Secret Agents: A Psychoanalytic Critique of Artificial Intelligence and Machine Learning

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Secret Agents: A Psychoanalytic Critique of Artificial Intelligence and Machine Learning. / Apprich, Clemens.
in: Digital Culture & Society, Jahrgang 4, Nr. 1, 27.07.2018, S. 29-44.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Bibtex

@article{0a50468394824a8eb2c72bcc1153deab,
title = "Secret Agents: A Psychoanalytic Critique of Artificial Intelligence and Machine Learning",
abstract = "“Good Old-Fashioned Artificial Intelligence” (GOFAI), which was based on a symbolic information-processing model of the mind, has been superseded by neural-network models to describe and create intelligence. Rather than a symbolic representation of the world, the idea is to mimic the structure of the brain in electronic form, whereby artificial neurons draw their own connections during a self-learning process. Critiquing such a brain physiological model, the following article takes up the idea of a “psychoanalysis of things” and applies it to artificial intelligence and machine learning. This approach may help to reveal some of the hidden layers within the current A. I. debate and hints towards a central mechanism in the psycho-economy of our socio-technological world: The question of “Who speaks?”, central for the analysis of paranoia, becomes paramount at a time, when algorithms, in the form of artificial neural networks, operate more and more as secret agents.",
keywords = "Digital media, Media and communication studies",
author = "Clemens Apprich",
year = "2018",
month = jul,
day = "27",
doi = "10.14361/dcs-2018-0104",
language = "English",
volume = "4",
pages = "29--44",
journal = "Digital Culture & Society",
issn = "2364-2114",
publisher = "transcript Verlag",
number = "1",

}

RIS

TY - JOUR

T1 - Secret Agents

T2 - A Psychoanalytic Critique of Artificial Intelligence and Machine Learning

AU - Apprich, Clemens

PY - 2018/7/27

Y1 - 2018/7/27

N2 - “Good Old-Fashioned Artificial Intelligence” (GOFAI), which was based on a symbolic information-processing model of the mind, has been superseded by neural-network models to describe and create intelligence. Rather than a symbolic representation of the world, the idea is to mimic the structure of the brain in electronic form, whereby artificial neurons draw their own connections during a self-learning process. Critiquing such a brain physiological model, the following article takes up the idea of a “psychoanalysis of things” and applies it to artificial intelligence and machine learning. This approach may help to reveal some of the hidden layers within the current A. I. debate and hints towards a central mechanism in the psycho-economy of our socio-technological world: The question of “Who speaks?”, central for the analysis of paranoia, becomes paramount at a time, when algorithms, in the form of artificial neural networks, operate more and more as secret agents.

AB - “Good Old-Fashioned Artificial Intelligence” (GOFAI), which was based on a symbolic information-processing model of the mind, has been superseded by neural-network models to describe and create intelligence. Rather than a symbolic representation of the world, the idea is to mimic the structure of the brain in electronic form, whereby artificial neurons draw their own connections during a self-learning process. Critiquing such a brain physiological model, the following article takes up the idea of a “psychoanalysis of things” and applies it to artificial intelligence and machine learning. This approach may help to reveal some of the hidden layers within the current A. I. debate and hints towards a central mechanism in the psycho-economy of our socio-technological world: The question of “Who speaks?”, central for the analysis of paranoia, becomes paramount at a time, when algorithms, in the form of artificial neural networks, operate more and more as secret agents.

KW - Digital media

KW - Media and communication studies

UR - https://www.transcript-verlag.de/media/pdf/d4/eb/be/ts4266_1.pdf#p26

U2 - 10.14361/dcs-2018-0104

DO - 10.14361/dcs-2018-0104

M3 - Journal articles

VL - 4

SP - 29

EP - 44

JO - Digital Culture & Society

JF - Digital Culture & Society

SN - 2364-2114

IS - 1

ER -

DOI