8 papers
The Behavioral Credibility Trilemma: When Calibrated Autonomy Becomes Impossible
Lauri Lovén, Nam Do, Hassan Mehmood +2
We prove that no reinforcement learning policy with confidence-gated autonomy can simultaneously achieve maximum helpfulness, optimal calibration, and full autonomy under rational…
Neural Router: Semantic Content Matching for Agentic AI
Lauri Lovén, Abhishek Kumar, Alexander Engelhardt +5
Large language models (LLMs) can serve as the semantic-matching engine of a content-based publish/subscribe broker for agentic AI across the edge-cloud computing continuum, bridgin…
AI-Augmented Science and the New Institutional Scarcities
Lauri Lovén
Artificial intelligence now produces convincing-looking scientific judgment (reviews, rankings, attributions, verifications) at almost no marginal cost. An influential reading of A…
Institutions for the Post-Scarcity of Judgment
Lauri Lovén
Each major technological revolution inverts a particular scarcity and rebuilds institutions around the shift. The near-consensus diagnosis of the AI revolution holds that AI collap…
The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting
Lauri Lovén, Sasu Tarkoma
Eliciting truthful reports from autonomous agents is a core problem in scalable AI oversight: a principal scores the agent's report using a strictly proper scoring rule, but the ag…
Honest Reporting in Scored Oversight: True-KL0 Property via the Prekopa Principle
Lauri Lovén
We prove the True-KL property for a parametric family of heterogeneous scoring rules arising in scored elicitation mechanisms (AI oversight, forecasting, expert surveys). An ag…