This article considers the question of embodiment in relation to gender and whether there are models of artificial intelligence (AI) which can enrol a concept of gender in their design. A central concern for feminist epistemology is the role of the body in the making of knowledge. I consider how this may inform a critique of the AI project and the related area of artificial life (A-Life), the latter area being of most interest in this paper. I explore briefly the (...) tensions between the treatment of the body in different branches of feminist theory, especially the tensions between the approaches of feminist sociology and feminist philosophy. I explore the ways in which writing from category theory and anthropological phenomenology offers rich suggestions as to how the body has been left out of objectivist accounts of epistemology, but struggles to offer an account of why. In its analysis of the links between women, knowledge and the body, feminist revisions of epistemology offer a more convincing why. This is explored briefly through a critique of symbolic AI, and more substantially through the problem of embodiment in artificial life. (shrink)

From the legendary inventor Daedalus to Goethe's tragic Faust, from the automata-making magicians of E.T.A Hoffmann to Mary Shelley's Victor Frankenstein – ...

Paper published on author's website available at http://www.garybanham.net/PAPERS_files/Artificial%20Life%20and%20the%20Inhuman%20Condition.pdf.

The new interdisciplinary science of artificial life has had a connection with the arts from its inception. This paper provides an overview of artificial life, reviews its key scientific challenges, and discusses its philosophical implications. It ends with a few words about the implications of artificial life for the arts.

The field of artificial life is enriching both the content and method of philosophy. One example of the impact of artificial life on the content of philosophy is the light it sheds on the perennial philosophical question of the nature of emergent pheonomena in general. Another second example is the way it highlights and promises to explain the suppleness of mental processes. Artificial life's computational thought experiments also provide philosophy with a methodological innovation. The limitations of the central arguments in (...) Stephen Jay Gould's.. (shrink)

The aim of this chapter is to show how the technological research activity called “artificial life” is shedding new light on human creativity. Artificial life aims to understanding the fundamental behavior of life-like systems by synthesizing that behavior in artificial systems (more on artificial life below). One of the most interesting behaviors of living systems is their creativity. Biological creativity can be found in both individual living organisms and in the whole biosphere—the entire interconnected system comprised of all forms of (...) life—but I will focus in this chapter on the biological creativity exhibited by the evolutionary process. This is the creativity that enabled the earliest simple life forms to spontaneously evolve into the incredibly rich and beautiful diversity of life that now surrounds us. This diversity of life includes the most complex adaptive and intelligent systems in the known universe. This is an amazingly powerful spontaneous creation process, indeed. I will refer to it as hyper-creativity to call attention to the way in which it produces qualitatively new and more complex kinds of adaptations. There is a similar quality in human creativity. I am thinking of the aesthetic and cultural creativity of artists, but also the intellectual creativity of scientists and scholars, as well as the commercial and practical creativity of craftsmen, businessmen, and entrepreneurs. And I want to focus especially on the hyper- creative aspects of human creativity—the way in which human activity can yield qualitatively new and more complex creations. (shrink)

Contemporary artificial life (also known as “ALife”) is an interdisciplinary study of life and life-like processes. Its two most important qualities are that it focuses on the essential rather than the contingent features of living systems and that it attempts to understand living systems by artificially synthesizing extremely simple forms of them. These two qualities are connected. By synthesizing simple systems that are very life-like and yet very unfamiliar, artificial life constructively explores the boundaries of what is possible for life. (...) At the moment, artificial life uses three different kinds of synthetic methods. “Soft” artificial life creates computer simulations or other purely digital constructions that exhibit life-like behavior. “Hard” artificial life produces hardware implementations of life-like systems. “Wet” artifi- cial life involves the creation of life-like systems in a laboratory using biochemical materials. (shrink)

Artificial life uses computer models to study the essential nature of the characteristic processes of complex adaptive systems proceses such as self-organization, adaptation, and evolution. Work in the field is guided by the working hypothesis that simple computer models can capture the essential nature of these processes. This hypothesis is illustrated by recent results with a simple population of computational agents whose sensorimotor functionality undergo open-ended adaptive evolution. These might illuminate three aspects of complex adaptive systems in general: punctuated equilibrium (...) dynamics of diversity, a transition separating genetic order and disorder, and a law of adaptive evolutionary activity. (shrink)

It’s sometimes said, and even more often assumed, that life is necessary for mind. If so, and if A-Life promises to throw light on the nature of life as such, then A-Life is in principle highly relevant to the philosophy of mind and cognitive science. However, very few philosophers have attempted to argue for the relation between life and mind. It’s usually taken for granted. Even those (mostly in the Continental tradition, including some with a following in A-Life) who have (...) insisted on the linkage have stated it rather than justified it. If an evolutionary account of intentionality is acceptable, then perhaps biological life ‘makes room’ for mind. But that claim is problematic, since it’s not clear that the type of self-organization involved in life-as-such must necessarily include evolution. Even if it does, it’s a further step to show that life is strictly necessary for mind. (shrink)

The first part of this paper explores the general issues in using Artificial Life techniques to program actual mobile robots. In particular it explores the difficulties inherent in transferring programs evolved in a simulated environment to run on an actual robot. It examines the dual evolution of organism morphology and nervous systems in biology. It proposes techniques to capture some of the search space pruning that dual evolution offers in the domain of robot programming. It explores the relationship between robot (...) morphology and program structure, and techniques for capturing regularities across this mapping. (shrink)

This paper explores how an evolutionary process can produce systems that learn. A general framework for the evolution of learning is outlined, and is applied to the task of evolving mechanisms suitable for supervised learning in single-layer neural networks. Dynamic properties of a network’s information-processing capacity are encoded genetically, and these properties are subjected to selective pressure based on their success in producing adaptive behavior in diverse environments. As a result of selection and genetic recombination, various successful learning mechanisms evolve, (...) including the well-known delta rule. The effect of environmental diversity on the evolution of learning is investigated, and the role of different kinds of emergent phenomena in genetic and connectionist systems is discussed. (shrink)

We could have been characters in a huge computer simulation. It is a familiar idea that the whole world might be simulated on a computer, and things would seem exactly the same to us (and indeed, who is to say that we are not).

The idea that biorobots can be used as a testbed for the evaluation of hypotheses about how an animal functions is supported. Generation of realistic feedback is a major advantage of biorobotic models. Nevertheless, skeptics can only be convinced that this approach is valid if significant biological insights are generated from its application.

There are two likely paths for philosophers to follow in their encounters with Artificial Life: they can see it as a new way of doing philosophy, or simply as a new object worthy of philosophical attention using traditional methods. Is Artificial Life best seen as a new philosophical method or a new phenomenon? There is a case to be made for each alternative, but I urge philosophers to take the leap and consider the first to be the more important and (...) promising. (shrink)

Is life a property of the material structure of a living system or an abstract form of organization that can be realized in other media; artificial as well as natural? One version of the Artificial Life research programme presumes, that one can separate the logical form of an organism from its material basis of construction, and that its capacity to live and reproduce is a property of the form, not the matter (Langton 1989). This seems to oppose the notion of (...) a cell within contemporary molecular biology, according to which "form" and "matter" do not represent separate realms. The information in a living cell is intimately bound to the properties of the material substrate. This condition may represent a restriction on the validity of formal theories of life. (shrink)

It is argued, that theory sf signs, especially in the tradition of the great philosopher Charles Sanders Peirce (1839–1914) can inspire the study of central problems in the philosophy of biology. Three such problems are considered: (1) The nature of biology as a science, where a semiotically informed pluralistic approach to the theory of science is introduced. (2) The peculiarity of the general object of biology, where a realistic interpretation of sign- and information-concepts is required to see sign-processes as immanent (...) in nature. (3) The possibility of an artificial construction of life, hereby discussed as a conceptual problem in the present form of the artificial life project and its implied definition of life. (shrink)

The invention of the computer has revolutionized science. With respect to finding the essential structures of life, for example, it has enabled scientists not only to investigate empirical examples, but also to create and study novel hypothetical variations by means of simulation: ‘life as it could be’. We argue that this kind of research in the field of artificial life, namely the specification, implementation and evaluation of artificial systems, is akin to Husserl’s method of free imaginative variation as applied to (...) the specific regional ontology of biology. Thus, at a time when the clarification of the essence of our biological embodiment is of growing interest for phenomenology, we suggest that artificial life should be seen as a method of externalizing some of the insurmountable complexity of imaginatively varying the phenomenon of life. (shrink)

Both Artificial Life and Artificial Mind are branches of what Dennett has called "reverse engineering": Ordinary engineering attempts to build systems to meet certain functional specifications, reverse bioengineering attempts to understand how systems that have already been built by the Blind Watchmaker work. Computational modelling (virtual life) can capture the formal principles of life, perhaps predict and explain it completely, but it can no more be alive than a virtual forest fire can be hot. In itself, a computational model is (...) just an ungrounded symbol system; no matter how closely it matches the properties of what is being modelled, it matches them only formally, with the mediation of an interpretation. Synthetic life is not open to this objection, but it is still an open question how close a functional equivalence is needed in order to capture life. Close enough to fool the Blind Watchmaker is probably close enough, but would that require molecular indistinguishability, and if so, do we really need to go that far? (shrink)

Artificial life can take two forms: synthetic and virtual. In principle, the materials and properties of synthetic living systems could differ radically from those of natural living systems yet still resemble them enough to be really alive if they are grounded in the relevant causal interactions with the real world. Virtual (purely computational) "living" systems, in contrast, are just ungrounded symbol systems that are systematically interpretable as if they were alive; in reality they are no more alive than a virtual (...) furnace is hot. Virtual systems are better viewed as "symbolic oracles" that can be used (interpreted) to predict and explain real systems, but not to instantiate them. The vitalistic overinterpretation of virtual life is related to the animistic overinterpretation of virtual minds and is probably based on an implicit (and possibly erroneous) intuition that living things have actual or potential mental lives. (shrink)

Artificial life (ALife) is the attempt to create artificial instances of life in a variety of media, but primarily within the digital computer. As such, the field brings together computationally-minded biologists and biologically-minded computer scientists. I argue that this new field is filled with interesting philosophical issues. However, there is a dearth of philosophers actively conducting research in this area. I discuss two books on the new field: Margaret A. Boden's The philosophy of artificial life and Christopher G. Langton's Artificial (...) life: an overview. They cover three areas of philosophical interest: the definition of life, the relationship between life and mind, and the possibility of creating life within a computational environment. This discussion allows me to critique past work in the philosophy of ALife that tends to see the field as a proving ground for traditional arguments from the philosophy of artificial intelligence. Instead, I suggest, what is interesting about ALife is how it differs from artificial intelligence and that the most interesting philosophical issues in the area are those derived from biology, not psychology. I recommend that these two books taken together constitute an interesting introduction to ALife and the wealth of philosophical issues found therein. (shrink)

Cyberfeminism and Artificial Life examines construction, manipulation and re-definition of life in contemporary technoscientific culture. It takes a critical political view of the concept of life as information, tracing this through the new biology and the changing discipline of artificial life and its manifestation in art, language, literature, commerce and entertainment. From cloning to computer games, and incorporating an analysis of hardware, software and 'wetware', Sarah Kember demonstrates how this relatively marginal field connects with, and connects up global networks of (...) information systems. As well as offering suggestions for the evolution of [cyber]feminism in Alife environments, the author identifies the emergence of posthumanism; an ethics of the posthuman subject mobilized in the tension between cold war and post-cold war politics, psychological and biological machines, centralized and de-centralized control, top-down and bottom-up processing, autonomous and autopoietic organisms, cloning and transgenesis, species-self and other species. Ultimately, this book aims to re-focus concern on the ethics rather than on the 'nature' of life-as-it-could-be. (shrink)

Recently, biologists and computer scientists who advocate the "strong thesis of artificial life" have argued that the distinction between life and nonlife is important and that certain computer software entities could be alive in the same sense as biological entities. These arguments have been challenged by Sober (1991). I address some of the questions about the rational reconstruction of biology that are suggested by these arguments: What is the relation between life and the "signs of life"? What work (if any) (...) might the concept of "life" (over and above the "signs of life") perform in biology? What turns on scientific disputes over the utility of this concept? To defend my answers to these questions, I compare "life" to certain other concepts used in science, and I examine historical episodes in which an entity's vitality was invoked to explain certain phenomena. I try to understand how these explanations could be illuminating even though they are not accompanied by any reductive definition of "life.". (shrink)

Inventions should belong to no one. It does not matter whether the invention is a genetically engineered life form or a mechanism such as the more familiar radio: it should not be private property. More precisely, types of things invented by people (such as the radio or the dog) as opposed to particular things (such as the radio in my car and the dog in my back yard) should not be private property, with one qualification: At most, people should expect (...) monopolies for brief periods of time on the use of the types of gadgets and creatures they invent, after which such types of things (again: as distinct from particular gadgets and creatures) should be freely accessible by all. The monopoly I have in mind bears some resemblance to the monopoly provided by the patent system, but towards the end of the essay I will suggest ways in which that system needs to be rethought, restructured, and extended. (shrink)

In this paper I explore the question of how artificial life might be used to get a handle on philosophical issues concerning the mind-body problem. I focus on questions concerning what the physical precursors were to the earliest evolved versions of intelligent life. I discuss how cellular automata might constitute an experimental platform for the exploration of such issues, since cellular automata offer a unified framework for the modeling of physical, biological, and psychological processes. I discuss what it would take (...) to implement in a cellular automaton the evolutionary emergence of cognition from non-cognitive artificial organisms. I review work on the artificial evolution of minimally cognitive organisms and discuss how such projects might be translated into cellular automata simulations. (shrink)

In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind and (...) anorganism. My approach in the current paper isto explore this and other key themes inneurosemantics through the use of computermodels of neural networks embodied and evolvedin virtual organisms. The models allow for thelaying bare of the causal economies of entireyet simple artificial organisms so that therelations between the neural bases of, forinstance, representation in perception andmemory can be regarded in the context of anentire organism. On the basis of thesesimulations, I argue for an account ofneurosemantics adequate for the solution of theeconomy problem. (shrink)

Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three-dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibit- ing positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputa- tional bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

This article concerns the claim that it is possible to create living organisms, not merely models that represent organisms, simply by programming computers ("virtual" strong alife). I ask what sort of things these computer-generated organisms are supposed to be (where are they, and what are they made of?). I consider four possible answers to this question: (a) The organisms are abstract complexes of pure information; (b) they are (...) material objects made of bits of computer hardware; (c) they are physical processes going on inside the computer; and (d) they are denizens of an entire artificial world, different from our own, that the programmer creates. I argue that (a) could not be right, that (c) collapses into (b), and that (d) would make strong alife either absurd or uninteresting. Thus, "virtual" strong alife amounts to the claim that, by programming a computer, one can literally bring bits of its hardware to life. (shrink)

Mirror neurons may play a role in representing not only signs but also their meaning. Because actions are the only aspect of behavior that are inter-individually accessible, interpreting meanings in terms of actions might explain how meanings can be shared. Behavioral evidence and artificial life simulations suggest that seeing objects or processing words referring to objects automatically activates motor actions.

Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment – Avida-ED – in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered.

In this paper I provide an epistemological context for Artificial Life projects. Later on, the insights which such projects will exhibit may be used as a general direction for further Artificial Life implementations. The purpose of such a model is to demonstrate by way of simulation how higher cognitive structures may emerge from building invariants by simple sensorimotor beings. By using the bottom-up methodology of Artificial Life, it is hoped to overcome problems that arise from dealing with complex systems, such (...) as the phenomenon of cognition. The research will lead to both epistemological and technical implications.
The proposed ALife model is intended to point out the usefulness of an interdisciplinary approach including methodological approaches from disciplines such as Artificial Intelligence, Cognitive Science, Theoretical Biology, and Artificial Life. I try to put them in one single context. The epistemological background which is necessary for this purpose comes from the ideas developed in both epistemological and psychological Constructivism.
The model differs from other ALife approaches— and is somewhat radical in this sense—as it tries to start on the lowest possible level, i.e. avoids several a priori assumptions and anthropocentric ascriptions. Due to this characterization, the project may be alternatively viewed as testing the complementary relationship between epistemology and methodology. (shrink)

Since antiquity, philosophers and engineers have tried to take life’s measure by reproducing it. Aiming to reenact Creation, at least in part, these experimenters have hoped to understand the links between body and spirit, matter and mind, mechanism and consciousness. Genesis Redux examines moments from this centuries-long experimental tradition: efforts to simulate life in machinery, to synthesize life out of material parts, and to understand living beings by comparison with inanimate mechanisms. Jessica Riskin collects seventeen essays from distinguished scholars in (...) several fields. These studies offer an unexpected and far-reaching result: attempts to create artificial life have rarely been driven by an impulse to reduce life and mind to machinery. On the contrary, designers of synthetic creatures have generally assumed a role for something nonmechanical. The history of artificial life is thus also a history of theories of soul and intellect. Taking a historical approach to a modern quandary, Genesis Redux is essential reading for historians and philosophers of science and technology, scientists and engineers working in artificial life and intelligence, and anyone engaged in evaluating these world-changing projects. (shrink)

The future of ethics -- Minds and related matters -- On transition -- The colors of life -- The far future -- At the limits of the conceivable -- Loose ends and final thoughts.

We have created the homunculus and have seen the monstrous being. Forty days the sperm lay buried in manure and each day at noon the Master turned his magnet across it, muttering foreign words. Then, on the fortieth day he showed me the resemblance of a man, but it was transparent, without a corpus. He told me we should feed the loathsome object for exactly forty weeks, and all this time allow it to lie in its bed of manure in (...) a continual and even temperature, so that its every member might develop. This we did, much against my will. And it grew into a human child, though much smaller than any born of Woman. Now, my friends ask me to make one for them That they may be as horrified as I. I would do so for their admiration, except that I am merely the apprentice of the Master, and I am afraid. (shrink)

Pioneer approaches to Artificial Intelligence have traditionally neglected, in a chronological sequence, the agent body, the world where the agent is situated, and the other agents. With the advent of Collective Robotics approaches, important progresses were made toward embodying and situating the agents, together with the introduction of collective intelligence. However, the currently used models of social environments are still rather poor, jeopardizing the attempts of developing truly intelligent robot teams. In this paper, we propose a roadmap for a new (...) approach to the design of multi-robot systems, mainly inspired by concepts from Institutional Economics, an alternative to mainstream neoclassical economic theory. Our approach intends to sophisticate the design of robot collectives by adding, to the currently popular emergentist view, the concepts of physically and socially bounded autonomy of cognitive agents, uncoupled interaction among them and deliberately set up coordination devices. (shrink)

This volume is the direct result of a conference in which a number of leading researchers from the fields of artificial intelligence and biology gathered to ...

Artificial Life (ALife) has two goals. One attempts to describe fundamental qualities of living systems through agent based computer models. And the second studies whether or not we can artificially create living things in computational mediums that can be realized either, virtually in software, or through biotechnology. The study of ALife has recently branched into two further subdivisions, one is “dry” ALife, which is the study of living systems “in silico” through the use of computer simulations, and the other is (...) “wet” ALife that uses biological material to realize what has only been simulated on computers, effectively wet ALife uses biological material as a kind of computer. This is challenging to the field of computer ethics as it points towards a future in which computer and bioethics might have shared concerns. The emerging studies into wet ALife are likely to provide strong empirical evidence for ALife’s most challenging hypothesis: that life is a certain set of computable functions that can be duplicated in any medium. I believe this will propel ALife into the midst of the mother of all cultural battles that has been gathering around the emergence of biotechnology. Philosophers need to pay close attention to this debate and can serve a vital role in clarifying and resolving the dispute. But even if ALife is merely a computer modeling technique that sheds light on living systems, it still has a number of significant ethical implications such as its use in the modeling of moral and ethical systems, as well as in the creation of artificial moral agents. (shrink)

What is artificial life? Much has been said about this interesting collection of efforts to artificially simulate and synthesize lifelike behavior and processes, yet we are far from having a robust philosophical understanding of just what Alifers are doing and why it ought to interest philosophers of science, and philosophers of biology in particular. In this paper, I first provide three introductory examples from the particular subset of artificial life I focus on, known as ‘soft Alife’ (s-Alife), and follow up (...) with a more in-depth review of the Avida program, which serves as my case study of s-Alife. Next, I review three well-known accounts of thought experiments, and then offer my own synthesized account, to make the argument that s-Alife functions as thought experimentation in biology. I draw a comparison between the methodology of the thought-experimental world that yields real-world results, and the s-Alife research that informs our understanding of natural life. I conclude that the insights provided by s-Alife research have the potential to fundamentally alter our understanding of the nature of organic life and thus deserve the attention of both philosophers and natural scientists. (shrink)

We explicate representational content by addressing how representations that ex- plain intelligent behavior might be acquired through processes of Darwinian evo- lution. We present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real-world examples of neural network control of animal behavior. We argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creature’s environ- ments (...) and further can do so only if their neural states are appropriately isomor- phic to environmental states. Further, these informational and isomorphism rela- tions are what are tracked by content attributions in folk-psychological and cognitive scientific explanations of these intelligent behaviors. (shrink)