Outonomy

The concept of autonomy, understood as the capacity of a system to set up and follow the norms of its own functioning, is of central relevance to contemporary science and society. Recently, the increasing acknowledgement of the deep interconnectedness, mutual dependence and multi-scale embeddedness of several natural and social phenomena, has directly challenged the very idea of autonomy, together with those of individuality and identity, and the possibility of its applications to scientific and social challenges. The project, led by the IAS-Research Center for Life, Mind and Society of the University of the Basque Country (UPV/EHU), in which we participated, aims to expand theories of autonomy beyond classical conceptions of the individual by including integrative, relational, collective and environmental dimensions into it.

 

To do so the project pursues 4 main goals:

1- To develop an account of integration in autonomous systems, as an organizational principle to understand how ‘physiological’ cohesiveness emerges within and across systems.

2- To understand how inter-actions between autonomous systems can give rise to supra-individual or collective forms of autonomy and how these can alter the autonomy of the former.

3- To investigate the extension of autonomous systems into their environment (from prebiotic scaffolds to technology) to achieve viability and coordinate regulatory self-governing processes.

4- To address the issue of sustainability (at different scales) of new eco and socio-ecological systems emerging from previously independent autonomous systems.

 

In order to achieve these trans-disciplinary goals, the methodology involves naturalist conceptual analysis and synthesis based on an active dialogue with empirical research, computational and mathematical models and scientific theories. The profiles of the 5 research team members in philosophy of science, philosophy of biology and complex systems is complemented by an international work team of 24 collaborators including social scientists, computer modellers, network and data analysts, biologists and environmental scientists.

If you want to know more about the project, we recommend you read and download our project description document attached below. Updates of publication can be found here.

 

 

 

 

Project content