Indexical AI

Abstract

This article argues that the algorithms known as neural nets underlie a new form of artificial intelligence that we call indexical AI. Contrasting with the once dominant symbolic AI, large-scale learning systems have become a semiotic infrastructure underlying global capitalism. Their achievements are based on a digital version of the sign-function index, which points rather than describes. As these algorithms spread to parse the increasingly heavy data volumes on platforms, it becomes harder to remain skeptical of their results. We call social faith in these systems the naive iconic interpretation of AI and position their indexical function between heuristic symbol use and real intelligence, opening the black box to reveal semiotic function.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 25 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.