Interperforming in AI: question of ‘natural’ in machine learning and recurrent neural networks

AI and Society:1-9 (forthcoming)

Abstract
This article offers a critical inquiry of contemporary neural network models as an instance of machine learning, from an interdisciplinary perspective of AI studies and performativity. It shows the limits on the architecture of these network systems due to the misemployment of ‘natural’ performance, and it offers ‘context’ as a variable from a performative approach, instead of a constant. The article begins with a brief review of machine learning-based natural language processing systems and continues with a concentration on the relevant model of recurrent neural networks, which is applied in most commercial research such as Facebook AI Research. It demonstrates that the logic of performativity is not brought into account in all recurrent nets, which is an integral part of human performance and languaging, and it argues that recurrent network models, in particular, fail to grasp human performativity. This logic works similarly to the theory of performativity articulated by Jacques Derrida in his critique of John L. Austin’s concept of the performative. Applying Jacques Derrida’s work on performativity, and linguistic traces as spatially organized entities that allow for this notion of performance, the article argues that recurrent nets fall into the trap of taking ‘context’ as a constant, of treating human performance as a ‘natural’ fix to be encoded, instead of performative. Lastly, the article applies its proposal more concretely to the case of Facebook AI Research’s Alice and Bob.
Keywords No keywords specified (fix it)
Categories (categorize this paper)
DOI 10.1007/s00146-019-00910-1
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

Our Archive


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 42,172
External links

Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library

References found in this work BETA

No references found.

Add more references

Citations of this work BETA

No citations found.

Add more citations

Similar books and articles

Internal Recurrence.Don Ross - 1998 - Dialogue 37 (1):155-162.
Internal Recurrence.Don Ross - 1998 - Dialogue 37 (1):155-161.
Currents in Connectionism.William Bechtel - 1993 - Minds and Machines 3 (2):125-153.
Recurrent Policy Gradients.Daan Wierstra, Alexander Förster, Jan Peters & Jürgen Schmidhuber - 2010 - Logic Journal of the IGPL 18 (5):620-634.

Analytics

Added to PP index
2019-09-11

Total views
1 ( #1,340,238 of 2,253,661 )

Recent downloads (6 months)
1 ( #1,031,559 of 2,253,661 )

How can I increase my downloads?

Downloads

Sorry, there are not enough data points to plot this chart.

My notes

Sign in to use this feature