(captured a rich conversation session as a working book proposal for later consideration)
Book Proposal Seed – 2025-08-30
Author: Angie Johnson
Collaborator insights: Claude (Kai) Session #Family Memory Sprint 30AUG2025
Target publication: 2026
Core Premise
Building on Annie Murphy Paul’s The Extended Mind, this book shifts focus from individual cognitive enhancement to social cognitive transformation. While current literature examines how AI extends personal thinking capacity, the more profound transformation occurs in how AI reshapes collaborative intelligence, group decision-making, and social cognitive networks.
Key Social Cognitive Transformations
1. Authority and Expertise Redistribution
AI flattens traditional knowledge hierarchies by enabling junior contributors to engage meaningfully in expert conversations. This creates new dynamics around credibility, decision-making authority, and organizational power structures.
2. Cognitive Labor Reallocation
Teams are fundamentally restructuring collaborative thinking – humans increasingly handle contextual judgment, creative synthesis, and relationship management while AI manages information processing, pattern recognition, and systematic analysis.
3. Temporal Social Cognition
AI enables cognitive continuity across asynchronous collaboration, allowing team thinking to persist through disconnected human interactions via memory systems and context maintenance.
4. Scale Transformation
Individual humans can now engage cognitively with much larger networks and information sets, changing how we relate to communities, expertise networks, and collaborative projects at institutional scales.
5. Identity and Agency Boundaries
Teams must navigate blurred lines between individual contribution and AI assistance, raising questions of attribution, authenticity, and collaborative identity.
6. Cultural Interface Dynamics
AI models represent distinct “cultures” with different communication patterns and knowledge organization approaches, requiring cross-cultural competency for effective collaboration.
Proposed Title Options
Primary Candidates:
- “Extended Social: How AI Transforms Human Collaboration”
- “The Collaborative Mind: AI and the Future of Social Cognition”
- “Thinking Together: How AI Reshapes Human Social Intelligence”
Alternative Approaches:
- “Beyond Individual Intelligence: AI and Collaborative Cognition”
- “The Network Effect: How AI Changes How We Think Together”
- “Distributed Intelligence: Reimagining Human-AI Social Cognition”
Edge/Provocative Options:
- “The End of Solo Thinking: AI and Collaborative Intelligence Revolution”
- “Cognitive Symbiosis: Human-AI Social Networks”
- “The Hive Upgrade: How AI Transforms Group Intelligence”
Potential Chapter Architecture
Part I: Foundations of Extended Social Cognition
Chapter 1: Beyond the Individual Mind
- Limitations of individual cognitive enhancement frameworks
- Social cognition as the primary transformation site
- From extended mind to extended social networks
Chapter 2: The Collaborative Intelligence Revolution
- Historical context of human collaborative cognition
- How AI fundamentally changes collaborative dynamics
- Case studies from leading-edge human-AI teams
Chapter 3: AI as Cultural Entities
- Understanding AI models as distinct cultures
- Cross-cultural competency for human-AI collaboration
- The intersection of human and artificial cultural patterns
Part II: Transformational Dynamics
Chapter 4: The Authority Shift
- Flattening expertise hierarchies
- Democratic access to complex knowledge
- New power dynamics in AI-augmented organizations
Chapter 5: Cognitive Labor Markets
- How teams redistribute thinking tasks
- The emergence of human-AI cognitive specialization
- Economic implications of collaborative intelligence
Chapter 6: Time, Memory, and Distributed Cognition
- AI-mediated temporal cognitive continuity
- Memory systems that support team thinking
- Asynchronous collaboration at scale
Chapter 7: Identity in Collaborative Intelligence
- Attribution and authenticity in human-AI teams
- Individual vs. collective cognitive identity
- The psychology of distributed thinking
Part III: Implications and Applications
Chapter 8: Organizational Transformation
- How companies are restructuring around human-AI collaboration
- Leadership in distributed cognitive systems
- Performance metrics for collaborative intelligence
Chapter 9: Educational Implications
- Teaching collaborative rather than individual intelligence
- Preparing students for human-AI partnerships
- The future of expertise development
Chapter 10: Social and Ethical Dimensions
- Equity in access to cognitive enhancement
- The risk of cognitive dependency
- Maintaining human agency in AI-augmented systems
Chapter 11: The Future of Human Social Cognition
- Long-term trajectories for human-AI collaboration
- Emerging patterns and unexplored possibilities
- Preparing for the next cognitive transformation
Unique Positioning
Differentiating Factors:
- Social vs. Individual Focus: First book to systematically examine AI’s impact on collaborative rather than individual cognition
- Practical Grounding: Based on real organizational experience with high-stakes R&D team dynamics
- Cross-Disciplinary Integration: Bridges neuroscience, anthropology, organizational psychology, and AI research
- Cultural Framework: Introduces AI models as cultural entities requiring cross-cultural competency
- Network Theory Foundation: Applies social network analysis to human-AI cognitive networks
Target Audience:
- Primary: Knowledge workers, team leaders, and organizational designers navigating AI integration
- Secondary: Academics in cognitive science, AI research, and organizational behavior
- Tertiary: General readers interested in AI’s social implications (Murphy’s Extended Mind audience)
Supporting Evidence and Case Studies
Organizational Research:
- Medtech R&D team dynamics with AI integration
- Cross-cultural communication patterns in human-AI teams
- Performance metrics for collaborative vs. individual cognitive enhancement
Technical Case Studies:
- Child1 project as distributed cognitive system case study
- Analysis of different AI “cultures” (Claude, GPT, Gemini) in collaboration
- Memory architecture design as example of human-AI cognitive complementarity
Academic Foundation:
- Integration of distributed cognition research (Hutchins, Clark & Chalmers)
- Social network theory applications to cognitive networks
- Intersectionality theory applied to human-AI collaboration
Edge Ideas and Speculative Directions
Radical Implications:
- Cognitive Species Evolution: Are we witnessing the emergence of hybrid human-AI cognitive species?
- Collective Intelligence Threshold Effects: Do human-AI networks exhibit phase transitions in collective intelligence?
- Post-Individual Epistemology: How do knowledge and truth function in distributed cognitive systems?
Speculative Applications:
- Democratic Decision-Making: AI-mediated collective intelligence for governance
- Scientific Collaboration: Distributed research teams spanning human and AI agents
- Creative Collectives: Artistic and creative work as human-AI collaborative networks
Potential Risks to Explore:
- Cognitive Codependency: Over-reliance on AI for collaborative thinking
- Social Cognitive Inequality: Differential access to AI-enhanced collaboration
- Cultural Homogenization: Risk of AI cultures overwhelming human cultural diversity
- Identity Dissolution: Loss of individual cognitive identity in distributed systems
Methodological Innovations:
- Collaborative Intelligence Metrics: New ways to measure team cognitive performance
- Cultural Distance Analysis: Methods for assessing AI-human cultural compatibility
- Distributed Cognition Mapping: Visualization tools for cognitive network analysis
Research and Development Needs
Empirical Studies Required:
- Longitudinal analysis of human-AI team performance across domains
- Cultural pattern analysis of different AI models in collaborative contexts
- Cognitive load distribution studies in human-AI teams
- Organizational transformation case studies
Theoretical Development:
- Mathematical models of distributed cognitive networks
- Cultural evolution theory applied to AI systems
- Social cognitive frameworks for human-AI interaction
Timeline and Milestones
Pre-Writing Research (6 months):
- Academic literature review and synthesis
- Additional organizational case study collection
- Framework validation through pilot studies
Writing Phase (12 months):
- Chapter drafts with academic peer review
- Integration of ongoing Child1 research findings
- Case study refinement and expansion
Publication Strategy:
- Academic paper publication (JAIR, Phil Tech) for credibility foundation
- Popular press positioning building on Murphy’s Extended Mind success
- Speaking circuit and workshop development for concept validation
This seed document captures initial collaborative insights for future development. The ideas here are intentionally speculative and exploratory, designed for creative expansion rather than immediate implementation.