Proceedings of the papers presented at the Symposium on "Revisiting Turing and his Test: Comprehensiveness, Qualia, and the Real World" at the 2012 AISB and IACAP Symposium that was held in the Turing year 2012, 2–6 July at the University of Birmingham, UK. Ten papers. - http://www.pt-ai.org/turing-test --- Daniel Devatman Hromada: From Taxonomy of Turing Test-Consistent Scenarios Towards Attribution of Legal Status to Meta-modular Artificial Autonomous Agents - Michael Zillich: My Robot is Smarter than Your Robot: On the Need for (...) a Total Turing Test for Robots - Adam Linson, Chris Dobbyn and Robin Laney: Interactive Intelligence: Behaviour-based AI, Musical HCI and the Turing Test - Javier Insa, Jose Hernandez-Orallo, Sergio España - David Dowe and M.Victoria Hernandez-Lloreda: The anYnt Project Intelligence Test (Demo) - Jose Hernandez-Orallo, Javier Insa, David Dowe and Bill Hibbard: Turing Machines and Recursive Turing Tests — Francesco Bianchini and Domenica Bruni: What Language for Turing Test in the Age of Qualia? - Paul Schweizer: Could there be a Turing Test for Qualia? - Antonio Chella and Riccardo Manzotti: Jazz and Machine Consciousness: Towards a New Turing Test - William York and Jerry Swan: Taking Turing Seriously (But Not Literally) - Hajo Greif: Laws of Form and the Force of Function: Variations on the Turing Test. (shrink)

The question about the potential for consciousness of artificial systems has often been addressed using thought experiments, which are often problematic in the philosophy of mind. A more promising approach is to use real experiments to gather data about the correlates of consciousness in humans, and develop this data into theories that make predictions about human and artificial consciousness. A key issue with an experimental approach is that consciousness can only be measured using behavior, which places fundamental limits on our (...) ability to identify the correlates of consciousness. This paper formalizes these limits as a distinction between type I and type II potential correlates of consciousness (PCCs). Since it is not possible to decide empirically whether type I PCCs are necessary for consciousness, it is indeterminable whether a machine that lacks neurons or hemoglobin, for example, is potentially conscious. A number of responses have been put forward to this problem, including suspension of judgment, liberal and conservative attribution of the potential for consciousness and a psychometric scale that models our judgment about the relationship between type I PCCs and consciousness. (shrink)

Computational functionalism posits that consciousness is a computation. Here we show, perhaps surprisingly, that it cannot be a Turing computation. Rather, computational functionalism implies that consciousness is a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation.

The term \synthetic phenomenology" refers to: 1) any attempt to characterize the phenomenal states possessed, or modeled by, an artefact ; or 2) any attempt to use an artefact to help specify phenomenal states. The notion of synthetic phenomenology is clari¯ed, and distinguished from some related notions. It is argued that much work in machine consciousness would bene¯t from being more cognizant of the need for synthetic phenomenology of the ¯rst type, and of the possible forms it may take. It (...) is then argued that synthetic phenomenology of the second type looks set to resolve some problems confronted by standard, nonsynthetic attempts at characterizing phenomenal states. An example of the second form of synthetic phenomenology is given. (shrink)

Scientific behavior is used as a benchmark to examine the truth status of computationalism (COMP) as a law of nature. A COMP-based artificial scientist is examined from three simple perspectives to see if they shed light on the truth or falsehood of COMP through its ability or otherwise, to deliver authentic original science on the a priori unknown like humans do. The first perspective (A) looks at the handling of ignorance and supports a claim that COMP is "trivially true" or (...) "pragmatically false" in the sense that you can simulate a scientist if you already know everything, which is a state that renders the simulation possible but pointless. The second scenario (B) is more conclusive and unusual in that it reveals that the COMP scientist can never propose/debate that COMP is a law of nature. This marked difference between the human and the artificial scientist in this single, very specific circumstance, means that COMP cannot be true as a general claim. The third scenario (C) examines the artificial scientist's ability to do science on itself/humans to uncover the "law of nature" which results in itself. This scenario reveals that a successful test for scientific behavior by a COMP-based artificial scientist supports a claim that COMP is true. Such a test is quite practical and can be applied to an artificial scientist based on any design principle, not merely COMP. Scenario (C) also reveals a practical example of the COMP scientist's inability to handle informal systems (in the form of liars), which further undermines COMP. Overall, the result is that COMP is false, with certainty in one very specific, critical place. This lends support to the claims (i) that artificial general intelligence will not succeed based on COMP principles, and (ii) computationally enacted abstract models of human cognition will never create a mind. (shrink)

This paper describes how Tononi’s information integration theory of consciousness was used to make detailed predictions about the distribution of phenomenal states in a spiking neural network. This network had approximately 18,000 neurons and 700,000 connections and it used models of emotion and imagination to control the eye movements of a virtual robot and avoid ‘negative’ stimuli. The first stage in the analysis was the development of a formal definition of Tononi’s theory of consciousness. The network was then analysed for (...) information integration and detailed predictions were made about the distribution of consciousness for each time step of recorded activity. This work demonstrates how an artificial system can be analysed for consciousness using a particular theory and in the future this approach could be used to make predictions about the phenomenal states associated with biological systems. (shrink)