary scholars. There is first of all the promise, roundly critiqued by Florian Cramer, that “semantic technology” can “allow people to phrase search terms as normal questions, thus giving computer illiterates easier access to the Internet.” Easier access (what Alan Liu more broadly critiques under the phrase, “user friendliness”) generally means a more complete cluelessness about what is actually being searched at the level of code because, at this level, there can be no “semantic language understanding.” As Cramer points out in his “Critique,” that grail has eluded Artificial Intelligence researchers for decades.

Neither should humanists hope to realize, through networked computers, the Aristotelian dream of universally valid categorizations. The so-called “ontologies” that computer scientists create are not ontological in the philosophical sense (no more than, say, the glossy “literature” promoting a product or company has anything to do with novels, poems, or essays). Semantic Web [SW] “ontologies” are not ways of being, but rather ways of sorting and selecting. Cramer calls them “cosmologies,” in the sense of Borges’s “Chinese encyclopaedia”:

In its remote pages it is written that the animals are divided into:  (a) belonging to the emperor, (b) embalmed, (c) tame, (d) sucking  pigs, (e) sirens, (f) fabulous, (g) stray dogs, (h) included in the  present classification, (i) frenzied, (j) innumerable, (k) drawn  with a very fine camelhair brush, (l) et cetera, (m) having just  broken the water pitcher, (n) that from a long way off look like  flies.

Cosmological systems, while good at proliferating differences, remain indifferent to meanings and ambiguities that, whether or not they are recognized in the world, certainly characterize literary work in any medium.

From a literary viewpoint, more promising than the SW’s knowledge management pretensions are the really quite modest methods of tagging texts. Assigning meaning at a second order, apart from the actual text encoding, depends entirely on people and the professional and communicative networks we establish. The creation of professional standards is essential.  Otherwise, semantic markup will only redouble the work needed to create the text proper, and we’ll have built, in Cramer’s words, “a library whose catalogs outnumber the books they reference.”

That can be avoided, I think, if humanists approach the tagging of works as a properly critical practice, developing with works a glossary of keywords and literary concepts. Doing this means that the ones vetting the works should be expected to ground their judgments in professional standards. The burden of understanding is placed on those who presume to evaluate the work, and that understanding needs to circulate with the work proper.

An evolving glossary of electronic literary terms (to echo M.H Abrams’s long established Glossary of Literary Terms in print) has to be applied to works consistently and with an awareness of tag clouds forming throughout the Internet (at www.rhizome.org, for example, and at the newly released Electronic Literature Directory, version 2.0). Moreover, the terms will have to change as the kind of work produced in electronic environments change, and these changes can be tracked. What scholars can then construct is not so much a universal set of categories defining “electronic literature,” “net literature,” or “digital or online literature,” but rather a practice capable of producing a poetics, as e-lit author and critical theorist Sandy Baldwin has recently argued. The novelist Robert Coover made a similar argument when he reported his experience “On Reading 300 Novels” for the 1984 PEN/Faulkner Awards – before the Internet existed, and roughly a decade before Coover himself would move decisively into electronic environments (without ever ceasing to write books). While conducting my own summer e-lit reading, I’ve kept Coover’s essay in mind, especially the criteria he used to distinguish settled and emerging genres.

Coover found that a majority of submissions were “serious” or “priestly” works praised by critics “for their vision, style, commitment, sensibility, honesty, their ‘intense realism.’” These are high-minded works that seek to “transcend mere storytelling, to reach past entertainment for its own sake into speculative and morally perplexing realms….” (38) Many such works are the product of Creative Writing programs, and they can seem “somewhat homogenized” despite the conscious search for a personal “voice.” A few best sellers, mostly formulaic exercises in established genres, also made it to Coover’s desk (and overflowed to his floor).

Ultimately, Coover supposes, “both of these voices are conservative. Both tend, through formal acquiescence, to extend the reign of the cultural establishment, even while challenging it now and then on the surface” (38). But occasionally, “rarely,”

a third voice arises, radically at odds with the priestly and folk traditions alike, though often finding its materials in the latter and sharing with it a basic distrust of the establishment view of things. This voice typically rejects mere modifications in the evolving group mythos, further surface variations on sanctioned themes, and attacks instead the supporting structures themselves, the homologous forms. Whereupon something new enters the world – at least the world of literature, if not always the community beyond. (38)

In a later, more famous essay, “The End of Books,” Coover would carry his investigations beyond “the supporting structures” of genre, psychology, and cultural anthropology to the medial infrastructure itself. In electronic archives, both structures, the generic and the medial, are capable of being transformed concurrently – and those transformations (as much as the work itself) are what need to be tagged and traced.

I don’t expect to find, in my sample of 300 e-lit works anything resembling The Public Burning or even many works in the mode of Coover’s proto-hypertext, “The Babysitter.” Only rarely have I applied the keywords, “Postmodern,” “Experimental,” “Fiction,” “Poem,” and even “Narrative” to electronic literature post-Web 1.0. A bifurcated story by Milorad Pavic on www.wordcircuits.com; a Pynchonesque presentation of the first Iraq War by Stuart Moulthrop (www.eastgate.com); the rude road trips, real and imagined, by Rob Wittig and the collective of “Unknown” writers (robwit.net/robwit/archives; unknownhypertext.com); Mark Amerika’s phon:e:me (phoneme.walkerart.org): these e-lit classics continued the deconstruction that the earlier generation of postmodern authors began. Or rather, one might now say, the first generation of e-lit works completed that deconstructive task, building the digital “Bookend” my conference colleagues and I discussed in Albany ten years ago.

What is being produced at this moment in a Web 2.0 environment cannot be categorized or neatly summarized, though it’s safe to say that the “narrative” and “semantic language understanding,” where found, will co-exist with codes and other non-verbal contexts, much as “the human” nowadays is bounded everywhere by non-human forces and objects. These may have been present always, but their mechanisms are coming to consciousness more readily, and more often. What I’m reading, for the most part, doesn’t often differentiate between “critical” and “creative” writing; the most prolific e-lit authors are also programmers and designers who seem to be as comfortable conversing with scientists and technologists as with other writers. Chances are, the history of the current era won’t appear (like Coover’s articles) in The New York Times or in traditional peer reviewed academic press books. That should not be a cause for gloating, among those who advocated early for a literary migration to new media, or cause for complacency among those who expect the printed book to outlast its new media upstarts. It is rather a call for constructing models of reception and commentary within the medium of our practice, and without too much worry about current disciplinary arrangements.

Works Cited

• Baldwin, Sandy. “Against Digital Poetics (Title in Process)” www.electronicbookreview.com/thread/electropoetics/against (under p2p review, July 2008).
• Coover, Robert. “On Reading 300 American Novels.” The New York Times Book Review (March 18, 1984): 1, 37-8.
• —. “The End of Books” The New York Times Book Review (June 21, 1992).
• Cramer, Florian. “Critique of the ‘Semantic Web.’ Nettime. Tue, 18 Dec 2007.
  [A rough transcript of a lecture manuscript written for the "Quaero Forum" on the politics and culture of search engines at Jan van Eyck Academy, Maastricht, September 2007.]
• Liu, Alan. The Laws of Cool Knowledge Work and the Culture of Information. Chicago: University of Chicago Press, 2004.
• Tabbi, Joseph. “Locating the Literary in New Media.” Contemporary Literature  (Summer 2008). Online at http://www.electronicbookreview.com/thread/criticalecologies/interpretive.
• —. “The Processual Page.” In The Future of the Page, ed. Peter Stoicheff and Andrew Taylor. Toronto: University of Toronto Press, 2004. Online at New Media and Culture: http://www.ibiblio.org/nmediac/fall2003/processual.html
• —. “Setting a Direction for the Electronic Literature Organization’s Directory: Toward a Semantic Literary Web.” http://eliterature.org/pad/slw.html

Whatever the terms “biopower” and “biopolitics” might mean, and they are being used in a growing number of simplistic ways, most of which bear scant relation to how Michel Foucault deployed them. Foucault’s genealogical elaboration of these terms had been conceptual, historical and non-totalizing. Above all, Foucault deployed concepts like “biopower” or “governmentality” in a mode that was expressively capable of recursive rectification. These concepts were to be used and refashioned as necessary. They were part of a History of the Present that was a preliminary effort to open up possibilities of more precise and pertinent thinking and inquiry. Foucault’s concepts were neither naming a unique deep meaning of Western or world history nor uncovering the nefarious workings of “governmentality” understood as social control. Foucault’s concepts were tools to think with — not verities that encouraged people to stop thinking, inquiring, examining their own thought and action.

There are striking similarities between Foucault’s use of genealogy in the History of the Present and Max Weber’s understanding of objectivity in the human sciences. Weber’s directive to those practicing the interpretive human sciences was to shift from attempts to characterize the “actual interconnections of things,” to those directed at distinguishing “the conceptual interconnections of problems.” By so doing, he counseled, there would be a better opportunity for “opening up significant new points of view.” Once such significant new points of view were forged, then sustained inquiry, both historical and anthropological, was the challenge to be met. For both Weber and Foucault, conceptual work on problems was the beginning of experimentation and research rather than a way to avert it.

This spirit and this orientation animated the work of the Human Practices Thrust at the Synthetic Biology Engineering Research Center (SynBERC). We oriented our efforts toward diagnosing what we took to be an emergent assemblage, approached from the vantage point of two stable apparatuses. The two apparatuses were “biopower” and “human dignity.” Initially we designated the assemblage as “the vital.” Our aim was to characterize zones, such as bio-security and bio-ethics, in which elements of the two apparatuses were being recombined as well as interfacing with and contributing to the formation of a third. We understood them as consisting of quite specific, if heterogeneous elements, such as objects and practices, elements in flux, in the course of re-assemblage.

Once we began sustained conceptual work, after multiple delays and blockages, however, we concluded that it was currently premature to diagnose a new “problematization” or “diagram” or “rationality.” First, it became clear that what each of these terms means is far from clear. Second, we came to think that while major changes in diverse empirical domains were unquestionably underway, it was not at all obvious that they had taken anything like a general or definitive form. Furthermore, we concluded that it was conceptually hazardous to assume that they ever would. Having reached an impasse, we decided to change strategies by shifting registers. Here Weber’s counsel was invaluable: pay attention to the conceptual interconnection of problems as a means of opening up significant new points of view that would orient us to inquiry.

Unlike the question of what comes “after” biopower, however, the challenge of specifying the vectors and contours of an uncertain problem-space is a pressing preliminary. Consequently, we decided to return to our site of inquiry. We shifted our efforts back to the challenge of figuring out how best to comprehend, invent, and practice the work we were mandated to take up as part of SynBERC. Given that choice, we decided that the next critical step was to construct a diagnostic. This diagnostic work should assist us in experimenting with and adjusting practices in our particular project, but should leave open the broader issue of whether or not a distinctive figure is emerging within and along side of existing figures, as responses to and factors in shifts in a larger problematization.

The diagnostic is composed of three figures and their equipmental correlates. The three figures in our diagnostic include two well recognized, if often misinterpreted figures, Biopower and Human Dignity, and an emerging constellation of elements that are being brought into relation to one another and may well be coalescing into a third figure. Provisionally, we name this emergent configuration Synthetic Anthropos. The term Synthetic Anthropos is a placeholder. It draws attention to the ways in which real-world problems are being taken up through redesign and reconfiguration so as to produce significant new forms. Examples of this work include synthetic biology, bio-complexity, and bio-security, to name three sites where re-assemblage of elements is underway.

As of 2009, in light of our initial experimentation, we are taking up synthetic anthropos less as an actual figure coalescing in the world, and more as a virtual figure in need of form. As a virtual figure, synthetic anthropos functions as a series of scientific and ethical design parameters and modes of composition. The design parameters facilitate critique and construction by throwing into relief externalities and critical limitations, and by showing where and how those externalities and critical limitations are contributing to scientific indeterminacy and ethical discordancy, to use John Dewey’s terms. They facilitate clarification, more precise adjacency, and a sharper orientation to secession in relation to existing configurations of indeterminacy and discordancy. Most importantly, they facilitate the work of re-imagining and re-constructing pathways toward better equipment and better venues.

For the time being, synthetic anthropos consists of a design challenge set within a compositional mode. In a compositional mode, the design parameters of synthetic anthropos should facilitate the work of transforming our lessons learned into modules suitable for new equipment. Subsequently, it should enable us to synthesize those modules into a more productive practice. To this end, our immediate priority consists less of discovering synthetic anthropos as an object of study, and more about rendering synthetic anthropos as an object of composition, with all that entails — above all — the challenge of constructing a venue capable of facilitating such work. In short, today we are in search of the elements, relations, objects and modes required compositionally for synthetic anthropos. We are in search of Ars Synthetica.

Fifteen years ago, John Searle posed a challenge to “strong” artificial intelligence (the program to create in an artificial medium intelligence comparable to that of humans).  He confidently proclaimed his challenge would withstand the test of time, including any possible advances in computer speed, memory, and robotic appliances.  His challenge, the so-called Chinese Room thought experiment, attracted considerable interest in its heyday, second in controversial appeal only to Alan Turing’s famous “Turing Test,” whose themes it reflected as if in a funhouse mirror.  Today the piece has become something of a historical curiosity.  The “strong” AI program is now widely acknowledged as a failure (although for somewhat different reasons than Searle argued), so it would seem that resurrecting Searle’s rhetorical tour de force would be akin to applying electrical shocks to assembled cadaver parts best left in peace.  As the metaphor suggests, however, the Chinese Room is not so much dead as undead; while its ostensible purpose is moribund, the presuppositions and unconscious assumptions that inform it are still very much alive.  I think the Chinese Room is worth a second look not for the force of its argument but for what it reveals about contemporary ideas on what constitutes the essence of the human, especially intelligence, consciousness, and meaning. Excavating these and juxtaposing them with current controversies over the boundaries of the human will enable us to see what has changed, why it has changed, and what the change signifies in the decade and a half that has passed since Searle delivered the coup de grace that failed to deliver.

Intel Celeron CPU, via Uwe Hermann's Flickr photostream

The Chinese Room experiment is easily explained.  Suppose, Searle writes, that “you are locked in a room, and in this room are several baskets full of Chinese symbols” (32).  You do not understand Chinese, but you have a rule book (in English) that tells you how to manipulate the symbols.  “So the rule might say: ‘Take a squiggle-squiggle sign out of basket number one and put it next to a squoggle-squoggle sign from basket number two’” (32).  “Now suppose that some other Chinese symbols are passed into the room, and that you are given further rules for passing back Chinese symbols out of the room” (32).  The instructions have been cleverly constructed so that an onlooker would think that after questions are passed into the room, appropriate answers issue forth.  This perception, however, is a mistaken illusion, for on “the basis of the situation as I have described it there is no way you could learn any Chinese simply by manipulating these formal symbols” (32). The point he hastens to drive home is that this is just what a so-called “intelligent” computer program does.  “If going through the appropriate computer program for understanding Chinese is not enough to give you an understanding of Chinese, then it is not enough to give any other digital computer an understanding of Chinese” (33).   Why?  “Because no digital computer, just by virtue of running a program, has anything that you don’t have.  All that the computer has, as you have, is a formal program for manipulating uninterpreted Chinese symbols. . . a computer has a syntax, but no semantics” (33).

We begin our interrogation by asking what role Chinese plays in this scenario.  Why not French, Swedish, or Thai?  Presumably Chinese appears because, as a non-alphabetic, non-Indo-European language, it will defeat any attempt by “you” (an English speaker) to guess at word meanings through cognates or common roots.  Chinese is also presumed to be so foreign to “you”  that Searle’s English-speaking audience will immediately sympathize with his description of Chinese ideograms as “squiggle-squiggles” and “squoggle-squoggles.”  Chinese thus functions as the inscrutable other, that which stands outside and apart from a reader’s cultural context and experience.  Furthermore, this alienness is presumed to be absolute.  No amount of “manipulating symbols” will ever give “you” any hint about what words mean through their association with one another-which symbol strings might function as nouns, for example, and which as verbs.  The Orientalist function of Chinese thus reinforces an absolutely crucial point for Searle:  that no bridge can ever be created between syntax and semantics on the basis of associating and manipulating symbols. Put another way, no bridge can be constructed between formal symbol manipulation and meaning.  Genuine (human) intelligence, Searle insists, has more than syntax; it also has content.  Thoughts and feelings are about something, and it is this “aboutness” (or intensionality, a term philosophers use to denote the “aboutness” quality) that marks the meaning-seeking drive essential to humans.

Given this narrative, one might object that given enough time, “you” may be quite likely to make  associations and hence to find meaning, however nascent, in the symbols “you” manipulate.  The division between syntax and semantics can remain inviolable only if no context can ever be created that would bridge the two–yet the simple act of mechanically matching symbols would be the first step in building such a context.  Also in play is the locus of human meaning-making. By placing a human in a locked room and inviting readerly identification by using the second person, Searle performs an act of literary violence upon “you,” reducing “your” capacity for human understanding to a rote mechanical act.  Nothing in the room is represented as extending your own cognitive capacities, which remain so severely stunted that “you” can function only as a non-comprehending automaton.  This painful reduction of human capacity is then equated with a digital computer, a construction that has the effect of making the computer signify as an extremely inadequate person, an idiot savant incapable of ever attaining a properly full and rich human understanding.  Only so does the odd construction make sense in which Searle writes that if you cannot understand Chinese, then no other digital computer can either.  The formula goes like this:  reduce the human to an automaton; equate the human automaton with the digital computer; imply that this reduction of human capacity is the natural (and only) state the computer occupies.

mri of brain, via Liz Henry's Flickr photostream

What does this construction suppress or make difficult to see?  Perhaps most importantly, it implies that the computer’s cognitive capacities reside solely in the CPU, the Central Processing Unit for which the encapsulated human stands.  But of course a computer is more than this, including memory, data storage and retrieval mechanisms, user interface, and so on.  Searle attempts to respond to this objection by saying that even if one includes the Chinese characters, baskets, rule books, etc. as part of the computational system, the divide between semantics and syntax still remains absolute.  He reasons that since none of these artifacts understand Chinese any more than “you” do, nothing essential changes.

Here his assumptions contrast starkly with contemporary theories of emergence in which systems exhibit behaviors that are more than the sum of their parts.  In particular, his assumptions are refuted by the idea of an extended cognitive system, a model that Andy Clark in Supersizing the Mind: Embodiment, Action, and Cognitive Extension refers to as EXTENDED.  Departing from fellow travelers such as Edwin Hutchins who argue that extended cognitive systems serve as scaffolding for human cognition, Clark performs the radically heuristic move of considering them as part of human cognition, a conclusion in direct contradiction to the model he calls BRAINBOUND.  Although Searle has a more capacious view of cognition than many BRAINBOUND theorists, in that he considers feelings as well as thoughts to be part of mind, he participates in a BRAINBOUND worldview in many ways, for example by focusing his attention on the human automaton as the CPU, while relegating the rest of the room’s artifacts to non-cognitive status.

If, on the contrary, we adopt the EXTENDED view that everything in the room is part of “your” extended cognitive system, the room can be said to “know” Chinese, at least in a behavioral sense.  As this qualification suggests, EXTENDED shifts the meaning of key terms, including “know,” “think,” and “understand.”  Once non-human cognizers are admitted as part of the system, self-aware consciousness can no longer be an adequate measure of what it means for the system to “know” Chinese.  The challenge posed by EXTENDED to Searle’s experiment is to question his assumptions that such terms must be understood in the context of self-aware consciousness, or at least embodied thought as represented by a human mind.

Another key term is meaning.  To see how it shifts in EXTENDED, consider the intimate relation between meaning and context.  As Othello discovers to his horror, meanings of words are notoriously context-dependent.  The context of full human life, at once evoked and reduced in the figure of “you” locked in the room, becomes in EXTENDED a cascading series of contexts.  The rule book, for example, knows which symbols match with which, the basket knows which symbols are incoming and outgoing, and so forth.  The EXTENDED model implies that context is not self-identical or solely human-centered but rather a chain of partially overlapping, partially discrete contexts interacting with each other as different cognizers within the system coordinate their activities.  In particular, meaning is tied in with the contexts in which information flows are processed.  As Edward Fredkin succinctly observes, “The meaning of information is given by the processes that interpret it.”  For a cell, these processes would include, for example, the flow of nutrients in and out of the cell walls, its metabolic activities, its expulsion of waste, and other such processes.  To acknowledge the non-conscious nature of such activities, the EXTENDED model typically replaces consciousness with the broader term “cognition.”  As I am using the term here, cognition requires as a minimum an information flow, embodied processes that interpret the flow, and contexts that support and extend the interpretive activities.  In the Chinese Room, the basket counts as a cognizer, the rule book as another.  Even the door slot through which the strings are passed can be considered a cognizer, for it receives information in the form of incoming characters, interprets these characters through processes that allow them to pass from outside to inside and from inside to outside, and constructs a context through its shape and position.

How does this view of cognition impact the absolute separation between syntax and semantics that Searle decrees?  As we have seen, Searle associates syntax with mechanical ordering, whereas semantics implies that thoughts and feelings have contents, and moreover that these contents are crucial components of understanding and knowledge.  If we agree with Searle that mind somehow emerges from brain, how does mind get from the brain’s non-conscious firing of neurons, mechanical operations of  neurochemical gradients, and other non-conscious activities to visions of God or mathematical proofs?  Contemporary answers to this age-old question, although still incomplete and controversial, nearly always involve the recursive feedback and feedforward loops acknowledged as crucial mechanisms necessary for emergence to occur.  A range of cognitive models as diverse as Maturana and Varela’s autopoiesis, Churchland et.al’s  neural nets, Edelman’s neuronal group selection and re-entry, and Hofstader’s fluid analogy computer programs incorporate recursive loops as central features.  The loops are crucial because they provide the means to bootstrap from relatively simple components to interactions complex enough to generate emergence.
Emergence does an end-run around Searle’s absolute distinction between syntax and semantics, for it implies that syntactical moves, if combined in structures making use of recursive loops and employing complex dynamics, can indeed bootstrap into semantics.

Although Searle positions his thought experiment as a refutation of strong AI, he shares with it certain key assumptions, particularly the emphasis on individual human thought.  Strong AI took as its model the single person thinking; this was the phenomenon researchers sought to duplicate in artificial media.  It is not surprising, then, that the strong AI literature is replete with scenarios in which intelligent computers complete with or supersede intelligent humans (Searle rehearses some of these in his argument), for in this view computers and humans seek to occupy the same ecological niche.  In the EXTENDED view, the emphasis on the individual is transformed by recognizing that the boundaries separating person from environment are permeable in both directions, inner to outer and outer to inner.  Always already a collective, the individual human is less a self-evident entity than the result of a certain focus of attention.  Shift the focus, and the scene modulates from “you” locked in a room to an extended cognitive system in which “knowing” Chinese is a systemic property rather than something inside “your” head.

Would this construction be likely to satisfy Searle?  Probably not, for it involves re-thinking and re-positioning terms he takes for granted.  From my point of view, this is precisely the point.  The value of re-visiting his thought experiment is not to argue, once again, whether it is right or wrong but to use it as a touchstone to gauge how far contemporary models have moved from his assumptions:  from cognition in the head to cognition distributed throughout a system; from the individual as the privileged unit of analysis to the complex dynamics of interacting components; from the language-specific unitary context of a culturally-bound and situated person (“you”) to a cascading series of overlapping contexts operating at macro- and micro-scale embodied specificities; from the human as a self-contained and self-determined person defined by its contrast to an automaton to the human as an assemblage containing both biological and non-biological parts, some of which may be automatons considered in isolation but which are capable of emergence when enrolled in an extended cognitive system.  In brief, the shift is from a person defined by individual consciousness to a collective defined by emergence.

This is the transformation through which our society is currently living.  Many would still identify with Searle’s assumptions, but EXTENDED poses a strong challenge that, at the very least, invites us to reconsider what constitutes the essence of the human.   Just as individual consciousness was the lynchpin of the liberal humanist subject, so Deleuzian assemblages, cognitive collectives, and dispersed subjectivities are the hallmarks of an age when globalization is blurring the boundaries of nationhood, transnational economies are transforming socioeconomic relations, and computer technologies are creating networks that make global communication an everyday fact of life.  As Gilles Deleuze observes in “Postscript on the Societies of Control,” the question is not whether the current configuration is better or worse than liberal humanism but rather what opportunities, challenges, and resistances are specific to the new models.  The first step in answering these questions is to recognize what those specificities are.  For that, we could do worse than to re-visit the Chinese room, excavating its assumptions as a measure of where we have come from so as better to decide where we want to go.

Endnotes

The “strong” AI proponents that Searle cites include Herbert Simon, Alan Newell, Freeman Dyson, Marvin Minsky, and John McCarthy.

Works Cited

Churchland, Paul.  1995.  The Engine of Reason, the Seat of the Soul: A Philosophical Journey into the Brain.  Cambridge:  MIT Press.

Clark, Andy.  2008.  Supersizing the Mind: Embodiment, Action, and Cognitive Extension.  New York: Oxford University Press.

Deleuze, Gilles. 1992.   “Postscript on the Societies of Control,” October 59 (Winter), 3-7.

Edelman, Gerald M. 1993.  Bright Air, Brilliant Fire:  On the Matter of the Mind.  New York: Basic Books.

Fredkin, Edward.  2007.  “Informatics and Information Processing versus Mathematics and Physics.”  Presentation at the Institute for Creative Technologies, Marina Del Ray, May 25.

Hofstader, Douglas. 1995.  Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought.  Cambridge: Basic Books.

Hutchins, Edwin.  1996.  Cognition in the Wild. Cambridge:  MIT Press.

Maturana, Humberto and Francisco Varela.  1973.  Autopoiesis and Cognition: The Realization of the Living.  Robert S. Cohen and Marx W. Wartofsky (Eds). Boston Studies in the Philosophy of Science 42.  Dordrecht:  D. Reidel Publishing Co.

Searle, John.  1984.  Minds, Brains, and Science.  Cambridge:  Harvard University Press.

Turing, Alan.  1950.  “Computing Machinery and Intelligence,” Mind:  A Quarterly Review of Psychology and Philosophy, 49.236: 433-460.

In Terrence’s Self-Tormentor the old man Chremes proclaims, “I am a human being. I consider nothing human alien to me” (homo sum, humani nil a me alienum puto) – a proclamation of magnanimity that lept out of this 2nd-century B.C. play and took on a proud, expansive life of its own. But alongside the humanistic magnanimity runs a disturbing question – the question of this Forum. Despite all the millennia during which we have been humanizing the world, “that uneasy stare at an alien nature is still haunting us, and the problem of surmounting it is still with us”, as Northrop Frye says in The Educated Imagination (1963: 22). So, reflecting the confrontation back onto ourselves we ask, what is this “human”, beyond whose verge lies something Other?

Ask that, it seems, and tribal, territorial, oppositional metaphors almost immediately come into play: human here, non-human there, with a nervously disputed boundary in between and turf to be won or lost. The same drama enacted among nations and races plays out in the academic world as well, with the less self-confident areas of enquiry put on the defensive. It would be good to know if, as seems, the humanities have found themselves more often than not in that position, defining themselves in terms of what they are not. Is this the humanities’ lot by virtue of their common trajectory toward “the alternativeness of human possibility” (Bruner 1986: 53) rather than utilitarian ends? In the Renaissance, Peter Burke points out, the scholar-revolutionaries nicknamed the humanistae brought the concerns belonging to man (literae humaniores) into focus by distinguishing them from and opposing them to the concerns belonging to God (literae divinae).

Since the mid to late 19th Century, especially in North America, the sciences have taken religion’s place as the privileged force to be reckoned with, in the popular imagination the gold-standard for reliable knowledge and source of public benefit.

The situation between beneficial sciences and problematic humanities continues to be exacerbated by those spatial metaphors that not only oppose ways of thinking but confine thought to a limited number of possibilities, like the Tree of Knowledge with its well-grown branches of learning or the geo-political images of turf and territory. My favourite but by no means unrepresentative example of the latter is from a lecture given by the Göttingen mathematician David Hilbert in neutral Zürich in 1917, as the empires of Europe were destroying each other all around him; apparently without irony he spoke of relations between his field and “the great empires of physics and epistemology” (1996/1918: 1107). We might name the superpowers of academia differently now, but Hilbert’s manner of characterizing them is instantly recognizable.

My concern, however, is not with epistemic warfare or diplomacy but with the deeply engrained way of understanding what one is or where one stands by opposition to an alien nature or place. Let me give substance to this concern by focusing on the specific opposition of Self to Other in computing. I want to do this not in terms of the nervousness, indeed outright fear that rippled through the humanities in the early days of computing – a fascinating historical question that I’m working on at the moment. Nor do I want to take up the question of the human as usually done in the philosophical neighbourhood of AI. The classic statements one finds there – Alan Turing’s imitation game and many subsequent positions for or against a perfect counterfeit (best argued by Hugh Kenner in The Counterfeiters) – seem to me to need considerable revision in the light of the machines we now have. For involvement with computing means not just better ways of doing certain old things and new ways of doing new things; it also hooks humanistic concerns to technological progress and so to an unstoppable force for change, continually modifying the problem to be considered. Unlike the situation Turing had in mind in 1950, our physical machines belong to us; they are intimately present, fast and (I am tempted to say) nearly resonant with us in the cybernetic sense. What’s now Other is not some hulking, room-filling, air-conditioned mainframe behind a partition, with labcoated technicians and engineers attending it, rather an indefinitely malleable scheme vested in increasingly accessible form (despite all the frustrations), by which we humanists are modelling whatever we care about. The Other is no longer plausibly out there but tangibly in here. How many of us now feel unwell when our computers don’t work? I admit to being one such person.

It is true that early hackers knew their machines in this sense, indeed that before them the first architects of programming, such as Herman Goldstine and John von Neumann, understood that instructing the machine “is not a static process of translation, but rather the technique of providing a dynamic background to control the automatic evolution of a meaning” (1947: 2). Here, however, I am concerned with computing as a cultural phenomenon, something that was perceived to be massively out there but is now scholarship’s familiar.

I want to ask questions from the inside of that relationship, in the spirit of Warren McCulloch’s “experimental epistemology” (1960), though certainly not as a neurophysiologist. My experience, as happens, is with works of literature – though any other artefacts of interest in the interpretative disciplines would do as well. Unlike most humanists involved with computing, my concerns nowadays are less with particular artefacts than with what tends to happen when computing becomes part of the interpretative act (which is among the most intimately human things we do). How does the question of the human look from there?

Let me take advantage of George Miller’s article “What is information measurement?” (1953), where he remarks on the contribution information theory might make to experimental psychology:

In the first blush of enthusiasm for this new toy it is easy to overstate the case. When Newton’s mechanics was flowering, the claim was made that animals are nothing but machines, similar to but more complicated than a good clock. Later, during the development of thermodynamics, it was claimed that animals are nothing but complicated heat engines. With the development of information theory we can expect to hear that animals are nothing but communication systems. If we profit from history, we can mistrust the “nothing but” in this claim. But we will also remember that anatomists learned from mechanics and physiologists profited by thermodynamics. Insofar as living organisms perform the functions of a communication system, they must obey the laws that govern all such systems. How much psychology will profit from this obedience remains for the future to show. (p. 3)

Indulge me for a moment in a bit of philology. Note the word “obedience”. In its sense closest to the human this denotes (1) an act of the will, a submission, as when I am obedient to the wishes of an equal or near-equal; then, (2) a yielding to some force or agency stronger than myself, as I would to someone with a massively persuasive argument or coercive weapon; then, (3) simply a manifestation of a force or agency so strong and in control that the very idea of resistance is nonsensical (as it is to say that a tightrope walker “defies” gravity).

In what sense is the human interpreter of a work of literature obedient, and how does the best of techno-science’s most influential invention, computing, compel his or her obedience now, or seems likely to in the future? Like the “nothing but” psychologist, he or she may be doctrinally obedient [1,2] to a school of interpretation, but what about obedience [3]? If we suppose that the interpreter of a text uses a computer persuasively to discover statistically significant regularities that go against some readings but favour others, what then? (Such uses have been impressively successful for some time.) A close look at the relevant research shows, however, that analysis proceeds recursively, in a virtuous, hermeneutic circle in which interpreter and statistical model interact. So intimately resonant are the statistical tools and the scholarly interpreter – indeed, in some cases the interpreter has developed these tools gradually to suit the developing results – that it makes no sense to distinguish “the dancer from the dance” (Yeats, “Among school children”). It would seem, then, that the challenge for the digital humanities is to figure out how more effectively to move in that cybernetic direction, using tools as some say we always have, to leverage the evolutionary processes in our own development.

So is there then no troubling question of the human for the humanities? Is the talk of a “theft of humanity” scare-mongering, or only a theft so long as the disciplines fight over infinite treasures as if they were finite things? Budgets and institutional plans are painfully finite, so there’s one problem. Another is what Langdon Winner in “Technologies as Forms of Life” (1986) calls our “technological somnambulism”, our proceeding as if we were not being culturally remade from the inside. Another is that we really have no idea even how to talk about the challenge with which computing confronts the humanities because we lack the vocabulary with which to bridge critical theory to technological methods. But let me focus attention rather on the question Peter Galison raises at the end of his article on the inheritance of cybernetics, “Ontology of the Enemy” (1994), and again in Image and Logic (1996): as objects and techniques move across cultural boundaries and through time, how goes what he calls their “(incomplete) disencumberance of meaning”? (1996: 435f). After considering the historical origins of Wiener’s cybernetics, Galison concludes,

Cultural meaning is neither aleatory nor eternal. We are not free by fiat alone to dismiss the chain of associations that was forged over decades in the laboratory, on the battlefield, in the social sciences, and in the philosophy of cybernetics. At the same time, it would clearly be erroneous to view cybernetics as a logically impelled set of beliefs…. What we do have to acknowledge is the power of a half-century in which these and other associations have been reinstantiated at every turn, in which opposition is seen to lie at the core of every human contact with the outside world. (1994: 265)

In conclusion let me ask: where, then, do we stand with respect to the computational Other, a human invention with a past as checkered and complicit as cybernetics, for so long viewed as inhumanely rigorous, provoking the fear of absolute enslavement to the cold machine, or itself put (like some of our fellow creatures) so far beyond the human pale as to provoke the thought of conscience-free slavery to support a prosperous leisure for humankind? (In 1971, in a review in the Times Literary Supplement, Sir Geoffrey Vickers noted this temptation as the greatest impediment to realizing computing’s signal contribution to epistemology.) Is this Other (which we have made), as Bruno Schulz wrote about art in 1935, something which connects us to a premoral and precognitive depth at which human values and thoughts are still “in statu nascendi“? Is this Other us? Should we be scared, or welcoming, or what?

Works cited.
Bruner, Jerome. 1986. “Possible Castles”. In Actual Minds, Possible Worlds. 44-54. Cambridge MA: Harvard University Press.

Burke, Peter. 2000. A Social History of Knowledge from Gutenberg to Diderot. London: Polity.

Frye, Northrop. 1963. The Educated Imagination. The Massey Lectures, Second Series. Toronto: Canadian Broadcasting Corporation.

Galison, Peter. 1994. “The Ontology of the Enemy: Norbert Wiener and the Cybernetic Vision”. Critical Inquiry 21.1: 228-66.

—. 1997. Image and Logic: A Material Culture of Microphysics. Chicago: University of Chicago Press.

Goldstine, Herman H. and von Neumann, John. 1947. Planning and Coding of Problems for an Electronic Computing Instrument. Part II, Volume I of Report on the Mathematical and Logical aspects of an Electronic Computing Instrument. Princeton NJ: Institute for Advanced Study. library.ias.edu/hs/digiarchives.php (26/4/09).

Hilbert, David. 1996/1918. “Axiomatic Thought”. In From Kant to Hilbert: A Sourcebook in the Foundations of Mathematics, vol. 2, ed. William Ewald. Oxford Science Publications. Oxford: Clarendon Press.

Kenner, Hugh. 2005/1968. The Counterfeiters: An Historical Comedy. Normal IL: Dalkey Archive Press.

McCulloch, Warren S. 1960. “What is a Number, that a Man May Know It, and a Man, that He May Know a Number?” Alfred Korzybski Memorial Lecture. General Semantics Bulletin 26 & 27: 7-18. www.generalsemantics.org/misc/akml/akmls/26-27-mcculloch.pdf (26/4/09).

Miller, George A. 1953. “What is information measurement?” American Psychologist 8: 3-11.

Schulz, Bruno. 1998/1935. “An Essay for S. I. Witkiewicz”. In The Collected Works of Bruno Schulz. Ed. Jerzy Ficowski. 367-70. London: Picador.

Turing, A. M. 1950. “Computing Machinery and Intelligence”. Mind N.S. 59.236: 433-60.

Winner, Langdon. 1986. “Technologies as Forms of Life”. In The Whale and the Reactor. Chicago: University of Chicago Press.

Vickers, Geoffrey. 1971. “Keepers of rules versus players of roles”. Rev. of The Impact of Computers on Organizations, by Thomas L. Whistler; The Computerized Society, by James Martin and Adrian R. D. Norman. Times Literary Supplement 21.5.71: 585.

Bommarito (like Olin) seems to find the experimental results unsurprising, given the commonplace that most (or all) people are not “Perfectly Rational Agents.”  Hard to argue this; if you’re not surprised, you’re not surprised.  But like Vazire, I am surprised, and would not have predicted (sans familiarity with social psychology) phenomena like the “Georgia effect.”  (Much as people in the early 1960s did predict the shocking rates of obedience in Milgram’s studies [see Doris 2002: 49], however familiar the results may seem today.)  I’m surprised because I find remarkable not so much the brute fact that people diverge from ideals of rationality, but the ways in which they do so.  As Haybron observes, it’s not astonishing when people are moved in ways “contrary to reason” by sex, drugs, and rock’n’roll.  Such considerations seem to tap motives that are both powerful and of a sort one is willing to count as compelling reasons in some, even many, circumstances.  (Perfectly reasonable to desire sex, one might think, so long as it is with the right person, in the right place, of the right sort, and so on.)  But the experimentally adduced motives don’t look like that:  they aren’t intuitively plausible candidates for the honorific reason.  So it seems that we have learned something new from the experiments: not that we are imperfectly rational agents, but that our divergence from standards of rationality may be effected by processes that are both unexpected and difficult to detect (quite unlike sex, drugs, and rock’n’roll).

Smyth is quite right to note the importance of the reasons/causes distinction. In fact, the challenge does not elide this distinction, but exploits it.  For what the studies point to is a class of motives that would not be counted as reasons by the actor, were she made aware of them.  Behaviors so described are plausibly thought of as irrational (or at least arational), so the studies identify a difficulty about human rationality.

None of this to deny that there are knotty questions about rationality.  As Young observes (with Nichols), for many behaviors it is quite unclear what a “rational explanation” would look like, or even that such an explanation is required.  Suppose I don’t have much articulate to offer when declining to partake in your soufflé of yak feces.  It’s “just yucky,” I say, much as I might say, regarding Haidt’s infamous example of sibling incest, it’s “just wrong.”  To lack a rationalization is not necessarily to act irrationally; to establish the latter, one seems to need a theory of rationality.

Yet it may be possible to motivate our difficulty on the theoretical cheap:  I’ve helped myself to a thinly subjective notion of rationality, in attempting to identify a class of cases where the operative motive is unlikely to be considered normatively compelling from the actor’s perspective.  Theoretical uncertainty notwithstanding, these cases look to be at least prima facie examples of irrationality, and I’ve proceeded on the assumption that such instances are enough to get the problematic off the ground.  Of course, much depends on the particulars of each case — if you like, the etiology of the judgments and actions at issue.  Some etiologies may be vindicating, and some debunking; the challenge intimated by the experimental literature is the prospect of surprising numbers of surprising etiologies that the actors themselves would regard as debunking. In the end, we’ll need substantive argument on particular normative issues, and (perhaps) more general argument on the theory of reasons (for example, on the authority of the subjective perspective).  But I think we can make a beginning without resolution of all the theoretical issues – as is usually the case.

In effect, Olin doubts that I’ve identified debunking etiologies: she is inclined to deny that the phenomena in question are instances of irrationality.  For example, the lovers on a bridge study does not show that the men asked out someone they found unattractive, which would look irrational; as Olin has it, the study identifies a causal factor plausibly implicated in the men finding the woman attractive, which is in turn implicated in their asking her out.  So on Olin’s reading, it’s not “they asked her out because they were frightened on the bridge,” but “they asked her out because they found her attractive.”  To put it more perspicuously, on Olin’s view it’s both, but so long as the second holds, there’s nothing much funny going on.
There’s something to this:  if I find someone attractive because of their clothes, or because of the champagne and oysters, I find them attractive all the same.   To say the heart (or other bits of anatomy) has its reasons is to say, in a sense, that the heart needn’t have reasons at all.  But I’m not sure the bridge case can be assimilated to the champagne and oysters case.   For I think that in evaluating one’s attractions (or career choices, etc.), the psychological history matters, and not all histories are created equal.  For matters of the heart, think of whatever sinister Freudian story you want.  Or try this: the philosophically ubiquitous mad scientist mucks about in your brain, making someone you previously found quite disgusting seem quite irresistibly attractive.  If you found out, how would you feel?  You might not care, and you might even decide to “go with it.”  But you might just as easily feel duped, or feel like you’d been manipulated.  We might say that your unlikely shift in attraction was not properly based on who you are, but on who the mad scientist is.  Described this way, the mad scientist’s science project seems creepy, and I’d have the same thought if I learned, say, that my inclinations of the heart were based on a fear of heights (so that I always date people who work on the ground floor).  And to observe, as I suspect Olin would, that attractions often are capricious in such ways, just is to make a point akin to that I want to make:  there’s likely more caprice, and less reason, in your decisions that you might have thought.

Nichols and I have gone ‘round about the Georgia effect many times, and here he seems to have upset my wagon with some straightforward calculations.  There is a Georgia effect, it turns out, but it looks to be tiny, increasing the likelihood of moving to Georgia by a nearly invisible .007 percent.  (Nichols calculations assume an equal likelihood of moving to each state.  If fact, number 9 Georgia has something like 20 times the population of number 50 Wyoming, but as Nichols observes, this does not substantially impact his point.)   In making this point, Nichols raises the issue of effect size, an extremely difficult and contentious issue in the methodology of social science.  As a philosopher, I’m in over my head here, but I’ll chance a few remarks.

The people who brought us the Georgia effect, Pelham and colleagues (2002), also found people were about 15% more likely than expected by chance to reside in cities with names resembling their surnames.  Once again, this might seem a ripe target for Nichols’ arithmetic, but as Pelham et al. (2002: 473) observe, the magnitude of this effect is about 3 times the effect size corresponding to the long term house advantage in roulette – and the house comes out ahead.

In a suggestive discussion, Meyer and colleagues (2001) report effect sizes in medicine in the form of correlation coefficients:

Aspirin consumption/reduced risk of heart attack: .02
Chemotherapy/surviving breast cancer: .03
Ever smoking/lung cancer within 25 years: .08

These numbers look puny too.  But it’s arguable – very arguable – that these effect sizes have clear practical implications: take the Aspirin, endure the chemo, and don’t light up. At this point, Nichols may want to say that these effects do not allow confident conclusions about particular outcomes for particular individuals, such as whether Sweet Georgia Brown will move to Georgia.  (Full disclosure: I’ve elsewhere registered a similar complaint about considerably larger effect sizes in personality psychology.) Quite true.  But wait.  Aspirin consumption (and “Georgia”) must be making a difference in some individual cases; or there would not be a significant correlation.  (Give the multitude of operative influences in any case, we cannot confidently say for whom the difference was made, but this sort of uncertainty is actually part of the problem, as we’ll now see.)

Like Haybron, I understand phenomena like the Georgia effect as a “foot in the door”; once we see that something like that can make a difference, we’re bound to admit there might be lots of such goofy influences, as indeed an enormous literature intimates.  And while each individual influence may be small (as in influences on our health), the additive effect may, for all we know, be quite potent.  If such additive effects may be plaguing our decisions, is rationality in doubt? Is there a good way to rule their presence out?

We can sharpen the difficulty by considering some remarks by Harman, who rightly observes that the studies are compatible with people exercising “considerable rational control.”  Obviously, the studies do not of show that self-ignorance is total: presumably the lovers on the bridge believed (rightly) that they were asking a woman out, and not a rutabaga.   As Greene intimates, a critical part of the question seems to be how much self-awareness is required for rational agency.  To put it another way, is self-ignorance limited to minor causal factors, or does it extend to major factors (or constellations of factors) that substantially determine behavioral outcomes?

I think self-ignorance extends to major factors.  Worse, I think some of these major factors are ones that those influenced would repudiate. Finally, I think such phenomena are widespread.

This is speculative.  But there is trouble enough without definitively establishing the empirical claims.  I suppose Harman would grant, as I think he should, that there are at least some cases where the kind of influences we are worrying about determine behavioral outcomes. And whatever we think about particular cases, I suppose Harman would grant, as I think he should, that there are some cases of such influence that should be counted as instances of irrationality, whether the actor has partial self-awareness or not.  We can argue (as I did with Olin) about whether individual cases look like irrationality; if you don’t like the ones I’ve used, there are many others, such as Comstock’s amusing example of the cancerous pork slabs.  But all that’s needed here is the highly plausible supposition that there are some such cases.

For to know that a person is acting rationally, one needs to rule out the presence of such factors – if you like, call these irrational influences defeaters.   But how is such a ruling out to be accomplished?  The answer, I think, is obscure; if I’m right about studies like the choice blindness experiments, it would be a mistake to appeal to something like introspection, or self-reports of experience.

The envisaged argument takes a familiar skeptical form:  a skeptical hypothesis is one that cannot be “ruled out,” and would falsify some belief, or category of beliefs, if true: if I cannot rule out the possibility of an epistemically malicious demon, or that I am an envatted brain, or that I’m frolicking about in a Matrix, I haven’t knowledge of the external world.  The present skepticism maintains that for any putative instance of something like rational agency, we cannot rule out the possibility of an alternate explanation of behavior that does not reference the materials of rational agency.  If we cannot rule out these hypotheses, we do not know that there are instances of rational agency.  Like other skeptical arguments, the argument is not that the phenomenon in question does not exist, but rather that there are not strong enough grounds for believing it does. (This argument is a much-compressed version of that appearing in Doris, forthcoming.) So far as I see, this argument has bite even if we concede to Harman, as I think we should, that the empirical record is compatible with considerable self- awareness.

Like O’Callaghan, what I find striking is the facility with which people produce “serviceable candidate explanations” for their behavior, even when their information, including about their own psychological states, is seriously inaccurate or incomplete.  I suspect that the kind of cases that strike Nichols and Young – call them instances of “rational dumbfounding” – are in fact pretty unusual.  Speaking for myself, I don’t often hear people say, “I have no idea why I did that.”  This is perhaps unsurprising, since such utterances will often not play very well.  While it may be that we’re genuinely clueless about matters of mate choice, for example, I doubt this is the understanding we typically go forward with. (Perhaps the married members of the audience will help us with an informal experiment:  go home and announce to your spouse,  “You know honey, I have no idea why I married you.”  I suspect the results, if listeners took the statement literally, would be illuminating.)  I’d be inclined to put O’Callaghan’s point like this:  what is most unsettling is just how well people can navigate the space of reasons, when this space is only tenuously related to the space of motives.   How does the discourse of reason work, then, and what purpose(s) does it serve?

Like Vazire, I want to find a place for personal self-direction that may fairly be considered rational agency, meaning I want to resist the skeptical argument.  I don’t suppose that this resistance will in the end amount to an eradication of skeptical anxiety — agency may well be harder to come by than one might suppose in a state of pre-scientific bliss — but I do believe substantial amelioration is possible.  But like Vazire, I believe there are difficult empirical questions here, ones that are not easy to systematically address; given the presence of phenomena like confabulation, what should be counted as evidence of genuine personal control?   But like Haybron, I believe the questions will become more tractable with the aid of the right sort of theory building.

I propose we undertake this theory building from the bottom up.  Start with an empirical question: how do human organisms regulate their behavior?  I expect that there will be more than one answer to this question: human organisms are likely possessed of multiple control systems.  Then we might ask, in a broadly pre-theoretical way, which – if any — control systems regulate behavior in ways that are apt for the attribution of agency.  On me view, this is a broadly Strawsonian exercise:  which forms of behavioral control appear to support behavior appropriately subject to “reactive attitudes” like anger and admiration?  At this point, we might indulge in some incipient theory building, and try to make some generalizations about the forms of control properly associated with reactive attitudes.  For example, we might find that many human achievements that merit admiration – keeping a marriage together, say, or writing a book – emerge socially and over time, and we might therefore want to focus some of our attention on socially and temporally extended processes, rather than on individual organisms and individual actions (as much philosophical action theory has done).  We’d then want to pursue longitudinal research on groups, and what we learn here might further refine both our pre-theoretical judgments and theoretical commitments. (I understand Vazire’s lab is now initiating such a project.)

My methodological proposal may seem both numbingly familiar and maddeningly vague.  Fair enough: it is, very substantially, an underformed riff on the Goodman-Rawls account of reflective equilibrium.  But notice that it contrasts sharply to a top-down approach to agency, such as that intimated by Bommarito’s comment, where one first develops, in a substantially a priori fashion, a ideal notion of agency (The “Perfectly Rational Agent”) and afterwards looks to the empirical literature to determine the extent to which actual human behavior approximates or diverges from this standard.  I won’t defend my methodology here.  I’ll only observe that in adopting it, one might reach an understanding of rational agency that is different from familiar philosophical understandings – and more human.

– John Doris

PS: I’m not familiar with the work of M.A. Curtis, which Lizzie commends.  Based on the linked excerpt, it represents a project quite different from, and much more ambitious than, mine.

References

• Doris, J. M. 2002. Lack of Character: Personality and Moral Behavior.  New York: Cambridge University Press.
• Doris, J. M. In preparation. A Natural History of the Self. Oxford: Oxford University Press.
• Doris, J. M. Forthcoming. “Skepticism about Persons.” Philosophical Issues 19: Metaethics.
• Meyer, G. J., Finn, S. E., Eyde, L., Kay, G. G., Moreland, K. L., Dies, R. R., et al. 2001. “Psychological Testing and Psychological Assessment: A Review of Evidence and Issues.” American Psychologist 56: 128–165