Table 2. Summary of propositions across the four-stage causal model

Stage	Proposition	Mediators	Boundary conditions	Expected outcome
Stage 1BAI↓Cognition	P1: If BAI adoption increases working memory capacity, then task accuracy and sustained focus will measurably improve.	M1: Speed of neural adaptationM2: Degree of personalization	B1: Long-term biocompatibilityB2: Hardware durability in daily use	Enhanced working memory
Stage 2Cognition↓Performance	P2: If coaching and response latency are optimized, job performance in complex environments will improve.	M3: Frequency of AI coachingM4: BAI response latency	B3: Task type (routine vs. creative)	Better task performance
Stage 3Performance↓Employment	P3: If culture and job design are supportive, retention and wages rise.	M5: Organizational acceptanceM6: Task redesign	B4: Labor elasticity; how easily firms adjust workforce size in response to demand (sectoral)	Higher retention and pay
Stage 4Employment↓Economy	P4: If macro conditions are favorable, labor gains contribute to GDP and fiscal growth.	M7: Real wage increaseM8: Tax revenue and transfer shifts	B5: Macroeconomic climate	GDP growth and fiscal balance

This table summarizes the causal progression from neurocognitive change to macroeconomic outcomes, specifying mediators and boundary conditions at each stage. Detailed interpretations for each proposition are elaborated in the subsequent ‘Stage-by-Stage Causal Model section’, which provides expanded discussion, contextual analysis, and practical implications.
P=Proposition: A concise, testable statement linking specified conditions to expected outcomes. Each proposition represents a hypothesis that can be empirically examined to assess causal relationships.
M=Mediator: An intervening variable that explains the mechanism through which the proposition operates. Mediators provide insight into the pathways and processes that connect conditions to outcomes, enabling more precise theoretical modeling.
B=Boundary Condition: A contextual factor that defines the circumstances under which a proposition remains valid or is applicable. These conditions determine the scope and applicability of the propositions across contexts, ensuring that findings are interpreted and applied with situational relevance.
The downward arrows (↓) indicate the directional flow of causality across the four sequential stages in the model: Stage 1 – BAI to Cognition, Stage 2 – Cognition to Performance, Stage 3 – Performance to Employment, and Stage 4 – Employment to Economy.
This four-stage causal model is designed to integrate micro-level cognitive mechanisms with macro-level socioeconomic outcomes. Each stage builds on the preceding one, creating a cumulative pathway from individual neural adaptation and performance improvement to workforce integration and, ultimately, national economic impact.
While the propositions are presented in a linear sequence, the model acknowledges potential feedback effects between stages in practical applications. However, for analytical clarity, such bidirectional effects are not depicted in this summary table.
AI, artificial intelligence; BAI, brain–artificial intelligence interfaces; GDP, gross domestic product.