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FT: AI without AGI

PART I — FORESIGHT SNAPSHOT  |  FT: AI without AGI  |  Fixed Time-Stamped Synthesis


2026 FT: AI without AGI

Card Type

Future Technology Possibility

Series

Immersive Futures Guild — Vision 2035

Layer

1 — Atomic Foresight Object

Status

Active

Confidence

Medium

Workshop

Circle of Scholars — January 2026

Facilitator

Circle of Scholars Workshop Team

Tags

narrow-AI  |  AI-capabilities  |  design  |  layer1  |  ft

Tally.so Form

https://tally.so/r/ilrn-if-ft-ainoagi-2026


Narrow AI systems — highly capable at specific tasks but without general intelligence — are already reshaping immersive learning design. This card addresses the practical implications of systems that are powerful but bounded: capable at content generation, adaptive feedback, and learning analytics, while remaining limited in contextual judgment, ethical reasoning, and genuine pedagogical understanding. The mismatch between AI capability perception and AI capability reality is itself a design and governance challenge.

Key Drivers / Contributing Conditions:

  • AI marketing overstating generalization capability

  • Demonstrated brittleness of AI systems outside training distribution

  • Educator overreliance on AI recommendations without critical evaluation

Tensions Carried Forward to Part II:

  • How should educators calibrate their reliance on AI systems whose limitations are systematically underrepresented in marketing?

Linked Scenarios / Strands: SCENARIO: Pragmatic Normalization | STRAND: Human-Centered AI + XR

Ways of Knowing: Tree  ·  Garden  ·  Lantern


PART II — COMMUNITY EVIDENCE & DIALOGUE TRACK  |  FT: AI without AGI  |  H2 2026 — Living


T

COMMUNITY CONTRIBUTION FORM  —  FT: AI without AGI

Submit case examples, methodological challenges, cultural perspectives, and proposed evidence criteria via: https://tally.so/r/ilrn-if-ft-ainoagi-2026


Part II — Scope and Instructions

This section collects community responses, case examples, and challenges to the Part I foresight snapshot above.

It opens July 1, 2026 and undergoes synthesis review in September 2026, November 2026, and January 2027.

Contributions are submitted via the Tally.so form above and appear in the registers below after editorial review.

The Part I text is not modified in response to Part II contributions; it is versioned at the Annual Handoff review.

Contribution categories:  Case Example  |  Methodological Challenge  |  Cultural/Community Perspective  |  Proposed Evidence Criterion

Ways of Knowing accepted:  Tree (evidence)  |  Garden (practice)  |  Lantern (futures)


Tensions Open for Community Response:

  • How should educators calibrate their reliance on AI systems whose limitations are systematically underrepresented in marketing?


Contributor / Date

Category

Way of Knowing

Contribution Summary

[ Awaiting contributions — form opens July 1, 2026 ]




 

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