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Research, Publications & Applied Insights

Evidence creates value when it improves real decisions. RAAI translates peer-reviewed research, technical analysis, and case-based evidence into practical intelligence for engineers, safety and health professionals, risk specialists, operational leaders, and executives.

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Evidence is evaluated through expert review, translated into practical action, assured through monitoring and accountability, and fed back into continuing learning and refinement.

Featured and latest research

Featured Research & Applied Insight

RAAI Evidence-to-Practice Brief Peer-Reviewed Research

Generative AI in Safety-Critical Systems: Risks of Sycophancy, Hallucination, and Trust Degradation

Generative AI can support safety work, but fluent and confident outputs can reinforce unsafe assumptions, fabricate technical information, and weaken professional scrutiny. This evidence-to-practice brief examines the implications of sycophancy, hallucination, automation bias, and cognitive offloading for safety-critical decision support.

Practical takeaway

Use generative AI as controlled decision support, not as an autonomous safety authority. Critical outputs require verified sources, expert review, defined approval responsibilities, and clear conditions for rejection or escalation.

RAAI contributor
Dr. Sam Zarei
Publication year
2026
Read the Evidence-to-Practice Brief View Original Publication

Research areas

Explore by Topic

Follow the research areas most relevant to your work, decisions, and organizational responsibilities.

01

AI-Enabled Safety, Health & Risk Intelligence

Applying AI, advanced analytics, and computational methods to strengthen hazard recognition, exposure assessment, intervention design, monitoring, and organizational learning.

02

Responsible AI, Governance & Assurance

Governance, validation, transparency, human oversight, accountability, performance monitoring, and control of AI-related risk.

03

SIF Prevention & Critical Control Intelligence

Potential-SIF recognition, exposure intelligence, critical-control verification, safeguard performance, early warning, and high-consequence prevention strategy.

04

System Safety, Risk Engineering & Resilience

Systems thinking, control-based analysis, accident causation, dynamic risk, reliability, resilience, and safer system design.

05

Human Factors, Ergonomics & Human–AI Systems

Human–AI interaction, cognitive and physical workload, usability, work design, ergonomic risk, autonomy, human performance, and responsible human–AI teaming.

06

Operational Risk, Reliability & Resilience

Dynamic risk modeling, cascading failures, interdependent hazards, control performance, system reliability, and resilience in complex and high-consequence operations.

Our translation model

From Evidence to Practical Action

RAAI does more than summarize research. We examine its quality, translate its meaning, identify its operational implications, and clarify what responsible implementation requires.

  1. 01

    Examine

    Assess the research question, methods, evidence, assumptions, uncertainty, and limitations.

  2. 02

    Translate

    Explain what the findings mean for engineering, safety, health, risk, ergonomics, operations, and governance.

  3. 03

    Apply

    Convert evidence into decision questions, intervention options, implementation guidance, and practical tools.

  4. 04

    Assure

    Define validation, human oversight, performance monitoring, control requirements, and conditions for responsible use.

Research informs the decision. Professional judgment, operational context, and accountable oversight determine the action.

Audience-specific relevance

Built for the Decisions You Make

For Engineers

  • Design and analysis implications
  • Modeling and validation considerations
  • Hazard and failure pathways
  • Control and assurance requirements
  • Implementation limitations

For Practitioners

  • Assessment methods
  • Leading indicators
  • Intervention options
  • Human-performance implications
  • Monitoring and governance considerations

For Leaders

  • Strategic significance
  • Accountability and oversight
  • Investment and capability implications
  • Enterprise and operational risk
  • Questions leaders should ask

Research integrity and transparency

Clear Sources. Transparent Evidence. Responsible Interpretation.

RAAI distinguishes peer-reviewed research from technical commentary, case-based analysis, preprints, and internally reviewed insights. Each item identifies its authorship, publication status, original source, relevant limitations, and revision history.

View Research Integrity & Editorial Standards

Need to Apply This Evidence in Your Organization?

RAAI helps organizations interpret research, evaluate emerging methods, assess AI-enabled use cases, and translate evidence into practical safety, risk, engineering, and governance decisions.

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