"That framing assumes science is just a method, a procedure for extracting truths from nature."
It also assumes science is not deeply dependent on the ability to experience and observe the world. And sure, eventually AI will be given senses in the form cameras and sensors, but is that enough?
Could a robot look an an apple falling from a tree and think, why is this apple falling and not going up?
Yes, Newton already discovered that but I have always felt deeply that science is not so much about all the available information (AIs bread and butter) it is about observing and and experiencing the world, then asking questions.
Way more philosophy of science was written after Kuhn than before, and most of the more recent stuff is much better than the older stuff. Even Kuhn has been superseded/rejected, though his influence is still felt. You might be better off with a contemporary anthology of philosophy of science, or a summary of the state of the field like Godfrey-Smith’s _Theory and Reality_.
Science at its root is something like: systematic inquiry into the nature of things, guided by some method of testing claims against experience or observation.
But what we call "science" today is actually many things layered on top of each other:
1. Fundamental inquiry — the original impulse to understand
2. Method refinement — ways of asking questions that yield reliable knowledge
5. Technological application — turning knowledge into capability
These layers aren't the same thing. And increasingly, AI as researcher operates primarily in layers 4-5, sometimes touching layer 2, rarely engaging layer 1
Is AI doing "legitimate research"? The answer depends on what layer of science you're asking about:
---Layer 4-5 (optimization, application): Yes, AI is already a legitimate and often superior researcher
---Layer 2 (method refinement): Partially — AI can suggest new techniques but rarely invents new kinds of techniques
--- Layer 1 (fundamental inquiry): Not yet — AI hasn't demonstrated the capacity to reframe what counts as a question worth asking
The deeper issue is: Modern science itself operates mostly in layers 2-5. The original impulse — What is this? Why does it exist? What does it mean? — has been largely outsourced to philosophy (and even there, marginalized).
So when we ask "Is AI a legitimate researcher?", we should also ask: "Has modern science itself remained true to the root impulse of human inquiry?"
"That framing assumes science is just a method, a procedure for extracting truths from nature."
It also assumes science is not deeply dependent on the ability to experience and observe the world. And sure, eventually AI will be given senses in the form cameras and sensors, but is that enough?
Could a robot look an an apple falling from a tree and think, why is this apple falling and not going up?
Yes, Newton already discovered that but I have always felt deeply that science is not so much about all the available information (AIs bread and butter) it is about observing and and experiencing the world, then asking questions.
Feels more like the weapoization of science. The practice requires curiosity? Whose?
Indeed, scientific stagnation is not simply because of a poor sense of ideas or theory or where to go. . . . .
Way more philosophy of science was written after Kuhn than before, and most of the more recent stuff is much better than the older stuff. Even Kuhn has been superseded/rejected, though his influence is still felt. You might be better off with a contemporary anthology of philosophy of science, or a summary of the state of the field like Godfrey-Smith’s _Theory and Reality_.
Science at its root is something like: systematic inquiry into the nature of things, guided by some method of testing claims against experience or observation.
But what we call "science" today is actually many things layered on top of each other:
1. Fundamental inquiry — the original impulse to understand
2. Method refinement — ways of asking questions that yield reliable knowledge
3. Institutional infrastructure — universities, journals, peer review, funding
4. Performance engineering — optimization, scalability, efficiency, replication
5. Technological application — turning knowledge into capability
These layers aren't the same thing. And increasingly, AI as researcher operates primarily in layers 4-5, sometimes touching layer 2, rarely engaging layer 1
Is AI doing "legitimate research"? The answer depends on what layer of science you're asking about:
---Layer 4-5 (optimization, application): Yes, AI is already a legitimate and often superior researcher
---Layer 2 (method refinement): Partially — AI can suggest new techniques but rarely invents new kinds of techniques
--- Layer 1 (fundamental inquiry): Not yet — AI hasn't demonstrated the capacity to reframe what counts as a question worth asking
The deeper issue is: Modern science itself operates mostly in layers 2-5. The original impulse — What is this? Why does it exist? What does it mean? — has been largely outsourced to philosophy (and even there, marginalized).
So when we ask "Is AI a legitimate researcher?", we should also ask: "Has modern science itself remained true to the root impulse of human inquiry?"
this statement seems a bit myopic " 90% of all scientists who have ever lived are alive today (de Solla Price)" ... see https://grow.scienceoffreedom.life/pages/doorwaytofreedom