AI in Mental Health Care: Helpful or Harmful?

Introduction

Artificial intelligence is becoming a regular part of health care, but mental health is a different terrain. Therapy relies on empathy, trust, and the sense that someone understands you as a human being. Machines cannot feel those things, but they are starting to play a role in the way support is delivered. Recent research shows that these tools bring both promise and real risk. Understanding what they can do, and what they absolutely should not do, helps us see where AI belongs in mental health care.

What Happens When AI Tries to Help With Therapy

A Stanford study looked at how AI therapy chatbots compare to real therapists. The results were blunt. When researchers examined the qualities that make a human therapist effective, they focused on empathy, fairness, and the ability to treat every patient equally and fairly. These qualities did not translate well to AI systems.

The study found that AI chatbots produced responses that showed bias and even stigma. The most concerning patterns appeared in reactions related to certain mental health conditions like schizophrenia. The bias was consistent across different models, including the newer ones that are supposed to be more advanced.

Some of the issues raised by this research are outlined below:

• Comments about severe mental health issues that are biased or stigmatized

• Answers that could mislead or discourage at-risk responders

• Lack of emotional understanding that prevents actual progress in therapy

Fun fact: Some mental health chatbots existed as far back as the 1960s, and users even then sometimes believed they were talking to actual support

The main takeaway from this research is simple. AI should not replace therapists. It can sit beside them and assist with tasks, but it should not be the one guiding someone through their darkest moments.

Where AI Can Still Be Useful

Even with its limitations, AI does have strengths. In the wider health care field, AI is used to support efficiency and early detection. Instead of acting as a therapist, it works best when handling the background tasks that help real clinicians do their jobs.

Some helpful uses include:

• Automating reminders and scheduling

• Summarizing patient records for quicker review

• Managing routine communication so clinicians can focus on people

• Analyzing large sets of data to spot early signs of mental health risks

• Monitoring sessions to identify warning signs that may need attention

• Simulating different patient scenarios for training new clinicians

These tools help therapists work more effectively. They remove administrative weight and offer insights that would be difficult to gather manually.

Fun fact: some of the earliest AI tools in psychology were used to train students, not treat patients. The technology was originally designed to help humans learn, not replace them.

Why Regulation Matters

Organizations such as the United Nations and the World Health Organization believe that AI needs strong regulation. The goal is not to stop progress but to make the progress protect rather than harm people. Good regulation makes sure that developers respect autonomy and safety, and that AI grows in a responsible direction.

The main principles recommended by global organizations include:

• Protecting individual autonomy

• Guarding public safety and well-being

• Promoting sustainable and responsible development

Although AI tools are becoming more common, experts believe that thoughtful regulation is what will keep them aligned with the public good.

Final Thoughts

AI in mental health care is not simply helpful or harmful. It is both, depending on the role it plays. The research suggests a clear boundary. AI should be supporting, not replacing, therapists. When it is carefully deployed, AI can manage records, monitor risks, and provide training for clinicians. But when it tries to be a therapist, it introduces bias and causes harm to the very people it's supposed to help.

Treatment of mental illness in the future may be handled by both man and machine. The value will not come from choosing one over the other. It will come from knowing exactly where each one belongs.

Written by Rosie and researched by Sara

2025 The HEAL Project