User:Tancre/2/thesis

Thesis

Part 1

The Hard Problem of Consciousness

Science used to address the challenge of explaining the mind by disassembling it in its functional, dynamical and structural properties . Consciousness has been described as cognition, thought, knowledge, intelligence, self-awareness, agency and so on, assuming that explaining the physical brain will resolve the mystery of the mind . From this perspective, our brain works as a complex mechanism that eventually triggers some sort of behavior. Consciousness is the result of a series of physical processes happening in the cerebral matter and determining our experience of controlling our body, thinking and feeling. This view has been able to explain many incognita of what happens in our mind, leading some to think that in a not-too-distant future we will be able to fully explain its inner secrets.

In 1995 the philosopher of mind David Chalmers published his article Facing up to the problem of consciousness , where he points out that the objective scientific explanation of the brain can solve only an easy problem. If we want to fully explain the mystery of the mind, instead, we have to face up the hard problem of consciousness: How do physical processes in the brain give rise to the subjective experience of the mind and of the world? Why is there a subjective, first-person, experience of having a particular kind of brain?

Explaining the brain as an objective mechanism is a relatively easy problem that eventually could be solved in a matter of time. But a complete understanding of consciousness and its subjective experience is an hard problem that the scientific objectivity can't directly access. Instead, scientists have to develop new methodologies, facing up that a hard problem exists — How is it possible that such a thing as the subjective experience of being me, here, now takes place in the brain? — and must be taken into consideration.

This new perspective distinguishing the subjective experience as phenomenal consciousness , echoes the mind-body problem initiated by Descartes and underlies whatever attempt to investigate the nature of our mind. It challenged the physicalist ontology of the scientific method. showing the unbridgeable explanatory gap between this dogmatic view of the world and the possibility to formulate a full understanding of consciousness. This produces the necessity of a paradigm shift in science allowing the study of consciousness from new alternative scientific methods embracing the challenge of investigating phenomenal consciousness.

The reactions to Chalmer's paper range between a total denial of the issue (Ryle 1949, Dennett 1978, 1988, Wilkes 1984, Rey 1997) to panpsychist positions (Nagel 1979, Bohme 1980, Tononi and Koch 2015), with some isolated case of mysterianism (McGinn 1989, 2012) advocating the impossibility to solve such a mystery. In any case, the last 30 years have seen exponential growth in multidisciplinary researches facing the hard problem with a constant struggle to build the blocks of a science of consciousness finally accepted as a valid field of study. This is a central subject of this thesis and we will regularly return to this contested field later in this text.

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The machinic life and its discontent (I)

To fully understand the relevance and consequences raised by exploring consciousness, we must shift our attention towards the evolution of technological systems. In particular, to the attempts to build autonomous machines, because they directly or indirectly tries to explain the secret mechanisms the mind. In 'The Allure of the Machinic Life' (2008), John Johnston attempts to organize the contemporary discourse on machines under a single framework that he calls 'machinic life'. '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. (...) Machinic life, unlike earlier mechanical forms, has a capacity to alter itself and to respond dynamically to changing situations.' Implying the whole attempt to produce life out of hardware and software in the definition of 'machinic life', allows us to re-consider the different experiences of the last century under the common goal of building autonomous adaptive systems and to understand their theoretical backgrounds as a continuum.

The mythological intuition of technology, subsumed in the concept of technè, already shows the main paths of the contemporary discourse. In fact in the myth of Talos and in the Daedalus' labyrinth, we can find the first life-like automaton and the first architectural design reflecting the complexity of existence and leading to the possibility of creating sentient machines outsourcing thought from human dominion. However only in the 19th century, with the new technological discoveries and a positivistic approach to knowledge, scientists started to build the bearing structures of what will become the two main fields of researches on autonomous machines of the 20th century.

On the one hand, the development of the steam engine (Watt 1776) through the study of thermodynamics (Sadi Carnot 1824) is joined with the studies of evolutionary biology (Lamark 1809, Darwin 1859). In 1858, Alfred Wallace made a specific relation between the 'vapour engine' and the evolutionary process. In the 1870s Samual Butler speculated on the evolution of machines. The autoregulation of animals (evolution) and machines (feedback mechanism) found their equivalence in the concept of 'adaptation'. These theories reflect the effort to reintroduce the idea of teleology (purpose) denied by the then ongoing debate on the origin of humankind contended between the purposeful design of Creationism (Paley 1802) and the blind chance of Darwinism. These developments made possible to theorize a framework where machines can auto-regulate and reproduce themselves, evolving exactly as biological organisms. Wallace and Butler's speculative theories will find their scientific correlative in the actual biological process of autoregulation called 'homeostasis' described by Walter Bradford Cannon in 1926, making possible its closer study and simulation in mechanical machines by Cybernetics.

On the other hand, the study of mathematics and logic, along with the revolution of Jacquard's loom (1804), led to the construction of advanced discrete-state machines [note] and the first practical translation of elementary logical function into binary algebra. Charles Babbage and Ada Lovelace's effort to develop and program the 'analytical' (1837) engine, together with Boolean logic (1854), give notice of a new computational era in which 'mental labor' was not exclusively the prerogative of humans but could be performed by an economy of machines [note]. The idea of formalizing thought in a set of rules (algorithm) can be traced back to Plato [note] and was theorized in the 17th century by Leibniz [note] as a universal symbolical system capable to solve every possible problem. Alan Turing and Alonzo Church will then demonstrate mathematically this speculation in 1936 leading to the formalization of the theory of computation. Together with the formalization of computer's architecture by John Von Neumann in 1945 and Claude Shannon's information theory in 1950, the digital computer was born making possible another framework of machinic life to raise: Artificial Intelligence (AI).

If the classical world had the intuition of the sentient machine, and the modern the realization of its possibility, it is only with the practical experience of Cybernetics and AI that the contemporary discourse of machinic life can be formulated. Nonetheless, the dual nature of contemporary discourse embodies the convergence of different theories in biological, mechanical and computational systems within a multidisciplinary approach to knowledge and life, driven by complexity and information. However, this already shows some of the weaknesses and biases that will become the limits of 'machinic life' in understanding and building working models of consciousness. For example, the idea that life can be reproduced outside of biological systems and the assumption that the human mind works as a symbolic computer (computationalism) discussed in the next chapter.