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By Sydney Webb, PhD; Carlos Siordia, PhD; Stephen Bertke, PhD; Diana Bartlett, MPH, MPP; and Dan Reitz

In 2018, NIOSH, the Bureau of Labor Statistics (BLS), and the Occupational Safety and Health Administration (OSHA) contracted the National Academies of Science (NAS) to conduct a consensus study on improving the cost-effectiveness and coordination of occupational safety and health (OSH) surveillance systems. NASs report recommended that the federal government use recent advancements in machine learning and artificial intelligence (AI) to automate the processing of data in OSH surveillance systems.

The main source of OSH information on fatal and non-fatal workplace incidents comes from the unstructured free-text injury narratives recorded in surveillance systems. For example, an employer may report an injury as worker fell from the ladder after reaching out for a box. For decades, humans have read these injury narratives to assign standardized codes using the U.S. Bureau of Labor Statistics (BLS) Occupational Injury and Illness Classification System (OIICS). Coding these injury narratives to analyze data is expensive, time consuming, and fraught with coding errors.

AI, namely machine learning text classification, offers a solution to this problem. If algorithms can be developed to read the injury narratives, data can be pulled from these surveillance systems in a fraction of the time of hand coding.

NIOSH developed an AI algorithm to apply OIICS codes based on injury narratives from a hospital emergency department surveillance system. However, the efficiency of this algorithm was not clear. To see if better coding algorithms could be developed, NIOSH turned to crowdsourcing.

While not unique to AI, crowdsourcing involves asking the crowd or people in the public with a variety of skill sets to provide their unique solution to a problem. The approach results in a large number of potential solutions that can be assessed to identify those that work best. Generally, the best crowd solutions are better than the original solution. In this case, NIOSH worked with two crowds one internal to CDC and one external to CDC to propose better solutions to NIOSHs initial coding algorithm.

Courtesy of NIOSH

Before conducting an external competition, a team of 17 researchers from NIOSH, the Centers for Disease Control and Prevention (CDC), BLS, OSHA, the Federal Emergency Management Administration (FEMA), the Census Bureau, the National Institutes of Health (NIH)7, and the Consumer Products Safety Commission hosted a competition for staff at CDC. A total of 19 employees competed to develop the best algorithm to code worker injury narratives. The team received nine algorithms, five of which outperformed the NIOSH baseline script, which had an accuracy of 81%. The internal crowdsourcing competition winning algorithm was 87% a 6% improvement.

In October 2019, NIOSH, together with National Aeronautics and Space Administration (NASA), hired a Tournament Lab vendor, Topcoder, to host the external crowdsourcing competition. This was the first-ever external crowdsourcing competition from CDC and NIOSH, which was partially funded through the CDC Innovation Fund Challenge. The competition accessed Topcoders global community of data science experts to develop a Natural Language Processing (NLP) algorithm to classify occupational work-related injury records according to OIICS.

Like the internal competition, the external competition was also a success. There were 961 submissions from 388 registrants representing over 26 countries (32% United States, 21% India). Those participating self-identified as having degrees in computer science and engineering, chemistry, computer engineering, computer science, data science, and economics to name a few. This competition produced 21% more registrants and 66% more submissions than the average Topcoder competition. The high-quality submissions achieved nearly 90% accuracy, which surpassed the 87% accuracy goal achieved during the internal competition.

The 1st place external crowdsource winner was Raymond van Veneti, who is a doctoral student in numerical mathematics at the University of Amsterdam. Second place was awarded to a senior data scientist at Sherbank AI lab in Russia; 3rd place was awarded to a developer and data scientist from China; 4th place was awarded to a biostatistician at the School of Medicine at Emory University in Atlanta, GA; and 5th place was awarded to a full stack engineer from Bangalore, India.

External crowdsource 1st place winner Raymond van Veneti.Courtesy of NIOSH

The external competition and the resulting algorithm support improving efficiency and reducing costs associated with coding occupational safety and health surveillance data. Ultimately, it is hoped that the improved algorithm will contribute to greater worker safety and health. The NIOSH project team will work with the 1st prize winners script to make an easy-to-use web tool for public use. In the interim, the top 5 winning solutions are available on GitHub.

For more information, visit https://blogs.cdc.gov.

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Artificial Intelligence Crowdsourcing Competition for Injury Surveillance - EC&M

Updated: May 25, 2018:

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Artificial Intelligence is Starting to Shape the Future of the Workplace - JD Supra

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Related read: 5 decisions CEOs need to make in 2020 for embracing technologies faster

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Artificial Intelligence + Robotic Process Automation: The Future of Business - Wire19

Artificial Intelligence, is the Future of Human Resources

Artificial intelligence AI takes the lead over intelligent automation IA. Intelligent automation is the combination of robotic process automation and artificial intelligence to automate processes, according to a recent article on the topic in HR Dive, a publication for human resources professionals. Organizations that embrace intelligent automation may experience a return on investment of 200% or more, according to an Everest Group report cited by HR Dive. However, that doesnt mean organizations can expect a reduction in headcount, according to the report. In fact, projections of a reduction in workforce thanks to intelligent automation may be highly exaggerated, the Everest Group noted.

The Everest Group identified eight companies it called Pinnacle Enterprises companies distinguished by their advanced intelligent automation capabilities and their superior outcomes. These companies generated about 140% ROI and reported more than 60% cost savings, thanks to artificial intelligence and intelligent automation. The companies the Everest Group identified as Pinnacle Enterprises also experienced a 67% improvement in operational metrics, compared to the 48% improvement reported by other organizations. The Pinnacle Organizations also experienced improvements in their top lines, time-to-market, and customer and employee experiences as a result of using artificial intelligence and intelligent automation in their businesses, according to the Everest Group report.

Technology, particularly artificial intelligence, and now, intelligent automation, is infiltrating businesses little by little, particularly in the human resources space. In fact, artificial intelligence in HR has been cited as a top employee benefits trend for 2020. Its a trend employers would do well to pay attention to, especially since cost savings and ROI seem to be significant potential positive outcomes of adopting such technologies.

Technology such as artificial intelligence and intelligent automation makes human resources more efficient. According to a Hackett Group report from 2019, HR in organizations that leverage automation technology can do more with fewer resources an important distinction in a department thats often considered the heart of an organization, and that typically has more work than staff to complete it. In addition, the utilization of artificial intelligence and intelligent automation are hallmarks of a distinguished organization. Per the Hackett Group data, cited by HR Dive, world-class HR organizations leverage [artificial intelligence] and, as a result, have costs that are 20% lower than non-digital organizations and provide required services with 31% fewer employees.

Despite the apparent benefits, not everyone is a fan of automated technologies such as artificial intelligence and intelligent automation. Professors at the Wharton School of the University of Pennsylvania and ESSEC Business School, an international higher education institution located in France, Singapore and Morocco, cautioned employers about the potential downsides of using artificial intelligence and intelligent automation in human resources functions. Specifically, they warned that artificial intelligence could create problems for human resources because its unable to measure some HR functions and infrequent employee activities because they generate little data, can solicit negative employee reactions and isconstrained by ethical and legal considerations. However, human resources professionals are finding some success in using artificial intelligence and intelligent automation to perform functions such as searching through resumes for keywords and assisting with other recruiting functions, for example.

Despite the concerns of some, its likely that artificial intelligence and intelligent automation will continue to command a presence in human resources. As such, automation will prompt organizations to make a heftier investment in talent, noted a study byMIT Sloan Management Review and Boston Consulting Groups BCG GAMMA and BCG Henderson Institute. The study found that employers who successfully embrace artificial intelligence and intelligent automation will build technology teams in-house and rely less on external vendors. Theyll also poach artificial intelligence talent from other companies and upskill current employees to be on the front lines of the automation movement. Artificial intelligence and intelligent automation is here to stay, and its only getting more pervasive, especially in human resources and employee benefits. Employers should be ready.

Steff C. Chalk is Executive Director of The Retirement Advisor University, a collaboration with UCLA Anderson School of Management Executive Education. Steff also serves as Executive Director of The Plan Sponsor University and is current faculty of The Retirement Adviser University.

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Artificial Intelligence, is the Future of Human Resources. - 401kTV