For the first time, speech has been decoupled from consequence. We now live alongside AI systems that converse knowledgeably and persuasively—deploying claims about the world, explanations, advice, encouragement, apologies, and promises—while bearing no vulnerability for what they say. Millions of people already rely on chatbots powered by large language models, and have integrated these synthetic interlocutors into their personal and professional lives. An LLM’s words shape our beliefs, decisions, and actions, yet no speaker stands behind them.
This dynamic is already familiar in everyday use. A chatbot gets something wrong. When corrected, it apologizes and changes its answer. When corrected again, it apologizes again—sometimes reversing its position entirely. What unsettles users is not just that the system lacks beliefs but that it keeps apologizing as if it had any. The words sound responsible, yet they are empty.
This interaction exposes the conditions that make it possible to hold one another to our words. When language that sounds intentional, personal, and binding can be produced at scale by a speaker who bears no consequence, the expectations listeners are entitled to hold of a speaker begin to erode. Promises lose force. Apologies become performative. Advice carries authority without liability. Over time, we are trained—quietly but pervasively—to accept words without ownership and meaning without accountability. When fluent speech without responsibility becomes normal, it does not merely change how language is produced; it changes what it means to be human.
This is not just a technical novelty but a shift in the moral structure of language. People have always used words to deceive, manipulate, and harm. What is new is the routine production of speech that carries the form of intention and commitment without any corresponding agent who can be held to account. This erodes the conditions of human dignity, and this shift is arriving faster than our capacity to understand it, outpacing the norms that ordinarily govern meaningful speech—personal, communal, organizational, and institutional.


So that I fully understand your argument, it is that other automation proves that what I posted is LLM output? Let’s sit with that for a moment. Your bullshit detector is accurate, but mine is not. This is essentially your thesis.
I’d workshop this for a bit.
Ohhh, I get it now. Thanks for spelling it out.
Sorry for hurting your feelings. I didn’t mean to imply your bs detector is broken but I can see how it would come across that way.
I would hazard a guess that you’ve spent less time in a newsroom than I have.