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Measuring base-rate bias error in workplace safety investigators.
Journal of Safety Research 2023 Februrary
INTRODUCTION: This study explored the magnitude of professional industrial investigators' bias to attribute cause to a person more readily than to situational factors (i.e., human error bias). Such biased opinions may relieve companies from responsibilities and liability, as well as compromise efficacy of suggested preventative measures.
METHOD: Professional investigators and undergraduate participants were given a summary of a workplace event and asked to allocate cause to the factors they found causal for the event. The summary was crafted to be objectively balanced in its implication of cause equally between two factors: a worker and a tire. Participants then rated their confidence and the objectivity of their judgment. We then conducted an effect size analysis, which supplemented the findings from our experiment with two previously published research studies that used the same event summary.
RESULTS: Professionals exhibited a human error bias, but nevertheless believed that they were objective and confident in their conclusions. The lay control group also showed this human error bias. These data, along with previous research data, revealed that, given the equivalent investigative circumstances, this bias was significantly larger with the professional investigators, with an effect size of dunb = 0.97, than the control group with an effect size of only dunb = 0.32.
CONCLUSIONS: The direction and strength of the human error bias can be quantified, and is shown to be larger in professional investigators compared to lay people.
PRACTICAL APPLICATIONS: Understanding the strength and direction of bias is a crucial step in mitigating the effects of the bias. The results of the current research demonstrate that mitigation strategies such as proper investigator training, a strong investigation culture, and standardized techniques, are potentially promising interventions to mitigate human error bias.
METHOD: Professional investigators and undergraduate participants were given a summary of a workplace event and asked to allocate cause to the factors they found causal for the event. The summary was crafted to be objectively balanced in its implication of cause equally between two factors: a worker and a tire. Participants then rated their confidence and the objectivity of their judgment. We then conducted an effect size analysis, which supplemented the findings from our experiment with two previously published research studies that used the same event summary.
RESULTS: Professionals exhibited a human error bias, but nevertheless believed that they were objective and confident in their conclusions. The lay control group also showed this human error bias. These data, along with previous research data, revealed that, given the equivalent investigative circumstances, this bias was significantly larger with the professional investigators, with an effect size of dunb = 0.97, than the control group with an effect size of only dunb = 0.32.
CONCLUSIONS: The direction and strength of the human error bias can be quantified, and is shown to be larger in professional investigators compared to lay people.
PRACTICAL APPLICATIONS: Understanding the strength and direction of bias is a crucial step in mitigating the effects of the bias. The results of the current research demonstrate that mitigation strategies such as proper investigator training, a strong investigation culture, and standardized techniques, are potentially promising interventions to mitigate human error bias.
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