Algorithmic Opacity
Origin: Concept used in the analysis of operative dispossession
Definition
Algorithmic opacity refers to the inaccessibility of the internal process by which an AI system produces its results. This is not merely a matter of trade secrets or intellectual property: it is a structural characteristic of large language models, whose generation mechanisms cannot be explained in terms of identifiable and traceable rules.
When an LLM produces a response, it is impossible (even for its designers) to retrace the exact reasoning that led to it. There is no reasoning in the logical sense of the term: there is a probabilistic generation, statistically coherent, but irreducible to a sequence of verifiable steps.
In my writings
Algorithmic opacity is one of the three constitutive dimensions of operative dispossession, along with the displacement of the locus of reflection and the reconfiguration of the role in the value chain.
It renders a posteriori control fundamentally insufficient. Validating a reasoning whose production mechanism one does not understand is not control in the full sense of the term: it is a formal validation that can mask structural errors. The professional who checks whether the cited source is real, without verifying whether the reasoning that mobilizes it is relevant, whether the problem framing is adequate, whether the premises are correctly laid out, exercises surface-level surveillance over an opaque process.
This is why a priori grammatization (imposing one’s cognitive grammar before delegating) is preferable to a posteriori control alone.