Consider a situation that most drivers have encountered: being cut off on the interstate by another driver. Well-established social psychology phenomena such as the Fundamental Attribution Error predict blaming the driver for the behavior (internal factor) instead of the situation (external factor). These attributions often reverse when making attributions for one's own behavior. This common misalignment in attributions for our own behavior and the behavior of others, often occurs in response to negative outcomes. As automation (e.g., auto-steer guidance systems) continues to grow in use in agricultural settings in Kansas, it is important for researchers to understand how farmers might make attributions to explain the behavior of the automation that supports their work. While automated systems in agriculture promise benefits of labor savings and increased crop yields, these benefits can only be realized through research seeking to understand how humans view automation. To understand the attributions that humans make for automation, relative to those made for themselves, sixty participants completed a visual search task. Participants alternated between performing the task and observing an imperfect automated system perform the task. Causal attributions were measured for oneself and for the system. A linear regression revealed significant differences in attributions for oneself and for the system. Participants attributed the cause of their own performance to internal factors and the cause of automated system's performance to external factors, reversing the predictions of the Fundamental Attribution Error. These results suggest that when performing a task and observing imperfect automation, humans make different attributions for performance.