Not the machine’s fault
Taxonomising AI failure as computational (mis)use
Bibliographic Data
| ID | 20397906 |
|---|---|
| Authors | Louisa Shen (The University of Sydney, corresponding author) |
| Year | 2025 |
| Volume | 40 |
| Issue | 8 |
| Pages | 5793-5807 |
| Publication date | 2025-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AI & Society (JOURNAL) |
| Journal identifiers | ISSN: 0951-5666 • E-ISSN: 1435-5655 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00146-025-02333-7 |
| OpenAlex | W4409544753 |
| Language | EN |
| References cited | 33 |
This paper proposes a re-examination of connectionist AI failures (controversial incidents) from the perspective of technological use. It advances four categories of failure: technically sound outputs inherent to connectionist programming; machine-world mis-configuration; motivational failure that deploys technology for illegitimate ends; and finally epistemic failure of misapplication where computing and AI are being used to solve for the wrong sets of social problems. Drawing on the history of computing, the paper argues that computational machines and its software (classical or connectionist) are numerical, procedural, and electronic in nature, and therefore, are geared to treat problems through the functions of numerical calculation, tabulation, approximation, and extrapolation. On account of these limitations, failure ensues when computers meet the many problems that cannot be solved on these grounds. The paper proposes and calls for an ontological comparison between computers and the problems they are pressed to serve prior to any pragmatic deployment
Art · Machine learning · Performing arts · Reliability engineering · Visual arts · Adversarial Robustness in Machine Learning · Computer Science · Engineering · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Artificial Intelligence
What computers still can't do
E Cognition
The Cybernetics Moment
AI models collapse when trained on recursively generated data
The Economist as Plumber
On Computable Numbers, with an Application to the Entscheidungsproblem
Causal inference in statistics
I.—computing Machinery and Intelligence
The Oxford Handbook of Reasons and Normativity
Operationalising AI ethics
Omission and commission errors underlying AI failures
Miscomputation
From Coding To Curing. Functions, Implementations, and Correctness in Deep Learning
Technology and History
The Oxford Handbook of 4E Cognition
The Scope, Nature, and Causes of Child Abuse and Neglect
The government machine
Epistemology
| Highly cited | No |
|---|