Whose voice and judgment?
Students, educators, researchers and affected participants may contribute purposes, experiences, interpretations and objections. Their roles and authority should be identified rather than collapsed into the word “user.”
PhygitAi | Beyond Phygital · Educational development
UAiPN User–AI Participation & Negotiation
A proposed educational framework under development for examining how learners and educators participate critically with AI, question its contributions, negotiate alternatives and reach reasoned decisions while preserving independent human judgment.
UAiPN is being developed within the ongoing PhygitAi research initiative initiated by Abbas Sibai, Ph.D. It draws on existing participatory design, human–AI interaction, AI education and negotiation research. Its procedure, educational usefulness and distinct contribution still require methodological comparison and classroom evaluation.
Working educational proposal
Procedure under author review
Empirical evaluation not completed
Purpose and boundaries
Participation is more than using AI. Negotiation is more than prompting.
UAiPN is intended to make the educational process of disagreement, critical evaluation and justified revision visible. It does not treat AI as a person, a moral stakeholder or an equal decision authority.
What did AI contribute?
AI may offer explanations, alternatives or critiques. Such outputs require examination of their basis, uncertainty and influence. A contribution is not an authorization or a demonstrated fact.
How is disagreement handled?
Learners can challenge, revise or refuse AI proposals and explain why. Negotiation here means a structured critical exchange, not an assertion that AI and humans possess equal rights or responsibility.
UAiPN is not a replacement for participatory design, human-centered AI, classroom pedagogy or the PhygitAi Six Gates and Intention–Behavior Record. Its intended educational function must be evaluated against established methods.
Methodological development · Candidate learning sequence
A working structure for educational inquiry.
These six activities are proposed design work for discussion and testing. They are not six newly approved PhygitAi Gates, a prescribed classroom sequence or a validated learning intervention. Educators may revisit activities according to the learning objective.
State what you think.
Develop an initial interpretation, intention or design response. Distinguish existing knowledge from assumptions before AI assistance.
Bound AI's role.
Specify the task, the requested contribution and what the AI is not being authorized to decide.
Question the output.
Examine evidence, source quality, uncertainty, omissions and disagreement with the learner's own position.
Explore alternatives.
Challenge AI suggestions, compare competing interpretations and revisit assumptions without treating fluent responses as authority.
Decide and justify.
Accept, adapt or reject an option. Explain the human rationale, remaining uncertainty and any required verification.
Show what was learned.
Reconstruct the reasoning and demonstrate understanding beyond the immediate AI-assisted exchange; revisit the decision if later evidence requires it.
The educational record should be proportionate. It may note an initial position, AI contribution, challenge, decision and reflection. The existing seven-field IBR remains the relevant PhygitAi instrument when a consequential design decision needs a trace; UAiPN does not silently add another formal IBR field.
Book III · Teaching, learning and research
An educational application within PhygitAi.
UAiPN is proposed for development and investigation first through design education, with possible later interdisciplinary adaptation. It relates to Book III's three inquiry horizons and its emphasis on independent competence, authorship, evidence and critical judgment.
AI-free · AI-supported · AI-primary
The instructor selects a condition appropriate to the learning aim. Independent work can establish a reference point; AI-supported work can make critical exchange observable. More AI use is not automatically better learning.
Designing with Intelligence
Investigate how AI influences research questions, ideation, interpretation, criticism and design choices, while learners retain responsibility for their judgments.
Designing for Intelligence
Examine how a proposed product's AI behavior, permissions and capacity for user intervention can be questioned and revised through design inquiry.
What an educator could examine
- Can learners explain their initial thinking independently?
- Can they identify what AI contributed and which claims require verification?
- Can they disagree with AI and justify a refusal or revision?
- Can they explain their final decision and demonstrate understanding beyond the tool?
These are candidate assessment questions, not proven learning outcomes. Any study involving students would require appropriate institutional arrangements, consent and ethical safeguards. See the Book III overview.
Established knowledge · Necessary comparison
The questions have precedents. UAiPN's contribution remains open.
Participation, negotiated interests, human–AI collaboration and educational agency are established research topics. The acronym UAiPN does not by itself demonstrate a distinct scientific or pedagogical method.
McGregor (2022)
Examines interfaces for expressing stakeholder interests and negotiating trade-offs in AI systems.
Curhan & Gratch (2026)
Distinguishes AI's roles in negotiation across teaching, research and implementation.
UNESCO (2024)
Outlines human-centered, ethical and creative AI competencies for students and teachers.
These sources are intellectual predecessors, not PhygitAi or UAiPN endorsements. Comparison should examine purpose, actual classroom function, learning records, workload and evidence—not labels alone.
Development roadmap · November 2026
From working proposal to teachable, testable practice.
| Development item | Current position |
|---|---|
| Definition and intended educational purpose | Proposed for review within PhygitAi |
| Methodological boundaries and comparisons | To be developed and critically examined |
| Educator guide, exercises and interactive tool | Planned; no released UAiPN tool is claimed |
| Classroom pilot and comparative evaluation | Not yet conducted |
The existing PhygitAi Toolkit and public platform editions support selected screening and studio inquiry workflows. They do not yet implement a separately tested UAiPN procedure. This page documents a proposed development direction, not a downloadable or accredited course.