In recent years, rapid technological changes in the financial markets have significantly altered the way orders are generated and executed. Many of the executions that were previously performed manually are now automated. Despite electronic algorithms growing relative to human action, there have been few controlled laboratory experiments dedicated to studying the interactions between human traders and automated trading agents (“robots”). Thus, this paper provides important insights and summarizes the valuable contribution made by experimental studies in extending the knowledge on financial markets, particularly automated trading strategies. It should be noted that human investors make slightly smaller profits than robots, except for robots that operate at a slower speed and do not operate during periods of greater market instability. In addition, this study finds that faster and more sophisticated trading algorithms can resort to market manipulation strategies and consequently reduce market efficiency. Further, to the best of our knowledge, there have been no scientific contributions (namely, laboratory experiments) that have evaluated the cognitive and behavioral biases in human–robot interactions. Our study opens up a new horizon to explore by serving as the starting point in a new direction for future research. We hope it will encourage more laboratory experiments that actively study the interactions between humans and automated trading agents.