The design of transformers (including LLMs and multi-modal transformer-based models such as OpenAI's image generators) is to attend to relevant details. OpenAI did this at first without guardrails. In response to public backlash, they bolted on "content filtering," which IMO seems like a very GOFAI approach, and regardless doesn't work very well. It routinely flags innocent prompts, then with crafty prompt hacking will generate these kinds of images.
The design of the model is literally to find patterns and attend to them. The infrastructure and process around an OpenAI model is intended to filter "bad" things (in this case, I agree that the outputs are bad), but is designed to stop some enumerated-ish list of things that aren't allowed, perhaps with some limited "reasoning" about them.
Exactly this. They are pretty damn good at generating and debugging code. Not to a degree where they can replace any actual software engineer, but for hacking together projects or rubber ducking problems with code, they're honestly pretty great.
That's it. I have yet to see a single other application of these things that I would call even 1/5th that good.
Defending the value of these tools is perfectly fine, and well espoused here on HN.
The fact that the average person deals with the harm and exhaust of these tools is a related but separate issue.
That cost isn't the foremost issue when the values are being extolled, but its a major consideration at the societal scale.
Most of us here don't think of NCII being created of us, or being defrauded easily by new tech, or getting sucked into a make-believe world crafted by an LLM.
If you see yourself, as just a coder, or software engineer, then these issues matter less. If you are someone who wants these tools to succeed, or is thinking of the larger implications of GenAI on society, then the costs matter.
So in this regard the model is definitely not working as designed.