A structured analysis of the instability inherent in emergent intention — from neurobiology to artificial cognition.
This Technical Perspective maps the complex pathways between stimulus and reflective choice, referencing how fragile intention arises from competing subsystems in the brain and AI architectures.
It explores prefrontal-limbic dynamics, decision delays, and the risk of collapse in goal-oriented systems lacking memory depth or error correction.
A key resource in understanding reflective design and intention modelling in conscious systems.

Chapter 23, Section 3. The Fragility of Intention. Technical Perspective

Medium Article:
"The Devil’s Advocate Architecture," by Dr. Jerry A. Smith, introduces a novel framework for designing highly reliable artificial intelligence (AI) by mirroring principles of human psychological and organizational decision-making. The core argument is that modern AI fails due to overconfidence and a lack of doubt, which the proposed multi-agent system counters through structured conflict and debate. This architecture employs three distinct roles—the Worker (proposing a solution), the Devil’s Advocate (critiquing risks), and the Reviewer (synthesizing the final decision)—to overcome cognitive biases like groupthink. Crucially, suppose the Reviewer’s confidence falls below a set threshold. In that case, the system initiates a Genetic Mutation Loop, forcing agents to fundamentally evolve their strategies in response to the identified failure mode, leading to antifragile, battle-hardened solutions. A case study of IT incident resolution demonstrates how this dialectical process and targeted evolution yield comprehensive, contingent plans, making the approach applicable to high-stakes fields such as medical diagnosis and financial planning.

The Devil’s Advocate Architecture-How Multi-Agent AI Systems Mirror Human Decision-Making Psychology

In-Depth Explorations of Neuroscience-Inspired Architectures Revolutionizing AI.

New tracks tagged #AI Decision Making