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If you are new to artificial intelligence or you want to understand some AI fundamentals, including how large language models (LLM) work, check out this AI primer from primerli. The free course discusses AI model fundamentals, AI domains, training approaches, neural networks, large language models and trends.
This glossary of terms for EHS professionals getting started with AI will help build confidence in your AI fluency.
AI is a tool. Like any technology, it is important to understand the problem you are trying to solve before applying a solution. Consider applying rubrics associated with the NSC Safety Innovation Journey before applying an AI solution for an EHS challenge.
AI may not be appropriate for your use case. While AI systems appear confident, these systems collect data that may be not be “clean” or may be biased, depending upon the environment in which it was obtained. Performance of many large language models is not fully understood. While continuously improving, they still have the potential to create responses that are not “real," also known as "hallucinations."
Validate information provided by AI, especially high-consequence inputs. This keeps the “human in the loop."
Data privacy, data security and organizational policies. AI tools might share or leak data, so be sure to refer to organizational policies and recognize the type of data being used. Data covered under privacy laws or protected health data would not be appropriate information for AI.
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