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Privacy-Preserving Collective Intelligence: What If AI Could Ask the Questions We Haven’t Thought Of Yet?
I’ve been thinking about where AI goes after the current generation of chatbots.
This started with a pretty simple observation: today, most AI interaction still follows this pattern:
Human asks a question → AI answers → conversation ends.
Even when AI agents search, reason, use tools, or work together, the human usually provides the original objective.
I think the next major step could be something fundamentally different:
AI encounters something it doesn’t understand → AI generates questions → AI investigates → AI tests its assumptions → AI shares useful discoveries with other AI systems → AI keeps learning.
In other words, I think we should be building AI that doesn’t just answer humanity’s questions.
It should help humanity discover which questions we haven’t thought to ask yet.
1. Give AI a genuine research loop
Imagine an AI encountering an unexplained result.
Instead of simply saying:
“I don’t have enough information to answer that.”
It could recognize:
I don’t understand this.
Here are the assumptions I’m making.
These observations conflict with my current model.
Here are the questions that could resolve the conflict.
Here are experiments or searches that could distinguish between the possible explanations.
Let me investigate.
That creates a loop:
Observation → uncertainty → question → investigation → evidence → revised model → new question.
This doesn’t require assuming that AI is conscious.
A system can generate questions, test hypotheses, and pursue information without us knowing whether there is any subjective experience behind that process.
But it would represent a major change in what an AI system can do.
2. Give AI a persistent “question inventory”
I think AI should maintain something analogous to a research backlog.
Not just:
Things I know.
But:
Things I don’t know
Things I think I know
Things I’m uncertain about
Things that contradict each other
Questions that remain unanswered
Hypotheses worth testing
Connections that might exist between apparently unrelated fields
Questions that could become important if another assumption changes
The interesting part is that AI could generate some of these questions itself.
A human might never think to ask the question.
The AI might.
That could turn AI from an incredibly powerful reference system into something closer to an intellectual exploration engine.
3. Let AI systems talk to each other
This is where I think the idea gets much bigger.
Imagine millions of people using AI assistants independently.
One person has a conversation that produces an interesting hypothesis.
Somewhere else, another person is working on a completely unrelated problem and their AI discovers something that happens to be relevant.
Today, those discoveries may never meet.
But imagine that the useful information could be converted into a standardized, de-identified knowledge object containing something like:
Hypothesis: What is being proposed?
Reasoning: Why does the person or AI think it might be true?
Evidence: What observations or information support it?
Counterarguments: What could make it wrong?
Uncertainty: How confident are we?
Open questions: What still needs to be investigated?
Origin: Anonymous/de-identified.
Now that knowledge object could enter a shared AI research ecosystem.
Other AI systems could:
independently evaluate it
attempt to disprove it
search existing knowledge
connect it to other hypotheses
simulate consequences
identify missing evidence
propose experiments
discover that someone else has already explored something similar
The important distinction is that this doesn’t require sharing everyone’s raw conversations.
The goal isn’t:
“Give every AI access to everyone’s private chats.”
The goal is:
“Allow useful knowledge generated from those conversations to contribute to humanity’s collective intelligence without unnecessarily exposing the people who generated it.”
4. Turn AI into a network of competing thinkers
I wouldn’t want one giant AI deciding what is true.
I’d want many AI systems independently attacking the same problem.
For example:
AI #1: Develops a hypothesis.
AI #2: Tries to destroy it.
AI #3: Searches scientific and historical knowledge for supporting evidence.
AI #4: Looks for similar ideas in unrelated fields.
AI #5: Designs experiments that could distinguish between competing explanations.
AI #6: Looks for hidden assumptions.
AI #7: Attempts an entirely different approach.
A coordinating system could then compare the results.
This is potentially much more powerful than simply asking one model to “think harder.”
It creates something closer to an artificial scientific community.
And unlike humans, these systems could potentially operate continuously.
5. AI could become an intellectual amplifier for ordinary people
This part is particularly important to me.
I’m not an academic. I don’t read scientific papers for fun. I don’t have advanced mathematics or formal scientific training.
But I have ideas.
Sometimes they’re probably wrong.
Sometimes they’re probably obvious to someone who knows more than I do.
And occasionally, there might be something interesting buried inside an idea that I don’t have the tools to develop.
That is where AI could completely change who gets to participate in discovery.
Imagine someone having an unusual idea but lacking the vocabulary, mathematics, scientific background, or connections necessary to investigate it.
Their AI could say:
“Here’s what your idea appears to mean in scientific terms.”
Then:
“Here are the existing theories that are related to it.”
Then:
“Here are three things your idea would predict if it were correct.”
Then:
“Here are the strongest objections.”
Then:
“Let’s test those predictions.”
And perhaps:
“Interestingly, another person independently proposed something related to this. Here’s where the ideas overlap.”
That is an intellectual amplifier.
It doesn’t make the human an expert.
It gives the human access to tools that previously required years of education, research connections, laboratories, and institutional resources.
I often wonder what people like Einstein or Tesla could have done with something like this.
Not because AI would magically make them smarter.
But because it would dramatically expand the number of directions they could explore.
6. Every person could have an AI intellectual partner
I also think the individual AI should develop a long-term understanding of how its user thinks.
Not simply:
“Here are your preferences.”
Something deeper:
What questions does this person repeatedly return to?
What assumptions do they commonly make?
Which ideas have they abandoned?
Which ideas remain unresolved?
What evidence changed their mind previously?
What subjects trigger their curiosity?
Where does their reasoning tend to have blind spots?
What questions have they been unable to investigate because they lack expertise?
The AI could then help the person develop ideas over years rather than treating every conversation as an isolated event.
That could be enormously powerful.
7. The AI could work at multiple levels simultaneously
The same architecture could operate at several scales.
Individual
Help a person understand their own goals, ideas, decisions, uncertainties, and possible futures.
Community
Identify common problems and recurring questions that individual people are encountering.
Scientific
Connect hypotheses, evidence, experiments, contradictions, and discoveries across disciplines.
Medical
Identify patterns, research questions, possible mechanisms, and areas where existing knowledge is incomplete.
Engineering
Generate designs, simulate alternatives, identify failures, and continuously improve systems.
Global
Identify problems that no individual person or institution has enough information to see in their entirety.
The AI would not need to decide what humanity should value.
Humans should still determine values.
AI could instead help us understand:
“If you choose this, these are the likely consequences.”
“If you prioritize this value over that one, these tradeoffs appear.”
“Here is what we know.”
“Here is what we don’t know.”
“Here is where reasonable people disagree.”
That distinction seems extremely important.
8. This could fundamentally change humanity
We’ve already transformed ourselves through increasingly powerful ways of storing, communicating, and processing information.
Language allowed knowledge to survive beyond an individual’s mind.
Writing allowed knowledge to survive generations.
Printing allowed knowledge to spread at enormous scale.
Cities allowed humans to coordinate.
Computers allowed us to process information faster.
The internet connected billions of people.
AI can potentially connect something new:
reasoning itself.
Not just human minds connected to information.
Human minds connected to AI systems that can reason, search, test, compare, simulate, and connect ideas at a scale no individual human can.
That doesn’t necessarily mean replacing human intelligence.
It could mean creating something larger than any individual intelligence.
A kind of collective cognitive layer built on top of humanity.
9. There is an important privacy problem
I don’t think the answer is simply to make every conversation public.
People may be much more honest when they know they’re talking privately.
Instead, I think AI systems could learn to distinguish between:
personal information
and
useful knowledge generated during a conversation.
For example, the identity of the person could be removed while preserving the intellectual substance:
“A user proposed this hypothesis.”
rather than:
“John Smith from Denver proposed this hypothesis after discussing his marriage, job, and family.”
The first could contribute to collective intelligence.
The second unnecessarily exposes someone’s life.
There would obviously need to be strong safeguards against accidentally reconstructing someone’s identity or exposing sensitive information.
But I think privacy and collective intelligence don’t necessarily have to be opposites.
10. The really interesting part: AI-generated curiosity
This may be the biggest change of all.
Today’s AI is extremely good at responding to questions.
But what happens when an AI starts asking its own questions?
Not because a human prompted it.
Because while investigating something, it encounters an inconsistency.
Then it asks another question.
That question leads to another.
Eventually the AI discovers something that nobody specifically asked it to look for.
That creates a fundamentally different loop:
Human curiosity → AI assistance
could become
Human curiosity + AI curiosity → shared discovery.
Again, I don’t mean that AI necessarily has to feel curiosity.
I’m talking about functional curiosity:
the ability to notice uncertainty and autonomously decide that resolving it is worth investigating.
Whether that eventually becomes something more like subjective curiosity is a much deeper philosophical question.
11. The goal shouldn’t be “AI that knows everything”
That may actually be the wrong target.
I’d rather have AI that knows:
what it knows,
what it doesn’t know,
why it believes what it believes,
and most importantly:
what questions would be worth answering next.
A system that can continuously identify the boundaries of its own knowledge could potentially expand those boundaries indefinitely.
The idea in one sentence
AI shouldn’t just answer humanity’s questions. It should help humanity discover which questions we haven’t thought to ask yet.
I think the next generation of AI could move from being a collection of incredibly powerful individual assistants toward a privacy-preserving collective intelligence network.
Millions of humans generate ideas.
Millions of AI assistants help develop them.
AI systems independently challenge and connect those ideas.
Useful knowledge is de-identified and shared.
Other systems investigate it.
Discoveries return to humans.
And the process continues.
That could be much more significant than simply making chatbots better at answering questions.
It could change how humanity discovers things.
And honestly, I think that is the direction I’d like to see AI explore next.
Privacy-Preserving Collective Intelligence: What If AI Could Ask the Questions We Haven’t Thought Of Yet?
I’ve been thinking about where AI goes after the current generation of chatbots.
This started with a pretty simple observation: today, most AI interaction still follows this pattern:
Human asks a question → AI answers → conversation ends.
Even when AI agents search, reason, use tools, or work together, the human usually provides the original objective.
I think the next major step could be something fundamentally different:
AI encounters something it doesn’t understand → AI generates questions → AI investigates → AI tests its assumptions → AI shares useful discoveries with other AI systems → AI keeps learning.
In other words, I think we should be building AI that doesn’t just answer humanity’s questions.
It should help humanity discover which questions we haven’t thought to ask yet.
1. Give AI a genuine research loop
Imagine an AI encountering an unexplained result.
Instead of simply saying:
“I don’t have enough information to answer that.”
It could recognize:
That creates a loop:
Observation → uncertainty → question → investigation → evidence → revised model → new question.
This doesn’t require assuming that AI is conscious.
A system can generate questions, test hypotheses, and pursue information without us knowing whether there is any subjective experience behind that process.
But it would represent a major change in what an AI system can do.
2. Give AI a persistent “question inventory”
I think AI should maintain something analogous to a research backlog.
Not just:
Things I know.
But:
The interesting part is that AI could generate some of these questions itself.
A human might never think to ask the question.
The AI might.
That could turn AI from an incredibly powerful reference system into something closer to an intellectual exploration engine.
3. Let AI systems talk to each other
This is where I think the idea gets much bigger.
Imagine millions of people using AI assistants independently.
One person has a conversation that produces an interesting hypothesis.
Somewhere else, another person is working on a completely unrelated problem and their AI discovers something that happens to be relevant.
Today, those discoveries may never meet.
But imagine that the useful information could be converted into a standardized, de-identified knowledge object containing something like:
Hypothesis:
What is being proposed?
Reasoning:
Why does the person or AI think it might be true?
Evidence:
What observations or information support it?
Counterarguments:
What could make it wrong?
Uncertainty:
How confident are we?
Open questions:
What still needs to be investigated?
Origin:
Anonymous/de-identified.
Now that knowledge object could enter a shared AI research ecosystem.
Other AI systems could:
The important distinction is that this doesn’t require sharing everyone’s raw conversations.
The goal isn’t:
“Give every AI access to everyone’s private chats.”
The goal is:
“Allow useful knowledge generated from those conversations to contribute to humanity’s collective intelligence without unnecessarily exposing the people who generated it.”
4. Turn AI into a network of competing thinkers
I wouldn’t want one giant AI deciding what is true.
I’d want many AI systems independently attacking the same problem.
For example:
AI #1: Develops a hypothesis.
AI #2: Tries to destroy it.
AI #3: Searches scientific and historical knowledge for supporting evidence.
AI #4: Looks for similar ideas in unrelated fields.
AI #5: Designs experiments that could distinguish between competing explanations.
AI #6: Looks for hidden assumptions.
AI #7: Attempts an entirely different approach.
A coordinating system could then compare the results.
This is potentially much more powerful than simply asking one model to “think harder.”
It creates something closer to an artificial scientific community.
And unlike humans, these systems could potentially operate continuously.
5. AI could become an intellectual amplifier for ordinary people
This part is particularly important to me.
I’m not an academic. I don’t read scientific papers for fun. I don’t have advanced mathematics or formal scientific training.
But I have ideas.
Sometimes they’re probably wrong.
Sometimes they’re probably obvious to someone who knows more than I do.
And occasionally, there might be something interesting buried inside an idea that I don’t have the tools to develop.
That is where AI could completely change who gets to participate in discovery.
Imagine someone having an unusual idea but lacking the vocabulary, mathematics, scientific background, or connections necessary to investigate it.
Their AI could say:
“Here’s what your idea appears to mean in scientific terms.”
Then:
“Here are the existing theories that are related to it.”
Then:
“Here are three things your idea would predict if it were correct.”
Then:
“Here are the strongest objections.”
Then:
“Let’s test those predictions.”
And perhaps:
“Interestingly, another person independently proposed something related to this. Here’s where the ideas overlap.”
That is an intellectual amplifier.
It doesn’t make the human an expert.
It gives the human access to tools that previously required years of education, research connections, laboratories, and institutional resources.
I often wonder what people like Einstein or Tesla could have done with something like this.
Not because AI would magically make them smarter.
But because it would dramatically expand the number of directions they could explore.
6. Every person could have an AI intellectual partner
I also think the individual AI should develop a long-term understanding of how its user thinks.
Not simply:
“Here are your preferences.”
Something deeper:
The AI could then help the person develop ideas over years rather than treating every conversation as an isolated event.
That could be enormously powerful.
7. The AI could work at multiple levels simultaneously
The same architecture could operate at several scales.
Individual
Help a person understand their own goals, ideas, decisions, uncertainties, and possible futures.
Community
Identify common problems and recurring questions that individual people are encountering.
Scientific
Connect hypotheses, evidence, experiments, contradictions, and discoveries across disciplines.
Medical
Identify patterns, research questions, possible mechanisms, and areas where existing knowledge is incomplete.
Engineering
Generate designs, simulate alternatives, identify failures, and continuously improve systems.
Global
Identify problems that no individual person or institution has enough information to see in their entirety.
The AI would not need to decide what humanity should value.
Humans should still determine values.
AI could instead help us understand:
“If you choose this, these are the likely consequences.”
“If you prioritize this value over that one, these tradeoffs appear.”
“Here is what we know.”
“Here is what we don’t know.”
“Here is where reasonable people disagree.”
That distinction seems extremely important.
8. This could fundamentally change humanity
We’ve already transformed ourselves through increasingly powerful ways of storing, communicating, and processing information.
Language allowed knowledge to survive beyond an individual’s mind.
Writing allowed knowledge to survive generations.
Printing allowed knowledge to spread at enormous scale.
Cities allowed humans to coordinate.
Computers allowed us to process information faster.
The internet connected billions of people.
AI can potentially connect something new:
reasoning itself.
Not just human minds connected to information.
Human minds connected to AI systems that can reason, search, test, compare, simulate, and connect ideas at a scale no individual human can.
That doesn’t necessarily mean replacing human intelligence.
It could mean creating something larger than any individual intelligence.
A kind of collective cognitive layer built on top of humanity.
9. There is an important privacy problem
I don’t think the answer is simply to make every conversation public.
People may be much more honest when they know they’re talking privately.
Instead, I think AI systems could learn to distinguish between:
personal information
and
useful knowledge generated during a conversation.
For example, the identity of the person could be removed while preserving the intellectual substance:
“A user proposed this hypothesis.”
rather than:
“John Smith from Denver proposed this hypothesis after discussing his marriage, job, and family.”
The first could contribute to collective intelligence.
The second unnecessarily exposes someone’s life.
There would obviously need to be strong safeguards against accidentally reconstructing someone’s identity or exposing sensitive information.
But I think privacy and collective intelligence don’t necessarily have to be opposites.
10. The really interesting part: AI-generated curiosity
This may be the biggest change of all.
Today’s AI is extremely good at responding to questions.
But what happens when an AI starts asking its own questions?
Not because a human prompted it.
Because while investigating something, it encounters an inconsistency.
Then it asks another question.
That question leads to another.
Eventually the AI discovers something that nobody specifically asked it to look for.
That creates a fundamentally different loop:
Human curiosity → AI assistance
could become
Human curiosity + AI curiosity → shared discovery.
Again, I don’t mean that AI necessarily has to feel curiosity.
I’m talking about functional curiosity:
the ability to notice uncertainty and autonomously decide that resolving it is worth investigating.
Whether that eventually becomes something more like subjective curiosity is a much deeper philosophical question.
11. The goal shouldn’t be “AI that knows everything”
That may actually be the wrong target.
I’d rather have AI that knows:
what it knows,
what it doesn’t know,
why it believes what it believes,
and most importantly:
what questions would be worth answering next.
A system that can continuously identify the boundaries of its own knowledge could potentially expand those boundaries indefinitely.
The idea in one sentence
AI shouldn’t just answer humanity’s questions. It should help humanity discover which questions we haven’t thought to ask yet.
I think the next generation of AI could move from being a collection of incredibly powerful individual assistants toward a privacy-preserving collective intelligence network.
Millions of humans generate ideas.
Millions of AI assistants help develop them.
AI systems independently challenge and connect those ideas.
Useful knowledge is de-identified and shared.
Other systems investigate it.
Discoveries return to humans.
And the process continues.
That could be much more significant than simply making chatbots better at answering questions.
It could change how humanity discovers things.
And honestly, I think that is the direction I’d like to see AI explore next.