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Abstract: This article is about minds and machines, or, to
be more precise, about cognitivism as a model for understanding the mind[1].
The sub-title is a quotation from Hilary Putnam ‘s famous 1960 paper
Minds and Machines, a sort of
manifesto for funcionalism in the philosophy of mind. Although Putnam himself
came to reject funcionalism, to a large extent because he now thinks that
reason cannot be naturalized, functionalism is central in what I will
call cognitivism. I will be considering cognitivism in a historical,
rather than argumentative, way. Basically I want to consider two aspects:
(i) some ideias of authors (such as H. Putnam, J. Searle, A. Turing, H. Simon
and D. Dennett) which I think may help us take a stand in an ongoing discussion
concerning the relevancy of cognitivism in thinking about the nature of
mind, (ii) a noteworthy consequence of cognitivism: although cognitivism
uses computational machines as a model, or metaphor, for understanding
the mind, this results in weakening, eventually doing away with, the
natural / artificial dichotomy, which we could assume was presupposed by
that model.
1. Putnam’s functionalism plus
Fodor’s Language of Thought
Hilary Putnam’s formulation
of functionalism, in the 60s, in papers such as Minds and Machines and The
Nature of Mental States, is a historical landmark in the philosophy
of mind. Putnam’s basic ideia is that mental states (contrary to
what Identity Theory materialists defended) are not brain states, but rather
functional states implemented in the brain (although they could be implemented
in another hardware – the ideia of multiple realizabilility of
mental states goes along with functionalism). In fact, it is exactly
because mental states can have diverse physical realizations that they
should not be identified with brain states. What Putnam suggests then, is
that mental states of beings such as us, are in a similar relation to
neurophysiological states as logical (functional) states of computational
machines are to the physical states of those machines (`the mind is to
the brain, as software to hardware'). Putnam intends, with this position,
to dissolve the mind-body problem. In other words, he wants to show that the
mind-body problem is not a genuine theoretical problem, but merely linguistic
and logical in nature. According to Putnam, the same problem would arise for
any cognitive system capable of self-monitoring and of producing
self-descriptions, if there were, in such a system, as there is in us, an
asymmetry between the access to the logical level, the program level, and
the access to the physical level. The program level is the level of the
system in respect to which the system is incorrigible – as we can see by the status of
statements such as I know I feel
pain, I know I think that p. There is no such incorrigibility in the system’s
access to its physical level (each of us must learn about his or her own
brain – the fact that our brain causes our mind does not by itself turn
a person into a neuroscientist). Putnam’s functionalism makes us
look at the (supposed) mind-body problem as related to this assimetry,
and not to some ‘unique nature of human subjective
experience’.
Functionalism, together with
the ideia according to which the functional level is an autonomous,
symbolic, representacional-computational level (elaborated for instance
by Jerry Fodor in his 1975 book in terms of a Language of Thought Hypothesis,
which may be summarized as No representations, no computations, no
computations, no mind) constitutes what I’m calling
cognitivism.
2. Strengths and weaknesses of
the model
What is wrong
and what is right with this model for understanding the mind? How important
is it today in the philosophy of cognitive science? How commited is the
model – which makes us look at the nature of minds
through the lens of computational machines –
with a natural / artificial dichotomy ? The first obvious comment
is that this picture of the nature of mind does not immediately call our
attention to something that may seem essential to our specific kind of mind:
consciousness. On the contrary, it can very easily allow for the mental
character of that which has never been, and will never be, conscious.
From a neo-cartesian point of view such as that of John Searle, for
instance, this is almost heretic, and anyway, an utterlly unjustified
position. Since the 60s much has been going on in the philosophy of mind
and in cognitive science, and I will try to describe some of that history
here in order to address the questions above. John Searle’s work
from the 80s and 90s is very helpful here: not only does he point
directly at what is lacking in the cognitivist model of the mind (namely,
consciousness) but also he clearly sees the close relation between
cognitivism and a specific discipline within cognitive science, ArtificiaI
Intelligence, and the significance of this relation. In fact, with his
celebrated Chinese Room thought experiment, Searle intends not only to
contest cognitivism but also to argue in favour of the impossibility of
what he calls Strong AI (Strong AI, in Searle’s own definition, is the
ideia according to which AI is concerned not only with simulation of
cognition but eventually with the real thing – any physical system
that runs the right program will have a mind; a system’s being
intelligent, or even conscious, depends only on the right kind of
functional organization, and so on programming, and not on hardware). As
far as that ‘condition of mentality’ may be formulated independently
of the system’s physical build-up and biological origins, it is conceivable
that physical systems other than humans, namely artificial systems, will
be, for the exact same reasons as humans, intelligent and conscious.
But what does
AI, as a discipline, have to do with cognitivism? Since the beginnings of
AI, philosophers have taken an interest in it, a very natural interest,
given the fact that philosophers have always been interested in the nature
of thought, and in its relation with the physical world. This interest produced extreme
positions about AI, ranging from the proclamation of an impossibility in
principle of non natural intelligence and consciousness, to the
conviction that through AI a more general and abstract conception of the
nature of intelligence would be reached, one which would allow us to see
human beings and all intelligent beings
– natural or non
natural – as examples of one same general phenomenon.
In contemporary
philosophy of the mind John Searle is a well known critic of both cognitivism
and Strong AI (whereas for instance philosophers such as David Chalmers
and Daniel Dennett defend both). The reason Searle’s Chinese Room thought
experiment is always brought in as a reference, is that it can been seen
as cooling down the excitement about cognitivism and AI. So, it is
especially interesting to notice that in this thought experiment the
critique of cognitivism takes the form of an intuitive test of the
difference between genuine mentality and simulated, merely attributed,
mentality.
Before coming back to the Chinese
Room, which is, as I said, an inevitable reference for thinking about cognitivism
as a model of the mind, and because I pointed out a close connection
between cognitivism and Strong AI, I want to make a few remarks about the
contributions of a philosopher, who has, in a way, preceded Searle, as
the official philosophical critic of AI. That philosopher is Hubert
Dreyfus, and some of his ideas were passed on more or less explicitly to
Searle (although Dreyfus is generally
closer to European phenomenology than Searle). Dreyfus noticed early the
overlap of interests of AI and philosophy and the result were some
polemical works such as Alchemy And Artifical Intelligence (1965)
and What Computers Can't Do (1972).
There he criticized the claims of AI, and insisted on the relation, that
seemed obvious to him, between the work then being developed in AI, based
on a conception of mind as a symbolic system and an ideia of intelligence
as problem-solving and the rationalist and intelectualist tradition in
philosophy. Dreyfus point was that AI was repeating the intelectualist errors
in the conception of mind and intelligence already pointed out by
philosophers such as Heidegger, Wittgenstein and Merleau-Ponty. His
rejection of a conception of mind as symbolic representations of the
world, and of a conception of intelligence as rule-governed problem-solving
was based on the conviction that these conceptions excluded important and
basic parts of the mental. Those `excluded parts’ were for instance,
body movements and pattern recognition, which, according to Dreyfus, underlay
the possibility of the explicit skills involved in representing and problem
solving.
Dreyfus’ writings
presented a sober perspective on some exaggerated forecasts that had accompanied
the beggings of AI. Although some of Dreyfus’s own forecasts have been
simply proved wrong (he had, for instance, the conviction that a computer
could not win a chess game with a human), what Dreyfus wanted to
criticize was the aprioristic assumption according to which mind
consisted in symbolic representations and rule-governed manipulation of
such representations. According to this intelectualist view, even a
cognitive skill such as perception would ultimately consist in problem-solving
by apllying rules. This conception was for instance totally oblivious of something
which, in Dreyfus’s eyes, played a fundamental role in cognition: background
knowledge or common sense. Background knowledge is not knowledge of
facts but, in the case of people, what they know without knowing that
they know it, something that they never learned but know how to act upon (as,
for example, that people move more easily forwards than backwards, or
that if one spills water on a towel on a table it will eventually get to
the legs underneath the table).
Other characteristics of human cognition which were absent from
these early attempts at simulation, and which Dreyfus pointed out, were fringe
consciousness, the tolerance of ambiguity, a proper body in the world
that organizes and unifies the experience of objects and subjective
impressions, the capacity for boredom, fatigue and loss of motivation, intentions
and interests that guide the way human subjects confront situations in
the world, making it the case that not all the facts in the world are
equally relevant at a given instant, and so differentiating ‘the
world’, etc. Some of Dreyfus’s criticisms have been since
then simply incorporated in the development of AI and Dreyfus himself was
quick to admit the proximity between the principles of conexionism and
the anti-intelectualist tradition in philosophy.
Let’s then move on to Searle, who is
perhaps the most well-known critic of the limits of the cognitivist model
of the mind. Searle likes to say that cognitive science is an exciting field
of research based on a conceptual error concerning the nature of mind
– cognitivism is the general name for that error and the Chinese
Room thought experiment was the first attack Searle launched against it. Minds,
Brains and Programs, the paper where the argument was first presented,
appeared in the journal Behavioral
and Brain Sciences in 1980 and the Chinese Room thought experiment
hasn’t moved out of the philosopher of mind’s tool-kit since
then. The Chinese Room consists of the following: somebody, who
doesn’t speak any Chinese, is locked inside a room, where there are
Chinese symbols in boxes. This person also has a book of instructions in
English, which tells her how to combine and transform symbol sequences, in
order to send them out of the room when other Chinese symbols are
introduced in the room through a small window. The person inside the room
knows nothing about this, but the people outside call the symbols which go
in `questions' and the symbols coming out `answers'. Therefore, from the
perspective of those people outside the room, verbally interacting with
it, the system speaks Chinese. Thus, the system behaves intelligently, passes
the ‘Turing Test ' – although the person inside knows very
well she does not understand a word of Chinese. Searle claims that the Chinese
Rooms makes the possibility of a system that has `attributed intentionality
' but no ` intrinsic intentionality ' or `genuine semantics' obvious.
It is not easy to say what exactly the argument is
supposed to prove. In fact, as Searle admits, the Chinese Room is more of
a parable than an argument. If it was presented as an argument it would
go from the premisses ‘Programs
are sintactic’ ‘Syntax
is not sufficient for semantics’ ‘Minds have semantic content’ to the conclusions ‘Implementing a program is not sufficient
for mind’ , ‘Strong
AI is unjustified’. Anyway, the Chinese Room is supposed to
show that mind is not a program and therefore appropriate programming
could never give mind to a system, since formal properties do not constitute
genuine intentionality. Searle always stresses the fact that his argument
has nothing to do with a specific state of evolution of technology, but concerns
only conceptual principles: cognitivism
is wrong in considering that formal properties per se would be sufficient for mind (this position would go
with the defense of Strong AI). For Searle, the essence of mind is consciousness,
and the existence of consciousness is a biological fact. Although in the
initial formulation of the Chinese Room, Searle evokes semantics and not
consciousness (`syntax is not sufficient for semantics', he says), the reason
why Searle thinks one cannot speak of syntactic mental processes without
speaking of semantics is the fact that he thinks that semantics and consciousness
are intimately connected. Basically, Searle thinks that one cannot
legitimatelly consider anything as mental if not for its relation (current
or potential) with consciousness. This is what Searle calls the Connection
Principle, which in fact he uses in another argument against cognitivism,
formulated in the 90s (in a 1992 book called The Rediscovery of Mind). The line of argument goes
– roughly – like this: Syntax is not a physical property; Cognitivism
assumes that physical events are syntactic; cognitivism is based on a
fallacy. Searle calls this fallacy the homunculus fallacy – what he
means is that cognitivist explanations of mental phenomena treat the
brain as if there were some agent inside it, doing symbol manipulation
and computations. According to Searle, symbols and computations are not intrinsic
features of the world. Yet cognitivism, evoking syntactic properties to
explain mental phenomena, totally overlooks this, and treats properties
which are there only for an observer as if they were natural properties. But
if syntax is not a feature of the natural world but an interpretation of
physical events, dependent on an observer, syntactic descriptions of
cognitive systems, assigned relative to observers, simply cannot do any
explanatory work. And so cognitivism is flawed.
Several aspects of Searle’s
‘Critique of Cognitive Reason’, as he calls it, may be
unified by noticing that for Searle, the Connection Principle is a basic principle
which should be used in thinking about the mind. It states that one can
conceive something which is currently unconscious as mental only as far
as one can think of it as a possible content of consciousness. Only this
– being potentially conscious – distinguishes intrinsic
intentionality from ersatz
intentionality (if not, how could we even start distinguishing a neuron from
a non evoked memory, calling one mental and the other not?). So, like
Descartes, although from a materialist point of view, Searle believes that
consciousness is the essence of the mind. Now, for Searle, consciousness
is a physical property of the brain, characterized by ontological
subjectivity. Something is ontologically subjective if we cannot describe
it from a 3rd person point of view (which is what we try to do when we
investigate for instance the neurophysiology of consciousness). The
problem that the existence of mind in the natural world poses is
connected with its ontological subjectivity. It is because of ontological
subjectivity that consciousness, although a physical property of the
brain, is irreducible to any other physical feature. This ontological
sense of subjectivity (the ideia
according to which this world is such that there are irreducibly
subjective elements in it) cannot be mistaken for an epistemological
sense of subjectivity (which concerns preconceptions that are supposed to
be eliminated in the pursuit of objectivity which is part of the spirit
of science). If we accept this
distinction, we will have to know next how is it that we can have an
objective conception of the ontologically subjective facts of consciousness.
Searle’s answer is biological naturalism: the idea that consciousness
is a biological feature of the brain, human and of other animals, and an
emergent property (as liquidity). Searle formulates the question in these
terms because he thinks that many materialists are wrong when they think
that without admitting reduction (something Searle himself does not
admit) one necessarily accepts dualism (and for Searle that does not have
that to be the case).
Let’s go back to the
Chinese Room, which, after all, opens the door to Searle’s discovery
of the irreducibly subjective element of this world. Searle uses it as an
instrument to criticize the artificiality of simulations of cognition and
the whole critique falls on the distinction between original, genuine,
and attributed intentionality. But exactly how are we supposed to
distinguish between genuine intentionality and merely attributed intentionality?
Searle evokes the causal power some physical systems (namely human
brains) have, while others don’t, as well as the Connection
Principle. But from a rhetorical point of view what Searle wants from us,
is that we identify with the human being inside the room, manipulating
the symbols and lacking any understanding. As is well known, the basic
reply to Searle is the so called systems reply: it is wrong to attribute
understanding to the executor of the program (incidentally a human). Understanding
is supposed to characterize the system as a whole, and that includes the
pieces of paper with the rules and symbols. By the way, it is worth
considering here that our neurons don’t have any understanding of
the language - Portuguese or English, or Swedish,… – that we
speak, either. Yet, we wouldn’t doubt that we, the global system, do
in fact understand Portuguese or English or Swedish – the lack of
genuine intentionality in our neurons is no proof of a lack of genuine understanding
in us. It isn’t fair, though, to take all this to mean that Searle thinks
that the distinction between genuine intentionality and attributed
intentionality corresponds to the distinction between ‘natural’
and ‘artificial’ – Searle is no simplistic critic of AI.
He does have a problem here, though: his appeal to intuition, on which in
fact the whole critique of cognitivism rests. I will now look for another
approach to these same issues (cognitivism, strong AI, intentionality,
the meaning of ‘natural’ and ‘artificial’) which
does not share that problem.
Until now I have been been considering only philosophers, now
I want to make a detour that will take us outside the discipline. Notice
that the model of mind I have been considering makes it very clear how
intelligence could be artificial: through the lens of the materialist and
dualist conception of cognitivism, we see mind as implemented sofware, a
software which can be implemented in a hardware other than the biological.
That’s how intelligence could be artificial. Now I want to bring in another ideia
concerning the nature of the natural / artificial relation, an ideia coming
from Herbert Simon, one of the founders of AI as a discipline, and put
forward for instance in his book Sciences of the The Artificial
(1969). This is an ideia that is shared by D. Dennett, who, as I said
before, unlike Searle, defends cognitivism and Strong AI. Simon thinks
that the sciences of the artificial by no means involve a move back, or
forth – away, anyway – from to natural sciences. The artificial
and the natural are not, according to Simon, two kingdoms but two points
of view, which do not stand opposed to one another. Everything that is
artificial (and that, to Simon, is everything that is a funcional/adaptive
device, to be assessed through norms of rational functioning) is also
natural (that is, it is utimately an object for physical explanation).
According to H. Simon, what distinguishes the artificial, then, is
something other than the existence of a distinct realm of entities. What
characterizes the point of view of the artificial is the fact that it aims
at systems in their status of interfaces of an interior and an
exterior, thus creating the (new, in the scope of natural sciences)
question of the rationality or adaptation of these interfaces to the environment.
In other words, for Simon a science of the artificial is a science of the
artificial because it deals with teleology, with the global behavior of systems
and the purposes of that behavior. Purposes relate the interior and the exterior,
independently of the material build-up of the systems. Both the interior of
the system and its exterior continue to belong to the natural sciences, it
is the interface that is specifically artificial. In fact, Simon also
defends that in some way certain natural organizations are in this sense
artificial, at least as far as a natural system (biological) can be
analyzed according to these parameters. And in The Sciences of the Artificial
H. Simon does include psychology (defined as the science of behaving
systems) in the sciences of the artificial: the psychology of a
system is a science of the artificial in contrast, namely, with the neurophysiology
of the same system, which aims exclusively at the physical interior of
the system and not at the interior/exterior interface and at the purposes
of the global behavior. Simon’s ‘artificial’ could be
called functional in the sense of teleological - what interests us here
is the fact that what makes the functional functional isn’t the
fact that is characterizes artifacts but the facts that it chracterizes
adaptive devices. Now, an adaptive device may be, or not, artificial in
the usual sense of artificial (being made or constructed by human beings).
By the way, we too are adaptive devices put together by evolution by
natural seleccion – and this is exactly what Dennett uses against
Searle, to fight Searle’s appeal to ‘intuitions’ and to
what’s ‘original’ and genuine about our type of
intentionality.
4. Functionalism, cognitivism
and the natural / artificial dichotomy. Conclusion: D. Dennett on natural
intelligence.
I will conclude taking
Dennett as a reference. It is a fact that his defense of cognitivist
funcionalism and Strong AI
involves, and this is essencial, a representational theory of the nature
of the consciousness that is very different from Searle’s theory of
consciousness, and also the reformulation of functionalism as an
hypothesis concerning not only the brain but the whole body. What
I’m interested in here, is how Dennett’s brand of cognitivism
makes us look at our own mind and intelligence. To start with, for Dennett
it is exactly the fact that funcionalist cognitivism does away with the distinction
between natural and artificial that unifies cognitive science as a field,
in that it allows us (i) to consider humans, animals and machines together
as cognitive systems (ii) to assume that cognitive performances of actual,
biologically based, minds are situated, with other possible types of
minds, in the same design space (in fact, not only cognitive
performances but also the systems to which they are due, as well as the
artifacts these systems produce, for example human instruments). From
here we must think in terms of thresholds, conditions of possibility for
human minds, as a specific kind of minds (as opposed to something
‘original’). These thresholds are, acccording to Dennett, connected
with architectures for communication and language, which render the speech
act nature of human thought possible. This, allowing namely for mental
acts such as endorsing and affirming one’s own beliefs through
language and making voluntary decisions, is what makes human minds so much
more powerful and sophisticated than those of other animals, so much so that,
frequently, the work of a philosopher approaching, for instance, the
problem of mind in cognitive ethology will consist in deflating interpretations
of animal behavior, namely overattributions of consciousness and
communication to other animals. Dennett’s cognitivist funcionalism,
with its deconstructionist stance on ‘genuine intentionality’
coexists, thus, both with a deflationary conception of animal mentality and
with the ideia that the distance between human minds and the minds of
other species, even the most intelligent, is enormous. It is big enough,
namely, to make all the difference in moral terms. Despite this, one should
not claim that there is any difference in kind, since it is still a
matter of cognitive architecture only, and so a difference in degree. All this goes against Searle’s
positions – but why? I want
to answer this question by evoking, as Dennett himself evokes, Alan
Turing, the english logician and mathematician. I’m interested here
in Turing as a philosopher –
the author of the paper Computing Machinery and Intelligence published
in the philosophical journal Mind in 1950 – rather than in the work
for which he is considered one of the fathers of the computer, the
creator of the concepts of Turing Machine and Universal Turing Machine. Computing
Machinery and Intelligence was already then written against the
critics of AI, and it is there that Turing proposes the Turing Test, the
test that Searle’s Chinese Room is supposed to have ‘refuted’.
The initial question is: can machines think? and the first thing Turing
says is that a conceptual quarrel around the questions what is a machine? what is thinking?
would lead to complications without end. The Turing Test is then
suggested as a practical substitute for approaching the nature of
intelligence. The Turing Test is an imitation game, one in which there
is, in the original situation, an interrogator and two people, of whose
gender the interrogator is unaware. The goal is to deceive the
interrogator (through verbal interaction, the only one allowed). In the
setting which interests us, thare’s no man and woman but rather a
human and a machine. Same rules, same type of interaction. The goal is again
to deceive the interrogator, this time concerning the status of machine
of the machine. As we know, there’s only verbal interaction, so all
that can be done to find out which is which is to formulate questions
(questions about mathematical calculations, interpretation of poems, ironic
comments or deciphering of metaphors, for instance). Turing’s point,
the intention behind the Test, is that we should think about thought in a
neutral, unbiased way – the Test
assumes that what behaves intelligently is intelligent, the
implicit suggestion is, I would say, holistic and pragmatic:
intelligence is intelligent behavior and not a special
substance (for example neuronal) or an extra ingredient (for example a
soul – or genuine intentionality).
In the remaining of
the paper Turing answers objections against the possibility of AI, all of
which are still around today: he calls them the theological objection (according
to which intelligence is due to a soul, only possessed by human beings),
the heads in the sand objection (one expects that AI does not come into
being or it would be terrible), the mathematical objection, evoking Godel’s
theorem (according to which the human beings have mental capacities which
exceed what is computable), the feeling and consciouness objection (according
to which a machine could not have states such as depression, love,
emotion, etc), the incapacities objection (according to which a machine would
never be capable of mood, learning, morality, passion), etc. He also considers
the argument according a machine does only what it is programmed to do, never
originates anything new, the argument of the continuity of the nervous
system. Turing analyzes these lines of objection one by one and continues to recommend the
test against any apriorist verdict or argument.
The conceptual points I want
to make as a minimal conclusion of this brief tour of cognitivism grow
out of Dennett’s endorsement of Turing’s strategy. If we side with Turing and Dennett against
Searle’s appeal to intuition and to something
‘original’ and unique about our minds, what we have is the
following (i) we should not be apriorists in defining intelligence, (ii) the
frontiers between machines and non machines, between thinking and non
thinking, may be fuzzier than what we would intuitively think, (iii) even
though we are mental beings, and so, in a way, incorrigible in accessing
our own minds, our intuition is not necessarily an infallible guide in
thinking about the nature of the mental.
References
ANDLER,
Daniel, 1992, Introduction aux
sciences cognitives, Paris, Gallimard.
BODEN,
Margaret (ed.), 1996, The Philosophy
of Artificial Intelligence, Oxford, Oxford University Press.
CHALMERS,
David, 1996, The Conscious Mind,
Oxford, Oxford University
Press.
DESCOMBES,
Vincent, 1995, La denrée mentale,
Paris, Minuit, 1995.
DREYFUS,
Hubert, 1965, Alchemy and
Artificial Intelligence, Rand Corporation Report, Santa Monica, California.
DREYFUS,
Hubert, 1972, What Computers
Can’t Do, New York,
Harper & Row.
FODOR,
Jerry, 1975, The Language of
Thought, Cambridge MA,
Harvard University Press.
HAUGELAND,
John (ed), 1981, Mind Design, Cambridge MA,
MIT Press.
MINSKY,
Marvin, 1985, The Society of Mind,
New York,
Simon &Schuster.
NEWELL,
Allen, 1990, Unified Theories of
Cognition, Cambridge MA,
Harvard
University Press.
PUTNAM,
Hilary, 1960, Minds and Machines,
in Philosophical Papers, vol.
2, Cambridge, Cambridge University
Press, 1975.
PUTNAM,
Hilary, 1967, The Nature of Mental
States, in Philosophical Papers,
vol. 2, Cambridge,
Cambridge University Press, 1975 (first published as Psychological Predicates).
SEARLE,
John, 1980, Minds, Brains and Programs, Behavioral and Brain Sciences, 3 (3).
SEARLE,
John, 1992, The Rediscovery of the
Mind, Cambridge MA, MIT Press.
SIMON,
Herbert, 1969, The Sciences of the
Artificial, Cambridge
Mass., MIT Press.
TURING,
Alan, Computing Machinery and
Intelligence (1950), in DENNETT e HOFSTADTER (eds.), 1981,The Mind’s I, New York,
Bantam Books.
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