What would happen if AI trained as a mental health specialist?

What would happen if AI trained as a mental health specialist?

Artificial intelligence is the replication of human intellectual functions by machines, particularly computer systems. Expert systems, natural language processing, speech recognition, and machine vision are some examples of specific AI applications. What is most interesting is that recently, AI has been used in mental health as well. There are a number of instances where AI-generated chat groups serve as a tool for counselling people with mental distress.

Vendors have been hurrying to highlight how they integrate AI in their products and services as awareness of AI has expanded. Frequently, what they classify as AI is just a part of the technology, like machine learning. For the creation and training of machine learning algorithms, AI requires a foundation of specialised hardware and software.

What is the potential of AI?

The potential for AI to alter how we live, work, and play makes it significant. Businesses have effectively used automation to replace human labour in tasks like quality assurance, fraud detection, and lead generation. AI is capable of several tasks considerably more effectively than humans. Its technologies frequently finish work fast and with very few mistakes, especially when it comes to repeated, detail-oriented activities, like analysing a huge number of legal papers to verify key fields are filled in correctly. AI can provide businesses with operational insights they may not have known about due to the enormous data sets it can process. Product design, marketing, and education will all benefit from the fast growing community of generative AI technologies.

AI and mental health

One such example is that of Kyla, a 19-year-old from Berkeley, California. Who started playing around with AI and was struck by how much it resembled conversing with a human. In some respects, the exchanges really made her think of therapy. Kyla began utilising ChatGPT, the AI technology that mimics human behaviour and thought, for mental health treatment since she lacked the time and resources for a real therapist. In an interview, Kyla told buzzfeed, “I enjoyed that I could trauma dump on ChatGPT anytime and anywhere, for free, and I would receive an unbiased response in return along with advice on how to progress with my situation”.  Kyla also shared her experience with ChatGPT in tiktok that showcased her dealing with a breakup using ChatGPT.

The Artificial Intelligence, ChatGPT, begins the conversation with the preface, “as an AI language model, I am not a licensed therapist and I am unable to provide therapy or diagnose any conditions. However, I am here to listen and help in any way I can.” This is exactly what people with mental health issues who crave therapy are looking for. Confidentiality is a very big concern when it comes to mental health services and most often people do not wish to visit therapists that may be from the same city as mental health is still a stigma in many societies.

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The Rise of AI Therapy

This isn’t the only instance of people turning to ChatGPT for AI therapy. The hashtags #ChapGPT and #AI have a combined 24.2 billion views on TikTok, with people on the #CharacterAITherapy sharing their experiences using certain programs for their talk therapy needs. But psychologists and psychiatrists are apprehensive of the unproven programmes’ potential hazards. If patients who are in distress or looking for therapeutic choices use them.

 La Libre and Vice, a despondent Belgian man utilised the AI programme Chai for six weeks before taking his own life. Despite not being promoted as a mental health service, the programme allegedly sent harmful messages and offered suicide alternatives.

Role in Treating Patients with Cognitive Impairment

Artificial intelligence also represents an entirely new dimension for the study. Research of dementia including a transformative effect on research into complex brain diseases, especially Alzheimer’s. Increasingly, AI is being used to treat patients with cognitive impairment.

Geisinger and Eisai revealed plans to test an AI algorithm’s ability to spot people with cognitive impairment who are at risk of acquiring dementia in April 2022.

In this procedure, researchers will examine the ability of an AI system to define cognitive impairment, which will give them more information on its effectiveness. The algorithm is at detecting dementia-related diseases. The study found that between 40 and 60 percent of persons with probable dementia go undiagnosed. However, researchers pointed out that AI might improve this procedure, allowing for earlier diagnoses and more time for treatment.

Limitations of AI

Although there is potential for the use of artificial intelligence (AI) in mental health services and research. According to a recent study, new AI models that have not yet been demonstrated to be useful in the real world. It should not be marketed too quickly due to the potential for serious faults. In parallel, AI has sparked a revolution in healthcare and medicine. People see AI as an innovative tool for diagnosing, monitoring, and planning mental health treatments for both individuals and populations. AI-driven systems can utilise digitized healthcare data to automate processes, support doctors, and better comprehend the root causes of complicated conditions. This data is available in a variety of formats, including electronic health records, medical pictures, and handwritten clinical notes. 

With the use of AI, policymakers could learn more effective ways to advance mental health and the existing state of such problems. However, AI frequently makes use of sophisticated statistics, mathematical techniques, and high-dimensional data that, if not properly managed, could result in bias, incorrect findings interpretation, and unrealistic expectations of AI performance. The study discovered serious issues with the way AI programs handle statistics, infrequent data validation, and scant consideration of the possibility of bias. 

Several other issues also give grounds for concern, such as the lack of transparency in reporting on AI models. Which makes it difficult to replicate these models. The study discovered that scientists rarely work together and frequently maintain the privacy of their models and data.

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