AI And The Maximization Versus Optimization Of Human Cognitive Mindfulness

In today’s column, I examine the topic of mindfulness and whether it is feasible or sensible to maximize mindfulness or instead seek to optimize mindfulness. There is an important distinction involved. To help illustrate the matter, I will dip into modern-era generative AI and large language models (LLMs) as a tool for examining mindfulness at human cognition boundaries.

The essence of the situation is this. Conceptual discussions about mindfulness suggest that the ultimate goal is to maximize mindfulness. Thus, one should always be seeking the peak of mindfulness, doing so in all circumstances at all times. But this underplays the downsides of such maximization. The goal should be to optimize mindfulness, namely applying the optimal mindfulness as appropriate for the matter at hand. Optimization is a reasonable and sensible aim, while maximization tends toward being overdone and counterproductive. I will use AI to explore various scenarios to help showcase these tradeoffs.

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).

Intertwining AI And Psychology

As a quick background, I’ve been extensively covering and analyzing a myriad of psychological 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 and LLMs such as ChatGPT, GPT-5, Claude, Gemini, Copilot, Grok, and others. For a recap of my two hundred analyses and postings about AI and mental health, see the link here and the link here. I frequently speak up about these pressing matters, including in an appearance on an episode of CBS’s 60 Minutes; see the link here.

AI And Mindfulness

Maximization Of Mindfulness

Consider this proposition: