AI models can’t tell time or read a calendar, study reveals

AI models can’t tell time or read a calendar, study reveals

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AI systems check out clocks properly just 38.7 % and calendars just 26.3 %
(Image credit: Alamy)

New research study has actually exposed another set of jobs most human beings can do with ease that expert system (AI) stumbles over– checking out an analogue clock or determining the day on which a date will fall.

AI might have the ability to compose code, produce natural images, develop human-sounding text and even pass examinations (to differing degrees of successIt regularly misinterprets the position of hands on daily clocks and stops working at the fundamental math required for calendar dates.

Scientists exposed these unforeseen defects in a discussion at the 2025 International Conference on Learning Representations (ICLR). They likewise released their findings March 18 on the preprint server arXivso they have actually not yet been peer-reviewed.

“Most people can tell the time and use calendars from an early age. Our findings highlight a significant gap in the ability of AI to carry out what are quite basic skills for people,” research study lead author Rohit Saxenaa scientist at the University of Edinburgh, stated in a declarationThese deficiencies need to be resolved if AI systems are to be effectively incorporated into time-sensitive, real-world applications, such as scheduling, automation and assistive innovations.”

To examine AI’s timekeeping capabilities, the scientists fed a custom-made dataset of clock and calendar images into different multimodal big language designs (MLLMs), which can process visual in addition to textual details. The designs utilized in the research study consist of Meta’s Llama 3.2-Vision, Anthropic’s Claude-3.5 Sonnet, Google’s Gemini 2.0 and OpenAI’s GPT-4o.

And the outcomes were bad, with the designs being not able to determine the right time from a picture of a clock or the day of the week for a sample date majority the time.

Related: Existing AI designs a ‘dead end’ for human-level intelligence, researchers concur

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