Machine learning - A new kind of cultural tool? - A “recontextualisation” perspective on machine learning & interprofessional learning

Aug 4, 2026

The paper argues that Machine Learning (ML) functions as a cultural tool that learns by perceiving patterns in data, yet it enables a more limited form of learning than sociocultural theory assumes. By tracing ML’s learning model and its implications, the work shows how ML extends and distributes human-machine relationships in cognition and learning. It then reframes the resulting human-machine working-learning problem through recontextualisation, linking ML and interprofessional learning (IPL) models, and distinguishes ML prediction from a ChatGPT question-answering learning approach.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages10

Reading Time25 min

AccessFree to download

Introduction

Cultural learning and social cognition

Sociocultural perspective on cognition, language, and tools

Cultural tools and the challenge from AI and ML

Recontextualisation for human-machine working-learning

Learning, Culture and Social Interaction 42 (2023) 100738 Contents lists available at ScienceDirect Learning, Culture and Social Interaction journal [homepage: www.elsevier.com/locate/lcsi](homepage: www.elsevier.com/locate/lcsi) | Review article
Machine learning – A new kind of cultural tool? A“recontextualisation” perspective on machine learning + interprofessional learning | | | | | --- | --- | --- | --- | | David Guile
UCL – Institute of Education, 20 Bedford Way, London WC1H 0NT, United Kingdom | | | | | A R T I C L E I N F O | | A B S T R A C T | | | Keywords:
Cultural tool
Machine learning Interprofessional learning Recontextualisation Cultural ecosystem | | The paper argues that (a) Machine Learning (ML) constitutes a cultural tool capable of learning through perceiving patterns in data,(b) the kind of learning ML is capable of nevertheless constitutes a more circumscribed kind of learning compared with how that concept has been interpreted in sociocultural (S-c) theory; and,(c) the development of ML is therefore further extending and distributing the complex relationship between human and machine cognition and learning. The paper explores these contentions by firstly, providing a broad-based account of the conception of cultural tools in S-c Theory. Secondly, offering a genealogy of ML, including the model of learning that underpins ML and highlights the challenge that a cultural too capable of some kind of learning presents for the extant S-c conception of a cultural tool. Thirdly, identifying the new human-machine working-learning problem the ML model of learning is generating. Finally, argues the concept of recontextualization offers a way to address that problem by providing a holistic perspective on the relationship between ML and IPL models of learning. In making this argument the paper distinguishes between the ML predictive and the Chat GPT answer to question(s) model of learning. | | 1. Introduction In The Cultural Origins ofHuman Cognition, Michael Tomasello (1999, p. 2) observes the “basic puzzle” about the development of Homo sapiens is that there has been insufficient time for the normal processes of biological evolution, involving genetic variation and natural selection, to have created the cognitive skills we require to “invent and maintain complex tool-use industries and technologies”and complex “forms of symbolic communication and representation” and “social organisations and institutions characteristic of modern societies.” Hence, he concludes there is only one possible solution to this puzzle “social or cultural transmission.” Drawing attention to three types of cultural learning that evolutionary anthropologists and development psychologists have identified facilitated the development of Homo sapiens – imitative learning (treating others as intentional agents to acquire their store of cultural knowledge), instructed learning (discursive cultural transmission) and collaborative learning (sharing and developing concepts and their implications for action)– Tomasello (1999, p. 5) argues they collectively culminated in “a single very special form of social cognition.” The distinguishing feature of this form of cognition was the ability of individuals to understand “conspecifics as beings like themselves who have intentional and mental lives like their own” and this involved “learning not just from the other but through the other (ibid italics in original)” because the tools, symbols and cultural practices they produced for example, language, text, art, E-mail address: [d.guile@ucl.ac.uk](d.guile@ucl.ac.uk). [https://doi.org/10.1016/j.lcsi.2023.100738](https://doi.org/10.1016/j.lcsi.2023.100738) Received 9 March 2022; Received in revised form 5 July 2023; Accepted 17 July 2023 Available online 27 July 2023 2210-6561/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ([http://creativecommons.org/licenses/by/4.0/]

FAQs

How does the paper define Machine Learning as a cultural tool?

It presents ML as a cultural tool that learns by perceiving patterns in data, extending cultural evolution beyond purely biological inheritance.

Why does the paper say ML’s learning is more circumscribed than sociocultural theory expects?

The argument is that sociocultural views link cultural tools to learning as ongoing accumulation, but ML’s learning model does not match that broader interpretation of learning capacity.

How does recontextualisation help address the human-machine working-learning problem?

Recontextualisation provides a holistic perspective on how ML and interprofessional learning (IPL) models relate, offering a way to manage the problem generated by ML’s learning model.

Aug 4, 2026

Upload by Ava Thompson