In a world that is increasingly enabling a fusion of human and artificial intelligence, the future Centaur model offers a new concept. This model, a further development of the classic Centaur model described by Garri Kasparov, promises a profound integration of human and digital life forms. At the centre of this discourse is the idea of the ‘emergence of an entity of an entropy’, i.e. the emergence of new entities and their potential role in overcoming global challenges.
1. The future centaur model and complex dynamic systems
The Future Centaur Model is best understood in the context of complex dynamic systems and 4E cognition. 4E (Embodied, Embedded, Extended, Enacted) cognition provides a framework for understanding cognitive processes as embodied, embedded, extended and enactive (Newen et al., 2018). In our context, 4E cognition serves as the basis for the interaction between human and digital components of the future centaur.
Emergence, a central concept in complex dynamic systems, describes the appearance of new, unexpected properties or behaviours (Goldstein, 1999). In connection with the information-theoretical concept of entropy (Shannon, 1948), the idea of an ‘emergence of an entity of an entropy’ arises – a new being or system that is able to manage, reduce or utilise entropy.
2. Overcoming existing resonance spaces
The future centaur promises to go beyond the human resonance spaces described by Rosa (2016). Through its integrated nature, it could create new, reciprocal resonance spaces that encompass both human and digital perspectives. This expanded form of intersubjectivity could lead to entirely new forms of understanding and interaction.
3. Application to global challenges (SDGs)
The potential applications of the future centaur model to the Sustainable Development Goals (SDGs) of the United Nations (2015) are manifold.
a) Overcoming cognitive biases: By integrating machine analysis capabilities, the Future Centaur could overcome the cognitive biases described by Kahneman (2011) and thus lead to more objective decisions.
b) Holistic systems view: The enhanced cognitive capabilities of the future centaur could enable a more comprehensive analysis of complex, interconnected systems, which is crucial for challenges such as climate change.
c) Creative problem solving: The combination of human creativity and machine data processing promises novel, unexpected approaches to solving the SDGs.
d) Ethical decision-making: Integrating human ethical considerations with data-driven analysis could lead to more balanced and fairer decisions.
4. Discussion and critical consideration
The idea of a future centaur, characterised by the ‘emergence of an entity of an entropy’, is consistent with theories of self-organisation in complex systems (Kauffman, 1993). It is also reminiscent of concepts such as ‘negentropy’ in information theory (Brillouin, 1953), which describe the ability of a system to create order out of chaos.
The application of this concept to the SDGs is based on the assumption that the integration of human and digital capabilities can lead to superior problem-solving capabilities. This is supported by research on human-AI collaboration, which shows that such partnerships often achieve better results than humans or AI alone (Jarrahi, 2018).
Despite the enormous potential, there are important challenges to consider:
• Technical feasibility: The development of such an integrated man-machine system poses enormous technical challenges.
• Ethical implications: The deep integration of human and digital entities raises complex ethical issues, particularly in relation to autonomy and identity.
• Social acceptance: The idea of such far-reaching human-machine integration could meet with social resistance.
• Unintended consequences: As with all complex systems, there is the possibility of unforeseen and potentially undesirable consequences.
Conclusion
The concept of a future centaur, characterised by the emergence of an ‘entity of an entropy’, offers a fascinating perspective on the possible evolution of human-machine interaction. It promises the potential to overcome previous cognitive and systemic boundaries and develop new approaches to global challenges.
The idea of an expanded intersubjectivity that goes beyond purely human or purely machine perspectives could lead to completely new forms of collective intelligence and problem solving, similar to that described by Lévy (1997) in his concept of ‘collective intelligence’.
At the same time, this concept requires careful ethical consideration and further research to fully understand its feasibility and implications. The challenges in terms of technical implementation, ethical issues and social acceptance are considerable and should not be underestimated.
The ‘emergence of an entity of an entropy’ in the context of the future centaur model represents an exciting area of research at the interface of complexity theory, cognitive science, information theory and futurology. It challenges us to rethink our understanding of intelligence, consciousness and the human-machine relationship.
As we continue to explore the opportunities and challenges of this concept, it is important to take a balanced approach that considers both the transformative potential and the potential risks. Only in this way can we ensure that the development of such advanced human-machine systems is in line with human values and for the benefit of society as a whole.
Continue to chapter
References:
Brillouin, L. (1953). The negentropy principle of information. Journal of Applied Physics, 24(9), 1152-1163.
Goldstein, J. (1999). Emergence as a construct: History and issues. Emergence, 1(1), 49-72.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
Kasparov, G. (2017). Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins. PublicAffairs.
Kauffman, S. A. (1993). The origins of order: Self-organization and selection in evolution. Oxford University Press.
Lévy, P. (1997). Collective intelligence: Mankind’s emerging world in cyberspace. Perseus Books.
Newen, A., De Bruin, L., & Gallagher, S. (Eds.). (2018). The Oxford handbook of 4E cognition. Oxford University Press.
Rosa, H. (2016). Resonanz: Eine Soziologie der Weltbeziehung. Suhrkamp Verlag.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development. United Nations, New York.