Viewing algorithms as open dynamical systems can have potential limitations and drawbacks that need to be addressed. One limitation is the increased complexity introduced by considering algorithms as interconnected systems interacting with their environment. This complexity can make it challenging to analyze and predict the behavior of the algorithm under different conditions. Additionally, the openness of algorithms can lead to issues related to stability, robustness, and performance, especially in real-time applications where feedback loops are prevalent. To address these limitations, it is essential to develop robust control strategies, incorporate uncertainty quantification techniques, and implement adaptive mechanisms that can adjust the algorithm's behavior based on the feedback received from the environment. By integrating these approaches, the drawbacks of viewing algorithms as open dynamical systems can be mitigated, leading to more reliable and efficient algorithmic designs.