The problem of alignment

Bibliographic Data

ID20397285
AuthorsTsvetelina Hristova (0000-0002-9059-795X, University of Winchester), Liam Magee (0000-0003-2696-1064, Western Sydney University, corresponding author), Karen Soldatic (0000-0001-8139-2912, Toronto Metropolitan University)
Year2025
Volume40
Issue3
Pages1439-1453
Publication date2025-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAI & Society (JOURNAL)
Journal identifiersISSN: 0951-5666 • E-ISSN: 1435-5655
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s00146-024-02039-2
OpenAlexW4401389494
LanguageEN
Citations received4
References cited30

Large language models (LLMs) produce sequences learned as statistical patterns from large corpora. Their emergent status as representatives of the advances in artificial intelligence (AI) have led to an increased attention to the possibilities of regulating the automated production of linguistic utterances and interactions with human users in a process that computer scientists refer to as ‘alignment’—a series of technological and political mechanisms to impose a normative model of morality on algorithms and networks behind the model. Alignment, which can be viewed as the superimposition of normative structure onto a statistical model, however, reveals a conflicted and complex history of the conceptualisation of an interrelationship between language, mind and technology. This relationship is shaped by and, in turn, influences theories of language, linguistic practice and subjectivity, which are especially relevant to the current sophistication in artificially produced text. In this paper, we propose a critical evaluation of the concept of alignment, arguing that the theories and practice behind LLMs reveal a more complex social and technological dynamic of output coordination. We examine this dynamic as a two-way interaction between users and models by analysing how ChatGPT4 redacts perceived ‘anomalous’ language in fragments of Joyce’s Ulysses. We then situate this alignment problem historically, revisiting earlier postwar linguistic debates which counterposed two views of meaning: as discrete structures, and as continuous probability distributions. We discuss the largely occluded work of the Moscow Linguistic School, which sought to reconcile this opposition. Our attention to the Moscow School and later related arguments by Searle and Kristeva casts the problem of alignment in a new light: as one involving attention to the social regulation of linguistic practice, including rectification of anomalies that, like the Joycean text, exist in defiance of expressive conventions. The “problem of alignment” that we address here is, therefore, twofold: on one hand, it points to its narrow and normative definition in current technological development and critical research and, on the other hand, to the reality of complex and contradictory relations between subjectivity, technology and language that alignment problems reveal

Art · Performing arts · Visual arts · Computability, Logic, AI Algorithms · Computer Science · Language and cultural evolution · Natural Language Processing Techniques · Artificial Intelligence

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