This kind of transformation is especially spurred through the use of advanced AI, including leveraging deep learning (DL), machine learning (ML), artificial neural networks (ANN), generative AI, and large language models (LLMs). It is a vital pursuit well worth undertaking. Expectations are strong that great results and new insights will be gleaned accordingly.

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).

AI And Mental Health Therapy

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 a quick summary of some of my posted columns on this evolving topic, see the link here, which briefly recaps about forty of the over one hundred column postings that I’ve made on the subject.

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 last year on an episode of CBS 60 Minutes, see the link here.

If you are new to the topic of AI for mental health, you might want to consider reading my recent analysis that also recounts a highly innovative initiative at the Stanford University Department of Psychiatry and Behavioral Sciences called AI4MH, see the link here. Indeed, today’s discussion is substantively shaped around a recent seminar conducted by AI4MH.

The Subjective Vs. The Objective

Let’s begin with a cursory unpacking of what is generally thought of as a type of rivalry or balance amid being subjective versus objective.

The conceptualization of “objective” consists of a quality or property intended to convey that there are hard facts, proven principles and precepts, clear-cut observations, reproducible results, and other highly tangible systemic elements at play. In contrast, “subjective” is characterized as largely speculative, sentiment-based, open to interpretation, and otherwise less ironclad.

Where does the consideration of subjective vs. objective often arise?

You might be surprised to know that the question of subjective versus objective has a longstanding root in two fields of endeavor, namely psychology and physics. Yes, it turns out that psychology and physics have historically been domains that richly illuminate the dialogue regarding subjective versus objective. The general sense is that people perceive physics as tilted more toward the objective and less toward the subjective, while the perception of psychology is that it is a field angled toward the subjective side more so than the objective.

Turn back the clock to the 1890s, in which the famed Danish professor Harald Hoffding made these notable points about psychology and physics (source: “Outlines of Psychology” by Harald Hoffding, London Macmillan, 1891):

• “Psychology is the science of mind -- that is the shortest description we can give of the subject of the present inquiries.”
• “It serves merely to mark psychology as the science of that which thinks, feels, and wills, in contrast with physics as the science of that which moves in space and occupies space.”
• “These two provinces include everything that can be the subject of human research.”

You might notice the rather stunning point that psychology and physics are themselves inclusive of everything that could potentially be the subject of human research. That’s amazingly alluring to those in the psychology and physics fields, while perhaps not quite as affable for all other domains.

In any case, on the thorny matter of subjective versus objective in the psychology realm, we can recall Pavlov’s remarks made in 1930:

• “I am convinced that an important stage of human thought will have been reached when the physiological and the psychological, the objective and the subjective, are actually united, when the tormenting conflicts or contradictions between my consciousness and my body will have been factually resolved or discarded.” (source: “Physiology of the Higher Nervous Activity” by Ivan Petrovich Pavlov, 1930, in C. Murchison (Ed.), Psychologies of 1930, Clark University Press).

Pavlov’s comments reflect a longstanding aspiration of the field of psychology to ascertain and verify bona fide means to augment the subjective aspects of mental health analysis with more exacting objective measures and precepts.

The final word on this goes to Albert Einstein as to the heady matter:

• “Body and soul are not two different things, but only two different ways of perceiving the same thing. Similarly, physics and psychology are only different attempts to link our experiences together by way of systematic thought.” (source: Albert Einstein in 1937 as cited in “Albert Einstein: The Human Side” by Helen Dukas and Banesh Hoffman, Princeton University Press, 1979).

It’s always an uphill battle to refute remarks made by Einstein, so let’s take them as they are.

Recent Seminar By Stanford AI4MH

Shifting gears, the topic of psychology and the challenging properties of subjective vs. objective was a major theme during a recent seminar undertaken by Stanford University on May 28, 2025, at the Stanford campus.

Conducted by the initiative known as AI4MH (Artificial Intelligence for Mental Health), see the link here, within the Stanford School of Medicine, Department of Psychiatry and Behavioral Sciences, the session was entitled “Insights from AI4MH Faculty: Transforming Mental Health Research with AI” and a video recording of the session can be found at the link here.

The moderator and the three speakers consisted of:

• Moderator: Dr. Kilian M Pohl, AI4MH Lead, Professor of Psychiatry and Behavioral Sciences (Major Labs and Incubator) and, by courtesy, of Electrical Engineering.
• First speaker: Dr. Kaustubh Supekar, Clinical Associate Professor, Psychiatry and Behavioral Sciences, Stanford University School of Medicine.
• Second speaker: Dr. Ehsan Adeli, Assistant Professor (Research) of Psychiatry and Behavioral Sciences (Public Mental Health and Population Sciences) and, by courtesy, of Computer Science and of Biomedical Data Science, Stanford University.
• Third speaker: Dr. Shannon Wiltsey Stirman, Professor of Psychiatry and Behavioral Sciences (Public Mental Health and Population Sciences), Stanford University.

I attended the session and will provide a recap and analysis here. In addition, I opted to look at various research papers by the speakers. I encompass selected aspects from the papers to further whet your appetite for learning more about the weighty insights provided during the seminar and based on their respective in-depth research studies.

I’ll proceed next in the same sequence as occurred during the seminar, covering each speaker one at a time, and then offer some concluding thoughts.

The Brain-Mind Matters

The human brain consists of around 86 billion neurons and approximately 100 trillion synapses. This elaborate organ in our noggin is often referred to in the AI field as the said-to-be wetware of humans. That’s a cheeky sendoff of computer-based hardware and software.

Somehow, in ways that we still aren’t quite sure, the human brain or wetware gives rise to our minds and our ability to think. In turn, we are guided in what we do and how we act via the miracle of what’s happening in our minds. For my related discussion about the Theory of Mind (ToM) and its relationship to the AI realm, see the link here.

In the presentation by Dr. Kaustubh Supekar, he keenly pointed out that the brain-mind indubitably is the source of our mental health and ought to be closely studied when trying to ascertain the causes of mental disorders. He and his team are using AI to derive brain fingerprints that can be associated with mental disorders.

It’s quite exciting to envision that we could eventually end up with a tight mapping between the inner workings of the brain-mind and how mental disorders manifest within the brain-mind. Imagine the incredible possibilities of anticipating, remedying, or at least aiding those incurring mental disorders.

In case you aren’t familiar with the formal definition of what mental disorders consist of, I covered the DSM-5 guidelines in a posting on AI-driven therapy using DSM-5, see the link here, and included this definition from the well-known manual:

• “A mental disorder is a syndrome characterized by clinically significant disturbance in an individual’s cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning.”

DSM-5 is a widely accepted standard and is an acronym for the Diagnostic and Statistical Manual of Mental Disorders fifth edition, which is promulgated by the American Psychiatric Association (APA). The DSM-5 guidebook or manual serves as a venerated professional reference for practicing mental health professionals.

In a recent research article that Dr. Kaustubh Supekar was the lead author of, entitled “Robust And Replicable Functional Brain Signatures Of 22q11.2 Deletion Syndrome And Associated Psychosis: A Deep Neural Network-Based Multi-Cohort Study” by Kaustubh Supekar, Carlo

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