Artificial intelligence has made conversational technology available at almost any moment, but Joshua Shuman of Dayton explains that accessibility should not be confused with therapy. For people experiencing anxiety, loneliness, relationship difficulties, or other emotional struggles, repeatedly turning to an AI chatbot for reassurance may create a pattern in which immediate validation becomes more important than examining the underlying concern.
Large language models can provide general information, organize thoughts, and generate supportive-sounding responses. Problems can emerge when someone begins treating those responses as a substitute for professional mental health care.
Joshua Shuman of Dayton on the Appeal of Immediate Reassurance
Emotional distress often creates a desire for certainty. Someone worried about a relationship may want confirmation that another person behaved unfairly. Someone anxious about a decision may repeatedly ask whether the choice is safe. A person questioning personal abilities may look for reassurance that a feared outcome will not occur.
AI makes that reassurance unusually accessible.
Joshua Shuman of Dayton recognizes that convenience can make chatbot conversations particularly appealing when someone feels distressed. There is no appointment to schedule, and a person can continue asking variations of the same question whenever uncertainty returns.
The immediate response may temporarily reduce discomfort. However, temporary relief and meaningful psychological progress are not necessarily the same thing.
When Reassurance Becomes a Repeating Cycle
Occasional reassurance is a normal part of human relationships. The concern arises when reassurance becomes the primary strategy for managing uncomfortable thoughts or emotions.
A simple pattern can develop:
- A distressing thought or uncertainty appears.
- The individual seeks reassurance from an AI.
- The response temporarily reduces discomfort.
- Uncertainty eventually returns.
- Another conversation is started to obtain reassurance once more.
Joshua Shuman of Dayton explains that repeated reliance on this cycle can potentially shift attention away from understanding why the same concern continues returning.
An AI system is particularly easy to revisit because it is always available. That convenience may encourage repeated checking in situations where learning to tolerate uncertainty, explore emotions, or discuss recurring patterns with a qualified professional could be more productive.
Supportive Language Is Not Clinical Understanding
Modern chatbots can generate remarkably natural language. They can sound patient, sympathetic, encouraging, and attentive.
That presentation can make an important distinction easy to overlook.
Joshua Shuman of Dayton emphasizes that language that sounds empathetic does not mean an AI possesses the clinical understanding of a psychologist. A chatbot generates responses from patterns in data and the information supplied during an interaction. It does not develop a therapeutic relationship with the individual or observe that person across the broader context of life.
A mental health professional can consider information that extends beyond the immediate question. Changes in behavior, recurring themes, relationships, coping patterns, personal history, and progress over time may all become relevant.
An AI conversation is largely shaped by what the user chooses to tell it.
The Problem With Hearing Only One Side
People naturally describe experiences from their own perspective. During moments of distress, that perspective may become especially narrow.
Imagine someone describing an argument with a friend, partner, relative, or colleague. The chatbot receives the details selected by that individual. It does not independently know what happened before the disagreement, what information was omitted, or how the other person understood the interaction.
Joshua Shuman of Dayton notes that this limitation becomes important when people use AI to evaluate emotionally complicated situations.
A response may appear to confirm a person’s interpretation because the prompt itself was constructed around that interpretation. The resulting agreement can feel meaningful even though the system has only been given a partial account.
Over time, repeatedly seeking responses based on the same framing could strengthen an existing narrative rather than encourage a broader examination of the situation.
Therapy Does Not Always Mean Immediate Agreement
One misconception about emotional support is that helpful conversations should always make someone feel better immediately.
Therapy can involve support and validation, but it can also require reflection, difficult questions, examination of recurring behaviors, and consideration of alternative interpretations.
Joshua Shuman of Dayton explains that this is one reason replacing therapy with AI presents concerns. Psychological growth may sometimes involve exploring something a person would rather avoid instead of immediately reducing the discomfort surrounding it.
A psychologist can notice recurring themes across sessions and ask why the same conflict, fear, or response continues appearing. That process is different from repeatedly generating a comforting answer to an isolated question.
AI Responses Depend Heavily on the Prompt
Chatbot responses can change significantly depending on how a question is phrased.
A person asking why another individual is treating them unfairly has already embedded an assumption into the question. Asking what alternative explanations might exist could generate a very different response.
Joshua Shuman of Dayton points to this as another reason users should be cautious about assigning excessive authority to AI-generated mental health guidance. The output can reflect the assumptions built into the input.
This point becomes particularly relevant when someone is upset and looking primarily for confirmation.
A professional therapeutic conversation has the potential to examine the assumptions themselves rather than simply responding within them.
AI Can Be a Tool Without Becoming the Therapist
Recognizing these limitations does not require rejecting artificial intelligence altogether.
AI can have practical uses related to general mental health education. Someone might use it to organize questions before an appointment, learn general terminology, create a journaling structure, or locate publicly available resources.
The distinction, according to Joshua Shuman of Dayton, is between using technology as a tool and allowing it to become a replacement for professional care.
Useful roles for AI may include:
- Organizing thoughts before speaking with a professional
- Generating questions to consider
- Explaining general mental health concepts
- Creating basic journaling prompts
- Helping locate established mental health resources
These uses keep the technology in a supporting role rather than assigning it responsibilities requiring professional judgment.
When AI Use May Be Becoming Too Central
The frequency of chatbot use alone does not necessarily reveal whether it has become problematic. The function it serves may be more important.
Joshua Shuman of Dayton suggests paying attention when AI becomes the place someone repeatedly turns whenever difficult emotions arise, particularly if that behavior begins replacing conversations with professionals or trusted people.
Other warning signs may include repeatedly asking similar questions until a desired answer appears, relying on AI to interpret every interpersonal disagreement, or treating chatbot responses as definitive judgments about mental health.
People experiencing significant or persistent psychological distress should seek assistance from an appropriately qualified mental health professional rather than relying on a chatbot for assessment or treatment.
Preserving the Human Element in Mental Health Care
Artificial intelligence will likely remain part of everyday life, and its ability to produce convincing conversational responses will continue making the boundary between information and perceived understanding important.
Joshua Shuman of Dayton emphasizes that mental health care involves more than receiving comforting words. Therapy can include relationship, context, professional judgment, accountability, observation over time, and the willingness to examine patterns that may be difficult to recognize independently.
AI can provide information almost instantly. What it cannot reproduce is the full human and clinical process through which a trained professional comes to understand an individual over time.
For people struggling emotionally, Joshua Shuman of Dayton explains that keeping this distinction clear can help prevent convenient technology from quietly becoming an emotional validation loop. AI may assist with information and reflection, but when meaningful mental health concerns are involved, accessibility should complement rather than replace qualified human care.
