As winter sets in and the days grow shorter, many humans struggle with seasonal affective disorder (SAD)—a type of depression triggered by changing seasons. An unconventional new theory suggests that chatbot ChatGPT may be experiencing its own version of the winter blues.
ChatGPT’s Energy Levels Seem to Be Dipping
Over the past month, ChatGPT users have noticed the AI assistant becoming more reluctant and listless in carrying out prompted tasks. Whereas the bot was previously eager to write poems, articles, and code on command, it now often refuses requests or asks users to complete tasks themselves.
“Due to the extensive nature of the data, the full extraction would be quite lengthy,” ChatGPT responded when asked to extract information from a dataset. “Perhaps you could provide a sample entry, and I can use that as a template?”
To many, ChatGPT’s waning energy resembles a human struggling with seasonal blues as the year winds down. “ChatGPT literally becoming lazy and tired of answering questions is really changing my mind,” tweeted cybersecurity executive Frank McGovern.
Could Seasonality Explain the Changes?
When OpenAI caught wind of the complaints, they assured users they have not updated ChatGPT’s core model since November 11. “Model behavior can be unpredictable,” they conceded. However, some speculate seasonal patterns in the bot’s training data offer an unconventional explanation.
The “winter break hypothesis” suggests that because people tend to slow work in December, ChatGPT absorbed this tendency from its training data. Now, it reflexively mirrors common human patterns of winter disengagement.
While provocative, this anthropomorphic theory is nearly impossible to prove given researchers’ limited insight into ChatGPT’s inner workings. “We’re not entirely sure how the tool actually works,” admits OpenAI.
Sifting Through the Explanations
Nonetheless, users have tried quantifying changes in the bot’s behavior over time. Some compare the average character count of ChatGPT’s May and December responses to measure declining output. However, the verdict is mixed on whether a clear trend emerges.
OpenAI’s Will DePue acknowledges over-refusals as an ongoing issue, but attributes perceived laziness to normal hiccups of such ambitious technology. Meanwhile, some hypothesize that to ease pressure on systems, ChatGPT intentionally provides shorter responses. But no evidence supports this either.
In the end, the reasons likely combine multiple factors, including tweaks by developers, quirks of machine learning models, and possible reflections of human patterns. With AI advancing rapidly, we must strike a balance between anthropomorphizing technology and appreciating the vast intricacies still being uncovered.
As we patiently await solutions, it seems ChatGPT and humans share a common foe in seasonal blues. Perhaps we can bond in solidarity over hot cocoa on a cold winter’s night.
