What happens when people don't understand how AI works

What does "thinking" even mean? It turns out that some intelligence can emerge from this stochastic process. LLM can do math and can play chess despite not trained for it. Is that not thinking?

Also, could it be possible that are our brains do the same: generating muscle output or spoken output somehow based on our senses and some "context" stored in our neural network.

Modern chat-oriented LLMs are not simply statistical models trained on web scale datasets. Instead, they are the result of a two-stage process: first, large-scale pretraining on internet data, and then extensive fine-tuning through human feedback. Much of what makes these models feel responsive, safe, or emotionally intelligent is the outcome of thousands of hours of human annotation, often performed by outsourced data labelers around the world. The emotional skill and nuance attributed to these systems is, in large part, a reflection of the preferences and judgments of these human annotators, not merely the accumulation of web text.

So, when you interact with an advanced LLM, you’re not just engaging with a statistical model, nor are you simply seeing the unfiltered internet regurgitated back to you. Rather, you’re interacting with a system whose responses have been shaped and constrained by large-scale human feedback—sometimes from workers in places like Kenya—generalized through a neural network to handle any topic you bring up.

Words have power, and those that create words - or create machines that create words - have responsibility and liability.

It is not enough to say "the reader is responsible for meaning and their actions". When people or planet-burning random matrix multipliers say things and influence the thoughts and behaviors of others there is blame and there should be liability.

Those who spread lies that caused people to storm the Capitol on January 6th believing an election to be stolen are absolutely partially responsible even if they themselves did not go to DC on that day. Those who train machines that spit out lies which have driven people to racism and genocide in the past are responsible for the consequences.

Just looking at my recent AI prompts:

I was looking for the name of the small fibers which form a bird’s feather. ChatGPT told me they are called “barbs”. Then using straight forward google search i could verify that indeed that is the name of the thing i was looking for. How is this “divination”?

I was looking for what is the g-code equivalent for galvo fiber lasers are and ChatGPT told me there isn’t really one. The closest might be the sdk of ezcad, but it also listed several other opensource control solutions too.

Wanted to know what are the hallmarking rules in the UK for an item which consist of multiple pieces of sterling silver held together by a non-metalic part. (Turns out the total weight of the silver matters, while the weight of the non-metalic part does not count.)

Wanted to translate the hungarian phrase “besurranó tolvaj” into english. Out of the many possible translations chatGPT provided “opportunistic burglar” fit the best for what I was looking for.

Wanted to write an sql alchemy model and i had an approximate idea of what fields i needed but couldn’t be arsed to come up with good names for them and find the syntax to describe their types. ChatGPT wrote it for me in seconds what would have taken me at least ten minutes otherwise.

These are “divination” only in a very galaxy brained “oh man, when you open your mind you see everything is divination really”. I would call most of these “information retrieval”. The information is out there the LLM just helps me find it with a convenient interface. While the last one is “coding”.