Event (Conference talk)
2023-09-06
From Mechanical Thinking to Models of Mind: Notes Towards a Historical Epistemology of Artificial Intelligence
What model of knowledge is the current form of AI (i.e. machine learning) representing? In the history of human civilizations tools have always emerged together with a system of (technical) knowledge associated to them, but this aspect seems very confused in an artefact that is said to directly automate human „intelligence“ and „learning.“ This epistemological dimension, that is the distinction between knowledge and tool of course exist also in machine learning as the distinction, for example, between programming languages and application, but it seems to be continuously removed from the debate on AI that is fixated on an equation unique in the history of epistemology: machine = intelligence. To criticize this assumption this keynote reads the idea of „machine intelligence“ not as a novelty but as the latest stage of the history of algorithmic thinking, and this as the confluence of the longer history of mechanical thinking with statistical thinking. Whereas the epistemology of mechanical thinking and statistical thinking has been flourishing, the epistemology on machine learning is still fragmentary and the keynote attempts an overview of the different epistemological schools and methods that could help consolidate this field.
What model of knowledge is the current form of AI (i.e. machine learning) representing? In the history of human civilizations tools have always emerged together with a system of (technical) knowledge associated to them, but this aspect seems very confused in an artefact that is said to directly automate human „intelligence“ and „learning.“ This epistemological dimension, that is the distinction between knowledge and tool of course exist also in machine learning as the distinction, for example, between programming languages and application, but it seems to be continuously removed from the debate on AI that is fixated on an equation unique in the history of epistemology: machine = intelligence. To criticize this assumption this keynote reads the idea of „machine intelligence“ not as a novelty but as the latest stage of the history of algorithmic thinking, and this as the confluence of the longer history of mechanical thinking with statistical thinking. Whereas the epistemology of mechanical thinking and statistical thinking has been flourishing, the epistemology on machine learning is still fragmentary and the keynote attempts an overview of the different epistemological schools and methods that could help consolidate this field.
