There is a mistake embedded in how our culture talks about the human mind — one so widespread it rarely gets named.
According to venture capitalist and consciousness researcher Adam Pelavin, it may also be one of the most consequential mistakes in the entire AI alignment debate.
The mistake?
Treating neuroscience and psychology as the same thing.
They are not.
And the difference matters more than most people in AI are willing to acknowledge.
Pelavin recently joined Don Finley on The Human Code podcast to unpack what he calls the “missing science” — a gap at the center of how we understand human minds, human values, and what it actually means to build technology that genuinely serves humanity.
As AI systems become more powerful and more embedded in consequential decisions, his argument becomes increasingly difficult to ignore.
Two Sciences, One Mind
Neuroscience studies the biological substrate of the mind:
- Neurons
- Synapses
- Neurotransmitters
- Brain regions
- Electrochemical signaling
It has produced extraordinary breakthroughs in understanding how the brain works — from memory formation and emotional regulation to sensory processing and neurological disorders.
But neuroscience was never designed to answer questions like:
- What does this experience mean to a person?
- How do identity and values shape decisions?
- What creates dignity, agency, or belonging?
- Why do people pursue meaning?
These are not questions about neurons.
They are questions about people.
And they require a different kind of science.
The Analogy That Changes the Conversation
Pelavin offers a simple analogy:
Neuroscience is to psychology as molecular biology is to medicine.
Molecular biology explains cells, proteins, and mechanisms.
But it cannot tell you why a patient is suffering, what their illness means in the context of their life, or what treatment will genuinely improve their wellbeing.
For that, you need medicine — a framework operating at the level of the whole person.
Psychology was meant to be that framework for the mind.
The science of:
- identity
- meaning
- values
- experience
- transformation
Not neurons.
People.
The problem, Pelavin argues, is that we gradually traded psychology for neuroscience — and in doing so, lost something essential.
Why This Becomes an AI Problem
This is not just an academic debate.
We are deploying AI into decisions that shape millions of lives:
- Healthcare recommendations
- Financial guidance
- Education systems
- Hiring decisions
- Criminal justice assessments
- Social media algorithms
Every one of these systems is attempting to optimize for outcomes that are supposedly “good for people.”
But what does good for people actually mean?
Today, most systems rely on thin proxies:
- Behavioral metrics (clicks, engagement, time spent)
- Revealed preferences (what people choose)
- Physiological indicators
Those signals matter.
But they are not the same thing as human flourishing.
Social media offers the clearest example.
Recommendation systems optimized relentlessly for engagement — and in many cases produced more anxiety, polarization, misinformation, and isolation.
Not because engineers were malicious.
Because engagement was a poor substitute for wellbeing.
That gap is the cost of the missing science.
What the Missing Science Would Study
Pelavin argues we need a serious scientific effort focused on the psyche itself.
Questions like:
How is human experience structured?
Not neurologically — phenomenologically.
How do people experience time, meaning, relationships, agency, and suffering?
How do values actually work?
Values are not simple preferences.
They are layered, contextual, contradictory, and deeply tied to identity.
What is the relationship between agency and wellbeing?
Humans need to feel ownership over their lives.
AI systems that optimize outcomes while quietly eroding agency may still create harm.
How does meaning work?
People are meaning-making creatures.
An AI system that optimizes for satisfaction while disrupting purpose, identity, or coherence may still fail profoundly.
What This Means for AI Alignment
AI alignment is trying to answer a difficult question:
How do we ensure AI systems pursue goals that are actually good for humanity?
Pelavin’s argument is not a criticism of alignment researchers.
It is a challenge to broaden the foundation.
You cannot align systems to human values if your model of human values is incomplete.
Otherwise, you are aligning AI to a simplified model — not reality.
And the gap between those two things is where harm emerges.
The solution is not less AI engineering.
It is more investment in understanding the human psyche with equal seriousness.
The Good News
Pelavin is optimistic.
The science may be incomplete — but it is not impossible.
We already have knowledge scattered across:
- Psychology
- Philosophy
- Literature
- Narrative research
- Contemplative traditions
- Clinical practice
What is missing is not raw material.
What is missing is the willingness to integrate it into a rigorous, well-funded science of human experience.
And given what is at stake — AI systems making decisions at unprecedented scale — that investment is becoming increasingly urgent.
The most powerful technology in human history is being built right now.
The question is whether we build it on a complete understanding of what it means to be human — or the incomplete model we have been settling for.
Pelavin’s answer is clear:
We can do better. We have to.
Listen to the Full Conversation
YouTube:
https://www.youtube.com/@TheHumanCode888
Spotify:
https://open.spotify.com/show/6SdOzNrG63cUIYz6rUri68
Apple Podcasts:
https://podcasts.apple.com/us/podcast/the-human-code/id1738092975
Read the full blog post:
https://findustries.co/the-missing-piece-of-ai-alignment-understanding-the-human-psyche/
