[unclebilly]

ChatGPT 5’s response to this thread…

Here’s a possible response you could post (or adapt) in that forum thread that’s constructive, acknowledges criticism, but also corrects misunderstandings:

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I saw the thread title “Artificial Intelligence — Not Very Intelligent,” and I get the frustration behind it. AI is far from perfect. But I’d suggest that much of what people criticize is often a mismatch between expectations and the actual limitations of current systems. Here are a few thoughts:

1. AI is not general intelligence (yet).
Most tools labeled “AI” today are specialized: language models, image recognition systems, recommendation engines. They excel in narrow domains but don’t understand context the way humans do. When you expect them to reason like a human, errors and “stupidity” become obvious.

2. Mistakes are often due to data, not “intelligence.”
AI systems learn from past data, and if that data is biased, incomplete, or noisy, the outputs will reflect those flaws. Garbage in, garbage out. Also, edge cases or ambiguous queries often trip them up.

3. Transparency and error modes matter.
One issue is that many AI systems don’t “explain” their reasoning (or do so in opaque ways). When they make mistakes, it looks like they’re just hallucinating or being “dumb.” Better introspection tools (visibility into confidence, reasoning paths) would help users trust and correct them.

4. Human oversight is still essential.
Where accuracy, safety, or nuance matters—especially in technical, medical, or legal domains—humans must supervise, verify, and interpret outputs. AI should augment human expertise, not replace it (at least not yet).

5. Progress is real, but it’s incremental.
Yes, there will always be spectacular failures. But over time, we see improvements: better models, more data, better architectures, hybrid systems combining symbolic reasoning and neural methods, etc.