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A Causal Foundation for Consciousness in Biological and Artificial Agents

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Abstract

Traditional approaches model consciousness as the outcome either of internal computational processes or of cognitive structures. We advance an alternative hypothesis – consciousness is the hallmark of a fundamental way to organise causal interactions between an agent and its environment. Thus consciousness is not a special property or an addition to the cognitive processes, but rather the way in which the causal structure of the body of the agent is causally entangled with a world of physical causes. The advantage of this hypothesis is that it suggests how to exploit causal coupling to envisage tentative guidelines for designing conscious artificial agents. In this paper, we outline the key characteristics of these causal building blocks and then a set of standard technologies that may take advantage of such an approach. Consciousness is modelled as a kind of cognitive middle ground and experience is not an internal by-product of cognitive processes but the external world that is carved out by means of causal interaction. Thus, consciousness is not the penthouse on top of a 50 stores cognitive skyscraper, but the way in which the steel girders snap together from bottom to top.

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Notes

  1. 1.

    A necessary caveat: In this paper, whenever we criticize other approaches it is only to the extent that they are presented as an explanation of consciousness. Thus, for example, we have nothing either against Baars’ theory of the global workspace as an excellent cognitive model, or Tononi’s notion of integrated information as a mean to achieve unified representations. However, at the present state of research, we do not understand how these models could justify the emergence of consciousness at the end of a computational process or as the output of a cognitive module.

  2. 2.

    We use outside and inside to refer to physical events inside and outside one’s body.

  3. 3.

    In causal terms, we may distinguish between ‘the cause and that without which the cause would not be a cause’ ([47], p. 119). The former may be taken to be an event actually occurring while the latter may be just a state of affairs. The latter may be formalized in terms of conditions G such that  P  \(\wedge \)  G  \( \Box \rightarrow \)  E  which may unfolded in three conditionals  P  \(\wedge \) \(\lnot \)G \(\rightarrow \) \(\lnot \)E,  \(\lnot \)C  \(\wedge \)  G  \(\rightarrow \)   \(\lnot \)E,  and  C \(\wedge \) \(\lnot \)G  \(\rightarrow \) \(\lnot \)E.

  4. 4.

    These properties may be a inhomogeneous set of actual physical properties such as the reflected colour spectrum, the percentage of certain components, or the contrastive ratios among different areas. For the sake of the example, consider just a set of wavelengths.

  5. 5.

    Ofcourse, these models do not rule out the importance of the external environment to guide the development of internal structures. Indeed, they consider necessary for a healthy brain to develop by means of continuous interactions with the environment. However, once the required neural connections are in place, the mind is taken to be an internal phenomenon.

  6. 6.

    Whenever it was necessary to point to the autonomy of the mental with respect to the physical domain, the issue of misperception has been the battering ram of both philosophers and scientists. Dream and hallucinations appear as formidable evidence in favour of an inner world. However, this approach promises to locate a physical cause for any experience in the physical surrounding. All cases of conscious experience ought to be revisited as cases of (admittedly unusual) perception. The approach presented here honestly stands or falls on whether it will succeed to show that – perhaps surprisingly – whenever there is consciousness, there is a physical phenomenon, which is the content of one’s experience. We cannot do justice here to the problem of misperception. However, we flesh out a template of the strategy – namely to address each purported case of misperception and to revise them in terms of perception. (One of the authors is actually working on such an account for most cases of misperception, from hallucination to illusions, from aftereffects to direct brain stimulations).

  7. 7.

    The distinction between strong and weak machine consciousness mirrors that between strong and weak AI [38]. Weak machine consciousness considers whether it is possible to build machines that behave as if they were consciousness. Strong machine consciousness ventures to consider the possibility of real conscious machines. We believe that skipping the ‘hard problem’ is not a viable option in the business of making conscious machines [61].

  8. 8.

    http://www.robocup.org/.

  9. 9.

    Consider the following example: In the literature, we find that cats are somewhat colour-blind concerning the colour red, they see it as a shade of grey (whereas they have a perfect colour vision concerning e.g. green and blue). Well, the first finding is that we cannot be really sure about that, since we can only predict that from their eye anatomy – but what kind of ‘consciousness’ cats really have concerning the colour red is a totally different topic because we don’t know anything about the design of the key-lock-structure at this point. It may be totally different from ours. The second – and much more important – insight is that it might be less important for a cat to be capable of seeing red than for example for a bear. Cats – being carnivores – do not have to differentiate between ripe and unripe apples since they would not eat them anyway. For a bear on the other hand – being omnivores consuming a large portion of fruits daily – the situation may show itself quite differently.

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Authors and Affiliations

  1. Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA, USA

    Riccardo Manzotti

  2. IMA/ZLW & IfU, RWTH Aachen University, Dennewartstr. 27, 52068, Aachen, Germany

    Sabina Jeschke

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  1. IMA/ZLW, RWTH Aachen Univ IMA/ZLW, Aachen, Germany

    Sabina Jeschke

  2. Faculty of Mechanical Engineering, IMA/ZLW & IfU - RWTH Aachen Univers Faculty of Mechanical Engineering, Aachen, Nordrhein-Westfalen, Germany

    Ingrid Isenhardt

  3. Faculty of Mechanical Engineering, IMA/ZLW & IfU - RWTH Aachen Univers Faculty of Mechanical Engineering, Aachen, Germany

    Frank Hees

  4. Faculty of Mechanical Engineering, IMA/ZLW & IfU - RWTH Aachen Univers Faculty of Mechanical Engineering, Aachen, Germany

    Klaus Henning

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Manzotti, R., Jeschke, S. (2016). A Causal Foundation for Consciousness in Biological and Artificial Agents. In: Jeschke, S., Isenhardt, I., Hees, F., Henning, K. (eds) Automation, Communication and Cybernetics in Science and Engineering 2015/2016. Springer, Cham. https://doi.org/10.1007/978-3-319-42620-4_40

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