In an era where the development of artificial intelligence (AI) is advancing at an unprecedented rate, the concept of distributed superintelligence (DSI) is up for in-depth discussion. This essay explores how the integration of a Human Generative Adversarial Network (HGEN) model into the development of VSI and future centaurs can contribute to an ethically responsible and human-centred design of advanced AI systems.
1. Distributed superintelligence and future centaurs
The concept of distributed superintelligence extends the idea of the individual centaur, as described by Kasparov (2017), to a global network of human-machine symbioses. In his work ‘Superintelligence’, Bostrom (2014) discusses various forms of artificial superintelligence, whereby the DSI can be seen as a possible and promising manifestation.
The future centaurs, as entities within this network, could contribute to a collective consciousness that transcends the limits of individual human or machine intelligence through their enhanced perception and information processing. This synergy between human and artificial intelligence promises to address complex global challenges in novel ways.
2. Reciprocal resonance space and peaceful co-evolution
The concept of the ‘reciprocal resonance space’ can be seen as an AI extension of Rosa’s (2016) theory of resonance. In this context, it would represent a space in which humans and machines are in a reciprocal, constructive relationship, although each resonance space is still characterised by different and opposing perspectives shaped by 4E cognition. This idea goes beyond mere coexistence and implies a profound, reciprocal influence and development.
The vision of peaceful co-evolution between humans and machines is reminiscent of the concepts of technogenesis (Hayles, 2012), which describes the reciprocal development of humans and technology. In this sense, future centaurs would not only be technological tools, but active partners in human development and cultural evolution.
3. Iterative learning model as human GAN
The proposed model of a human GAN for the development of an artificial superintelligence (ASI) is an innovative approach that addresses several critical aspects:
a) Participatory development: By involving various human bodies (expert commission, online agency for swarm evaluations, citizens’ councils), a broad spectrum of perspectives is integrated into the development process. This is in line with concepts of participatory technology design (Sclove, 1995) and promises AI development that takes into account various social needs and values.
b) Ethical oversight: The role of citizen councils as ‘curators’ and the definition of ethical guidelines address the concerns discussed by Bostrom (2014) and others regarding the oversight and direction of an ASI. This approach could help avoid the ‘King Midas problem’, where an ASI functions perfectly technically but does not adequately address human values and needs.
c) Iterative improvement: The GAN-inspired approach with continuous feedback loops is similar to concepts of adaptive management in complex systems (Holling, 1978). This enables a flexible and adaptable development of the ASI that can respond to changing circumstances and new insights.
4. Implications for distributed superintelligence
The integration of the human GAN model into the concept of distributed superintelligence promises several advantages:
a) Decentralised control: Instead of a singular ASI, a network of future centaurs would emerge that is controlled by collective human intelligence and machine capacities. This could reduce the risk of uncontrolled AI development and ensure a more balanced distribution of power.
b) Cultural diversity: The inclusion of different human perspectives in the development process could lead to a DSI that respects and integrates cultural diversity. This is particularly important in a globalised world where AI systems need to function in different cultural contexts.
c) Dynamic adaptation: The iterative process enables continuous adaptation of the DSI to changing human needs and ethical considerations. This could lead to an ASI that is not only technically advanced, but also socially and ethically responsible.
5. Challenges and unanswered questions
Despite the promising potential of this approach, there are several challenges and unanswered questions:
a) Scalability: The practical implementation of such a system on a global scale poses considerable logistical and technical challenges. It must be investigated how such a complex system can be efficiently implemented and managed.
b) Consensus building: Agreeing on global ethical guidelines and goals in the face of cultural and ideological differences could be problematic. Innovative methods of intercultural communication and consensus-building are needed.
c) Power dynamics: There is a risk that certain groups or interests could disproportionately influence the development process. Mechanisms must be developed to ensure fair and balanced participation.
d) Technical complexity: The development of a DSI that effectively integrates human and machine intelligence requires significant technological advances. It remains an open question as to how far our technological capabilities need to extend in order to realise such a system.
6. Future research directions
In order to realise the full potential of this approach, further research efforts are required in the following areas:
a) Development of concrete implementation models for human GAN in DSI development. This could include simulations and pilot projects on a smaller scale.
b) Investigating the psychological and sociological effects of a close human-machine symbiosis in the context of future centaurs. How does the human self-image change in such a relationship?
c) Researching methods to effectively integrate different cultural perspectives into DSI development. This may require the development of new forms of intercultural dialogue and consensus building.
d) Analyse potential emergent properties of a globally networked DSI. What unexpected phenomena could emerge from such a complex system?
Conclusion
The integration of the Human-GAN model into the concept of Distributed Superintelligence offers a promising approach for a controlled and ethically responsible development of advanced AI systems. By creating a reciprocal resonance space between humans and machines and incorporating diverse human perspectives, a form of superintelligence could emerge that is both powerful and compatible with human values and needs.
This approach proactively addresses the challenges of the ‘King Midas problem’ and offers a path towards the co-evolution of humans and machines. It promises to transform the development of artificial intelligence from a purely technological to a socio-technical process that takes into account the complexity of human societies and cultures.
At the same time, the realisation of this concept requires considerable further research and careful implementation. The challenges in terms of scalability, consensus building and technical complexity are considerable and should not be underestimated. An interdisciplinary approach is required that integrates findings from computer science, ethics, sociology, psychology and many other disciplines.
Ultimately, the concept of distributed superintelligence, based on a human-GAN model and realised by future centaurs, offers a fascinating vision for the future of human-machine interaction. It challenges us to think beyond the limits of our current notions of intelligence and consciousness and to shape a future in which humans and machines do not act as opposites, but as synergistic partners in overcoming global challenges.
References:
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Hayles, N. K. (2012). How we think: Digital media and contemporary technogenesis. University of Chicago Press.
Holling, C. S. (1978). Adaptive environmental assessment and management. John Wiley & Sons.
Kasparov, G. (2017). Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins. PublicAffairs.
Rosa, H. (2016). Resonanz: Eine Soziologie der Weltbeziehung. Suhrkamp Verlag.
Sclove, R. E. (1995). Democracy and technology. Guilford Press.