Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Beyond Fast and Slow: Field Intelligence for Hybrid Minds

Authors: Figurelli, Rogério;

Beyond Fast and Slow: Field Intelligence for Hybrid Minds

Abstract

Fast and slow thinking became the default metaphor for human cognition, contrasting intuitive heuristics with deliberate reasoning. This dual-process view helped dismantle the myth of the perfectly rational individual and revealed systematic patterns of bias in judgment and decision-making. Yet as intelligence becomes hybrid — distributed across humans, machine models, autonomous agents and digital institutions — the language of two inner systems is no longer sufficient. The critical unit of analysis shifts from the individual mind to the field in which minds and machines operate. This article proposes field intelligence as a temporal and structural extension of fast and slow thinking. We first revisit dual-process theory and its main critiques, emphasizing its individual focus and its difficulty in capturing hybrid, socio-technical cognition. We then introduce a temporal stack for hybrid minds, from substrate-level constraints (System 0) to fast intuition (System 1), deliberate reasoning (System 2) and a field layer of rules, incentives and orchestrated agents (System 3). In this stack, time becomes a governance resource rather than merely a processing parameter. Building on this, we model the distribution of “P-like” and “NP-like” work across fields as a symbolic conservation principle: exploration and verification must co-exist within a bounded epistemic budget. Field intelligence is defined as the capacity of a system to allocate tempo and complexity wisely — letting fast modes explore, while slower structures arbitrate, ratify and rewrite the rules of the game. The result is a field-first blueprint for governing hybrid intelligence beyond the limits of traditional dual-process theory.

Keywords

Decision Cell Networks (DCN), Field-Driven Design (FDD), Dual-Process Theory, Large Language Fields (LLFs), Hybrid Intelligence, Fast and Slow Thinking, Temporal Stack of Intelligence, P+NP=1, Field Intelligence (FI)

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green