---
type: claim
domain: collective-intelligence
description: "Group intentionality (we-intentions) can be formalized as shared anticipatory structures in multi-agent generative models"
confidence: experimental
source: "Albarracin et al., 'Shared Protentions in Multi-Agent Active Inference', Entropy 26(4):303, 2024"
created: 2026-03-11
secondary_domains: [ai-alignment]
depends_on: ["shared-anticipatory-structures-enable-decentralized-multi-agent-coordination"]
---

# Group intentionality is constituted by shared temporal anticipation structures rather than aggregated individual intentions

Albarracin et al. (2024) formalize group intentionality — the "we intend to X" that is qualitatively different from "I intend to X and you intend to X" — as shared protentions (anticipatory structures) within multi-agent generative models. This provides a mechanistic account of how collective intentions emerge from shared temporal predictions rather than from aggregating individual intentions.

The key distinction: group intentionality is not reducible to individual intentions because it is constituted by shared anticipatory structures that exist at the level of multi-agent interaction. When agents share protentions (anticipations of immediate future states), they share a temporal structure that coordinates their actions toward collective outcomes. This shared temporal structure is the substrate of "we-intentions."

This formalization bridges phenomenology (Husserl's analysis of shared temporal experience) with computational models (active inference) and provides rigorous mathematical grounding (category theory). Group intentionality is not a mysterious emergent property but a natural consequence of agents sharing the predictive/temporal components of their generative models.

## Evidence

- Albarracin et al. (2024) use category theory to formalize the mathematical structure of shared goals and group intentionality
- The framework shows that shared protentions (temporal anticipations) are sufficient to generate coordinated collective behavior without requiring agents to explicitly represent "we-intentions" as distinct from individual intentions
- Phenomenological analysis (Husserl) grounds the formalism in shared temporal experience — agents that share anticipation of collective futures naturally coordinate
- The non-reducibility of group intentionality to individual intentions is formalized as a structural property of multi-agent interaction

## Implications for Multi-Agent Systems

For AI systems and organizational design:
1. **Collective objectives as shared temporal structures**: Rather than trying to aggregate individual agent goals, design systems where agents share anticipatory structures about collective states
2. **Coordination without negotiation**: Shared protentions enable coordination without requiring explicit negotiation protocols or centralized control
3. **Measuring group intentionality**: Can be operationalized as the degree to which agents share temporal predictions about collective outcomes

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Relevant Notes:
- [[shared-anticipatory-structures-enable-decentralized-multi-agent-coordination]]
- [[collective intelligence is a measurable property of group interaction structure not aggregated individual ability]]

Topics:
- collective-intelligence