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As Arthur Conan Doyle’s fictional detective Sherlock Holmes put it in the short story ‘A Scandal in Bohemia’, ‘It is a capital mistake to theorize before one has data.’ But that was itself a capital mistake. We never know any data before interpreting it through theories. All observations are, as Popper put it, theory-laden,
Testability is now generally accepted as the defining characteristic of the scientific method. Popper called it the ‘criterion of demarcation’ between science and non-science.
For example, if we are simply curious about something, it means that we believe that our existing ideas do not adequately capture or explain it.
I shall call a situation in which we experience conflicting ideas a problem.
Solving a problem means creating an explanation that does not have the conflict.
Since theories can contradict each other, but there are no contradictions in reality, every problem signals that our knowledge must be flawed or inadequate. Our misconception could be about the reality we are observing, or about how our perceptions are related to it, or both.
If an explanation could easily explain anything in the given field, then it actually explains nothing.
The quest for good explanations is, I believe, the basic regulating principle not only of science, but of the Enlightenment generally.
That is what makes good explanations essential to science: it is only when a theory is a good explanation – hard to vary – that it even matters whether it is testable. Bad explanations are equally useless whether they are testable or not. Most accounts of the differences between myth and science make too much of the issue of testability
That is what a good explanation will do for you: it makes it harder for you to fool yourself.
Because an error in experimental science is a mistake about the cause of something. Like an accurate observation, it is a matter of theory. Very little in nature is detectable by unaided human senses. Most of what happens is too fast or too slow, too big or too small, or too remote, or hidden behind opaque barriers, or operates on principles too different from anything that influenced our evolution. But in some cases we can arrange for such phenomena to become perceptible, via scientific instruments.
Let me assume that you are reading this on Earth.
What is it like there? Imagine the whole of space notionally divided into cubes the size of our solar system. If you were observing from a typical one of them, the sky would be pitch black. The nearest star would be so far away that if it were to explode as a supernova, and you were staring directly at it when its light reached you, you would not see even a glimmer. That is how big and dark the universe is. And it is cold: it is at that background temperature of 2.7 kelvin, which is cold enough to freeze every known substance except helium.
This increasingly intimate connection between explaining the world and controlling it is no accident, but is part of the deep structure of the world.
while every other organism is a factory for converting resources of a fixed type into more such organisms, human bodies (including their brains) are factories for transforming anything into anything that the laws of nature allow. They are ‘universal constructors’.
The only uniquely significant thing about humans (whether in the cosmic scheme of things or according to any rational human criterion) is our ability to create new explanations, and we have that in common with all people. You do not become less of a person if you lose a limb in an accident; it is only if you lose your brain that you do.
That means that one physical system – say, an astrophysicist’s brain – contains an accurate working model of the other, the jet. Not just a superficial image (though it contains that as well), but an explanatory theory that embodies the same mathematical relationships and causal structure. That is scientific knowledge.
The knowledge in human brains and the knowledge in biological adaptations are both created by evolution in the broad sense: the variation of existing information, alternating with selection. In the case of human knowledge, the variation is by conjecture, and the selection is by criticism and experiment. In the biosphere, the variation consists of mutations (random changes) in genes, and natural selection favours the variants that most improve the ability of their organisms to reproduce, thus causing those variant genes to spread through the population.
good adaptations, like good explanations, are distinguished by being hard to vary while still fulfilling their functions.
A good design is hard to vary:
An April-nesting gene is no longer able to propagate itself to the next generation, even though it is functionally the best variant. The early-nesting gene that replaced it may still be tolerably functional, but it is fittest for nothing except preventing variants of itself from procreating.
The most general way of stating the central assertion of the neo-Darwinian theory of evolution is that a population of replicators subject to variation (for instance by imperfect copying) will be taken over by those variants that are better than their rivals at causing themselves to be replicated.
what science – and creative thought in general – achieves is unpredictable creation ex nihilo. So does biological evolution. No other process does.
Holists also often share with reductionists the mistaken belief that science can only (or should only) be reductive, and therefore they oppose much of science.
But it is no mystery where our knowledge of abstractions comes from: it comes from conjecture, like all our knowledge, and through criticism and seeking good explanations. It is only empiricism that made it seem plausible that knowledge outside science is inaccessible; and it is only the justified-true-belief misconception that makes such knowledge seem less ‘justified’ than scientific theories.
I guess that no true explanation is entirely disconnected from any other.
Gradually, the ability of these catalysts to promote their own production became robust and specific enough for it to be worth calling them replicators.
Then you discover a cure that will cause your blue receptors to start working. Before administering the cure to yourself, you can confidently make certain predictions about what will happen if it works. One of them is that, when you hold up a blue card as a test, you will see a colour that you have never seen before. You can predict that you will call it ‘blue’, because you already know what the colour of the card is called (and can already check which colour it is with a spectrophotometer). You can also predict that when you first see a clear daytime sky after being cured you will experience
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In the case of the Turing test, we deliberately ignore the issue of how the knowledge to design the object was created. The test is only about who designed the AI’s utterances: who adapted its utterances to be meaningful – who created the knowledge in them? If it was the designer, then the program is not an AI. If it was the program itself, then it is an AI.
My guess is that every AI is a person: a general-purpose explainer.
I think we have to face the fact, both with artificial evolution and with AI, that these are hard problems. There are serious unknowns in how those phenomena were achieved in nature. Trying to achieve them artificially without ever discovering those unknowns was perhaps worth trying. But it should be no surprise that it has failed. Specifically, we do not know why the DNA code, which evolved to describe bacteria, has enough reach to describe dinosaurs and humans.
Even artificial evolution may not have been achieved yet, despite appearances. There the problem is that we do not understand the nature of the universality of the DNA replication system.
At Infinity Hotel, it is never necessary to make a reservation.
almost all mathematical truths have no proofs. They are unprovable truths. It also follows that almost all mathematical statements are undecidable: there is no proof that they are true, and no proof that they are false.
Mathematical truth is absolutely necessary and transcendent, but all knowledge is generated by physical processes, and its scope and limitations are conditioned by the laws of nature.
a computation or a proof is a physical process in which objects such as computers or brains physically model or instantiate abstract entities like numbers or equations, and mimic their properties.
The whole motivation for seeking a perfectly secure foundation for mathematics was mistaken. It was a form of justificationism. Mathematics is characterized by its use of proofs in the same way that science is characterized by its use of experimental testing; in neither case is that the object of the exercise. The object of mathematics is to understand – to explain – abstract entities. Proof is primarily a means of ruling out false explanations; and sometimes it also provides mathematical truths that need to be explained. But, like all fields in which progress is possible, mathematics seeks
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The unpredictability of the content of future knowledge is a necessary condition for the unlimited growth of that knowledge.
Genetic studies suggest that our own species came close to extinction about 70,000 years ago, as a result of an unknown catastrophe which reduced its total numbers to only a few thousand.
Like scientific theories, policies cannot be derived from anything. They are conjectures. And we should choose between them not on the basis of their origin, but according to how good they are as explanations: how hard to vary.
The question about the sources of our knowledge…has always been asked in the spirit of: ‘What are the best sources of our knowledge – the most reliable ones, those which will not lead us into error, and those to which we can and must turn, in case of doubt, as the last court of appeal?’ I propose to assume, instead, that no such ideal sources exist – no more than ideal rulers – and that all ‘sources’ are liable to lead us into error at times. And I propose to replace, therefore, the question of the sources of our knowledge by the entirely different question: ‘How can we hope to detect and
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The Medici were soon promoting the new philosophy of ‘humanism’, which valued knowledge above dogma, and virtues such as intellectual independence, curiosity, good taste and friendship over piety and humility.
various discrete attributes. This also raises the issue of whether time itself is a continuous variable. In this discussion I am assuming that it is. However, the quantum mechanics of time is not yet fully understood, and will not be until we have a quantum theory of gravity (the unification of quantum theory with the general theory of relativity), so it may turn out that things are not as simple as that. One thing we can be fairly sure of, though, is that, in that theory, different times are a special case of different universes.
All fiction that does not violate the laws of physics is fact.
what a Mach–Zehnder interferometer does to a single photon: the path that was not taken affects the one that was.
Thus quantum theory – the deepest discovery of the physical sciences – has acquired a reputation for endorsing practically every mystical and occult doctrine ever proposed.
This form of explanationless science is just bad philosophy disguised as science.
Arrow proved that the axioms that I have just listed are, despite their reasonable appearance, logically inconsistent with each other. No way of conceiving of ‘the will of the people’ can satisfy all five of them. This strikes at the assumptions behind social-choice theory
It is a mistake to conceive of choice and decision-making as a process of selecting from existing options according to a fixed formula. That omits the most important element of decision-making, namely the creation of new options.
People can learn to see many things as beautiful or ugly. But, there again, people can also learn to see false scientific theories as true, and true ones as false, yet there is such a thing as objective scientific truth. So that still does not tell us whether there is such a thing as objective beauty.
