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How AI Can Enhance Incident Investigations & Job Safety Analysis

Safety management systems have helped reduce non-serious injuries, but Serious Injury & Fatality (SIF) incidents are declining more slowly. Identifying potential SIFs (pSIFs) is crucial for recognizing hazards and implementing controls. Discover how Artificial Intelligence (AI) effectively analyzes incident data to identify pSIFs and provides insights into hazards, root causes, and preventive measures.

While addressing pSIFs is an important step in reducing SIFs, this is a reactive approach that relies on incident reporting. Job Safety Analysis (JSA) offers a more proactive method to assess risks, document controls, and identify additional needs. However, JSAs can be time-consuming, require strong hazard recognition skills, and are often subjective. Uncover how AI further enhances the JSA process by identifying overlooked hazards and recommending effective controls, helping organizations better manage and mitigate SIF risks.

Attendees of this session will learn:

• How AI can highlight subtle patterns and connections within incident reports that might otherwise be missed, thus improving the accuracy of pSIF identification.
• Identify three ways that AI can enhance the process of incident and near-miss investigation.
• Explain three benefits of using AI in the JSA process.

Bonus: This session is eligible for CEU credit! Attendees will receive a completion certificate for this 60-minute session, which they can submit to professional associations for credit, including BCPE, BCSP, ABIH, and others.

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