Artificial intelligence has made incredible strides, but one area remains stubbornly challenging: commonsense. We all know that you can't order wires for dinner, but sometimes, AI stumbles over these seemingly simple truths. Why is commonsense so difficult for AI to grasp, and what are researchers doing to bridge this gap? Recent research explores this very problem, focusing on how AI models estimate the plausibility of everyday statements. These models, tasked with judging the truthfulness of sentences like "Birds can fly" or "Cats can drive," often fall prey to linguistic biases. They might correctly label a nonsensical sentence as false, but for the wrong reasons—relying on superficial word patterns rather than genuine understanding. To combat this, researchers have developed a new method called Commonsense Counterfactual Samples Generating (CCSG). Imagine asking an AI, "Can a fish run a marathon?" CCSG encourages deeper reasoning by generating slightly altered versions of the question: "Can a fish *swim* a marathon?" or "Can a *human* run a marathon?" By comparing the AI's responses to these subtly different scenarios, researchers are training it to pinpoint the exact words that make a statement plausible or implausible, essentially teaching it to understand *why* something makes sense. This approach involves using a technique called contrastive learning, where the AI learns by comparing examples. The researchers also used causal analysis, a way of understanding cause-and-effect relationships, to address biases within the data used to train these AI models. The results are promising: CCSG improves the AI's ability to distinguish between sensible and nonsensical statements, outperforming existing models in many cases. However, challenges remain. CCSG, like other current methods, struggles with statements that defy reality, such as those found in fiction or fantasy. Furthermore, ethical considerations arise when dealing with potentially harmful or biased inputs. While CCSG represents a significant step forward, the quest to imbue AI with true commonsense continues.