We conducted a meta-analysis to determine how people blindly comply with, rely on, and depend on diagnostic automation. We searched three databases using combinations of human behavior keywords with automation keywords. The period ranges from January 1996 to June 2021. In total, 8 records and a total of 68 data points were identified. As data points were nested within research records, we built multi-level models (MLM) to quantify relationships between blind compliance and positive predictive value (PPV), blind reliance and negative predictive value (NPV), and blind dependence and overall success likelihood (OSL).Results show that as the automation’s PPV, NPV, and OSL increase, human operators are more likely to blindly follow the automation’s recommendation. Operators appear to adjust their reliance behaviors more than their compliance and dependence. We recommend that researchers report specific automation trial information (i.e., hits, false alarms, misses, and correct rejections) and human behaviors (compliance and reliance) rather than automation OSL and dependence. Future work could examine how operator behaviors change when operators are not blind to raw data. Researchers, designers, and engineers could leverage understanding of operator behaviors to inform training procedures and to benefit individual operators during repeated automation use.