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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