Artificial Intelligence: unpredictable or unprestatable?

Current AI technologies have demonstrated impressive results, mainly driven by large language models (LLMs). The most diffused applications of LLMs are in the so-called generative AI, which consists in techniques that produce texts, music, pictures or videos--often in a multimodal setting. Challenging the intuition that machines cannot be truly creative, the artefacts produced by LLMs are sometimes considered as surprising, novel and creative. This view is also supported by observing that there are both theoretical and practical limitations on the predictability of AI systems' outcomes.Actual creativity relies on the capability of being transformative and inventive, hence not just unpredictable but unprestatable: true novelty arises within a process whose evolution of the very possibility space cannot be predicted.Prominent examples of unprestatability are the evolution of the biosphere and artistic human productions.In this contribution, we elaborate on the notions of predictability and prestatability in the context of current AI systems. We maintain that these systems are, to some extent, unpredictable but not unprestatable. A consequence of our contention is the definition of the limits of what AI systems can and cannot do, and therefore the contexts for which these technologies are best suited.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-08
DOI
https://doi.org/10.5281/zenodo.18187447
Primary Topic
Language and cultural evolution
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence: unpredictable or unprestatable?

Sauro Succi, Andrea Roli, Stuart Kauffman
Zenodo (CERN European Organization for Nuclear Research)
Language and cultural evolution
article

Artificial Intelligence: unpredictable or unprestatable?

Sauro Succi, Andrea Roli, Stuart Kauffman
article en

Abstract

Current AI technologies have demonstrated impressive results, mainly driven by large language models (LLMs). The most diffused applications of LLMs are in the so-called generative AI, which consists in techniques that produce texts, music, pictures or videos--often in a multimodal setting. Challenging the intuition that machines cannot be truly creative, the artefacts produced by LLMs are sometimes considered as surprising, novel and creative. This view is also supported by observing that there are both theoretical and practical limitations on the predictability of AI systems' outcomes.Actual creativity relies on the capability of being transformative and inventive, hence not just unpredictable but unprestatable: true novelty arises within a process whose evolution of the very possibility space cannot be predicted.Prominent examples of unprestatability are the evolution of the biosphere and artistic human productions.In this contribution, we elaborate on the notions of predictability and prestatability in the context of current AI systems. We maintain that these systems are, to some extent, unpredictable but not unprestatable. A consequence of our contention is the definition of the limits of what AI systems can and cannot do, and therefore the contexts for which these technologies are best suited.

Zenodo (CERN European Organization for Nuclear Research)
Harvard University Press (US), Italian Institute of Technology (IT), Institute for Systems Biology (US), InSysBio (Russia) (RU), University of Bologna (IT)
Quality Education
Openalex Percentile: Top 95%
Language and cultural evolution
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Artificial Intelligence: unpredictable or unprestatable? — Sauro Succi, Andrea Roli, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS