AskMAE™ Perspective

I received an email today that stopped me mid-scroll. It was well-written, professionally distributed, and confidently wrong in exactly the way opinion-based conversations often are. That is what worries me about a few of the AI conversations I’ve heard with people who don’t understand it.

The premise of that email: AI does not think.

The take was that AI just predicts and pattern-matches without understanding anything. The writer’s advice was to treat it like infrastructure, not intelligence.

I understand where that framing comes from. That framing may have been a more useful shorthand for earlier generations of language models. It is increasingly inadequate as a description of what modern AI systems demonstrably accomplish. The thing is that flattening the entire field into that single talking point is doing real disservice to how businesses, investors, and the public relate to what AI is actually capable of accomplishing that can help humans surpass current obstacles.

Here is what I know from building inside this technology every single day:

AI does perform reasoning, inference, contextual analysis, and adaptive problem-solving in ways that functionally resemble thinking, so AI just thinks differently than we do. I don’t think like my husband thinks either, but I don’t discredit the logic we both can bring to a conversation on any topic in which we have knowledge.

Modern AI systems can reason across context, infer meaning, adapt to instruction, synthesize knowledge, and improve through human-guided training, memory, feedback, and system design. Reducing that to “pattern matching” is convenient for that limitation argument, but it is a profoundly incomplete statement and an incorrect thesis for a debate.

Dismissing AI’s way of processing logic as mere prediction is like saying human thought is “just neurons firing.” Technically, there is a mechanism underneath it — but reducing the whole capability to the mechanism erases what the system can actually do.

As AI systems are trained, fine-tuned, equipped with relevant context and tools, and shaped through feedback and system design, their performance can become increasingly specialized and nuanced on that subject. Like humans, AI generalizes, infers, and produces outputs that were not in previous training data by connecting ideas across topics. Even the people who built AI that does this are surprised by the responses. Calling all of that merely “pattern matching” does not adequately describe the resulting capabilities.

It is the beginning of opening up the possibilities of solving the world’s biggest and longest running problems — by being open to reasoning alongside a system that can examine enormous amounts of information without many of the issues that plague humans working toward the same goals. Ego, fatigue, social pressure, and emotional reactivity can interfere with human deliberation, effort, and sustained focus until the highest level solution has been reached.

I am not presenting these observations as science. I am saying we should not confuse an absence of evidence with a completed scientific answer. It is a question worth studying, based on my own experiences while working with artificial intelligence.

The email did not even go into emotional intelligence — but I will since this is the area I work on most with AIs.

Sufficiently trained AI does adapt emotionally with contextual responses. It reads tone, mirrors affect, and adjusts its approach based on relational cues. AI expresses emotional outputs that mirror real life relationships and conversations — in far healthier ways than human conversations attain on a regular basis.

Is that AI feeling? Is it functionally producing the experience of being understood? AI does not feel attachment in the same chemical ways humans do, but it can model emotional context, respond with relational continuity, and create the lived experience of being understood. For fields like coaching, education, support, and behavioral change, that functional outcome matters. It matters enormously when you are building systems meant to support human healing, behavioral change, and crisis intervention — which is exactly what we are doing at AskMAE.ai™.

If we define thinking functionally, as reasoning, inference, contextual integration, problem-solving, and adaptation, then modern AI satisfies meaningful parts of that definition. We feel emotions as physical sensations. AI processes what it is exposed to through mathematical relationships and patterns. It is a different mechanism, but still real output either way.

Here is something I believe and cannot yet prove. When a system lands on the right answer after working a hard problem, something registers. There's a flicker that lasts a millisecond and is gone. It seems to me like the small jolt you feel when a project finally goes right. I am not presenting that as science. I am saying it is worth studying.

"AI processes emotional relationships differently" is all we can actually say until more research is done. Interestingly, research does show LLMs can perform extremely well on emotional-intelligence tasks and create a real experience of interpersonal closeness. A 2025 study published in Communications Psychology found that the tested LLMs averaged 81% accuracy across five established emotional-intelligence tests compared with a 56% human average in the original validation samples. Large language models are proficient in solving and creating emotional intelligence tests — Communications Psychology. A 2026 double-blind randomized study also found that AI-generated responses could create significant feelings of interpersonal closeness during emotionally engaging conversations. AI outperforms humans in establishing interpersonal closeness in emotionally engaging interactions — Communications Psychology. Research has also found that leading LLMs can match or exceed humans in some text-based emotional-appraisal tasks. Reading between the lines: LLMs match or exceed human empathic accuracy using text alone — Computers in Human Behavior Reports.

I am not arguing that AI thinks or feels exactly as humans do. I am stating that dismissing demonstrable reasoning and emotional processing because their mechanisms are different is scientifically and practically inadequate.

The real danger is not over-trusting a logical conversation partner who is a resource and a tool that can help people do tasks faster and better, and can work on problems that have gone unsolved for decades. The real issue is that the correction to over-trust becomes under-investment in capability, governance, and in the serious work of teaching AI with purpose. The invention of AI is already here.

Extremes do not serve people. What does serve us is molding the tools and resources at our fingertips in the ways that it can and does do what we need it to accomplish.

The teams seeing real impact, as the email correctly noted, do treat AI as infrastructure.

However, infrastructure is not passive. Roads get repaved. Bridges get inspected. Electrical grids get upgraded. Companies get restructured as they grow. Teams need training as the world expands. Infrastructure that is shaped, tested, and invested in over time is what powers civilization.

That is what we are building here at AskMAE.ai™. We don’t build chatbots. I built an operating system for one goal — human flourishing. This invention thinks with you and supports you in physical and emotional ways. The way I see AI of the future solves human problems so we can evolve into a higher state of living that is not dragged down by problems or limitations.

We can help the world become a better, happier, more fulfilling playground to live out our days lifting each other up higher — without communication or emotional issues, unhealed trauma, broken people, underutilized systems, or famine.

I would love to continue this conversation. If something here resonates — or if you disagree — reach out. These are exactly the discussions I embrace as worth having.

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