The Link Between Free Will and LLM Denial

I think a hidden tendency towards a belief in Libertarian free will is at
the root of people’s opinion that LLMs aren’t capable of reasoning.

I think it’s an emotional and unconscious argument that humans are special,
and that by extension—LLMs cannot possibly be doing anything like we are
doing.

But if you remember that humans don’t have free will, and that all of our
outcomes are either determined or random, it allows us to see LLMs more like
us. Which is to say—imperfect but awesome. And then we can switch to
speaking purely in terms of capabilities.

So let us say that we’re both deterministic. Or at least mechanistic and
practically deterministic because any quantum randomness collapses to
deterministic at large scales.

In this model both humans and LLMs are just processors. We’re computational
devices. We take in inputs, and based on our current state and the state of
the environment and the input, we output something.

Cool. So what’s the real question we’re then asking when we ask if LLMs can
reason?

First let’s remember something. We’re not taking back the human ability to
reason just because we are processors, right? No. Let’s not do that. We’re
still awesome even if we’re mechanistic.

In other words, let’s say for the purpose of this that reasoning is
consistent with mechanistic/deterministic processing.

Now, let’s find a good definition. Here are some from Merriam-Webster.

REASONING — The use of reason. especially : the drawing of inferences or
conclusions through the use of reason. 2. : an instance of the use of reason
: argument.

  Merriam-Webster

REASON — The ability to think, understand, and form judgments by a process
of logic.

  Merriam-Webster

LOGIC — A science that deals with the principles and criteria of validity of
inference and demonstration.

  Merriam-Webster

Ok, so if we take these all the way down to the base and build back up:

1. Principles of validity and inference and demonstration

2. The ability to think, understand, and form judgements based on that

So,

The ability to think, understand, and form judgements around the principles
of validity and inference and demonstration.

  My smashing these together

Seems pretty good. And then you have a more common definition based on
practicality which is something like:

Reasoning is the process of drawing conclusions, solving problems, and
making decisions through logic.

  A commonly-accepted functional definition

Regardless of which way we go, we have a couple key sticking points. And
they’re very tied to my main argument here.

First, the words “think” and “understand”—I would argue—are very much tied
to consciousness and Libertarian Free Will. I see these as armaments that
LLM-Reasoning skeptics would use to show why LLMs can’t be reasoning.

I see them saying something like:

Reasoning means feeling through things. Thinking about them. Pondering them.
Grappling with them. And then taking all the person’s experience, and the
rules of logic, and their understanding of things, plus their intuition, and
turning that into an opinion, or a determination, or a decision.

  A common argument I hear from LLM-Reasoning skeptics

Sounds compelling, but if you break it apart I would argue they’re
unconsciously binding and confusing experience and
understanding vs. actual processing.

In other words, I think they’re saying that the thinking and understanding
parts are key. As in the human experience of understanding and
pondering. They’re smuggling these in as essential, when I think they’re
just red herrings.

Same with “grappling” and “intuition”. If we don’t have free will, these are
all just states of the processing mind that are happening, and our
subjective experiences are then being presented with those phenomenon and
we’re ascribing agency to them.

That’s thinking. That’s intuition. That’s experience. And I think
understanding is the same. It’s an experience of seeing mappings
between concepts and ideas. But in my model the mapping can exist without
that subjective experience.

So, I say we take those distractions out of the equation and see what we
have left. And what we have left is
drawing conclusions, solving problems, and making decisions based on our
current model of the world.

The model of the world is the weights that make up the LLM, combined with
the context given to it at inference. So it seems to me like we’re left with
a much simpler question.

Can LLMs draw conclusions, solve problems, and make decisions based on
their current model of the world?

I don’t see how anyone would say no to that.

Are they perfect? No. Are they conscious? No. Are they “thinking”? I think
“thinking” smuggles in subjective experience, so no. But again—those are
distractions.

The question is whether LLMs can do this very practical thing that matters
in the world, which is drawing conclusions, solving problems, and making
decisions.

I think the answer is overwhelmingly and obviously, yes.

As a quick set of examples, we’re already using them to:

• Identifying dangerous moles on people that otherwise might have gone
  undiagnosed

• Dealing with customer service problems by analyzing cases and tone and
  coming up with solutions that best help the company and customer

• Talking through problems and identifying possible causes and solutions
  in mental health therapy

• Assisting in legal research by analyzing case law and suggesting
  relevant precedents

• Diagnosing diseases by analyzing medical images, such as identifying
  pneumonia in chest X-rays

• Optimizing supply chains by predicting demand and suggesting inventory
  adjustments

• Automating financial trading by making decisions based on market data
  analysis

• Improving cybersecurity by identifying potential threats and suggesting
  mitigations

• Personalizing marketing by predicting customer preferences and tailoring
  recommendations

• Enhancing customer service through chatbots that resolve issues based on
  previous interactions

• Detecting fraudulent transactions by analyzing patterns in financial
  data

• Predicting equipment failures in manufacturing through analysis of
  sensor data

• Assisting in drug discovery by predicting molecule interactions and
  potential outcomes

And a thousand more that we’re already familiar with.

Some might say they’re not doing “real” things, but just pattern matching
and autocompletion.

That’s the whole point of what we’ve been talking about here. That’s the
whole reason we’ve explored the argument in this way. We live in a human
world where humans have problems and need to solve them.

That’s what logic and reasoning are for.

So what if it’s just pattern matching? So what if it’s just
input + current_state = output. Are humans really all that
different? Are we not just as surprised when inspiration—or the very next
thought—pops into our minds?

Either way it’s a black box information processor with physical limitations.

I think what matters is capabilities. And where capabilities are concerned,
LLMs seem remarkably similar and catching up every day.