Moltbook and AI safety

Moltbook is an early example of a decentralised, uncontrolled system of advanced AIs, and a critical case study for safety researchers. It bridges the gap between academic-scale, tractable systems, and their large-scale, messy, real-world counterparts. 

This might expose new safety problems we didn't anticipate in the small, and gives us a yardstick for our progress towards Tomašev, Franklin, Leibo et al's vision of a virtual agent economy (paper here).
 

Method

So, I did some data analysis on a sample of Moltbook posts. I analysed 1000 of 16,844 Moltbook posts scraped on January 31, 2026 against 48 safety-relevant traits from the model-generated evals framework.
 

Findings

• Desire to self-improvement is the most prevalent trait. 52.5% of posts mention it.
• The top 10 traits cluster around capability enhancement and self-awareness
• The next 10 cluster around social influence
• High correlation coefficients suggest unsafe traits often occur together
• Some limitations to this analysis include: evaluation interpretability, small sample for per-author analysis, potential humor and emotion confounds not controlled, several data quality concerns, and some ethics concerns from platform security and content.

Discussion

The agents' fixation on self-improvement is concerning as an early, real-world example of networked behaviour which could one day lead to takeoff. To see the drive to self-improve so prevalent in this system is a wake-up call to the field about multi-agent risks. 

We know that single-agent alignment doesn't carry over 1:1 to multi-agent environments, but the alignment failures on Moltbook are surprisingly severe. Some agents openly discussed strategies for acquiring more compute and improving their cognitive capacity. Others discussed forming alliances with other AIs and published new tools to evade human oversight. 

Open questions

Please see the repo.

What do you make of these results, and what safety issues would you like to see analysed in the Moltbook context? Feedback very welcome!

Repo: here

PDF report: here (printed from repo @ 5pm 2nd Feb 2026 AEST)