Threatening AI Does Not Make It More Useful. Why Sergey Brin Is Wrong

We work in the arena of automated AI workflows where consistency of success is vital. When you threaten an LLM you are drawing the LLM into the texts where threats occur (flame wars, parody, etc.). So intuitively you would expect it to work sometimes, but also fail with even more ardent refusal (increasing the variance of success).

Jailbreak approaches like "Bad Likert Judge" ( https://unit42.paloaltonetworks.com/multi-turn-technique-jai... ) and similar persuasive techniques (see https://xthemadgenius.medium.com/how-persuasion-techniques-c... ) move the text domain to more policy, analysis, or scientific papers, where deeper analysis, discussion, and compliance is the norm.

So I'm curious about the extremes (variance) of success with threatening vs. polite discussion, but I haven't seen direct research on that.