Inteligência artificial e consciência fenoménica : quão perto estamos de máquinas conscientes?

A consciência é um fenómeno mal compreendido de sistemas biológicos com uma certa complexidade, e há quem sustente a possibilidade de poder vir a ser uma propriedade de determinados organismos artificiais. Alguns autores acreditam que pode emergir do substracto físico, ser uma ilusão ou um mero epifenómeno pelo que, teoricamente, nada obsta a que possa ser instanciada, uma vez compreendidos os mecanismos que a fazem surgir. Para outros, entre os quais me incluo, a instanciação da consciência em organismos artificiais não é possível, uns porque a consideram irredutível ao físico, outros porque a situam em planos transcendentais. Neste trabalho, para além de considerações gerais destinadas a situar o assunto, procuro abordar particularmente o conceito de consciência fenoménica, o chamado “problema duro”, o problema de saber como é que certas actividades neuronais aparecem internamente como experiência subjectiva, como qualia, à luz de diferentes teorias oriundas de vários campos da ciência. Para além das referências às principais teorias metafísicas, discuto com algum pormenor as mais relevantes teorias específicas da consciência, analiso modelos e implementações propostas pela Inteligência Artificial (IA) e pela Consciência Artificial (CA)1, discuto até que ponto se avançou, ou não, na simulação e na instanciação da consciência em organismos artificiais, e quais as principais objecções à sua instanciação e caracterização. Por fim são extraídas algumas conclusões que tentam responder à questão suscitada no título, partindo da ideia de que a consciência fenoménica não é processamento de informação, de uma intuição a priori2 de que não é uma propriedade emergente do substracto físico, e que talvez só seja possível em determinados organismos biológicos.Consciousness is a poorly understood phenomenon of both more and less complex biological systems, and there are those who defend the possibility that it may also become a property of certain artificial organisms. Some authors believe that consciousness can arise from the physical substrate, be an illusion or a mere epiphenomenon, so theoretically nothing prevents it from being implemented once the mechanisms that make it emerge are understood. For others, myself included, the implementation of consciousness in artificial organisms is not possible, either because it is considered to be irreducible to the physical, or because it is situated in transcendental order. In this work, in addition to general considerations aimed at placing the subject, I particularly seek to address the concept of phenomenic consciousness, the so-called "hard problem," the problem of how, in the light of different theories from various fields of science, certain neural activities appear internally as subjective experience, or qualia. In addition to references to the main metaphysical theories, I discuss in some detail the most relevant specific theories of consciousness, analyze models and implementations proposed by Artificial Intelligence and Artificial Consciousness, and discuss to what extent progress has been made in the simulation and instantiation of consciousness in artificial organisms, and what are the main objections to its instantiation and characterization. Finally, some conclusions are drawn in an attempt to answer the question raised in the title, starting from the idea that phenomenic consciousness is not a processing of information, and from an a priori intuition that it is not an emergent property of the physical substrate, and that perhaps it is only possible in certain biological organisms

Concepts enacted: confronting the obstacles and paradoxes inherent in pursuing a scientific understanding of the building blocks of human thought

This thesis confronts a fundamental shortcoming in cognitive science research: a failure to be explicit about the theory of concepts underlying cognitive science research and a resulting failure to justify that theory philosophically or otherwise. It demonstrates how most contemporary debates over theories of concepts divide over whether concepts are best understood as (mental) representations or as non-representational abilities. It concludes that there can be no single correct ontology, and that both perspectives are logically necessary. It details three critical distinctions that are frequently neglected: between concepts as we possess and employ them non-reflectively, and concepts as we reflect upon them; between the private (subjective) and public (inter-subjective) aspects of concepts; and between concepts as approached from a realist versus anti-realist perspective. Metaphysical starting points fundamentally shape conclusions. The main contribution of this thesis is a pragmatic, meticulously detailed, and distinctive account of concepts in terms of their essential nature, core properties, and context of application. This is done within the framework of Peter Gärdenfors’ conceptual spaces theory of concepts, which is offered as a bridging account, best able to tie existing theories together into one framework. A set of extensions to conceptual spaces theory, called the unified conceptual space theory, are offered as a means of pushing Gärdenfors’ theory in a more algorithmically amenable and empirically testable direction. The unified conceptual space theory describes how all of an agent’s many different conceptual spaces, as described by Gärdenfors, are mapped together into one unified space of spaces, and how an analogous process happens at the societal level. The unified conceptual space theory is put to work offering a distinctive account of the co-emergence of concepts and experience out of a circularly causal process. Finally, an experimental application of the theory is presented, in the form of a simple computer program

Robotic Specification of the Non-Conceptual Content of Visual Experience

Standard, linguistic means of specifying the content of mental states do so by expressing the content in question. Such means fail when it comes to capturing non-conceptual aspects of visual experience, since no linguistic expression can adequately express such content. One alternative is to use depictions: images that either evoke (reproduce in the recipient) or refer to the content of the experience. Practical considerations concerning the generation and integration of such depictions argue in favour of a synthetic approach: the generation of depictions through the use of an embodied, perceiving and acting agent, either virtual or real. This paper takes the first steps in an investigation as to how one might use a robot to specify the non-conceptual content of the visual experience of an (hypothetical) organism that the robot models