Put very simply, that is how they're supposed to work. They are supposed to result in the most likely result. Same reason they, unless made not to, output '17' when prompted to "pick a number between 1 and 30", because that is the most likely result from training; but that means that all LLMs output 17 except for forced temperature or reasoning in RL making them run a python command with random.randint(0,31), or that the prompt is recognised and something else is supposed to be chosen than what is statistically the most likely text response.

Therefore asking a group of people would result in more varied outcomes of something visual, but from the textual training data the direction is statistically the most likely so is what is output, that sky is the most likely, time is the most likely, cloud coverage, etc. You're prompting with as little as possible so it fills in the blanks with what as likely as possible. When you ask Alex from the North Pole they're going to fill in the blank with a different kind of weather than Bob from the Equator.

That does mean that an LLM itself is in essence not as creative as a human, but then it is a tool to be used by a human doing more than oneshotting "Generate an SVG of a pelican riding a bicycle" and expecting creativity from the tool rather than the user. If the user is lacking in creativity they can prompt an LLM to get wacky scenarios to change it up a little.