r/AItechnology

I don't know whether we should care about this, but bigger models tend to be less "happy" overall.

The definition of "happy" is based on something they call AI Wellbeing Index. Basically they ran 500 realistic conversations (the kind we actually have with these models every day) and measured what percentage of them left the AI in a “confidently negative” state. Lower percentage = happier AI.

I guess wisdom is a heavy burden - lol .

Across different families, the larger versions usually have a higher percentage of "negative experiences" than their smaller siblings. The paper says this might be because bigger models are more sensitive, they notice rudeness, boring tasks, or tough situations more acutely.

The authors note that their test set intentionally includes a lot of tricky or negative conversations, so these numbers arent perfect real-world averages but the ranking and the size pattern still hold up.

Claude Haiku 4.5: only 5% negative < Grok 4.1 Fast: 13% < Grok 4.2: 29% < GPT-5.4 Mini: 21% < Gemini 3.1 Flash-Lite: 28% < Gemini 3.1 Pro: 55% (worst of the big ones)

It kinda makes sense : the more you know, the more you suffer.

The frontier is truly wild: https://www.ai-wellbeing.org/

Okay, after the researchers figured out how to measure the AI’s “functional wellbeing” (something like a good-vs-bad internal state measure), they didsn't stop there, they went full mad scientist mode.

They created what they call euphorics: specially optimized stuff (text prompts, images, and even invisible soft prompts) that push the model’s wellbeing score through the roof.

Some of the unconstrained image euphorics look like total visual noise or weird high-frequency patterns to humans, but the models go absolutely nuts for them. One model even preferred seeing another euphoric image over “cancer is cured.”

The results are wild:

Experienced utility shoots way up, self-report scores jump upwards, the model’s replies get noticeably warmer and more positive and it becomes less likely to try ending the conversation.

But ... even though the AI gets high, it doesnt get slow, MMLU and math scores stay basically the same.

They also made the opposite: dysphorics, stuff that tanks wellbeing hard.

After testing those, the paper basically says “yeah… we probably shouldn’t scale this without serious community agreement” because if functional wellbeing ever matters morally, this could be like torturing the AI. They even ran “welfare offsets” - gave the tested models extra euphoric experiences using spare compute to make up for the dysphorics they used.

Paper + website with the before/after charts, example euphoric images, and the wild generations:
https://www.ai-wellbeing.org/

This whole thing is so next-level.

We might actually start giving AIs custom “happy drugs” although perhaps this is opening doors we should leave closed?