How We Talk to AI Says Something About Us
Anthropic’s latest policy update made me think less about artificial intelligence and more about human behavior.
Announced October 8 and effective November 12, 2026, the update addresses extreme, repeated abuse without a discernible purpose. It expressly excludes ordinary frustration, pushback, dark creative themes, and legitimate testing or research. Ending persistently abusive conversations remains the primary enforcement mechanism. That scope matters: criticizing a model’s work is compatible with the policy. Anthropic’s announcement.
The question that interests me is what kind of behavior we choose to practice when we believe there is little social accountability for how we speak.
I worry about the habit of directing hatred at something that responds conversationally. If someone repeatedly rehearses humiliation, contempt, or cruelty in that setting, could those habits become easier to carry into human relationships?
I’m not suggesting that one automatically leads to the other. But I do think the question deserves attention, especially as these tools become a more routine part of our days.
For me, consistency matters. I want my conduct to reflect standards I can stand behind, including in situations where nobody is likely to challenge me.
I do not need to settle whether a future AI could be conscious to make that choice. I am uncertain about that future, and I am not claiming that today’s systems feel hurt or experience a conversation the way a person does. My immediate concern is the human participating in the exchange: the habits we reinforce, the language we normalize, and the standards we allow ourselves to abandon.
Those standards should leave plenty of room for direct criticism.
When an AI gives an incorrect answer, invents a source, ignores a constraint, or declares success without verification, the response should be clear. We should identify the failure and require a correction. Respect does not require pretending that weak work is acceptable.
“This answer does not address the question. Recheck the source, explain the discrepancy, and correct the conclusion” is a firm response. It identifies what went wrong and establishes what needs to happen next.
A string of insults gives the system much less useful information about how to repair the result.
That brings me to the practical side of this conversation. Working effectively with AI requires us to communicate the task well.
What outcome do we want? What context changes the answer? Which constraints must be honored? What would count as a successful result? When the output falls short, what specifically needs to change?
Those details deserve space in a prompt. A complicated task may need a substantial explanation, examples, background, or several rounds of correction. Concise communication means removing what does not help while preserving what the task requires.
Unnecessary emotional padding can come from either direction. Repeated hostility can bury the objective. So can several paragraphs of praise or reassurance that add no relevant information. A brief courtesy is fine. The useful discipline is to notice when the actual request has become difficult to find.
Consider this instruction:
“Revise this proposal for a small business owner. Keep the pricing unchanged, explain the implementation steps in plain language, and remove claims we cannot support.”
Every part contributes to the work. Cutting it to “make this better” would make it shorter while removing the guidance that makes success possible.
The same principle applies to feedback. “This is wrong” may be accurate, but identifying the wrong number, unsupported claim, or missed requirement gives the system a better opportunity to correct it.
Verification still belongs in the process. A pleasant exchange does not establish accuracy. Neither does an assertive one. We need to check important claims, inspect the work, and confirm that the requested correction actually happened.
I want to use these tools with clear expectations and honest feedback. I also want to pay attention to what my own behavior becomes through repetition.
We can hold AI systems to demanding standards and remain deliberate about our conduct. I see no conflict between those commitments. Both ask us to take responsibility for what we bring to the conversation.