nettime: Reification, Schizophrenia, Artificial Intelligence - Phoebe Sengers

[Pit Schultz <pit@contrib.de>]

                        Fabricated Subjects:
         Reification, Schizophrenia, Artificial Intelligence

                          Phoebe Sengers 
           Computer Science --- Literary and Cultural Theory
                    Carnegie Mellon University
                        phoebe@cs.cmu.edu

Schizophrenia is the ego-crisis of the cyborg.  How could it be any
other way?  Cyborgs are the fabrications of a science invested in the
reproduction of subjects it takes to be real, a science whose first
mistake was the belief that cyborg subjects were autonomous agents,
that they existed outside any web of pre-existing significations.
Pre-structured by all comers, but taken to be pristine, the artificial
agent is caught in the quintessential double bind.  Fabricated by the
the techniques of mass production, the autonomous agent shares in the
modern malady of schizophrenia.  This paper tells the story of that
cyborg, of the ways it has come into being, how it has been
circumscribed and defined, how this circumscription has led to its
schizophrenia, and the ways in which it might one day be cured.

The Birth of the Cyborg:  Classical AI
--------------------------------------

The cyborg was born in the 1950's, the alter ego of the computer.  It
was launched into a world that had already defined it, a world whose
notions of subjectivity and mechanicity not only structured it but
provided the very grounds for its existence.  It was born from the
union of technical possibility with the attitudes, dreams, symbols,
concepts, prejudices of the men who had created it.  Viewed by its
creator as pure potentiality, it was, from the start, hamstrung by the
expectations and understandings which defined its existence.

Those expectations were, and are, almost unachievable.  The artificial
subject is one of the end points of science, the point at which the
knowledge of the subject will be so complete that its reproduction is
possible.  The twin births of Artificial Intelligence and Cognitive
Science represent two sides of the epistemological coin: the move to
reduce human existence to a set of algorithms and heuristics and the
desire to re-integrate those algorithms into a complete agent.  This
resulting agent carries all the burden of proof on its back; its
``correctness'' provides the objective foundation for a huge and
complicated system of knowledge whose centerpiece is rationality.
 
Make no mistake, rationality is the central organizing principle of
classical AI.  The artificial agent is fabricated in a world where
`intelligence,' not `existence,' is paramount, and `intelligence' is
identified with the problem-solving behavior of the scientist.  For
classical AI, the goal is to break intelligent behavior down into a
set of more-or-less well-defined puzzles, to solve each puzzle in a
rational, preferably provably correct, manner, and, one day, to
integrate all those puzzle-solvers to create an agent
indistinguishable (within a sufficiently limited framework) from a
human.

That limited framework had better not exceed reason.  Despite initial
dreams of agents as emotionally volatile as humans, the baggage of a
background in engineering quickly reduced agenthood to rationality.
For example, Allen Newell, one of the founders of AI, wrote an
influential paper which stated that the decision procedure of an agent
must necessarily follow the ``principle of rationality.''  Any agent
worthy of its name must have a set of goals it is pursuing, and any
action taken must, in its opinion, help to achieve one of its goals.
In the narrow constraints of this system, any agent that defies pure
rationality is explicitly stated to be completely incomprehensible,
and hence scientifically invalid.

Given these expectations, it was all too ironic when the artificial
agent began to show signs of schizophrenia.  Designing a rational
decision procedure to solve a clearly defined puzzle was
straight-forward; connecting these procedures together to function
wholistically in novel situations proved to be well-nigh impossible.
Bound in the straitjacket of pure rationality, the cyborg began to
show signs of disintegration: uttering words it did not understand
upon hearing, reasoning about events that didn't affect its actions,
suffering complete breakdown on coming across situations that did not
fit into its limited system of pre-programmed concepts.  Being
understood purely on its own terms and not with respect to any
environment, the agent lived in a fabricated world of its own making,
with only tenuous connections to shared physical and social
environments.  Autistic?  Schizophrenic?  In any case, deranged.


The Promise of Alternative AI
-----------------------------

It was time for therapy.  The shortcomings of the classical agent were
becoming more and more obvious: it could play chess like a master,
re-arrange blocks on command in its dream world, configure computer
boards, but it could not see, find her way around a room, or maintain
routine behavior in a changing world.  It was defined and fabricated
in an ideal, Platonic world, and could not function outside the
boundaries of neat definitions.  Faced with an uncertain, incompletely
knowable world, it ground to a halt.

Understanding that the cyborg was caught in a rational, disembodied
double bind, some AI researchers abandoned the terrain of classical
AI.  Alternative AI --- aka Artificial Life, behavior-based AI,
situated action --- sought to treat agents by the redefinition of the
grounds of their existence.  No longer limiting itself to the
Cartesian subject, the principle of situated action shattered notions
of atomic individualism by redefining an agent in terms of its
environment.  An agent is, and should be, understood as engaged in
interactions with its environment, and its `intelligence' can only be
gauged by understanding the patterns of these interactions.
`Intelligence' is not located in an agent but is the sum total of a
pattern of events occuring in the agent and in the world---the agent
no longer `solves problems,' but `behaves;' the goal is not
`intelligence' per se but `life.'

Redefining the conditions of existence of the agent breathed new life
into the field, if not into the agent itself.  Where once there had
been puzzle-solvers and theorem-provers as far as the eye could see,
there were now herds of walking robots, self-navigating cans-on-wheels
and other varieties of charming stupidity.  Alternative AI had given
the cyborg its body and had lifted some of the constraints on its
behavior.  No longer required to be rational, or even to use mental
representations, the artificial agent found new vistas open to itself.
It did not, however, escape schizophrenia.  Liberated from the
constraints of pure rationality, practitioners of alternative AI,
unwittingly following the latest rages in postmodernism, embrace
schizophrenia as a factor of living experience.  Rather than creating
schizophrenia as a side-effect, they explicitly engineer it in: the
more autonomous an agent's behaviors are, the fewer traces of
Cartesian ego left, the better.  May the most fractured win!

At the same time, that schizophrenia becomes a limit-point for
alternative AI, just as it has been for classical AI.  While
acknowledging that schizophrenia is not a fatal flaw, alternativists
have become frustrated at the extent to which schizophrenia hampers
them from building extensive agents.  Alternativists build agents by
creating behaviors; the integration of those behaviors into a larger
agent has been as much of a stumbling block in alternative AI as the
integration of problem-solvers is in classical AI.  Alternativists are
stuck with the major unsolved question of ``how to combine many
(e.g. more than a dozen) behavior generating modules in a way which
lets them be productive and cooperative.''  Despite their differences
in philosophy, neither alternativists nor classicists know how to keep
an agent's schizophrenia from becoming overwhelming.  What is it about
the engineering of subjectivities that has made such divergent
approaches ground on the same problem?

Fabricating Schizophrenias
--------------------------

There can be no doubt that alternative and classical AI have very
different stakes in their definitions of artificial subjectivity.
These different definitions lead to widely divergent possibilities for
the range of constructed subjects.  At the same time, these subjects
share a mode of breakdown; could it be that these agent-rearing
practices, at first blush so utterly opposed and motivated by
radically dissimilar politics, really have more in common than one
might suspect?

The agents' schizophrenia itself can point the way to a diagnosis of
the common problem.  Far from being autonomous and pristine objects,
artificial agents carry within themselves the fault lines, not only of
their physical environment, but also of the scientific and cultural
environment that created them.  The breakdowns of the agent reflect
the weak points of their construction.  It is not only the agents
themselves that are suffering from schizophrenia, but the very
methodology that is used to create them -- a methodology which, at its
most basic, both alternative and classical AI share.

In classical AI, the emphasis is on agent as problem-solver and
rational goal-seeker, and agents are built using functional
decomposition.  The agent is presumed to have a variety of modules
corresponding more or less to problem-solving methods in its mind.
Researchers work to `solve' each method, creating self-contained
modules for vision, speaking and understanding natural language,
reasoning, planning out behavior, learning, and so on.  They hope that
once they've built each module, they can with not too much effort glue
them back together again and, presto, a complete problem-solving agent
appears.  This is generally an untested hope, since integration, for
classicists, is at once undervalued and nonobvious.  Here,
schizophrenia appears as an inability to seamlessly integrate the 
various competences into a complete whole; the various parts have
conflicting presumptions and divergent belief systems, turning local
rationality into global irrationality.

For practitioners of alternative AI, the agent is thought of
behaviorally, and the preferred methodology is behavioral
decomposition.  Instead of dividing the agent into modules
corresponding to the various abstract abilities of the agent, the
agent is striated along the lines of the behaviors it engages in.  An
agent might typically be constructed by building modules that each
engage in a particular observable behavior: hunting, exploring,
sleeping, fighting.  Alternativists hope to avoid the form of
schizophrenia under which classicists suffer by integrating all the
agent's abilities from the start into specific behaviors in which the
agent is capable of seamlessly engaging.  The problem, again, comes
when those behaviors must be combined into a complete agent: the agent
knows what to do, but not when to do it or how to juggle its
separate-but-equal behaviors.  The agent sleeps instead of fighting,
or tries to do both at once.  Once again the agent is not a seamlessly
integrated whole but a jumble of ill-organized parts.

At its most fundamental, in both forms of AI, an artificial agent is
an engineered reproduction of a `natural' phenomenon and consists of a
semi-random collection of rational decision procedures. Both classical
and alternative AI use an analytic methodology, a methodology that was
described by Marx long before computationally engineering
subjectivities became possible: ``the process as a whole is examined
objectively, in itself, that is to say, without regard to the question
of its execution by human hands, it is analysed into its constituent
phases; and the problem, how to execute each detail process, and bind
them all into a whole, is solved by the aid of machines, chemistry,
&c'' (Marx 380).  In AI, one analyzes human behavior without reference
to cultural context, then attempts, by analysis, to determine and
reproduce the process that generates it.  The methodology of both
types of AI follows the straight, narrow, and ancient road of
objective analysis, with the following formula:

1. Identify a phenomenon in the world to reproduce.

2. Characterize that phenomenon by making a finite list of properties
that it has.

3. Reproduce each one of these properties in a rational decision
procedure.

4. Put the rational decision procedures together, perhaps under another
rational decision procedure, and presume that the original phenomenon
results.

The hallmarks of objectivity, reification, and exclusion of external
context are clear. Through their methodology, both alternative and
classical AI betray themselves as, not singularly novel sciences, but
only the latest step in the process of industrialization.

        In a sense, the mechanical intelligence provided by computers
        is the quintessential phenomenon of capitalism.  To replace
        human judgement with mechanical judgement - to record and
        codify the logic by which rational, profit-maximizing
        decisions are made - manifests the process that distinguishes
        capitalism: the rationalization and mechanization of
        productive processes in the pursuit of profit.... The modern
        world has reached the point where industrialisation is being
        directed squarely at the human intellect. (Kennedy 6)

This is no surprise, given that AI as an engineering discipline has
often been a cozy bedfellow of big business.  Engineering and capital
are co-articulated; fueled by money that encourages simple problem
statements, clear-cut answers, and quick profit unmitigated by social
or cultural concerns, it would in fact be a little surprising if
scientists had managed to develop a different outlook. Reificatory
methods seem almost inevitable.

But reification and industrialization lead to schizophrenia - the hard
lesson of Taylorism. And the methodology of AI seems almost a
replication of Taylorist techniques. Taylorists engaged in analyses of
workers' behavior that attempted to optimize the physical relation
between the worker and the machine. The worker was reduced to a set of
functions, each of which was optimized with complete disregard for the
psychological state of the worker. Workers were then given orders to
behave according to the generated optimal specifications; the result
was chaos. Workers' bodies fell apart under the strain of repetitive
motion. Workers' minds couldn't take the stress of mind-numbing
repetition. Taylorism fell prey to the limits of its own myopic
vision. 

Taylorism, like AI, demands that, not only the process of production,
but the subject itself become rationalized.  ``With the modern
`psychological' analysis of the work-process (in Taylorism) this
rational mechanisation extends right into the worker's `soul': even
his psychological attributes are separated from his total personality
and placed in opposition to it so as to facilitate their integration
into specialized rational systems and their reduction to statistically
viable concepts'' (88). This rationalization turns the subject into an
incoherent jumble of semi-rationalized processes, since ``not every
mental faculty is suppressed by mechanisation; only one faculty (or
complex of faculties) is detached from the whole personality and
placed in opposition to it, becoming a thing, a commodity'' (99).  At
this point, faced with the machine, the subject becomes schizophrenic.

And just the same thing happens in AI; a set of faculties is chosen as
representative of the desired behavior, is separately rationalized,
and is reunited in a parody of wholism. It is precisely the reduction
of subjectivity to reified faculties or behaviors and the naive
identification of the resultant system with subjectivity as a whole
that leads to schizophrenia in artificial agents.  When it comes to
the problem of schizophrenia, the analytic method is at fault.


Schizophrenization and Science
------------------------------

Where does this leave our cyborg?  Having traced its schizophrenia to
the root, it would seem that the antidote is straightforward: jettison
the analytic method, and our patient is cured.  However, just as there
are times when a patient cannot recover because his/her family needs
him/her to be sick, the cyborg cannot recover because its creators
cannot give up analysis.  The analytic method is not incidental to
present AI, something that could be thrown away and replaced with a