A primer on machine learning and its potential applications in EHS

Description

Current and future occupational environmental health and safety (OEHS) professionals should embrace AI tools and methodologies for two reasons. First, such tools and methodologies will lessen the burden of manual data entry and simple data interpretation tasks thereby providing more time for OEHS professionals to engage with workers. Second, such tools and methodologies will benefit workers by allowing them to be more informed of their workplace hazards and empower them to be stakeholders in OEHS. This session will introduce machine learning, a subset of artificial intelligence, and propose ways that machine learning can be applied to mitigate OEHS hazards.

Learning Objectives

1. Describe artificial intelligence and its subsets
2. Distinguish between supervised and unsupervised machine learning
3. Identify AI resources for OEHS professionals

Mwangi Ndonga, CIH, CSP, CHMM

Mwangi Ndonga, CIH, CSP, CHMM is enthusiastic about embracing artificial intelligence tools aimed at reducing occupational injuries and illnesses. He is Chair of the AIHA Technology Initiatives Strategic Advisory Group and past Secretary of the Society for Total Worker Health (2023).