Category: Artificial Intelligence
Exploring Approaches to Keep an AI-Enabled Workplace Safe for Workers
Artificial intelligence (AI)—the field of computer science that designs machines to perform tasks that typically require human intelligence—has seen rapid advances leading to cutting‐edge innovations in language, vision, reasoning, and human‐machine collaboration across industries, economies, and labor markets.[1] [2] In the workplace, the adoption of AI technologies can result in a broad range of Read More >
Posted on by Leave a commentAlgorithms and the Future of Work
An algorithm is a series of precise, step-by-step instructions used by a machine to perform a mathematical operation.[1] The use of algorithm-enabled systems and devices will bring many benefits to occupational safety and health but, as with many new technologies, there are also risks to workers. A new commentary in the American Journal of Industrial Read More >
Posted on by Leave a comment100 Million and Counting!
When researchers at the National Institute for Occupational Safety and Health (NIOSH) set out to develop a tool that could improve the use of industry and occupational data from surveys, death certificates and other sources, we could only dream that our efforts would be this successful. A Tool to Advance Research, and It’s Free We Read More >
Posted on by 3 CommentsThe Role of Demographics in the Future of Work
The future of work continues to be shaped by ongoing changes in the workplace, work, and workforce. Shifting workforce demographics will present both opportunities and challenges for occupational safety and health (OSH). A central challenge will be ensuring the equitable distribution of work-related benefits and risks that accompany these transformations. To meet this challenge, Read More >
Posted on by 4 CommentsUsing Machine Learning to Code Occupational Surveillance Data: A Cooperative Effort between NIOSH and the Harvard Computer Society – Tech for Social Good Program
The National Institute for Occupational Safety and Health (NIOSH) depends on surveillance data collected through the occupational supplement to the National Electronic Injury Surveillance System (NEISS-Work) to study and understand nonfatal occupational injuries. Collected through an interagency agreement with the Consumer Product Safety Commission, NEISS-Work captures hospital emergency department-treated occupational injuries to paid, self-employed, Read More >
Posted on by 2 CommentsThe Role of Artificial Intelligence in the Future of Work
As discussed in a previous NIOSH Science Blog, artificial intelligence (AI) is in the process of transforming almost all aspects of society. Whether using an application to determine the best route to drive, receiving recommendations from Netflix on what to watch, or using face detection to logon to a personal smartphone, the use of AI Read More >
Posted on by 6 CommentsArtificial Intelligence Crowdsourcing Competition for Injury Surveillance
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. NAS’s report recommended that the federal government use recent advancements in machine Read More >
Posted on by 16 CommentsArtificial Intelligence: Implications for the Future of Work
What does Artificial Intelligence (AI) have to do with workplace safety and health? NIOSH has been at the forefront of workplace safety and robotics, creating the Center for Occupational Robotics Research (CORR) and posting blogs such as A Robot May Not Injure a Worker: Working safely with robots. However, much remains unknown regarding the related Read More >
Posted on by 65 CommentsAI and Workers’ Comp
The Journal of Occupational and Environmental Medicine just awarded the article “Applying Machine Learning to Workers’ Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities, Ohio, 2001 to 2011” with an Adolph G. Kammer Merit in Authorship Award for the best article published in their journal last year. The article details how researchers used Read More >
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