What are neural networks not good at? On artificial creativity
Bibliographic Data
| ID | 5260938 |
|---|---|
| Authors | Anton Oleinik (0000-0002-5229-1052, Memorial University of Newfoundland, corresponding author) |
| Year | 2019 |
| Volume | 6 |
| Issue | 1 |
| Publication date | 2019-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951719839433 |
| OpenAlex | W2936242438 |
| Language | EN |
| Citations received | 3 |
| References cited | 50 |
This article discusses three dimensions of creativity: metaphorical thinking; social interaction; and going beyond extrapolation in predictions. An overview of applications of neural networks in these three areas is offered. It is argued that the current reliance on the apparatus of statistical regression limits the scope of possibilities for neural networks in general, and in moving towards artificial creativity in particular. Artificial creativity may require revising some foundational principles on which neural networks are currently built
Artificial neural network · Cognitive science · Creativity · Extrapolation · Sociology · Advanced Text Analysis Techniques · Cognitive Science and Education Research · Computational and Text Analysis Methods · Computer Science · Mathematics · Psychology · Social Psychology · Artificial Intelligence
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Universe of the mind
The sociology of science
The Sociology of Philosophies
Explaining Creativity
Machine Learners
Personality, Gender, and Age in the Language of Social Media
Word associations contribute to machine learning in automatic scoring of degree of emotional tones in dream reports
Exploiting affinities between topic modeling and the sociological perspective on culture
Shared Mental Models
Text as Data
A Method of Automated Nonparametric Content Analysis for Social Science
Using Supervised Machine Learning to Code Policy Issues
Algorithmic paranoia and the convivial alternative
Adapting computational text analysis to social science (and vice versa)
Lost in a random forest
The Thomas Theorem and the Matthew Effect
Machine Translation
The cultural environment
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,75 |
| Citation span | 2022 - 2024 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |