AI Is Shoring Up Cognitive Errors Made By Mental Health Therapists

Generative AI and large language models are emerging as tools to help mental health therapists identify cognitive errors. Therapists, being human, are susceptible to biases and errors during calling for sessions, which can occur before, during, or after client interactions.

While AI is already widely used AI can analyze session transcripts to flag potential issues like confirmation bias, mind-reading, or overgeneralization.

Crucially, AI prompts must be carefully designed to provide non-accusatory feedback, fostering collegial assessment. This dual-use technology offers significant potential to enhance therapeutic practice, provided it's used judiciously and not as an infallible source. In today’s column, I examine the use of generative AI and large language models (LLMs) to aid in identifying cognitive errors that mental health therapists make.

Key Analysis and Detailed Timeline

This is not to somehow knock on therapists or undercut the amazing work that they do. Therapists are human. They are subject to human foibles.

Acknowledging this facet is actually a prudent alignment with the field of psychology. Psychological research has shown that cognitive errors can arise in any domain, even Therapists operate in an environment of intense time pressures while saddled with incomplete information. It is a volatile recipe and gives rise to cognitive errors.

These errors can occur during, before, and after a therapeutic session. A therapist might manage to catch themselves when they have made a cognitive error, hopefully so. But there are occasions where the error slips through without the therapist noticing.

Broader Impact and Sector Outlook

The good news is that there are practical ways to try to detect cognitive errors and deal with them before they get out of hand. One such means is to use modern-era AI to identify errors and apprise the therapist as a handy heads-up. Let’s talk about it.

This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here). 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 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. I’d like to set the stage on how generative AI and large language models (LLMs) are typically used in an ad hoc way for 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 1 billion 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 in August of this year accompanied the legal action filed against OpenAI for their lack of AI safeguards when it came to providing cognitive advisement.

Despite alleges For my follow-on analysis of details about the OpenAI legal action and how AI can foster delusional thinking in humans, see my analysis at the link here. As noted, I have been earnestly predicting that eventually all of the major AI makers will be taken to the woodshed for their paucity of robust AI safeguards.

Today’s generic LLMs, such as ChatGPT, Claude, Gemini, Grok, and others, are not at all akin to the robust capabilities of human therapists. Meanwhile, specialized LLMs are being built to presumably attain similar qualities, but they are still primarily in the development and testing stages. See my coverage at the link here.

I have been extensively identifying and examining the myriad ways that AI enters into the role of professional therapists. Some therapists refuse to think about AI and want nothing to do with it. Others are embracing AI and using AI as part of their therapeutic process with clients.

Indeed, I have predicted that the therapy realm is being transformed from the traditional dyad of therapist-client and inevitably becoming a new triad of therapist-AI-client, see my analysis at the link here. My view is that whether therapists are keen on AI is not the headspace they should be in.

AI is coming, and to a great degree, it is already here.

Clients nowadays come in the door with AI-generated advice and want their therapist to tell them what it means. In other instances, clients will post-session try to double-check what their therapist informed them and lean into AI as a means of judging the mental health advice they are getting from the clinician.

AI is a reality that therapists must face, regardless of their desire to do so.

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Having one’s head in the sand is not prudent, as I will be illuminating momentarily. There are lots more variations of the role of AI in therapy and regarding therapists, including these circumstances that I have judiciously addressed: Shifting gears, I’d like to dive into the nature of cognitive errors that human therapists might make.

After doing so, we can look into the use of AI to aid in detecting and correcting those errors. First, let’s consider that cognitive errors can occur at any of these three stages: Before a session, a therapist might make a therapy-oriented cognitive error while preparing to meet with the client.

I am emphasizing that these are therapeutic mistakes and not other types of cognitive mistakes, such as those that are administrative.

This isn’t about mistakes in billing or paperwork. The focus is on cognitive errors intertwined with therapy. An example of a pre-session cognitive error would be the therapist anchoring on a pre-fixed diagnosis that they intend to carry into the session.

They become resolute that no matter what else happens, they are going to dogmatically insist on the pre-determined diagnosis. During a session, everything the client says will be interpreted solely within that frame of mind. The client has a near-zero chance of being understood in any other manner, and the therapist is going to confirm the preconceived diagnosis.

If a therapist does allow their thinking to be unyielding in this manner during a session, you could say that the pre-session cognitive error has been compounded. The therapist has committed a cognitive error at the pre-session stage and then committed a second cognitive error during the actual session. Cognitive errors can arise spontaneously during a session.

One of the most frequent cognitive errors that a therapist makes is to undertake a semblance of mind-reading. Here’s how that goes. The client says something, perhaps an innocuous statement.

The therapist leaps on that statement and assumes all sorts of facts about how the client feels or what they mean. It is a case of mind-reading. A therapist should avoid that type of behavior and aim to ensure that they clarify what the client has stated.

Do not jump to premature conclusions. A cognitive error might arise post-session. A common cognitive error happens when a therapist is preparing their notes about a session.

Sometimes, a therapist wants to put a tidy bow on what took place. They force the discussion to fit a particular narrative. This is known as a narrative fallacy.

The issue is that the bias of the therapist is reducing uncertainty and ambiguity into a cohesiveness that doesn’t truly belong there. In an excellent article on therapists and cognitive error, namely a posting entitled “Special Report: Addressing Cognitive Error in Psychiatric Practice” H.

Paul Putman III, Psychiatric News, December 22, 2025, these salient points were made (excerpts): The research brings up the various nuances associated with Type I versus Type II thinking, the use of abductive reasoning, hypothetico-deductive reasoning, and inductive reasoning.

It is very easy to falter when using any of those thinking processes. Therapists are prone to the same cognitive errors that we all encounter in our daily lives. We cherry-pick data, we look at the pieces of a situation without considering the whole, we anchor on a way of thinking, and so on.

Recommendations are made on ways that therapists can try to prevent cognitive errors, along with spotting errors and correcting errors. The hallmark points are worthwhile to keep at the top of mind. Avoid making rapid diagnoses.

Use a pluralistic approach to assessment. Get multi-sourced feedback. Enhance communication skills.

An additional means or avenue to contend with cognitive errors is to prudently employ generative AI and LLMs. A therapist can pick and choose which of those AI uses they believe are valuable for them. In some therapy practices, AI is being adopted for all three stages and considered part-and-parcel of performing therapy.

You might be wondering whether AI can identify cognitive errors that a therapist might have made. One aspect to keep in mind is that cognitive errors are oftentimes hard to spot and might not actually be cognitive errors.

Even a human reviewer or supervisor might claim they have found a cognitive error, but it turns out that the declared concern is falsely flagged.

The gist is that you need to be extremely cautious in summarily assuming that just because a cognitive error might seem to exist, it isn’t as easy as finding a number that’s out of sequence or detecting that two plus two came out to five. Cognitive errors are elusive. They can be subtle.

In a therapeutic context, be mindful of not rashly proclaiming that a cognitive error has been found. The best bet would be to calmly discuss with the therapist whether a cognitive error arises. Of course, that’s a difficult discussion since a therapist might naturally be defensive.

To give you a sense of how contemporary AI might be used to tentatively identify potential cognitive errors, I fed a transcript of some therapist-client sessions into AI and requested the AI to see if there were cognitive errors.