research/

thesis

My thesis is in philosophy and centres on the research question: how does time manifest in algorithmic reason?

I define algorithmic reason as the style of reason which emerges from the introduction of feedback to computational machines in the 1940s. By drawing on Ian Hacking’s styles project, I argue that rather than being merely a way of thinking, algorithmic reason is better understood as a style of reason in its contemporary form, as it introduces new forms of evidence, new sentences, new ways of determining truthfulness and falsehood and so on.

As feedback is necessarily part algorithmic reason, we must also untangle the ontology of time in cybernetics if we are to understand how time manifests in algorithmic reason. Cybernetics, as it emerged in the 1940s, approached intelligence as a matter of purposeful teleological behaviours that involve negative feedback. As such, intelligence is to be found in the teleological (and adaptive) behaviour of animals and machines, rather than in, for instance, the ability to reason. Thus, cybernetics ventured beyond an emphasis on formal logic as an expression of intelligence, as well as the representational ontology which lies at the centre of modern sciences in general, and what is often referred to as Good Old-Fashioned AI in particular. That involves, among many other things, a recognition of the active role of time in intelligent life.

There are explicit references to the French philosopher Henri Bergson’s philosophy of time in early writings on cybernetics, where cybernetics is sometimes defined as the science of mechanisms where time is Bergsonian. The central tenets of Bergson’s philosophy of time, which I also discuss on two of the podcasts linked to on this site, is that time is an active force distinct (but inseparable) from space. Creation, the unexpected, and life is what happens in the tension between time and space. As compared to the time of Einsteinian physics - and Good Old-Fashioned AI - Bergsonian time, and cybernetic time, is an inherent part of the phenomena observed, rather than a constant and linear variable to be added to what we know, so that we can draw a straight line from cause to effect.

With these reflections in mind, I posit Bergson’s philosophy of time as a starting point to interrogate how time manifests in algorithmic reason as it is composed by technologies and ontologies drawn from both AI and cybernetics. From that interrogation I proceed with a discussion on what the implications of algorithmic time(s) are for notions of memory, speed, future, and creation as algorithmic reason imposes itself on ever-more spheres of our lives through the rapid development and spread of computational technologies.

[Bergson] [AI] [cybernetics] [algorithmic reason] [philosophy of time]

publications

Henriksen EE (2024) ‘Algorithmically generated memories: automated remembrance through appropriated perception’ Memory, Mind & Media 3(e11):1-15, doi:10.1017/mem.2024.8

This article is on algorithmically generated memories: data on past events that are stored and automatically ranked and classified by digital platforms, before they are presented to the user as memories. By mobilising Henri Bergson's philosophy, I centre my analysis on three of their aspects: the spatialisation and calculation of time in algorithmic systems, algorithmic remembrance, and algorithmic perception. I argue that algorithmically generated memories are a form of automated remembrance best understood as perception, and not recollection. Perception never captures the totality of our surroundings but is partial and the parts of the world we perceive are the parts that are of interest to us. When conscious beings perceive, our perception is always coupled with memory, which allows us to transcend the immediate needs of our body. I argue that algorithmic systems based on machine learning can perceive, but that they cannot remember. As such, their perception operates only in the present. The present they perceive in is characterised by immense amounts of data that are beyond human perceptive capabilities. I argue that perception relates to a capacity to act as an extended field of perception involves a greater power to act within what one perceives. As such, our memories are increasingly governed by a perception that operates in a present beyond human perceptual capacities, motivated by interests and needs that lie somewhat beyond interests of needs formulated by humans. Algorithmically generated memories are not only trying to remember for us, but they are also perceiving for us.

[digital memories] [Bergson] [perception] [social media] [memory]