|The 17th International Conference on Image Analysis and Processing (ICIAP) is endorsed by the International Association for Pattern Recognition (IAPR), by IEEE Technical Committee PAMI, and by IEEE Computational Intelligence Society and is organized every two years by the Italian Group of Researchers in Pattern Recognition (GIRPR).|
Artificial consciousness: theoretical and empirical issues
Naples 11-13 September, ICIAP
Naples 11-13 September, ICIAP 2013
The purpose of the tutorial is to offer an overview of the theoretical and empirical issues in artificial consciousness. Is it possible to devise, project and build a conscious machine? Is it possible to achieve awareness in an artificial agent? What are the theoretical challenges? What are the technical difficulties? What advantages will a conscious machine have with respect to intelligent agents? This tutorial will review the current state of the art and will suggest where research may go to achieve such a far-reaching technical goal.
Will a Machine
Ever Be Conscious?
In the last few years, the once “incongruous” idea of machine consciousness gained increasing momentum (Adami, 2006; Aleksander, 1994, 2008; Aleksander et al., 2008; Buttazzo & Manzotti, 2008; Buttazzo, 2000; Chella & Manzotti, 2009a, 2009b; Clowes, Torrance, & Chrisley, 2007; Holland, 2004, 2003; Koch & Tononi, 2008; Seth, 2009; Taylor, 2007). This upsurge of interest in a such a technological possibility (Adami, 2006; Manzotti & Tagliasco, 2008; Seth, Dienes, Cleeremans, Overgaard, & Pessoa, 2008) has been encouraged by the parallel increase in consciousness-related research in the field of neuroscience (Jennings, 2000; Koch, 2004; Miller, 2011; Noë & Thompson, 2004; M. Overgaard & Grunbaum, 2012; R. Overgaard & Overgaard, 2010). Are these studies of any relevance in the field of robotics, artificial intelligence, and computer vision? Artificial consciousness, sometimes labeled as machine consciousness, is the attempt to model and implement those aspects of human cognition that are identified with the often elusive and controversial phenomenon of consciousness (Chella & Manzotti, 2009a; Holland, 2003; Mccarthy, 1995; Molyneux, 2012; O’Regan, 2012).
In brief, the tutorial will outline the complete theoretical framework in which current consciousness related scientific research is carried on. The tutorial will also list the most promising models (Global Work Space, Tononi’s information integration, Embodied Cognition, Externalist approaches to conscious experience, Seth’s model) contrasting advantages and shortcomings (Baars, 1997; Gamez, 2010; Koch & Tononi, 2008; Manzotti & Tagliasco, 2005; Manzotti, 2012; Shanahan, 2010; Tononi, 2008).
Questions to be discussed include: What advantage does consciousness provide to biological agents? Why does the brain produce a conscious representation of cognitive processing? What are the physical underpinnings of phenomenal experience? Couldn’t be the case that conscious experience is the hallmark of a certain style of information processing? Will conscious machines be able to outperform as to autonomy, semantic understanding, dealing with unexpected events, showing personal identity, achieving satisfactory human-machine communication?
Riccardo Manzotti (short bio). Riccardo Manzotti (PhD in Robotics, Professor of Psychology at IULM University, Milan) has been working for the best part of the last ten years on the topic of machine consciousness. He is coeditor of the “International Journal on Machine Consciousness”, He has written several papers on artificial consciousness as well as consciousness (Buttazzo & Manzotti, 2008; Chella & Manzotti, 2009a, 2009b, 2012; Manzotti & Tagliasco, 2005; Manzotti, 2011a) as well as on consciousness (Manzotti, 2006a, 2006b, 2008, 2011b, 2011c) and has co-organized or be an active presenter in several international workshop on machine consciousness and related topics (International Workshop on Artificial Consciousness 2005, Nokia Workshop on Machine Consciousness 2008, BICS 2010. Brain-Inspired Cognitive Systems Conference, BICA. Biologically Inspired Cognitive Architectures 2009, Machine Consciousness 2011: Self, Integration and Explanation, BICA 2012). In 2007, he edited a book on the topic of Artificial Consciousness together with Prof. Chella (Artificial Consciousness, Imprint Academic, http://www.amazon.com/Artificial-Consciousness-Riccardo-Manzotti/dp/1845400704 ). In 2008, he edited a special issue of the journal “Artificial Intelligence and Medicine” on the topic of Artificial consciousness.
Adami, C. (2006). What Do Robots Dream Of ? Science, 314, 1093–1094.
Aleksander, I. (2008). Machine consciousness. Scholarpedia, 3(2), 4162.
Aleksander, I., Awret, U., Bringsjord, S., Chrisley, R., Clowes, R., Parthermore, J., Stuart, S., et al. (2008). Assessing Artificial Consciousness. Journal of Consciousness Studies, 15(7), 95–110.
Baars, B. J. (1997). In The Theatre of Consciousness, 4(4), 292–309.
Buttazzo, G. (2000). Can a machine ever become self-aware? In R. Aurich, W. Jacobsen, & G. Jatho (Eds.), (p. 49). Los Angeles: Goethe Institute.
Buttazzo, G., & Manzotti, R. (2008). Artificial consciousness: Theoretical and practical issues. Artificial Intelligence in Medicine, 44, 79–82.
Chella, A., & Manzotti, R. (2009a). Artificial Consciousness. Thorverton.
Chella, A., & Manzotti, R. (2009b). Machine Consciousness: A Manifesto for Robotics. International Journal of Machine Consciousness, 1(1), 33–51.
Chella, A., & Manzotti, R. (2012). AGI and Machine Consciousness. Theoretical Foundations of Artificial General Intelligence, 4, 263–282.
Clowes, R., Torrance, S., & Chrisley, R. (2007). Machine Consciousness. Journal of Consciousness Studies, 14(7), 7–14.
Gamez, D. (2010). Information integration based predictions about the conscious states of a spiking neural network. Consciousness and Cognition, 19, 294–310.
Holland, O. (2003). Machine consciousness. New York: Imprint Academic.
Holland, O. (2004). The Future of Embodied Artificial Intelligence: Machine Consciousness? In F. Iida (Ed.), (pp. 37–53). Berlin: Springer.
Jennings, C. (2000). In Search of Consciousness. Nature Neuroscience, 3(8), 1.
Koch, C. (2004). The Quest for Consciousness: A Neurobiological Approach. Englewood (Col): Roberts & Company Publishers.
Koch, C., & Tononi, G. (2008). Can Machines Be Conscious? IEEE Spectrum, 45(6), 47–51. doi:10.2307/539906
Manzotti, R. (2006a). A Process Oriented View of Conscious Perception. Journal of Consciousness Studies, 13(6), 7–41.
Manzotti, R. (2006b). Consciousness and existence as a process. Mind and Matter, 4(1), 7–43.
Manzotti, R. (2008). A Process-Oriented View of Qualia. In E. Wright (Ed.), The Case for Qualia (pp. 175–190). Cambridge (Mass.): MIT Press.
Manzotti, R. (2011a). Machine Free Will: Is Free Will a Necessary Ingredient of Machine Consciousness? In C. Hernandez, R. Sanz, J. Gomez-Ramirez, L. S. Smith, A. Hussain, A. Chella, & I. Aleksander (Eds.), From Brains to Systems (pp. 81–89). Dordrecht: Springer.
Manzotti, R. (2011b). The Spread Mind. Seven Steps to Situated Consciousness. Journal of Cosmology, 14, 4526–4541.
Manzotti, R. (2011c). The Spread Mind. Is Consciousness Situated? Teorema, 30(2), 55–78.
Manzotti, R. (2012). The Computational Stance Is Unfit for Consciousness. International Journal of Machine Consciousness, 4(2), 401–420.
Manzotti, R., & Tagliasco, V. (2005). From behaviour-based robots to motivation-based robots. Robotics and Autonomous Systems, 51, 175–190.
Manzotti, R., & Tagliasco, V. (2008). Artificial consciousness: A discipline between technological and theoretical obstacles. Artificial Intelligence in Medicine, 44(2), 105–117.
Mccarthy, J. (1995). Making Robots Conscious of their Mental States. In S. Muggleton (Ed.), Machine Intelligence (pp. 1–39). Oxford: Oxford University Press.
Miller, G. (2011). Neuroscience. Feedback from frontal cortex may be a signature of consciousness. Science, 332(6031), 779.
Molyneux, B. (2012). How the Problem of Consciousness Could Emerge in Robots. Minds and Machines. doi:10.1007/s11023-012-9285-z
Noë, A., & Thompson, E. (2004). Are there Neural Correlates of Consciousness? Journal of Consciousness Studies, 11(1), 3–28.
O’Regan, K. J. (2012). How to Build a Robot that is Conscious and Feels. Minds and Machines, 22(2), 117–136.
Overgaard, M., & Grunbaum, T. (2012). Cognitive and non-cognitive conceptions of consciousness. Trends in Cognitive Sciences, 16(3), 137.
Overgaard, R., & Overgaard, M. (2010). Neural Correlates of Contents and Levels of Consciousness. Frontiers in Psychology, 1.
Seth, A. K. (2009). The Strength of Weak Artificial Consciousness. International Journal of Machine Consciousness, 1(1), 71–82.
Seth, A. K., Dienes, Z., Cleeremans, A., Overgaard, M., & Pessoa, L. (2008). Measuring consciousness: relating behavioural out neurophysiological approaches. Trends in Cognitive Sciences, 12(8), 314–321.
Shanahan, M. P. (2010). Embodiment and the Inner Life. Cognition and Consciousness in the Space of Possible Minds. Oxford: Oxford University Press.
Taylor, J. G. (2007). CODAM: A neural network model of consciousness. Neural Networks, 20, 983–992.
Tononi, G. (2008). Consciousness as integrated information: a provisional manifesto. The Biological Bulletin, 215(3), 216–42.