Isn't "hallucinate" anthropomorphizing as well? Likewise for "confabulating".

Naomi Klein wrote in The Guardian, "Why not algorithmic junk? Or glitches?" I think those are pretty descriptive and not anthropomorphic.

I guess so, but hallucination doesn't imply intent.

Ascribing "hallucination" to an algorithm does reinforce anthropomorphizing however.

But it also helps lowering ourselves from the pedestal.

We don't yet understand how our brains work but they do "work" somehow and a lot can be understood by looking at how it "fails".

Hallucinations are an interesting window in how our brains work and seeing similarities with what other processes do can be useful

You make valid and interesting points.

I guess, for me, it is a matter of minimizing bias and implicit personification when considering the value AI has, as well as how to better understand it for what it is.

For example, I can better contemplate the innate intelligence of a whale if I do not attempt to quantify same based on what tools they create.

Perhaps that is just me though.

Agreed. it's just the probabilistic language model running away with generating next (token | word | phrase | sentence | paragraph ) or however it really works under the hood. Rather different than what is going on within the noggin of a human who is hallucinating.

Isn't that sort of how actual confabulation works? Between various inputs and certain fractured or corrupted "memories" a new input is generated that would attempt to satisfy the initial prompt?

*new output is generated

I like the term “synthesize”. Sometimes what the user wants is non-factual. The other terms have a negative connotation when it could very well be an acceptable response for a given request.

That doesn't really convey the non-factuality or "correctness" of the answer relative to the context and expected output. Every answer is in some sense "synthesized" so its not really a meaningful way to distinguish output. Confabulation seems to me to be the least-problematic way of describing it.

I prefer it’s displaying abductive reasoning. It’s able to produce likely answers with limited information or confounding information. It’s a type of reasoning that falls between inductive and deductive reasoning, and is a type of reasoning AI has been before now poor at.

Note that reasoning isn’t itself accurate in that LLMs have no agency. But they display characteristics of abductive reasoning. By integrating LLMs into goal based agents and tying them together with inductive and deductive solvers, optimizers, and IR systems you can probably get very close to a system that can truly reason.

I agree with your overall description, but I still think reasoning is a term requiring autonomy.

A calculator doesn't reason.

'Abductive reasoning' in this special ML sense is a matter of statistical calculation.

My point being that we should stop implying that we're reconstructing human behavior, when what we are doing is _mimicking it_ through advanced recursion and statistics over huge amounts of inputs (big data).

Abductive reasoning OTOH relies on huge imperfections: human bias, flawed logic, misremembered facts, invented facts, all of whom are culturally situated, a sense of abstract self, a biological self and always an overarching, immanent telos.

Speculatively we might be inventing an entirely new category of existence whose logical categories (such as a special case 'abductive reasoning') cannot be understood in anthropomorphic terminology without distorting it. To me that's still science fiction, so far I've only seen automatons; shallow mimicking robots.

I agree that we won’t create a human intelligence. If we create an intelligence it’ll at best be a warped “something else.” However I’ll make the trite point that I don’t think we understand what makes human intelligence manifest. There’s no reason to believe its not at its basis a statistical optimization based on reinforced gradient descent. In fact it’s fairly likely to be the case. My assertion is as we mix other AI techniques in a feedback cycle we will see something more than this simple single model exploration can do and it’ll converge to what we would consider intelligence. But I agree fundamentally it won’t map to a human intelligence modality.

Maybe it's anthropomorphic but I like hallucinations because it reminds me of the DeepDream psychedelic generator

> Hallucinates is a far more accurate description.

This is still a form of anthropomorphism.

Every non-deterministic search algorithm (a.k.a. "AI") relies on pseudo-random number generators (PRNG's) and usually employ scoring/weighting functions to determine what the algorithm will search.

Sometimes PRNG values will result in an algorithm searching less likely solution-spaces despite what a scoring function may rate. This is needed in order to avoid over-specialization and allow for edge-case discovery (amongst other benefits). Depending on the algorithm, this may be the only solution proffered.

BS'ing