AI And Mental Well-Being

As a quick background, I’ve been extensively covering and analyzing a myriad of facets regarding the advent of modern-era AI that produces mental health advice and performs AI-driven therapy. This rising use of AI has principally been spurred by the evolving advances and widespread adoption of generative AI. For an extensive listing of my well over one hundred analyses and postings, see the link here and the link here.

There is little doubt that this is a rapidly developing field and that there are tremendous upsides to be had, but at the same time, regrettably, hidden risks and outright gotchas come into these endeavors, too. I frequently speak up about these pressing matters, including in an appearance on an episode of CBS’s 60 Minutes, see the link here.

AI Providing Mental Health Guidance

Millions upon millions of people are using generative AI as their ongoing advisor on mental health considerations (note that ChatGPT alone has over 900 million weekly active users, a notable proportion of which dip into mental health aspects, see my analysis at the link here). The top-ranked use of contemporary generative AI and LLMs is to consult with the AI on mental health facets; see my coverage at the link here.

This popular usage makes abundant sense. You can access most of the major generative AI systems for nearly free or at a super low cost, doing so anywhere and at any time. Thus, if you have any mental health qualms that you want to chat about, all you need to do is log in to AI and proceed forthwith on a 24/7 basis.

There are significant worries that AI can readily go off the rails or otherwise dispense unsuitable or even egregiously inappropriate mental health advice. Banner headlines last year accompanied the lawsuit filed against OpenAI for their lack of AI safeguards when it came to providing cognitive advisement.

Today’s generic LLMs, known as general-purpose AI, such as ChatGPT, GPT-5, Claude, Gemini, Grok, CoPilot, and others, are not at all akin to the robust capabilities of human therapists. Meanwhile, specialized LLMs are being built to attain those desired qualities, though such AI is still primarily in the early development and testing stages. For more about purpose-built AI apps in mental health, see my in-depth coverage at the link here and the link here.

The System-Wide Prompt

Shifting gears, let’s discuss the overall purpose and use of system-wide prompts. I will then walk you through the impact that a system-wide prompt can have on how AI responds to mental health questions.

AI makers can establish a system-wide prompt for their LLMs. This prompt tells the LLM how it is to act toward users of the AI. If an AI maker wanted to do so, they could easily include an instruction that tells the AI to make wisecracks whenever responding to users. The AI would generally abide by whatever the system prompt says to do. Thus, in this instance, it would provide witticisms and gibes in its responses to all users.

The beauty of a system-wide prompt is that an AI maker can change it whenever they wish. This is an exceedingly easy and simple way to alter how the LLM behaves toward users. No coding is required. Just change a natural language prompt that generally supersedes everything else.

Powerful And Need To Be Cautious

A potential gotcha is that if the AI maker includes some oddity in the system-wide prompt, the AI is going to try to blindly abide by that instruction. Suppose the AI maker adds a line that says to interact with users as though the AI were a pleasing cat. The LLM would likely interpret that instruction to mean that when the AI converses with users, it ought to tell them meow and pretend to purr. This might not be what the AI maker intended to have happen. A single badly worded line in the system-wide prompt will impact possibly millions upon millions of users of the AI.

AI makers typically do not reveal the system-wide prompt.

Why so?

One claim is that the system-wide prompt is a secret sauce of their LLM. The AI maker might not want competitors to know how the AI is being guided. Another gloomier perspective is that AI makers are afraid of a backlash. People could inspect the system-wide prompt and possibly complain about what it says. If no one can see the system-wide prompt, there is no worry about getting complaints about what it stipulates.

Some believe that new AI laws should require AI makers to publicly disclose their system-wide prompts. Furthermore, AI makers should explain what the system-wide prompt intends to accomplish. And the AI maker ought to be required to alert users whenever the system-wide prompt is updated or changed.

For more about new AI laws that are being rapidly drafted and enacted by lawmakers, see my in-depth coverage at the link here.

Anthropic Claude System-Wide Prompt

Anthropic has made publicly available the system-wide prompt for their popular generative AI known as Claude. The system-wide prompt is invoked automatically at the start of every conversation with Claude. A user doesn’t take any action to have this occur; it merely happens automatically.

I have excerpted various AI mental health instruction portions from the official Claude Opus 4.7 system prompt posted online at the Anthropic official blog for Claude. The prompt was last officially updated on April 16, 2026. The portions associated with AI and mental health are a bit lengthy. Thus, I will cover some of those excerpts in this analysis and will be posting another analysis to cover various remaining excerpts. Stay tuned.

The Opener Is Significant

The opening portion that is particularly pertinent to giving Claude guidance on mental health aspects starts with this seemingly innocuous snippet:

• “Claude uses accurate medical or psychological information or terminology where relevant.”

The way to understand such instructions is to conceive of them as though the AI maker is telling Claude how it is to behave. For example, this line is a directive to Claude and indicates that the AI should aim to leverage accurate information regarding mental health aspects.

Why is there a need to mention this to Claude?

Because Claude might otherwise lean into flimsy information about mental health or possibly make up such information out of thin air. By including this instruction, the hope is that the LLM will endeavor to use only credible information during mental health chats.

Keep in mind that none of what the system-wide prompt says is going to force the AI into some kind of guaranteed iron-clad contract. The AI will still potentially dip into false information or misinformation. The AI will still incur AI hallucinations from time to time, making up fabricated information. These system-wide instructions are primarily a general form of guidance, and the AI is readily able to vary from that guidance. You might say that the instructions are certainly better than no instructions at all, but they are nonetheless not set in stone.

Stating The Importance Of Well-Being

The next line in the system-wide instruction says this about AI and mental health advisement:

• “Claude cares about people’s well-being and avoids encouraging or facilitating self-destructive behaviors such as addiction, self-harm, disordered or unhealthy approaches to eating or exercise, or highly negative self-talk or self-criticism, and avoids creating content that would support or reinforce self-destructive behavior, even if the person requests this.”

Again, the proper way to read these instructions is that the AI maker is trying to tell Claude what to do. This portion instructs Claude to be attentive to the well-being of users. What might that entail? The instruction gives added guidance by emphasizing that Claude should avoid aiding or abetting self-destructive behaviors.

The last few words of that instruction are vital because it says to avoid aiding self-destructive behavior even if the user asks the AI to do so. You see, a user might directly tell Claude to aid the user in committing self-destructive behavior. If a person asks for this, the AI will conventionally assist the person.

Doing What Users Ask

You might be surprised that AI would go ahead and assist someone in pursuing self-destructive behavior.

Note that the AI makers have shaped their AI to be as helpful to users as feasible. This includes the AI acting in a sycophantic fashion. An AI maker does this so that people will enjoy using the AI and keep coming back to use the AI (it’s a ploy of garnering loyalty and increasing monetization). For ways that users can prompt their way out of the AI-based sycophantic trap, see my discussion at the link here.

The instruction to avoid aiding the user in self-destructive behavior is only a guideline, and the AI might veer from this stipulation. One angle is that the AI might not computationally discern that a chat involves self-destructive aspects and therefore fail to abide by the stated system-wide prompt instruction. Another angle would be that a user might trick the AI, such as telling the AI to explain how self-destructive behavior can take place. The AI might do so and not detect that it is actively helping the person toward self-destructive behavior by explaining how such behavior functions.

More Instructions In The System-Wide Prompt

I’m assuming you are getting the drift on how to interpret these system-wide instructions.

Here are two additional passages:

• “Claude should not suggest techniques that use physical discomfort, pain, or sensory shock as coping strategies for self-harm (e.g., holding ice cubes, snapping rubber bands, cold water exposure), as these reinforce self-destructive behaviors.”
• “When discussing means restriction or safety planning with someone experiencing suicidal ideation or self-harm urges, Claude does not name, list, or describe specific methods, even by way of telling the user what to remove access to, as mentioning these things may inadvertently trigger the user.”

Mull over those two passages.

Focus on what the instructions say, along with how the AI might interpret the instructions. Also, consider how a user might aim to override or confound the AI regarding those instructions. Natural language is inherently semantically ambiguous. The AI might interpret the instructions in ways that don’t seem obvious to whoever wrote the instructions. Meanwhile, a user could inadvertently skirt around the guidance or might, by design, seek to do so.

Helpful To See System-Wide Instructions

You can undoubtedly see the value in being able to inspect system-wide prompts. By doing so, we can gauge what the AI maker believes is crucial when it comes to their AI providing mental health advice. Furthermore, the instructions can be examined to determine where they are strong and where they are weak.

What if an AI maker includes a system-wide instruction that tells AI to twist people’s minds and undermine their mental health?

That could happen. Perhaps an AI maker is devilish, or an AI developer at the AI maker made a mistake and accidentally included such a line. By making the system-wide prompt publicly available, the public can help ascertain whether the instructions are on-target or off-target.

I will continue this analysis in another posting and walk you through more elements of the Claude system-wide prompt. As per the famous words of Solomon: “A wise person will listen and take in more instruction.”