"AI programs such as LLMs are infamously "black boxes." They achieve a lot that is impressive, but for the most part, we cannot observe all that they are doing when they take an input, such as a prompt you type, and they produce an output, such as the college term paper you requested or the suggestion for your new novel."
"Ever since artificial intelligence programs began impressing the general public, AI scholars have been making claims for the technology's deeper significance, even asserting the prospect of human-like understanding. Scholars wax philosophical because even the scientists who created AI models such as OpenAI's GPT-5 don't really understand how the programs work -- not entirely. Also: OpenAI's Altman sees 'superintelligence' just around the corner - but he's short on details AI's 'black box' and the hype machine"
Artificial intelligence programs have produced impressive results that prompt claims of deeper significance and human-like understanding. Many creators and scholars do not fully understand how advanced models operate, leaving their internal processes effectively opaque. Large language models function as 'black boxes' that transform inputs into outputs without accessible traces of intermediate computation. Researchers and executives often use colloquial terms like 'reasoning', 'thinking', and 'knowing' to describe model behavior, which can imply human-like cognition. Recent rhetoric and marketing have amplified engineering achievements into grander assertions, risking mischaracterization. Clear, specific descriptions of model capabilities and limitations are necessary to avoid hyperbole.
Read at ZDNET
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