In the increasingly networked and technologised world of the 21st century, the concept of resonance spaces is being expanded – especially in artificial resonance spaces. These spaces, whether in the physical or digital sense, are characterised by a special dynamic that goes beyond mere perception. They are places where collective images and representations are created that shape our understanding of the world and our society. This essay explores the various social mechanisms that contribute to the creation of these shared images and sheds light on the role that artificial intelligence (AI) and computer vision can play in this process.
1. Social mechanisms of image creation in resonance spaces
The development of shared images and representations in resonance spaces takes place through various social mechanisms:
a) Rituals and ceremonies:
As early as 1912, Émile Durkheim argued that rituals play a central role in the creation of collective representations [1]. Shared experiences and meanings are created through joint participation in rituals. These shared experiences form a collective consciousness that forms the basis for a shared world view.
b) Narratives and myths:
In 1991, Jerome Bruner emphasised the importance of narratives for the construction of social reality [2]. Shared stories and myths shape collective ideas and values. They provide a framework within which individuals can interpret and understand their experiences.
c) Symbolic interaction:
In 1969, Herbert Blumer described how people negotiate and construct shared meanings through symbolic interaction [3]. This process of continuous negotiation and reinterpretation of symbols and their meanings is fundamental to the emergence and development of collective images.
d) Media and communication technologies:
Marshall McLuhan argued in 1964 that media not only transmit information, but also shape the way we perceive and understand the world [4]. In today’s digital era, this realisation is particularly relevant, as social media and digital platforms have become central resonance spaces.
e) Institutions and education:
In 1966, Peter L. Berger and Thomas Luckmann discussed how institutions and educational systems contribute to the social construction of reality [5]. These structural elements of society play an important role in the mediation and consolidation of collective images and ideas.
2. AI and computer vision as a mirror of society
Research in AI and computer vision can serve as a mirror for society in several ways and contribute to the further development of social models:
a) Detection of bias:
AI systems that are trained on social data can uncover implicit prejudices and inequalities in society. Joy Buolamwini and Timnit Gebru, for example, revealed gender and skin colour bias in commercial facial recognition systems in 2018 [6]. These findings can help to visualise and address hidden social inequalities.
b) Modelling social dynamics:
Complex AI models can be used to simulate and analyse social interactions and dynamics. Joshua M. Epstein and Robert Axtell demonstrated this in 1996 with their ‘Sugarscape’ model [7]. Such models can help to better understand complex social phenomena and test possible interventions.
c) Broadening human perspectives:
AI systems can recognise patterns and correlations in large amounts of data that are not obvious to humans, thus opening up new perspectives on social phenomena. This can lead to a deeper understanding of social dynamics and the development of innovative solutions for social challenges.
d) Ethical challenges:
The development of AI systems raises ethical questions that force society to rethink and further develop its values and norms. This can serve as a catalyst for important social discussions and reflections.
3. Artificial resonance spaces and hyperscanning
The concept of hyperscanning, particularly in the context of human-human interaction, is a promising approach for investigating the emergence of collective images in resonance spaces. Hyperscanning enables the simultaneous measurement of neuronal activities of several individuals during social interactions. This method could provide valuable insights into the neuronal basis of the emergence of shared representations and expand our understanding of resonance spaces on a biological level.
Conclusion
The creation of collective images in resonance spaces is a complex process that is characterised by various social mechanisms. From rituals and narratives to symbolic interactions and institutional influences, many factors contribute to shaping our shared reality. The integration of AI and computer vision into this field of research opens up new perspectives and possibilities for understanding and analysing these processes. At the same time, these technologies act as a mirror of society by revealing biases, modelling social dynamics and initiating ethical discussions.
Future research in this area should focus on analysing the interactions between traditional social mechanisms and new technological influences. The development of artificial resonance spaces and the use of hyperscanning technologies could provide important insights. A deeper understanding of these processes could not only expand our theoretical knowledge, but also have practical implications for the design of more inclusive and reflective social structures.
[1] Durkheim, E. (1912). The Elementary Forms of Religious Life. Free Press.
[2] Bruner, J. (1991). The narrative construction of reality. Critical inquiry, 18(1), 1-21.
[3] Blumer, H. (1969). Symbolic interactionism: Perspective and method. Prentice-Hall.
[4] McLuhan, M. (1964). Understanding Media: The Extensions of Man. MIT Press.
[5] Berger, P. L., & Luckmann, T. (1966). The Social Construction of Reality: A Treatise in the Sociology of Knowledge. Doubleday.
[6] Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Conference on fairness, accountability and transparency, 77-91.
[7] Epstein, J. M., & Axtell, R. (1996). Growing artificial societies: social science from the bottom up. Brookings Institution Press.