Technical Insight
Building Anti-Hallucination and Safety Controls for AI Modules
A layered architecture for explicit rules, core constraints, conflict checks, abnormal shutdown, evidence, tools, actions and continuous evaluation.
Direct answer
A sensitive-word list cannot prevent hallucination by itself. Intelligent devices need controls across input, model behavior, knowledge, tools, output and physical action, with degradation or stop behavior for abnormal conditions. LANCUN's Lexicon, Ideological Imprint, Paradox Lock and Deactivation System address different layers, alongside permissions, audit and ongoing evaluation.
Key points
- Model factual errors, unauthorized tools and dangerous actions separately.
- Rules, core policies, conflict checks and abnormal stop need to complement each other.
- Knowledge and tools require provenance, permissions, versions and fallback.
- Measure safety continuously with a versioned test set.
Separate the failure modes
Factual errors, invented sources, persona drift, prompt injection, privacy leakage, incorrect tool parameters and unsafe actions are different problems. Each needs distinct signals, handling and ownership.
Device products must also account for sensor error, network failure and actuator faults rather than attributing every risk to the language model.
Use complementary safety layers
The Lexicon System handles explicit patterns; the Ideological Imprint maintains role, value and task boundaries; the Paradox Lock detects requests or plans that conflict with core rules; the Deactivation System restricts, degrades or stops capability under persistent deviation or high-risk abnormality.
These names describe safety responsibilities. Deployments still combine model policies, rule engines, permissions, version control and human operations.
Constrain knowledge, tools and actions
Retrieved information needs source and time metadata, and answers should communicate uncertainty when evidence is insufficient. Tools require structured parameters, least privilege, confirmation, timeout and audit. Physical actions add edge-side state checks and interlocks.
High-risk domains should provide escalation to people or specialized systems rather than using generated text as the final decision.
Replace one-time acceptance with continuous evaluation
A safety suite should cover normal requests, edge cases, adversarial prompts, long-session drift, tool overreach and action failures, with regression after model, knowledge, rule or supplier changes.
Safety overhead, improvement rates and certification coverage should be tied to test reports and a defined scope. Each deployment still needs its own safety assessment and operating process.