Munchies:
Do you use AI to write your responses? The all come off as hella soulless.
Also, your premise is flawed. Generative AI stifles creativity. Think of it like a muscle. We all have different starting points, but if we want to improve our use of them, we have to train. AI is like having an exosuit.
Sure, an exosuit will enhance your strength without you needing to spend hours training. But there's a limit to what you can achieve with them. And if you compare what someone can do with an exosuit to what someone can do with training, it's a night-and-day difference. There's a flexibility and agility you can only get with training. Plus, exosuits end up stifling you by putting more strain on your body.
AI is essentially a machine that runs on mathematical probability. Creativity does not work like that. You cannot program generative AI to replicate the same spontaneity and logical leaps a brain (human or otherwise) can do. Maybe one day we will have the technology, but it won't be with generative AI. It will have to be something else entirely.
My apparent soullessness is a stylistic choice — I conduct this debate dispassionately and logically, without responding to provocation.
You are wrong on several points:
"Generative AI stifles creativity" is too broad. It removes routine work and can serve as a stimulus or collaborative partner in creative processes.
"AI = only probability, therefore not creative" ignores that new, surprising, and useful combinations can emerge from probabilities — practically creative.
Your exosuit metaphor is misleading. Better: AI is a powerful toolkit, not a permanent substitute for craft. Tools increase the range and speed of what you can build; they do not replace the skills needed to design and adapt complex, robust solutions.
AI does not automatically inhibit; effects depend on design, use, and user behavior.
Saying AI could never make abstract leaps is careless:
Models learn procedures, concepts, and causal patterns from large datasets and can generalize to new contexts (one-/few‑shot learning).
Hybrid approaches (neural nets + symbolic systems), self‑supervised learning, and reinforcement learning improve planning, abstraction, and reasoning‑like abilities.
In practice, systems already provide complex problem solving, creative strategy suggestions, and surprising insights — not identical to human intuition, but often functionally equivalent.
Claiming such leaps are fundamentally impossible ignores ongoing progress and is therefore an untenable absolute.
In short: your critique may apply in specific cases, but as a blanket judgment it is too narrow.