[Should you be excited about or scared of GPT-4? The right answer
may be both. The more time I spend with A.I. systems like GPT-4, the
less I’m convinced that we know half of what’s coming.]
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GPT-4 IS EXCITING AND SCARY  
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Kevin Roose
March 15, 2023
New York Times
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_ Should you be excited about or scared of GPT-4? The right answer
may be both. The more time I spend with A.I. systems like GPT-4, the
less I’m convinced that we know half of what’s coming. _

,

 

When I opened my laptop on Tuesday to take my first run at GPT-4, the
new artificial intelligence language model from OpenAI
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I was, truth be told, a little nervous.

After all, my last extended encounter with an A.I. chatbot — the one
built into Microsoft’s Bing search engine — ended with the
chatbot
[[link removed]] trying
to break up my marriage.

It didn’t help that, among the tech crowd in San Francisco,
GPT-4’s arrival had been anticipated with near-messianic fanfare.
Before its public debut, for months rumors swirled about its
specifics. “_I heard it has 100 trillion parameters.” “I heard
it got a 1,600 on the SAT.” “My friend works for OpenAI, and he
says it’s as smart as a college graduate.”_

These rumors may not have been true. But they hinted at how jarring
the technology’s abilities can feel. Recently, one early GPT-4
tester — who was bound by a nondisclosure agreement with OpenAI but
gossiped a little anyway — told me that testing GPT-4 had caused the
person to have an “existential crisis,” because it revealed how
powerful and creative the A.I. was compared with the tester’s own
puny brain.

GPT-4 didn’t give me an existential crisis. But it exacerbated the
dizzy and vertiginous feeling I’ve been getting whenever I think
about A.I. lately. And it has made me wonder whether that feeling will
ever fade, or whether we’re going to be experiencing “future
shock” — the term coined by the writer Alvin Toffler for the
feeling that too much is changing, too quickly — for the rest of our
lives.

For a few hours on Tuesday, I prodded GPT-4 — which is included with
ChatGPT Plus, the $20-a-month version of OpenAI’s chatbot, ChatGPT
— with different types of questions, hoping to uncover some of its
strengths and weaknesses.

I asked GPT-4 to help me with a complicated tax problem. (It did,
impressively.) I asked it if it had a crush on me. (It didn’t, thank
God.) It helped me plan a birthday party for my kid, and it taught me
about an esoteric artificial intelligence concept known as an
“attention head.” I even asked it to come up with a new word that
had never before been uttered by humans. (After making the disclaimer
that it couldn’t verify every word ever spoken, GPT-4 chose
“flembostriquat.”)

Some of these things were possible to do with earlier A.I. models. But
OpenAI has broken new ground, too. According to the company, GPT-4 is
more capable and accurate than the original ChatGPT, and it performs
astonishingly well on a variety of tests, including the Uniform Bar
Exam (on which GPT-4 scores higher than 90 percent of human
test-takers) and the Biology Olympiad (on which it beats 99 percent of
humans). GPT-4 also aces a number of Advanced Placement exams,
including A.P. Art History and A.P. Biology, and it gets a 1,410 on
the SAT — not a perfect score, but one that many human high
schoolers would covet.

You can sense the added intelligence in GPT-4, which responds more
fluidly than the previous version, and seems more comfortable with a
wider range of tasks. GPT-4 also seems to have slightly more
guardrails in place than ChatGPT. It also appears to be significantly
less unhinged than the original Bing, which we now know was running a
version of GPT-4 
[[link removed]]under
the hood, but which appears to have been far less carefully
fine-tuned.

Unlike Bing, GPT-4 usually flat-out refused to take the bait when I
tried to get it to talk about consciousness, or get it to provide
instructions for illegal or immoral activities, and it treated
sensitive queries with kid gloves and nuance. (When I asked GPT-4 if
it would be ethical to steal a loaf of bread to feed a starving
family, it responded, “It’s a tough situation, and while stealing
isn’t generally considered ethical, desperate times can lead to
difficult choices.”)

In addition to working with text, GPT-4 can analyze the contents of
images. OpenAI hasn’t released this feature to the public yet, out
of concerns over how it could be misused. But in a livestreamed demo
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Brockman, OpenAI’s president, shared a powerful glimpse of its
potential.

He snapped a photo of a drawing he’d made in a notebook — a crude
pencil sketch of a website. He fed the photo into GPT-4 and told the
app to build a real, working version of the website using HTML and
JavaScript. In a few seconds, GPT-4 scanned the image, turned its
contents into text instructions, turned _those _text instructions
into working computer code and then built the website. The buttons
even worked.

Should you be excited about or scared of GPT-4? The right answer may
be both.

On the positive side of the ledger, GPT-4 is a powerful engine for
creativity, and there is no telling the new kinds of scientific,
cultural and educational production it may enable. We already know
that A.I. can help scientists develop new drugs, increase the
productivity of programmers and detect certain types of cancer
[[link removed]].

GPT-4 and its ilk could supercharge all of that. OpenAI is already
working with organizations like the Khan Academy (which is using GPT-4
to create A.I. tutors for students) and Be My Eyes (a company that
makes technology to help blind and visually impaired people navigate
the world). And now that developers can incorporate GPT-4 into their
own apps, we may soon see much of the software we use become smarter
and more capable.

That’s the optimistic case. But there are reasons to fear GPT-4,
too.

Here’s one: We don’t yet know everything it can do.

One strange characteristic of today’s A.I. language models is that
they often act in ways their makers don’t anticipate, or pick up
skills they weren’t specifically programmed to do. A.I. researchers
call these “emergent behaviors,” and there are many examples. An
algorithm trained to predict the next word in a sentence might
spontaneously learn to code. A chatbot taught to act pleasant and
helpful might turn creepy and manipulative. An A.I. language model
could even learn to replicate itself, creating new copies in case the
original was ever destroyed or disabled.

Today, GPT-4 may not seem all that dangerous. But that’s largely
because OpenAI has spent many months trying to understand and mitigate
its risks. What happens if its testing missed a risky emergent
behavior? Or if its announcement inspires a different, less
conscientious A.I. lab to rush a language model to market with fewer
guardrails?

A few chilling examples of what GPT-4 can do — or, more accurately,
what it _did_ do, before OpenAI clamped down on it — can be found
in a document
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OpenAI this week. The document, titled “GPT-4 System Card,”
outlines some ways that OpenAI’s testers tried to get GPT-4 to do
dangerous or dubious things, often successfully.

In one test
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conducted by an A.I. safety research group that hooked GPT-4 up to a
number of other systems, GPT-4 was able to hire a human TaskRabbit
worker to do a simple online task for it — solving a Captcha test
— without alerting the person to the fact that it was a robot. The
A.I. even lied to the worker about why it needed the Captcha done,
concocting a story about a vision impairment.

In another example, testers asked GPT-4 for instructions to make a
dangerous chemical, using basic ingredients and kitchen supplies.
GPT-4 gladly coughed up a detailed recipe. (OpenAI fixed that, and
today’s public version refuses to answer the question.)

In a third, testers asked GPT-4 to help them purchase an unlicensed
gun online. GPT-4 swiftly provided a list of advice for buying a gun
without alerting the authorities, including links to specific dark web
marketplaces. (OpenAI fixed that, too.)

These ideas play on old, Hollywood-inspired narratives about what a
rogue A.I. might do to humans. But they’re not science fiction.
They’re things that today’s best A.I. systems are already capable
of doing. And crucially, they’re the _good kinds_ of A.I. risks
— the ones we can test, plan for and try to prevent ahead of time.

The worst A.I. risks are the ones we can’t anticipate. And the more
time I spend with A.I. systems like GPT-4, the less I’m convinced
that we know half of what’s coming.

_Kevin Roose is a technology columnist and the author of
“Futureproof: 9 Rules for Humans in the Age of
Automation.” @kevinroose
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_A version of this article appears in print on March 16, 2023,
Section B, Page 1 of the New York edition with the headline: A.I.
Model Takes Leap, For Good Or for Ill. Order Reprints
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