Every day, work-related injury records are generated. The National Institute for Occupational
Safety and Health (NIOSH), part of the Centers for Disease Control and Prevention (CDC), recently
announced the start of an external crowdsourcing competitionexternal icon?, exploring the use of
artificial intelligence (AI) to automate data processing in occupational safety and health surveillance
systems.

Currently, whenever an employee is injured at work, an explanation of how the injury occurred is recorded
by a person using free-text narratives, or rather, free form. For decades, humans have then read these
injury narratives and assigned codes to classify the injuries, often large volumes of information, which
has resulted in time, cost and the risk of human error influencing occupational safety and health data.

Through an interagency agreement with the National Aeronautics and Space Administration (NASA)'s Tournament
Lab, NIOSH is working with vendor TopCoder to host this online competition, asking programmers to compete
in the development of an algorithm that will best employ the use of AI in automatically reading injury
records and classifying them according to the Occupational Injury and Illness Classification System (OIICS).

The National Institute for Occupational Safety and Health (NIOSH)

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