SSRN 6573518
Learning Model Orchestration: Beyond Personalization in the Age of AI
Proposes LMO — intentional selection, sequencing, and combination of learning models when knowledge scarcity gives way to learning model scarcity.
SSRN · 6 papers
SSRN 6573518
Proposes LMO — intentional selection, sequencing, and combination of learning models when knowledge scarcity gives way to learning model scarcity.
SSRN 6535458
Develops ALT as a framework for latency as a structural, distributive externality — invisible, cumulative, and unevenly borne across users and contexts.
SSRN 6534959
Argues that under generative abundance, value completes through human judgment — selection, validation, adoption, and accountability — not at the moment of generation.
SSRN 6536198
Advances the motivational reweighting thesis — generative AI redistributes creative motives rather than replacing them, with expression-weight restoration in low-stakes creation.
SSRN 6534580
Introduces Expression Distortion Cost (EDC) and Self-Alignment Load (SAL), developing an Authenticity–Cost Model for user-side interaction quality.
SSRN 5401725
Introduces the AI Waiting Tax (AWT) — the psychological and cognitive burdens of waiting for AI responses, foregrounding idle time as a hidden cost of AI-mediated interaction.