By DS —
There is no AI company on earth, currently, that has a Human Intelligence Research Lab. This means a lab that exists just to study and show how human intelligence works. None, zero.
Sedona, AZ — This lab would not cost them as much as AI, and could become more important and profitable than their work on AI — given the world’s population. However, they don’t, even the so-called good people doing AI for humanity research. Something like, for all the investments in AI, this fraction must go to outlining [natural] human intelligence. Human intelligence is human jurisdiction. AI, regardless of whose, is based without, subjecting its availability to facilities.
There is no lab, anywhere — in or of any organization — that has produced a model of how human intelligence works. Simply, there is no lab, currently, anywhere, that seems close to that goal or seeking — directly — to develop and explain how human intelligence works.
There are all kinds of human and machine cognition labs. Many often state that they are using AI to understand the human brain. There is little to no merit to any project whatsoever, around using large language models [LLMs], or other AI approaches toward understanding how human intelligence works. They have no outstanding postulate, no case for probable components — aside from neurons — and no way to show what they are doing, without AI.
Human intelligence is defined as the use of memory [or information] in the brain. Simply, excellence in using what is known is intelligence. Now, how does an individual use what is known to result in intelligence? Say there is information, how does the individual use the information for the best possible outcome, in reality? What was mechanized in the brain? What are the components of intelligence? What are the attributes? How are they similar or different from those of memory, emotion, feeling, and regulation of internal sensations?
Maybe working on human intelligence is so hard it seems impossible. Maybe labs have given up on human intelligence. Maybe some have concluded that human intelligence is hopeless so nothing can be done to change it. However, no matter the excellence of artificial intelligence, it is still not humans’ in terms of unassisted [or unattached] possession. Neurotechnology is also not humans. They are all external and will be externally accessed. They could be owned in some form or controlled by others, or subject to external servicing and management. The are no guarantees that natural intelligence would widely benefit [all humans] no matter their [AI and neurotechnology universal] adoption.
AI in Education
If AI is helping in education, what exactly should AI be helping since AI can do it all, including aspects of work, post-college. Simply, while AI can assist understanding, what can AI currently change or not change, about the [natural, not augmented] efficiency of human intelligence?
How should AI guide learning, that, without AI, learning can advance, naturally? What should be known about how human intelligence works to ensure that the architecture is used to set boundaries about AI’s impending sweep of the educational system?
Human Intelligence
How does any human being pass an exam? Study and answer questions in smart ways? How does anyone do an activity, with great planning and then carefully execution, to have the desired outcome?
Only two factors matter, it appears, in the question of human intelligence, what information exist in the brain and how they go from one point to the other to result in [use as] intelligence?
If complex solutions are sort to problems, what makes figuring them out difficult or otherwise? What can be shown as a basic model of how human intelligence works to prospect approaches to memory, learning, comprehension and problem solving, to move the world forward by humans, wherever located, without ultimate dependencies on AI, or neurotech?
Conceptually, human intelligence is predicated on two factors, electrical and chemical signals, as sets, in clusters of neurons. Electrical and chemical signals organize information [as functions] including memory. The relay [or use] of information across memory areas, results in intelligence.
The model can then show how information is organized and the attributes of the components, to output intelligence. Neurons are conceptually ruled out as the basis of information organization or transportation because they are cells. They are not that flexible. While they send axons in different directions, they, even in clusters, do not configure information or move around to transport it — as extensively as information travels, in the nervous system [for human life and experiences]. Those, theoretically, are the responsibilities of electrical and chemical signals, working as sets, with neurons as their domicile — and carriage.
Human Intelligence Research Lab
Modeling human intelligence based on electrical and chemicals signals — empirically established in neuroscience to be involved in all functions — of neurons [for human experiences] can become a display to show how learning and problem-solving works, to enhance the dynamics of doing so, to [better] prevent AI misuse and abuse in education, training, tasks and so forth.
There are several attributes to show. There are also several directions of information organization to show. As a product or service, it is possible to have this spread, increasing the probabilities for advances, even as artificial intelligence sprawls.
AI would get better. Human intelligence should not be left behind. A dedicated research lab may turn the tide in the favor of humans — directly.
There is recent [May 7, 2025] spotlight in New York Magazine, Everyone Is Cheating Their Way Through College. ChatGPT has unraveled the entire academic project, with the quotes, “College is just how well I can use ChatGPT at this point. Massive numbers of students are going to emerge from university with degrees, and into the workforce, who are essentially illiterate meaning these are people who not only didn’t write the paper but also didn’t read their own paper before submitting it. I was told to grade based on what the essay would’ve gotten if it were a ‘true attempt at a paper.’ So I was grading people on their ability to use ChatGPT. The ideal of college as a place of intellectual growth, where students engage with deep, profound ideas, was gone long before ChatGPT. In a way, the speed and ease with which AI proved itself able to do college-level work simply exposed the rot at the core. It’s not just the students: Multiple AI platforms now offer tools to leave AI-generated feedback on students’ essays. Which raises the possibility that AIs are now evaluating AI-generated papers, reducing the entire academic exercise to a conversation between two robots — or maybe even just one. If I took the time to learn that, instead of just finding it out, would I have learned a lot more? Adolescents benefit from structured adversity, whether it’s algebra or chores. They build self-esteem and work ethic.
There is a new [August 12, 2025] story in The Atlantic, The AI Takeover of Education Is Just Getting Started, stating that, “Using MagicSchool AI, instructors can upload course material and other relevant documents to generate rubrics, worksheets, and report-card comments. Roughly 2.5 million teachers in the United States currently use the platform. This past year, Iowa made an AI-powered reading tutor available to all state elementary schools; elsewhere, chatbots are filling in for school-counselor shortages. Last month, Microsoft pledged to give more than $4 billion toward advancing AI education across K–12 schools, community and technical colleges, and nonprofits. The same week as Microsoft’s announcement, the American Federation of Teachers, one of the country’s largest teachers unions, announced a $23 million partnership with Microsoft, OpenAI, and Anthropic. One of the partnership’s first efforts is a “National Academy for AI Instruction,” opening in New York City this fall, where instructors will learn how to use AI for generating lesson plans and other tasks.”
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