CMD: Experiments in Bio-Algorithmic-Politics
In collaboration with VU University Amsterdam
CMD: Experiments in Bio-Algorithmic-Politics
In collaboration with VU University Amsterdam
CMD: Experiments in Bio-Algorithmic-Politics uses self-learning algorithms that test different market strategies of competition and collaboration to see which relations of production allows the bacterial cultures to thrive in the long run.
CMD: Experiments in Bio-Algorithmic-Politics | Photo: Boudewijn Bollmann
CMD: Experiments in Bio-Algorithmic-Politics | Photo: Boudewijn Bollmann
CMD: Experiments in Bio-Algorithmic-Politics | Photo: Boudewijn Bollmann
The post Anthropocene will be marked by the agency of everything non-human. From self-organizing urban infrastructure to ubiquitous politically driven digital networks, these interconnected systems are impacting and regulating the societies and ecosystems that made their advent possible.
Facing this paradigm shift, some questions urgently need to be asked. Will this act as a catalyst of already existing tensions or allow for totally new distributions of power? CMD is an experimental setup aiming at highlighting the hopes and issues relative to these topics where the political, the technological and the ecological meets.
CMD is an artificial ecosystem comprised of photosynthetic bacterial cultures that are sharing scared light resources. Governance of this resources is executed by a constantly refining algorithm. The photosynthetic cells and the computer are experimenting with different political systems granting access to this life necessary resource. While the system oscillates between selfinterest and communitarianism, between a fair distribution of wealth and unbalanced relationship of power, the algorithm is optimizing for the greater good of the community.
Each colony of photosynthetic cells can claim access to light thanks to credits earned for their oxygen production. A piece of software executes a decision making algorithm empowering each bioreactor with an agency over the financial system. This algorithm computes growth rates and historical data about the market and light exposure of the colonies to come up with an auction strategy to support the life of the bacteria.
Michael Sedbon designed and build the whole installation from scratch. Next to the 12 bioreactors It consists of a data collection apparatus able to monitor the growth and oxygen production while a cybernetic and automated array of pumps distributes the nutrient required for the bacteria to grow in optimal conditions. It is a life support machine whose efficiency is ultimately dependant on the precision of sensors. It can be seen as an evolutionary computer. Because of the emergent nature of societal forms of cognitions, it shows how relevant it is to embed genetic concepts into the design of political artificial intelligence.