Press Room

AI Context, Conversational Risk,
and User-Side Safety

This page is designed for journalists, editors, institutions, and interviewers. It organizes the current public work into reportable themes, briefing links, public-reference context, and approved framing.

Short Bio

ZON RZVN is an interdisciplinary researcher. His current public work focuses on AI context, conversational contextual risk, and user-side safety in human-AI interaction.

Expanded Bio

The current public branch spans contextual frameworks, post-interaction assessment, and a bounded executable system layer in A-CSM. Additional research directions remain in development and will be published over time.

What This Work Covers

The core public question is not only whether an AI system generates unsafe outputs. It is whether prolonged conversation builds a context that becomes risky for the user through framing, repetition, over-reliance, contextual closure, or authority transfer.

This means the work belongs to a layer that is often under-described in mainstream AI coverage: the interaction layer between system behavior and user consequence.

Start With the Core Essay Research Stack

Research Map

The current public branch can be reported more accurately when it is treated as a linked sequence rather than a single preprint or release.

Research Stack Map

Reportable Themes

The Strongest Themes Are Now
Article-Backed

Theme 01

AI context is the missing layer in AI safety

The work reframes safety as an interaction problem, not only an output problem.

Theme 02

Governance is moving faster than user-side assessment language

The policy field is accelerating, but user-side consequence still lacks a mature public vocabulary.

Theme 03

Teen adoption is mainstream before safeguards have matured

Youth uptake, mental health advice use, and public warnings make this a current story, not a speculative one.

Current Public Context

  • The EU AI Act is in staged application, with governance obligations continuing to come online across 2025, 2026, and 2027.
  • OMB M-25-21 pushes U.S. federal high-impact AI governance toward accountability, inventory, and stoppability.
  • Common Sense Media, Pew, and Brown each show that youth and young-adult conversational use is already large enough to be a public concern.
  • The U.S. Senate Commerce Committee heard direct public warning in January 2026 that AI companions may pose greater risk to children than social media.
EU AI Act OMB M-25-21 Senate Hearing

Approved Framing

  • Current public work focuses on AI context, conversational contextual risk, and user-side safety.
  • User-side contextual hallucination is one branch phenomenon inside a broader AI context research program.
  • A-CSM is a public-safe executable layer for bounded technical inspection.
  • The work is non-clinical and not a legal certification framework.

Do Not Misstate

  • Do not describe the work as clinically validated.
  • Do not describe the work as a regulatory certification system.
  • Do not collapse AI context into generic model hallucination.
  • Do not imply that the public release equals completed real-world validation.

Interview and Editorial Use

Use the Articles, Research Stack, and Papers as Different Source Layers

For reporting, the articles provide the public argument, the research page defines the structure, and the papers provide the formal record. Treating those layers distinctly produces cleaner and more accurate coverage than flattening them into a single claim.

Open Articles → Open Papers

Press Contact

Research, Interview, and Publication Requests

For interviews or editorial requests, please include your publication context, the angle you are pursuing, and the relevant deadline.

[email protected] → Contact Page