To understand the picture the machine should reason like this. First: Look for focus, detect zone in which eyes are looking. Result: The focus is on the man at

To understand the picture the machine should reason like this. First: Look for focus, detect zone in which eyes are looking. Result: The focus is on the man at the right since eyes are directed at him. Second: Sentiment Analysis Whatever he is doing people find it funny. People like to play jokes that make you experience strange things that you can't understand at the moment. Hypothesis: The man B near the main character A is interacting with A. It seems that the foot of B is interacting with the machine M. So B interacts with M that interacts with A. Generated question: What kind of interaction could be exerted by B on M to cause M get A confused? Hypothesis: B's foot is making the machine to malfunction in such a way to give a false message to A. Hypothesis: To make this image more noticeable the men are well known people or famous people. Data: The more serious the role this people play at society the more funny is the image, since their behavior is more unexpected. Reasoning like this the machine could get a plausible hypothesis of what is happening in the scene: A famous man B that probably do a serious and responsible role in society is playing a trick on a man A by making a machine M to malfunction in such a way that it gives a false message or information to A. The malfunction is caused by putting the foot on the machine. To make it funnier, the main character can't see that, ... Having a general context like this the machine could look for machines and people which could play such a role and give a heavier weight to those that make the joke a better one. The next generation of machines could modify the image to make the joke better since it can understand perfectly the context and purpose of it.