{"schema_version":1,"assessment_id":"eoa_inverse_innovation_exp03_opportunity320_20260801","source_experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"negative_space_design__tech_ethics_ai_governance","archetype_slug":"negative_space_design","domain_slug":"tech_ethics_ai_governance","title":"Protected negative-space format for AI deployment review","opportunity_summary":"Test whether a reversible, sparse primary review surface, an interpretation interval, chair-held silence, explicit absence labels, and immediate retrieval of omitted material improve detection of unresolved AI hazards and articulation of dissent relative to a conventional review packet. The proposed effect, problem prevalence, and distinctiveness remain unverified hypotheses.","adopter_authorizer":"The AI governance chair can authorize a non-production shadow-format simulation; the established approval body retains authority over deployment decisions and policy changes.","scores":{"meaningful_impact":{"score":4,"rationale":"If the stated failure occurs, preventing missed high-severity hazards, misread evidence gaps, and suppressed objections could materially improve accountable deployment decisions. The packet does not establish how often the failure occurs or the realized effect size."},"stakeholder_pull":{"score":2,"rationale":"Reviewers, dissenters, exposed groups, and approval bodies have plausible interests in more reliable review, but the sealed candidate contains no interviews, requests, adoption commitments, observed demand, or prevalence evidence."},"incremental_advantage":{"score":3,"rationale":"The composition adds protected interpretation time, chair-held silence, labeled evidence absence, and recoverable omission beyond the named risk-ranking dashboard rival. Whether these features outperform ordinary facilitation or expert review is untested."},"distinctiveness_plausibility":{"score":3,"rationale":"The combined use of bounded omission, protected silence, explicit absence states, and immediate retrieval is structurally specific, but prior art is unsearched and the packet cannot establish novelty or uncommonness."},"technical_implementability":{"score":4,"rationale":"A synthetic or de-identified crossover simulation can be implemented with review templates, controlled case materials, retrieval controls, panel procedures, and outcome coding. Accessibility and faithful preservation of context require deliberate design but no speculative technology."},"adoption_authority_feasibility":{"score":4,"rationale":"The candidate identifies an AI governance chair who can authorize a shadow test and reserves production and policy authority for the established approval body. Actual willingness, procurement constraints, and institutional permissions remain unknown."},"evidence_readiness":{"score":4,"rationale":"The packet specifies a comparator, measurable outcomes, problem and intervention falsifiers, excluded actions, and halt conditions. Case construction, meaningful-effect thresholds, coding reliability, recruitment, and analysis procedures still need prespecification."},"safety_net_benefit":{"score":4,"rationale":"The intervention targets premature approval by making unresolved hazards, ambiguous absence, and dissent more salient while retaining immediate access to the complete record. It could instead hide dependencies or pressure lower-power participants, so benefit must be demonstrated under explicit stopping rules."},"scalability":{"score":3,"rationale":"Templates, absence labels, timed review beats, and retrieval mechanisms could be replicated across panels, but their effects may depend on case complexity, governance culture, accessibility needs, chair behavior, and power relations."}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"50K_TO_250K","scope":"Design and run a bounded crossover simulation with synthetic or de-identified cases, conventional and negative-space formats, recruited panels, participant support, accessibility checks, outcome coding, statistical analysis, and an adverse-effect review.","confidence":"MODERATE","assumptions":["A small multi-panel study is sufficient for an initial decision rather than definitive validation.","Usable synthetic or de-identified cases can be prepared without purchasing a large proprietary dataset.","Costs include governance staff, research design, facilitation, participant time, accessibility work, analysis, and reporting.","No result affects a live deployment decision."]},"initial_deployment_startup":{"band_2026_usd":"50K_TO_250K","scope":"After favorable evidence, adapt one organization's review templates, absence taxonomy, retrieval controls, facilitation protocol, accessibility safeguards, audit trail, and training for a limited shadow workflow.","confidence":"LOW","assumptions":["The organization already has an AI review body and document-management infrastructure.","Deployment remains shadow-mode until separately authorized.","No major platform rebuild or regulatory approval program is required.","Legal, compliance, affected-party, and accessibility review are included."]},"operational_launch":{"band_2026_usd":"250K_TO_1M","scope":"Launch the validated format across multiple review panels or business units, including workflow integration, facilitator training, quality assurance, change management, independent evaluation, monitoring, and rollback capability.","confidence":"LOW","assumptions":["Launch covers one medium-to-large organization rather than an industry-wide program.","Existing governance and records systems can be configured rather than replaced.","Complete evidence remains immediately retrievable and auditable.","The range allows for coordination across risk, compliance, model-owner, accessibility, and affected-party functions."]},"annual_recurring":{"band_2026_usd":"50K_TO_250K","scope":"Maintain templates and retrieval controls, train chairs and reviewers, audit omissions and absence labels, monitor adverse effects and decision quality, support accessibility, and periodically revalidate the format.","confidence":"LOW","assumptions":["The process is used by several panels within one organization.","Monitoring can be incorporated into an existing AI governance function.","Recurring expense excludes major platform replacement and external regulatory proceedings.","Periodic sampling is adequate rather than review of every meeting by an independent evaluator."]}},"research_burden":"MODERATE","earliest_credible_horizon":"3_TO_12_MONTHS","pipeline_gates":{"recognizable_externally_supportable_problem":{"status":"UNCERTAIN","reason":"The candidate defines observable failure states and a clear falsifier, but supplies no external or baseline evidence that crowded review materials, chair commentary, ambiguous blanks, or suppressed dissent cause consequential review errors in the intended setting."},"identifiable_adopter_or_authorizer":{"status":"YES","reason":"The AI governance chair is identified as the authorizer for a shadow-format test, while the established approval body retains production and policy authority."},"distinct_testable_incremental_claim":{"status":"YES","reason":"The proposal claims that recoverable subtraction, a protected interpretive interval, chair-held silence, and explicit absence labels will improve hazard detection, absence interpretation, and dissent relative to a conventional packet; the crossover comparison can falsify that claim."},"bounded_next_evidence_step":{"status":"YES","reason":"A non-production crossover simulation with synthetic or de-identified cases, a conventional-format comparator, specified outcomes, adverse-effect measures, and rollback conditions is explicitly authorized."},"no_unresolved_safety_or_authority_stop":{"status":"YES","reason":"The first step cannot control deployment, excludes hiding required evidence or coercing speech, preserves retrieval, and stops for missed critical context, retrieval or accessibility failure, misread absence, distress, or power-based pressure."},"implementation_cost_scope_and_range":{"status":"YES","reason":"The proposed simulation and possible organizational rollout can be bounded into case preparation, facilitation, participant time, workflow configuration, compliance, accessibility, evaluation, training, monitoring, and retrieval controls, with broad resource-equivalent ranges stated under explicit assumptions."}},"blocking_evidence":["Baseline evidence that intended review panels materially miss or misclassify unresolved high-severity hazards, misunderstand empty evidence fields, or fail to articulate dissent under conventional review conditions.","Crossover evidence that the negative-space format produces a decision-relevant improvement over the conventional format in hazard detection, absence interpretation, or dissent.","Evidence that omitted context remains complete, auditable, immediately retrievable, and accessible without creating material retrieval delay or missed dependencies.","Evidence that protected silence does not create distress, imply consent, or intensify power-based pressure on lower-authority participants.","Prior-art comparison establishing whether the combined format offers a meaningful incremental distinction from existing governance review and facilitation practices."],"next_evidence_step":"Run a preregistered, non-production crossover simulation using matched synthetic or de-identified AI deployment cases. Randomize review order so each panel assesses one conventional packet and one negative-space packet; compare prespecified rates of unresolved-hazard detection, correct classification of absent evidence, independently articulated dissent, omitted-context retrieval success and delay, decision time, overconfident approval, accessibility failure, and participant distress. Falsify advancement if there is no meaningful gain in the primary decision-quality outcomes or if missed context, retrieval failure, distress, accessibility loss, or overconfident approval increases.","research_questions":["Do baseline panels reliably detect and classify unresolved high-severity risks despite packet crowding and chair speaking time?","Which component—recoverable subtraction, protected interpretation, chair-held silence, or explicit absence labeling—accounts for any observed effect?","What minimum effect size in hazard detection, absence interpretation, or dissent would justify added process burden?","Can reviewers retrieve all omitted dependencies quickly enough to preserve completeness and auditability?","How do hierarchy, facilitation style, accessibility needs, case complexity, and reviewer expertise modify benefits or harms?","Does sparse presentation increase perceived evidentiary completeness or overconfident approval even when absence labels are present?","How does the combined design overlap with existing AI governance review, red-team, pre-mortem, silent-review, and dissent-elicitation formats?"] ,"recommendation":"PARTNERED_RESEARCH","uncertainty_constraints":["No external sources were consulted under the closed-book constraint.","Problem prevalence, stakeholder demand, realized impact, adoption willingness, and market size are unsupported by the packet.","Causal effectiveness is hypothetical and has not been demonstrated in simulation or practice.","World novelty and incremental distinctiveness cannot be established because prior art has not been searched.","Cost bands are resource-equivalent planning ranges, not quotes or point estimates.","Generalization across organizations, jurisdictions, risk classes, accessibility needs, and power structures is unknown."],"closed_book_prior_art_boundary":"Prior art is unsearched and unverified. This closed-book assessment makes no claim about novelty, prevalence, existing implementations, market position, or superiority over practices beyond the single rival described in the sealed candidate."}