The Machine–Organism Distinction

The idea that analysis of organisms can proceed by distinguishing organisms from machines is common to many areas of philosophy. This thesis argues that our search for a philosophy of organisms should not proceed by defining or relying on a Machine–Organism Distinction (MOD). We are often able to take biological theories that are thought to characterize organ- isms, such as theories of organismal autonomy and stability, and apply them to machines. I argue that we should not provide an analysis of organisms according to an MOD because there is no distinction available that holds up to scrutiny and evidence. There have been several major attempts to provide an MOD. I divide these in consecutive chapters according to the property of organisms offered as an MOD: teleology (Nicholson 2013), autonomy (Mossio and Moreno 2015), stochasticity (Skillings 2015; Godfrey-Smith 2016) and pro- cessual stability (Dupré and Nicholson 2018). I address these major attempts to provide an MOD by showing how each fails to provide an analysis of organisms that distinguishes them from machines. To do this, I examine a diversity of machines and organisms that serve as naturalistic counterexamples. Discoveries in molecular biology and ecology, as well as developments in robotics and biotechnology, show the failure of MODs in contemporary philosophy and biology. Moreover, not only does the MOD consistently fail, but philosophical arguments that rely upon MODs consistently misrepresent organisms themselves. I conclude with the idea that we should consider machines not as external to, or distinguished from, organisms, but as proper objects of biological science.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2021

Author dc:creator

• Brunet, Tyler

Advisor dc:contributor.advisor

• Lewens, Tim

• Philosophy of Biology
• Philosophy of Technology
• Machines and Organisms

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/948d91eb-d64f-4458-b091-26b9f9e2ad73/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0002-7609-7254

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/324630