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Episode Transcript
I keep seeing this advice pop up online. Just tell
the AI to act like a university professor, as if
that one line magically turns chat, GPT or Gemini into
an expert who suddenly knows more, thinks better, or becomes
more accurate. It sounds clever, it feels like a shortcut,
but it isn't, and recent research backs that up. What
(00:22):
studies and testing have shown is that when you ask
an LM to act like a professor, what actually changes
is not the quality of the information, but the style
of the delivery. The language becomes more formal, the tone
sounds confident, the structure feels authoritative, but the facts underneath
often exactly the same and sometimes wrong. In fact, in
(00:44):
some cases, those mistakes become hard at a spot because
they're delivered with such confidence, and that's where the real
risk lies. Large language models don't understand expertise in the
way humans do. They don't suddenly gain access to hidden
knowledge because you gave them a title. They predict words
based on patterns. When you say act like a professor,
(01:04):
they switch to what academic writing sounds like, not what
academic thinking actually is. And humans are very easily persuaded
by tone. There's another important point here. These models are
designed to always give you an answer even when they're unsure,
even when the information is incomplete. They don't like to
say I don't know, so if you haven't given them
(01:27):
enough context, or if the question itself is vague, the
model will still respond. It will fill in the gaps,
sometimes accurately, sometimes not. This is what people refer to
as hallucination, not lying, not intention just confident guesswork. This
is why shortcuts don't work. If you give an AI
(01:49):
a lazy prompt, you'll get a lazy result. If you
try to skip thinking, research, or structure, the output will
reflect that you only ever get out what you put in.
But when you use these tools properly, they're incredibly powerful.
If you give them clear context, your intent, your structure,
and your constraints, they become excellent assistance. They help refine language,
(02:11):
they improve clarity, they help explore ideas. They do not
replace judgment, they do not replace responsibility, and they absolutely
do not replace thinking. And even the tools themselves say this.
They openly warn that they can make mistakes. That's not
a flaw, that's honesty. The safeguard is the human in
(02:32):
the loop, the person who checks challenges and decides. So
the takeaway is simple. Asking an AI to act like
a professor may make it sound smarter, but intelligence doesn't
come from tone. It comes from guidance, context, and human oversight.
There are no magic prompts, no shortcuts, just better collaboration
(02:54):
between people and machines. AI is an assistant an authority,
and when we treat it that way, it becomes one
of the most useful tools we've ever had.
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