👉 Wrong computing refers to the misuse or inappropriate application of computational resources and techniques, often leading to inefficient, ineffective, or even harmful outcomes. This can occur when algorithms are poorly designed, causing them to consume excessive resources like CPU or memory, leading to slower performance or system crashes. For example, using an overly complex machine learning model on a small dataset might result in overfitting, where the model performs well on training data but fails to generalize to new data. Similarly, applying the wrong data preprocessing steps can lead to biased or inaccurate results. In essence, wrong computing involves not just the technical execution of tasks but also a lack of understanding or consideration of the problem's context, leading to suboptimal solutions.
