New study finds AI copies humans in the winter and gets lazier
You'd never imagine that a "digital entity" could take on human traits, but they do ...
Cite or link to this article
Griffin, M. (2023) 'New study finds AI copies humans in the winter and gets lazier', 311 Institute, 25 December. Available at: https://www.311institute.com/new-study-finds-ai-copies-humans-in-the-winter-and-gets-lazier/ (Accessed: 25 October 2026).
It seems that GPT-4 Turbo, the most recent incarnation of the Large Language Model (LLM) from OpenAI, winds down for the winter and gives worse answers to questions in much the same way that people who are winding down for the December holidays seem to do.
We all get those end of year holiday season chill vibes and, after a new study, that appears to be why GPT-4 Turbo seems to be giving worse answers because when it’s been trained on datasets from December it seems to have “learned” that humans do worse work and then “adopted” those same behaviours. Weird I know right!?
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As Wccftech highlighted, the interesting observation on the AI’s behavior was made by an LLM enthusiast, Rob Lynch, on X (formerly Twitter).
The claim is that GPT-4 Turbo produces shorter responses, to a statistically significant extent, when the Artificial Intelligence (AI) believes that it’s December, as opposed to May, with the testing done by changing the date in the system prompt.
So, the tentative conclusion is that it appears GPT-4 Turbo learns this behaviour from us, an idea advanced by Ethan Mollick who’s an Associate Professor at the Wharton School of the University of Pennsylvania who specializes in AI.
Apparently GPT-4 Turbo is about 5% less productive if the AI thinks it’s the Holiday season. This is known as the ‘AI winter break hypothesis’ and it’s an area that is worth exploring further. Because not only is it odd but, yet again, it shows how oddly and unexpectedly AI’s can behave …
What it goes to show is how unintended influences can be picked up by an AI that we wouldn’t dream of considering, although some researchers obviously did notice and consider it, and then test it. But still, you get what I mean, and there’s a whole lot of worry around these kinds of unexpected developments.
As AI progresses, its influences, and the direction that the tech takes itself in, need careful watching over, hence all the talk of safeguards for AI being vital. We’re rushing ahead with developing AI, or rather, the likes of Google, Microsoft, and OpenAI certainly are, caught up in a tech arms race, with most of the focus on driving progress as hard as possible, with safeguards being more of an afterthought.
At any rate, regarding this specific experiment, it’s just one piece of evidence that the winter break theory is true for GPT-4 Turbo, and Lynch has urged others to get in touch if they can reproduce the results, and we do have one report of a successful reproduction so far. Still, that’s not enough for a concrete conclusion yet, watch this space.
What this means for your organisation
Unseen habits can shape outputs.
Tests found GPT-4 Turbo wrote shorter answers when the system prompt said December instead of May. The gap was about 5% in productivity. Large language models can pick up traits from their training data that nobody planned for.
Treat the finding as a hypothesis.
This is one experiment, with one reported reproduction so far. Rob Lynch has asked others to try to repeat it. Run your own checks and record the date and prompt settings used, so odd drops in quality can be traced.
Safeguards still trail the race.
Google, Microsoft and OpenAI are caught in a tech arms race, and safeguards are often an afterthought. 311 rates large language models as Act now, with wide use from 2024. Leaders should set their own monitoring rules before relying on them at scale.
Three questions for your next leadership meeting
- Do we test our AI tools at different times of year?
- Who checks our AI outputs for drops in length or quality?
- What safeguards do we require before an AI tool is used at scale?
The trends and technologies behind this story
From the 311 Starburst, the 311 Strategic Intelligence Unit’s map of the technologies and trends shaping the next 50 years.
Analysis by the 311 Strategic Intelligence Unit, from Matthew Griffin’s article and 311 data. First published on Fanatical Futurist.
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You'd never imagine that a "digital entity" could take on human traits, but they do ...
About the author
Matthew Griffin Founder, President and Futurist, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 17-time best selling author of the "Codex of the Future" series, Matthew is the Founder, President and Futurist of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity programme, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
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