A Daoist-Inspired Critique of AI’s Promises: Patterns, Predictions, Control

Contemporary discussions of AI are often framed according to generally held assumptions which have largely escaped serious critical analysis. For instance, those who promote AI tout its predictive prowess: powerful algorithms fed massive amounts of data are able to discover knowable patterns that can accurately forecast the behaviors in anything from individual movie preferences to financial markets. Armed with this type of knowledge we can then use AI, the hope goes, to be more objective in our ethical practices. And most seriously, we must extend this to the way we develop AI, not only do we want AI to function ethically, but we caution ourselves that if Artificial General Intelligence (AGI), superintelligence, or anything like the “singularity” is ever developed, it should be positively aligned with human values. Reflecting on these positions from the perspective of classical Daoism gives us reason to pause. While Daoist texts also assume there are patterns in the world which one can successfully go along with, they are not enthusiastic about the rational or knowable nature of these patterns—rather, they encourage us to appreciate them as fundamentally complex and mysterious. In this article, some Daoist attitudes are also concretely applied to ethical considerations, which cannot easily be controlled or known, much less put into code. Inspired by Daoist texts, we might cultivate an attitude less filled with hubris than humility, where we are allowed more space from which we can reflect on how we think about AI. Many of the most pressing issues associated with AI could, in fact, be significantly alleviated simply by shifting the way we think about, use, and develop these technologies.

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Publication Details

Journal
Religions
Published
2025-09-29
DOI
https://doi.org/10.3390/rel16101247
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

A Daoist-Inspired Critique of AI’s Promises: Patterns, Predictions, Control

Paul J. D’Ambrosio
Religions
Cognitive Science and Mapping
article

A Daoist-Inspired Critique of AI’s Promises: Patterns, Predictions, Control

Paul J. D’Ambrosio
article en

Abstract

Contemporary discussions of AI are often framed according to generally held assumptions which have largely escaped serious critical analysis. For instance, those who promote AI tout its predictive prowess: powerful algorithms fed massive amounts of data are able to discover knowable patterns that can accurately forecast the behaviors in anything from individual movie preferences to financial markets. Armed with this type of knowledge we can then use AI, the hope goes, to be more objective in our ethical practices. And most seriously, we must extend this to the way we develop AI, not only do we want AI to function ethically, but we caution ourselves that if Artificial General Intelligence (AGI), superintelligence, or anything like the “singularity” is ever developed, it should be positively aligned with human values. Reflecting on these positions from the perspective of classical Daoism gives us reason to pause. While Daoist texts also assume there are patterns in the world which one can successfully go along with, they are not enthusiastic about the rational or knowable nature of these patterns—rather, they encourage us to appreciate them as fundamentally complex and mysterious. In this article, some Daoist attitudes are also concretely applied to ethical considerations, which cannot easily be controlled or known, much less put into code. Inspired by Daoist texts, we might cultivate an attitude less filled with hubris than humility, where we are allowed more space from which we can reflect on how we think about AI. Many of the most pressing issues associated with AI could, in fact, be significantly alleviated simply by shifting the way we think about, use, and develop these technologies.

ReligionsVol. 16(10)
East China Normal University (CN), Zhejiang University (CN)
Openalex Percentile: Top 86%
Cognitive Science and Mapping
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