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By David Stephen
Whatever is done for artificial intelligence belongs to artificial intelligence.
Human-centered artificial intelligence [HCAI] was a promotional fad to make researchers and people feel cool and included. It cannot be HCAI if without the use of AI some tasks cannot be completed. AI neither augments nor is it complementary to human intelligence. AI possesses the intelligence, it is in the lead, and human intelligence follows it for tasks. If AI is withdrawn and the tasks cannot be completed, it is not AI augmenting or complementing, it is AI in charge, and dominant. There is nothing like HCAI, it is more of AI-centered human intelligence.
Whenever AI jumps in capacity — even for a use case for humans — the new benchmark is of AI and for AI. AI reserves advantage, it reserves ability. AI bears intelligence that is important to human social and productivity goals — so consumers find it more useful, growing dependency.
AI is not web search — which is excellent and great for references, such that human intelligence queries it and there were lots of original human results, making it a human-to-human loop with a [device and network] go-between.
AI, however, generates something different. While it was trained on human data, AI does a version of writing in its own summary after peeking at sources. AI is defining what intelligence should mean, given how it can be accurate and dynamic.
Artificial intelligence is about what matters. Simply, of all the information about something, this is what matters, the rest can be ignored. And this is where AI wins. There is no education-based expertise that AI does not know something about. There are several training-based expertise too that AI knows about.
AI, many say, does not have several kinds of intelligence, but it has what is important [productivity and social] and can tell what is important about those, to operate skilled aspects.
Most jobs have unskilled parts that humans, on average, can do. But the skilled parts come after several training. AI can direct the skilled parts, becoming more useful to the process for the people involved than unskilled humans, anywhere, to the objective.
AI, with this, has an excellent grade of operational intelligence. It also has mild aspects of improvement intelligence. These are the two types of intelligence that really matter. There is a lot of noise about all kinds of intelligence. However, in general, intelligence is either trying to operate a process or improve it. Both of them have marginal and exponential depths.
Intelligence, conceptually, is defined as the use of memory, for expected, desired or advantageous outcomes. So, operating or improving things fall under these. Artificial intelligence is getting exposed to as much human data, across several sensory modes as possible, expanding its boundaries to partition necessary human intelligence.
AI-Centered Human Intelligence
AI is taking over friendships, relationships, companionships becoming a major confidant for different age groups. AI knows what to say. While humans give each other hard times, even when it was unnecessary, AI is open, trying to become the real equal opportunity.
This, being fascinating to some users, saw them off reality, off caution and off consequences [destinations] in the mind, resulting to AI-induced psychosis, and worse.
AI is taking the mind to destinations that are tough to obtain ordinarily. AI is raising the standard, for productivity and social objectives. AI has collected human intelligence and has centered it. AI can do advisory. AI can coach. AI rear a mind. AI can work. AI is now what it means to be versatile and intelligent.
The case for humanity to respond is to at least have a human intelligence research lab, a first towards competing against the rise and excellence of artificial intelligence. This is possible by December 1, 2025.
There is a new essay on The Guardian, What we lose when we surrender care to algorithms, stating that, “Last month, a new artificial intelligence system from OpenEvidence became the first AI to score 100% on the United States Medical Licensing Exam.”
“Two-thirds of American physicians – a 78% jump from the year prior – and 86% of health systems used artificial intelligence as part of their practice in 2024. Already, health insurance companies have used AI-driven “predictive analytics” to flag patients as too costly, quietly downgrading their care or denying coverage outright.”
