Compare and Contrast
Compressorhead -- Ace of Spades
Georgia Tech -- Shimon, robotic marimba player
There are two ways of looking at these pictures:
Frank Popper (1993), Art of the Electronic Age
There is no doubt that this conjunction of the real and the virtual engendered by simulation is at the heart of present research by many technological artists. They consider that 'virtual space', 'virtual environments', or 'virtual realities' in general usher in an entirely new era in art, allowing the participants a multi-sensorial experience never encountered before.
The key words 'artificial intelligence' as an aesthetic problem open up a vast, time-worn discussion of the relationship between man and the machine. Artificial intelligence embraces techniques which enable machines, and in particular computers, to simulate human thought processes, particularly those of memory and deducation [sic].
Hans Haacke (1967), Untitled Statement
In the past, a sculpture or painting had meaning only at the grace of the viewer. His projections into a piece of marble or canvas with particular configurations provided the programme and made them significant. Without his emotional and intellectual reactions, the material remained nothing but stone and fabric. The systems's programme, on the other hand, is absolutely independent of the viewer's mental participation. It remains autonomous -- aloof from the viewer. As a tree's programme is not touched by the emotions of lovers in its shadow, so the system's programme is untouched by the viewer's feelings and thoughts.
Naturally, also a system releases a gulf of subjective projections in the viewer. These projections, however, can be measured relative to the system's actual programme. Compared to traditional sculpture, it has become a partner of the viewer rather than being subjected to his whims. A system is not imagined; it is real.
In the first video we have a masterpiece of pre-programmed German engineering (not to be stereotypical, but just imagine what the Swiss would do with it, eh?). In the second the machine gets a bit of a chance to decide how it will behave.
In the first quote Popper posits that technology is used to simulate virtual environments for the viewer's delectation. In the second, which is a founding document of Systems Art, Haacke partners the art-system with the viewer in the real world.
So, we can have machines that are either pre-determined Automata or else Autonomous beings. And they can be either virtual or real, i.e., Simulated or Situated in reality. One path gives us total control. The other requires, if not abdication of control, at least collaboration with our materials and creations.
An Autonomous Situation
Art can be ... or could have been ... a research program:Repetto, Douglas (2010).
Doing It Wrong.
(from the 2010 Symposium -- Frontiers of Engineering: Reports on Leading-Edge Engineering)
Although musical innovators throughout history would have articulated these ideas differently, I believe they shared the central tenets that creative acts require deviations from the norm and that creative progress is born not of optimization but of variance. More explicit contemporary engagement with these ideas leads one to the concept of creative research, of music making with goals and priorities that are different from those of their traditional precursors -- perhaps sonic friction, in addition to ear-pleasing consonances, for example, or "let’s see what happens" rather than "I’m going to tell you a story."
The problem is that most machines, even the of the art variety, are well controlled models. But what is interesting is new behavior, not the recapitulation of what went before. Rather than models we should be building autonomous beings that have lives of their own and behave in new ways. This is a research program.
When a system gets a chance to decide how it will behave we may not perceive the results as aesthetically interesting. From our lofty height we might not recognize it as living. And for now, it doesn't even have to be very complicated. One can make the argument that a thermostat responds to its feelings of being too hot or too cold and adjusts its environment accordingly. Since we have no idea what its internal mental states might be this description is just as valid as the physical explanation of how the sensors and actuators work. (I need to emphasize that I am not anthropomorphizing machines here but rather mechanizing human responses, putting both on a similar level.) Giving machines lives that are of no practical use while not going out of the way to make them attractive, didactic, or transparent allows them to rise through ontological cracks to just being themselves.
In a virtual world where interactivity and intelligence are simulated this can't be done easily. The beauty and curse of simulation is that it can respond in any way we like; we can make up any structure, or none at all. This is our Spectacular Simulacra: It's potentially all noise and no signal. Just like listening to a radio tuned between stations, when there is no signal there is very little to be learned from an interaction. On a large scale, this is a reason that wikipedia is considered unsuitable for academic references. Anyone can edit it to say anything they like, and it may not be corrected -- whatever that means -- quickly or accurately. The US Congress has been a serial offender in this respect.
However systems that are situated in the real world get input that already has structure; the constraints on the system make it work. It is this interaction with the world, the constraints and the underlying materials, that gives us the feedback we need to learn and function. If a machine interacts with a physical environment it has a better chance of grounding its knowledge and jumping the syntactic/semantic fence. As an example, you may use the phrase "fire is hot" in a syntactically correct sentence. But I assert that the only way you will learn the semantic meaning, and dare I say the underlying semiotic relationships, is if I hold your feet to the fire.
[edit, added 1/27/13]
When talking of living machines with minds of their own, the specter of Dr. Frankenstein's Monster appears. What we forget is that the Monster wasn't a monster until after it accidentally killed and was further persecuted for being different. Looking deeper into the question, the fears that Machines Will Enslave Us are rooted in the assumption that those machines will behave as animals (and humans) do. But when creating our artificial life forms we might dispense with the Darwinian necessities of Fear, Disgust, Anger, Greed -- and the rest of the deadly sins upon which modern economics is based -- and instead have them optimize the desire to, e.g., be the best possible musical improviser who knows when to lay back and listen and when to barge right in.
So where do we start?
Is Chaos Theory Postmodern Science?
This is the title of a paper -- which seems to have vanishingly close to zero citations -- by a Professor of Interdisciplinary Studies who comes to the unsurprising conclusion that:Postmodern science does, in fact, exist, and literature just may be it.
Mackey, J. L. (2006).
Is Chaos Theory Postmodern Science?
(in reconstruction: studies in contemporary culture, Jan 24, 2006)
Now, depending on your parser, this is either a tautology or a category error. However, if one reads "Chaos Theory" as Complexity Science, it does contain a kernel of truth. At its roots, Post Modernism is interested in systemic structures. In its branches it deconstructs those systems to find underlying paradigmatic narratives -- assumptions -- which (in)form, and even create, the structures. Complexity Science, rooted in Cybernetics, also takes a systems view. It shares with Post Modernism an interest in how underlying structure gives rise to system wide behavior. Complexity also provides Emergence as a framework for considering that systems may be more than the sum of their parts -- accepting that some phenomenon cannot be subjected to Modernist reduction.
As a counter example to the Mackey, and in more depth, I recommend these two books which look into some of the background and possibilities. (Note that I'm biased as the authors are friends...)
Victoria Alexander posits self-organization as an explanation for the perception that natural phenomenon have goals or develop towards some final purpose (teleology). In chapters 1-4 she "deconstructs" what purpose means and how it might arise from otherwise non-directed mechanisms, both in nature and human artifact. As a bonus, chapter 5 is a (fairly) clear explanation of C.S. Peirce's semiotics...
Alexander, V. N. (2011).From the chapter 1:
The Biologist's Mistress: Rethinking Self-organization in Art, Literature, and Nature.
Emergent Publications.
What I do share with all teleologists, authentic or so-called, is a deeply felt folk-sense of purposefulness in nature. It is clear to me that many processes and patterns in nature can't be fully explained by Newton's laws or Darwin's mechanism of natural selection. These are processes that are organized in ways that spontaneously create, sustain and further that organization. Although I believe that mechanistic reductionism is inadequate to describe these processes, I don't believe that purposeful events and actions require guidance from the outside -- from divine plans or engineering deities. Nature's purposeful processes are self-organizing and inherently adaptive, which is the essence of what it is to be teleological.
John Johnston provides a history of Cybernetics, Artificial Life, and related fields with an analysis of their significance to modern culture. If you are not Lacanian I would skip chapter 2, but Section III, Machinic Intelligence, is especially relevant to the program outlined here.
Johnston, J. (2008).From the preface:
The allure of machinic life: cybernetics, artificial life, and the new AI.
MIT Press.
This book explores a single topic: the creation of new forms of "machinic life" in cybernetics, artificial life (ALife), and artificial intelligence (AI). By machinic life I mean the forms of nascent life that have been made to emerge in and through technical interactions in human-constructed environments. Thus the webs of connection that sustain machinic life are material (or virtual) but not directly of the natural world. Although automata such as the eighteenth-century clockwork dolls and other figures can be seen as precursors, the first forms of machinic life appeared in the ‘‘lifelike’’ machines of the cyberneticists and in the early programs and robots of AI. Machinic life, unlike earlier mechanical forms, has a capacity to alter itself and to respond dynamically to changing situations.
Here we are
Self-organization and Artificial Life are areas of Complexity Science that can provide inspiration as well as mechanism. Although some of the original work in these fields may have been more Art than Science -- making grander claims than could be supported in the, as they say, dominant paradigm -- years of more cautious work have produced concrete results. On the other hand there is something to be said for throwing caution to the winds...Because they have no requirement to make useful artifacts or produce scientifically supported results, artists might be in an ideal position to create these machines. This would also encourage détente in the science-wars, bringing the Humanities and Sciences closer to productive collaboration. But Art has now become identified with Spectacle rather than research, so I propose a new title: Bricoleur.
So far, work in the arts has been done in a sporadic fashion due to confusion about both purposes and methods when using advanced technology and especially computers. Generative Art -- art which emerges from computer programs -- has been conflated with Artificial Life -- programs that have their own behaviors. The following paper skates between the two but seems to come down on the "make pretty things" side.
McCormack, J., & Dorin, A. (2001, January).
Art, emergence, and the computational sublime.
In Proceedings of Second Iteration:
A Conference on Generative Systems in the Electronic Arts.
Melbourne: CEMA (pp. 67-81).
In a design sense, it is possible to make creative systems that exhibit emergent properties beyond the designer's conscious intentions, hence creating an artefact, process, or system that is "more" than was conceived by the designer. This is not unique to computer-based design, but it offers an important glimpse into the possible usefulness of such design techniques -- "letting go of control" as an alternative to the functionalist, user-centred modes of design. Nature can be seen as a complex system that can be loosely transferred to the process of design, with the hope that human poiesis may somehow obtain the elements of physis so revered in the design world. Mimicry of natural processes with a view to emulation, while possibly sufficient for novel design, does not alone necessarily translate as effective methodology for art however.
Whereas this next paper gets us moving in the right direction. It was prompted by an exhibition: Emergence -- Art and Artificial Life (Beall Center for Art and Technology, UCI, December 2009). The author and a handful of other artists have been experimenting with complex systems for some time -- see the end of my timeline for pointers to various work that I've been able to ferret out of the 'net.
Penny, Simon (2009).
Art and Artificial Life a Primer.
4.1 An Aesthetics of Behavior
With the access to computing, some artists recognized that here was a technology which permitted the modeling of behavior. Behavior - action in and with respect to the world - was a quality which was now amenable to design and aesthetic decision-making. Artificial Life presented the titillating possibility of computer based behavior which went beyond simple tit-for-tat interaction, beyond hyper-links and look-up tables of pre-programmed responses to possible inputs, even beyond AI based inference -- to quasi-biological conceptions of machines, or groups of machines that adapted to each other and to changes in their environment in potentially unexpected, emergent and ‘creative’ ways.
We have a long way to go...
And it's not going to be easy: |
| Is Slime Mold Smarter Than a Roomba? IEEE Spectrum (December 2012) |
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