FAQ: AIHA’s Free Improving Exposure Judgments (IEJ) Tools

May 7, 2025|News & Headlines

with Brent Altemose, PhD, CIH, CSP

Q) Why is it important to improve your exposure judgment accuracy?

A) Research has shown that people tend to hold overly favorable views of their own abilities, known as the “Dunning-Kruger” effect. While this effect is particularly true for the inexperienced, we all are, at times, overconfident in our ability to judge exposures. It’s important to be aware of this effect and your own potential biases. I’ve experienced this firsthand, early in my career, and was judging too many exposures inaccurately. Using tools and thinking in terms of probabilities instead of certainties improved my ability to predict outcomes.

Q) What benefits have you seen as a result of using the IEJ tools?

A) Sometimes in IH we treat new tools like test driving a car. We take them out for a spin, see how they feel, but we often don’t want to commit to buying one—much less more than one. If we do invest in one, we get comfortable with it and stick with it. We don’t want to look at different options in the future.

In the case of the free IEJ tools, they’re all worth the investment of time because not only will using them make you more effective in making exposure judgments, but they can actually save you time in the long run. Plus, we keep improving the tools we already have. Using tools to improve qualitative judgments helps optimize when and where we collect samples. Using tools to analyze data helps optimize the frequency and number of samples we collect. Ultimately, all of this optimizes exposure controls for worker protection.

Q) Can you provide an example of when using statistical tools improved your accuracy?

A) Early in my career (25 years ago!), I was vaguely aware that statistical tools should be used to evaluate IH data. But since I usually only had one or a few data points, and since the culture of IHs around me was to simply use professional judgment and “eyeball” the data, I rarely applied statistical tools. Then, the company I worked for implemented a Bayesian statistical approach. I quickly found that using the tool, even with limited data, I was able to identify many instances where I had too quickly decided that exposure was acceptable.

It’s interesting to note, though, that I experienced the Dunning-Kruger effect firsthand using Bayesian tools. Once I learned to use the tool, I became a bit overconfident applying “prior” probabilities based on my professional judgment that were skewing my decisions. I realized over a period of time, as I collected more data from the same set of operations, that there were still too many instances where I concluded an exposure was acceptable where I shouldn’t have. Applying a “flat prior” rectified this problem in most cases, but this experience highlights how important it is to understand the limitations of the tools you’re using, and to realize that different scenarios may call for different tools.

Q) What advice would you give to someone who is looking to improve their exposure judgments?

A) When making exposure judgments, pause and take stock of the information available, and apply the tools at your fingertips to make the best judgment possible. Be deliberate and analytical in assessing the exposure. If you don’t know the answer yet, be comfortable saying you don’t know. Also don’t be shy, consult with other experienced IHs—a group is often better at making judgments than an individual.