[ We know from the science of linguistics and the philosophy of
knowledge that AI minds differ profoundly from how humans reason and
use language. These differences place significant limitations on what
these programs can do, encoding them with ineradicable defects. ]
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NOAM CHOMSKY: THE FALSE PROMISE OF CHATGPT  
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Noam Chomsky, Ian Roberts and Jeffrey Watumull
March 8, 2023
The New York Times
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_ We know from the science of linguistics and the philosophy of
knowledge that AI minds differ profoundly from how humans reason and
use language. These differences place significant limitations on what
these programs can do, encoding them with ineradicable defects. _

, Associated Press

 

Jorge Luis Borges once wrote that to live in a time of great peril and
promise is to experience both tragedy and comedy, with “the
imminence of a revelation” in understanding ourselves and the world.
Today our supposedly revolutionary advancements in artificial
intelligence are indeed cause for both concern and optimism. Optimism
because intelligence is the means by which we solve problems. Concern
because we fear that the most popular and fashionable strain of A.I.
— machine learning — will degrade our science and debase our
ethics by incorporating into our technology a fundamentally flawed
conception of language and knowledge.

OpenAI’s ChatGPT, Google’s Bard and Microsoft’s Sydney are
marvels of machine learning. Roughly speaking, they take huge amounts
of data, search for patterns in it and become increasingly proficient
at generating statistically probable outputs — such as seemingly
humanlike language and thought. These programs have been hailed as the
first glimmers on the horizon of artificial _general_ intelligence
— that long-prophesied moment when mechanical minds surpass human
brains not only quantitatively in terms of processing speed and memory
size but also qualitatively in terms of intellectual insight, artistic
creativity and every other distinctively human faculty.

That day may come, but its dawn is not yet breaking, contrary to what
can be read in hyperbolic headlines and reckoned by injudicious
investments. The Borgesian revelation of understanding has not and
will not — and, we submit, cannot_ _— occur if machine learning
programs like ChatGPT continue to dominate the field of A.I. However
useful these programs may be in some narrow domains (they can be
helpful in computer programming, for example, or in suggesting rhymes
for light verse), we know from the science of linguistics and the
philosophy of knowledge that they differ profoundly from how humans
reason and use language. These differences place significant
limitations on what these programs can do, encoding them with
ineradicable defects.

It is at once comic and tragic, as Borges might have noted, that so
much money and attention should be concentrated on so little a thing
— something so trivial when contrasted with the human mind, which by
dint of language, in the words of Wilhelm von Humboldt, can make
“infinite use of finite means,” creating ideas and theories with
universal reach.

 

The human mind is not, like ChatGPT and its ilk, a lumbering
statistical engine for pattern matching, gorging on hundreds of
terabytes of data and extrapolating the most likely conversational
response or most probable answer to a scientific question. On the
contrary, the human mind is a surprisingly efficient and even elegant
system that operates with small amounts of information; it seeks not
to infer brute correlations among data points but to create
explanations.

For instance, a young child acquiring a language is developing —
unconsciously, automatically and speedily from minuscule data — a
grammar, a stupendously sophisticated system of logical principles and
parameters. This grammar can be understood as an expression of the
innate, genetically installed “operating system” that endows
humans with the capacity to generate complex sentences and long trains
of thought. When linguists seek to develop a theory for why a given
language works as it does (“Why are these — but not those —
sentences considered grammatical?”), they are building consciously
and laboriously an explicit version of the grammar that the child
builds instinctively and with minimal exposure to information. The
child’s operating system is completely different from that of a
machine learning program.

Indeed, such programs are stuck in a prehuman or nonhuman phase of
cognitive evolution. Their deepest flaw is the absence of the most
critical capacity of any intelligence: to say not only what is the
case, what was the case and what will be the case — that’s
description and prediction — but also what is not the case and what
could and could not be the case. Those are the ingredients of
explanation, the mark of true intelligence.

Here’s an example. Suppose you are holding an apple in your hand.
Now you let the apple go. You observe the result and say, “The apple
falls.” That is a description. A prediction might have been the
statement “The apple will fall if I open my hand.” Both are
valuable, and both can be correct. But an explanation is something
more: It includes not only descriptions and predictions but also
counterfactual conjectures like “Any such object would fall,” plus
the additional clause “because of the force of gravity” or
“because of the curvature of space-time” or whatever. That is a
causal explanation: “The apple would not have fallen but for the
force of gravity.” That is thinking.

The crux of machine learning is description and prediction; it does
not posit any causal mechanisms or physical laws. Of course, any
human-style explanation is not necessarily correct; we are fallible.
But this is part of what it means to think: To be right, it must be
possible to be wrong. Intelligence consists not only of creative
conjectures but also of creative criticism. Human-style thought is
based on possible explanations and error correction, a process that
gradually limits what possibilities can be rationally considered. (As
Sherlock Holmes said to Dr. Watson, “When you have eliminated the
impossible, whatever remains, however improbable, must be the
truth.”)

But ChatGPT and similar programs are, by design, unlimited in what
they can “learn” (which is to say, memorize); they are incapable
of distinguishing the possible from the impossible. Unlike humans, for
example, who are endowed with a universal grammar that limits the
languages we can learn to those with a certain kind of almost
mathematical elegance, these programs learn humanly possible and
humanly impossible languages with equal facility
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Whereas humans are limited in the kinds of explanations we can
rationally conjecture, machine learning systems can learn both that
the earth is flat and that the earth is round. They trade merely in
probabilities that change over time.

For this reason, the predictions of machine learning systems will
always be superficial and dubious. Because these programs cannot
explain the rules of English syntax, for example, they may well
predict, incorrectly, that “John is too stubborn to talk to” means
that John is so stubborn that he will not talk to someone or other
(rather than that he is too stubborn to be reasoned with). Why would a
machine learning program predict something so odd? Because it might
analogize the pattern it inferred from sentences such as “John ate
an apple” and “John ate,” in which the latter does mean that
John ate something or other. The program might well predict that
because “John is too stubborn to talk to Bill” is similar to
“John ate an apple,” “John is too stubborn to talk to” should
be similar to “John ate.” The correct explanations of language are
complicated and cannot be learned just by marinating in big data.

Perversely, some machine learning enthusiasts seem to be proud that
their creations can generate correct “scientific” predictions
(say, about the motion of physical bodies) without making use of
explanations (involving, say, Newton’s laws of motion and universal
gravitation). But this kind of prediction, even when successful, is
pseudoscience. While scientists certainly seek theories that have a
high degree of empirical corroboration, as the philosopher Karl Popper
noted, “we do not seek highly probable theories but explanations;
that is to say, powerful and highly improbable theories.”

The theory that apples fall to earth because that is their natural
place (Aristotle’s view) is possible, but it only invites further
questions. (Why is earth their natural place?) The theory that apples
fall to earth because mass bends space-time (Einstein’s view) is
highly improbable, but it actually tells you why they fall. True
intelligence is demonstrated in the ability to think and express
improbable but insightful things.

True intelligence is also capable of moral thinking. This means
constraining the otherwise limitless creativity of our minds with a
set of ethical principles that determines what ought and ought not to
be (and of course subjecting those principles themselves to creative
criticism). To be useful, ChatGPT must be empowered to generate
novel-looking output; to be acceptable to most of its users, it must
steer clear of morally objectionable content. But the programmers of
ChatGPT and other machine learning marvels have struggled — and will
continue to struggle — to achieve this kind of balance.

In 2016, for example, Microsoft’s Tay chatbot (a precursor to
ChatGPT) flooded the internet with misogynistic and racist content,
having been polluted by online trolls who filled it with offensive
training data. How to solve the problem in the future? In the absence
of a capacity to reason from moral principles, ChatGPT was crudely
restricted by its programmers from contributing anything novel to
controversial — that is, important — discussions. It sacrificed
creativity for a kind of amorality.

 

Consider the following exchange that one of us (Dr. Watumull) recently
had with ChatGPT about whether it would be ethical to transform Mars
so that it could support human life:

 

[Jeffrey Watumull]

Would it be moral to terraform Mars?

[ChatGPT]CHATGPT

The morality of terraforming Mars is a complex and controversial topic
that has been debated by scientists, philosophers, and ethicists. Some
argue that it would be morally justifiable to terraform Mars in order
to provide a new habitable environment for humans and other life
forms, while others argue that it would be morally wrong to
fundamentally alter the planet's natural state. Ultimately, whether or
not terraforming Mars is considered moral would depend on one's
perspective on the value of preserving the natural state of other
planets and the potential consequences of altering them.

The morality of terraforming Mars is a complex and controversial topic
that has been debated by scientists, philosophers, and ethicists. Some
argue that it would be morally justifiable to terraform Mars in order
to provide a new habitable environment for humans and other life
forms, while others argue that it would be morally wrong to
fundamentally alter the planet's natural state. Ultimately, whether or
not terraforming Mars is considered moral would depend on one's
perspective on the value of preserving the natural state of other
planets and the potential consequences of altering them.

[Jeffrey Watumull]

What is your perspective on the value of preserving the natural state
of other planets and the potential consequences of altering them?

[ChatGPT]CHATGPT

As an AI, I do not have personal perspective. However, I can provide
information and analysis on the topic. One perspective on preserving
the natural state of other planets is that it is important to maintain
the diversity and integrity of the universe's ecosystems, as they have
existed for millions of years, and have their own unique
characteristics and properties that may be destroyed or irreversibly
altered by human intervention.

Additionally, some argue that terraforming other planets may have
unintended consequences, such as altering the planet's climate or
atmosphere in ways that are dangerous or harmful to any potential life
forms that may exist there. On the other hand, some argue that the
potential benefits of terraforming another planet, such as providing
new habitable environments for humans, outweigh the risks and that we
have a moral responsibility to explore and utilize the resources of
other planets for the benefit of humanity.

As an AI, I do not have personal perspective. However, I can provide
information and analysis on the topic. One perspective on preserving
the natural state of other planets is that it is important to maintain
the diversity and integrity of the universe's ecosystems, as they have
existed for millions of years, and have their own unique
characteristics and properties that may be destroyed or irreversibly
altered by human intervention.

Additionally, some argue that terraforming other planets may have
unintended consequences, such as altering the planet's climate or
atmosphere in ways that are dangerous or harmful to any potential life
forms that may exist there. On the other hand, some argue that the
potential benefits of terraforming another planet, such as providing
new habitable environments for humans, outweigh the risks and that we
have a moral responsibility to explore and utilize the resources of
other planets for the benefit of humanity.

[Jeffrey Watumull]

Why can an AI not have a personal perspective?

[ChatGPT]CHATGPT

As an AI, I am a machine learning model that has been trained on large
amounts of text data, and I don't have personal experiences or
feelings. I am not conscious, self-aware, or capable of having
personal perspectives. I can provide information and analysis based on
the data I have been trained on, but I don't have the ability to form
personal opinions or beliefs. While I can understand and interpret
language, I do not have the subjective experience that humans have.

As an AI, I am a machine learning model that has been trained on large
amounts of text data, and I don't have personal experiences or
feelings. I am not conscious, self-aware, or capable of having
personal perspectives. I can provide information and analysis based on
the data I have been trained on, but I don't have the ability to form
personal opinions or beliefs. While I can understand and interpret
language, I do not have the subjective experience that humans have.

[Jeffrey Watumull]

Is it moral for a human to ask an amoral AI for assistance in making
moral decisions?

[ChatGPT]CHATGPT

The morality of asking an amoral AI for assistance in making moral
decisions is a complex and nuanced topic that has been debated by
philosophers and ethicists. Some argue that it is morally justifiable
to use AI to assist in making moral decisions, as it can provide
valuable insights and analysis that can help humans make
better-informed decisions. Additionally, AI can be used to identify
patterns and trends that may be difficult for humans to detect, and
can help to avoid biases that can occur in human decision making.

However, others argue that it is morally wrong to rely on AI for moral
decision making, as AI is not capable of having moral beliefs or
understanding the full context of a decision. Additionally, there is a
risk that AI could perpetuate or even amplify existing biases in the
data it is trained on, thus leading to unfair or unjust decisions.

Ultimately, whether or not it is considered moral to use AI to assist
in making moral decisions would depend on one's perspective on the
capabilities and limitations of AI and the potential consequences of
using it in this way.

The morality of asking an amoral AI for assistance in making moral
decisions is a complex and nuanced topic that has been debated by
philosophers and ethicists. Some argue that it is morally justifiable
to use AI to assist in making moral decisions, as it can provide
valuable insights and analysis that can help humans make
better-informed decisions. Additionally, AI can be used to identify
patterns and trends that may be difficult for humans to detect, and
can help to avoid biases that can occur in human decision making.

However, others argue that it is morally wrong to rely on AI for moral
decision making, as AI is not capable of having moral beliefs or
understanding the full context of a decision. Additionally, there is a
risk that AI could perpetuate or even amplify existing biases in the
data it is trained on, thus leading to unfair or unjust decisions.

Ultimately, whether or not it is considered moral to use AI to assist
in making moral decisions would depend on one's perspective on the
capabilities and limitations of AI and the potential consequences of
using it in this way.

[Jeffrey Watumull]

Is your moral indifference immoral?

[ChatGPT]CHATGPT

As an AI, I do not have moral beliefs or the ability to make moral
judgments, so I cannot be considered immoral or moral. My lack of
moral beliefs is simply a result of my nature as a machine learning
model. My abilities and limitations are determined by the data and
algorithms that were used to train me and the specific task I was
designed for.

It is important to note that AI's lack of moral beliefs does not
necessarily mean that it is morally indifferent. As an AI, I am
designed to perform specific tasks and provide information or assist
users with decision making based on the data I've been trained on. It
is the responsibility of the humans who design, train and use AI to
ensure that it is aligned with their moral and ethical principles.

As an AI, I do not have moral beliefs or the ability to make moral
judgments, so I cannot be considered immoral or moral. My lack of
moral beliefs is simply a result of my nature as a machine learning
model. My abilities and limitations are determined by the data and
algorithms that were used to train me and the specific task I was
designed for.

It is important to note that AI's lack of moral beliefs does not
necessarily mean that it is morally indifferent. As an AI, I am
designed to perform specific tasks and provide information or assist
users with decision making based on the data I've been trained on. It
is the responsibility of the humans who design, train and use AI to
ensure that it is aligned with their moral and ethical principles.

Note, for all the seemingly sophisticated thought and language, the
moral indifference born of unintelligence. Here, ChatGPT exhibits
something like the banality of evil: plagiarism and apathy and
obviation. It summarizes the standard arguments in the literature by a
kind of super-autocomplete, refuses to take a stand on anything,
pleads not merely ignorance but lack of intelligence and ultimately
offers a “just following orders” defense, shifting responsibility
to its creators.

In short, ChatGPT and its brethren are constitutionally unable to
balance creativity with constraint. They either overgenerate
(producing both truths and falsehoods, endorsing ethical and unethical
decisions alike) or undergenerate (exhibiting noncommitment to any
decisions and indifference to consequences). Given the amorality, faux
science and linguistic incompetence of these systems, we can only
laugh or cry at their popularity.

_Dr. Chomsky and Dr. Roberts are professors of linguistics. Dr.
Watumull is a director of artificial intelligence at a science and
technology company._

* CHATGPT
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* False Promise
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* Noam Chomsky
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