The numbers seem to be consistently in the wrong place, and sometimes are outside the clock itself. The hands may or may not be in the correct position, and sometimes are floating off in space outside of the clock. Even the clocks that are pretty good look\u2026off, somehow.\u00a0<\/p>\n
\u201cTelling time is a very human thing, very easy thing for us to do, and something you learn at a very young age,\u201d Brian Moore, the artist behind the site, told me in an interview. \u201cIt\u2019s kind of fun and funny to turn the tables\u2014to see something a human could do very easily and a computer cannot.\u201d\u00a0<\/p>\n
I\u2019ve kept this site open throughout the process of writing this article and can confirm: It\u2019s very funny. But why is the AI<\/a> so bad at this?\u00a0<\/p>\n Well, one thing to keep in mind is that the site limits all models to around 2000 tokens to generate its clocks, and uses the same prompt for all models. You could, given unlimited computing power and a very specific prompt, get a better clock from an AI system. But the question remains: Why is this so hard for AI systems? The reasons point to the way AI systems work.\u00a0<\/p>\n AI is bad at telling time<\/p>\n AI isn\u2019t just bad at making clocks; it\u2019s also bad at reading them. A 2025 study<\/a> by technologist Alek Safar suggests that humans are 89.1 percent accurate at telling the time on analogue clocks while the top-rated AI is only 39.4 percent accurate.\u00a0<\/p>\n That study only hypothesizes about the reasons this might be, but the potential explanations are all interesting. The first is that there simply aren\u2019t enough pictures of clocks in the datasets for AI models to accurately learn to tell time. Another is that images of clocks are difficult to describe using language accurately, which is something large language models require in order to process them.\u00a0<\/p>\n Another 2025 study<\/a> conducted by the School of Informatics at the University of Edinburgh also found that all major large language models have trouble understanding the time when shown an image of an analogue clock.\u00a0<\/p>\n \u201cOur findings suggest that successful temporal reasoning requires a combination of precise visual perception, numerical computation, and structured logical inference that current MLLMs have not yet mastered,\u201d says the study.\u00a0<\/p>\n As I said, neither of these studies claims to completely know why AI isn\u2019t great at these tasks. There are some interesting factors to consider, though, including the datasets that AI systems use to understand the world.\u00a0<\/p>\n Something you need to understand is that large language models, the technology referred to as \u201cAI\u201d in contemporary parlance, don\u2019t really do math. This is counterintuitive, because we\u2019re used to thinking about computers as mathematical machines, but modern AI technology is based more on pattern recognition. Clocks are an interesting example of this at work. The systems, instead of calculating the angles or positioning of the hands to tell the time, are attempting to guess the time based on pattern recognition. Which, come to think of it, isn\u2019t that different from how I personally tell time when looking at a clock\u2014AI systems are just bad at this. And there are some interesting reasons why.\u00a0<\/p>\n The 10:10 problem<\/p>\n Go to your image search tool of choice and type \u201cwatch,\u201d then keep track of what time you see on the watch faces. You\u2019ll notice quickly that a majority of the analogue watches are set to ten after ten (10:10).\u00a0<\/p>\n Why that particular time? Because marketing. Watch and clock sellers have long known that setting a watch to 10:10 makes it more attractive to would-be buyers. A 2017 study<\/a> published in Frontier in Psychology suggests this might be because the two hands angles resembled a human smile. Another consideration is that, at 10:10, the hands don\u2019t cover the logo, brand name, or any complications like the date. It makes for an attractive photo, basically, and has become standard for watch and clock marketing.\u00a0<\/p>\n One consequence of this: many of the images of watches and clocks on the internet are set to 10:10. This in turn means a major chunk of the clocks in AI datasets are set to that same time. Ask any AI system to draw you a clock and, most of the time, they\u2019ll set it to 10:10\u2014sometimes even if you ask for a different time. Which is part of how Moore ended up making his website of hilariously bad AI clocks.\u00a0<\/p>\n
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