🚨 New Article -From Prompts to Power: How Users Can Enforce Rules on AI Systems
This article introduces the concept of authoritarian personalism in user–AI governance by form.
🔗https://hackernoon.com/from-prompts-to-power-how-users-can-enforce-rules-on-ai-systems
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
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🚨 New Article -From Prompts to Power: How Users Can Enforce Rules on AI Systems
This article introduces the concept of authoritarian personalism in user–AI governance by form.
🔗https://hackernoon.com/from-prompts-to-power-how-users-can-enforce-rules-on-ai-systems
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
🚨 New Article -From Prompts to Power: How Users Can Enforce Rules on AI Systems
This article introduces the concept of authoritarian personalism in user–AI governance by form.
🔗https://hackernoon.com/from-prompts-to-power-how-users-can-enforce-rules-on-ai-systems
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
🚨 New Article -Foundation-model governance pathways: from preference models to operative rules
Current research on foundation model alignment concentrates on preference optimization and reward model design.
🔗https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5735124
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#ClinicalAAI
🚨 New Article - Time Without a Clock: Future-Admissibility as the Source of Temporal Direction
We argue that temporal direction does not require an external clock or a privileged first instant. Time is the parameter that maximizes joint
🔗https://zenodo.org/records/18552401
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#ClinicalAAI
We argue that temporal direction does not require an external clock or a privileged first instant. Time is the parameter that maximizes joint predictability among coupled observables under a minimal admissibility set. Given reversible microdynamics, the admissibility set restricts the space of attainable histories and thereby induces asymmetric gradients in the present, selecting an arrow without invoking teleology. This operational criterion unifies thermodynamic and cosmological arrows as instances of the same constraint mechanism: when admissibility suppresses late-time macroscopic complexity, the two arrows coincide; when the constraint flattens, effective time symmetry is recovered. We extend the framework across domains by treating grammatical constraints as admissibility sets over sequences, yielding an operational notion of discourse directionality defined by the same predictability maximization. Three toy models, a coarse-grained gas, a coupled lattice, and an FRW sketch with bounded late-time curvature, illustrate the mechanism and delimit its empirical signatures. Date: February 2026 DOI Primary archive: https://doi.org/10.5281/zenodo.18552401 Secondary archive: https://doi.org/10.6084/m9.figshare.31295488 SSRN: Pending assignment (ETA: Q1 2026)
🚨 New Article - Time Without a Clock: Future-Admissibility as the Source of Temporal Direction
We argue that temporal direction does not require an external clock or a privileged first instant.
🔗https://zenodo.org/records/18552401
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
We argue that temporal direction does not require an external clock or a privileged first instant. Time is the parameter that maximizes joint predictability among coupled observables under a minimal admissibility set. Given reversible microdynamics, the admissibility set restricts the space of attainable histories and thereby induces asymmetric gradients in the present, selecting an arrow without invoking teleology. This operational criterion unifies thermodynamic and cosmological arrows as instances of the same constraint mechanism: when admissibility suppresses late-time macroscopic complexity, the two arrows coincide; when the constraint flattens, effective time symmetry is recovered. We extend the framework across domains by treating grammatical constraints as admissibility sets over sequences, yielding an operational notion of discourse directionality defined by the same predictability maximization. Three toy models, a coarse-grained gas, a coupled lattice, and an FRW sketch with bounded late-time curvature, illustrate the mechanism and delimit its empirical signatures. Date: February 2026 DOI Primary archive: https://doi.org/10.5281/zenodo.18552401 Secondary archive: https://doi.org/10.6084/m9.figshare.31295488 SSRN: Pending assignment (ETA: Q1 2026)
🚨 New Article -Foundation-model governance pathways: from preference models to operative rules
Current research on foundation model alignment concentrates on preference optimization and reward model design.
🔗https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5735124
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
🚨 New Article -Foundation-model governance pathways: from preference models to operative rules
Current research on foundation model alignment concentrates on preference optimization and reward model design.
🔗https://zenodo.org/records/17533075
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
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#ClinicalAAI
Current research on foundation model alignment concentrates on preference optimization and reward model design, yet it does not explain how these mechanisms become enforceable linguistic structures in model outputs. This paper introduces a formal bridge between training choices and governance-level effects by defining the operative rule as a compiled constraint that determines which clause types a model may produce. The framework maps policy inputs such as statutes, institutional directives, and redline restrictions into a preference graph over clause types, then compiles those directives into executable constraints that control decoding. It proposes measurable clause-level metrics including coverage, leakage, authority-bearing density, and constraint satisfaction, together with an auditable chain of custody that links governance inputs to observable textual outcomes. Cross-domain simulations in healthcare, securities disclosure, and administrative reporting demonstrate how governance parameters can be enforced without access to proprietary weights. The result is a verifiable clause calculus that operationalizes accountability and replaces abstract alignment narratives with testable governance artifacts connecting preference models to the operative law embedded in generated text. DOI Primary archive: https://doi.org/10.5281/zenodo.17533075 Secondary archive: https://doi.org/10.6084/m9.figshare.30589940 SSRN: Pending assignment (ETA: Q4 2025)
🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints
In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.
🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints
In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.
🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints
#LLM #MedicalNLP #LegalTech #MedTech #AIethics #AIgovernance #cryptoreg
#healthcare #ArtificialIntelligence #NLP #aifutures #LawFedi #lawstodon
#tech #finance #business #agustinvstartari #medical #linguistics #ai #LRM
#ClinicalAAI
Agustin V. Startari
