The article discusses how representing different levels of automation on a decision ladder can help design better interfaces for automated financial trading systems. By categorizing tasks into stages of automation and shading them based on the level of automation, the researchers show how human and automated activities are distributed. They use examples of low and high automation trading tasks to illustrate this concept. This work helps us understand automated trading and human-automation interactions better, leading to improved design requirements.