Since explanationless prediction is actually impossible, the methodology of excluding explanation from a science is just a way of holding one’s explanations immune from criticism. [316]
Tag: justification
The royal road to tyranny and revolution
Ideas have consequences, and the ‘who should rule?’ approach to political philosophy is not just a mistake of academic analysis: it has been part of practically every bad political doctrine in history. If the political process is seen as an engine for putting the right rulers in power, then it justifies violence, for until that right system is in place, no ruler is legitimate; and once it is in place, and its designated rulers are ruling, opposition to them is opposition to rightness. The problem then becomes how to thwart anyone who is working against the rulers or their policies. By the same logic, everyone who thinks that existing rulers or policies are bad must infer that the ‘who should rule?’ question has been answered wrongly, and therefore that the power of the rulers is not legitimate, and that opposing it is legitimate, by force if necessary. Thus the very question ‘Who should rule?’ begs for violent, authoritarian answers, and has often received them. It leads those in power into tyranny, and to the entrenchment of bad rulers and bad policies; it leads their opponents to violent destructiveness and revolution.
Advocates of violence usually have in mind that none of those things need happen if only everyone agreed on who should rule. But that means agreeing about what is right, and, given agreement on that, rulers would then have nothing to do. And, in any case, such agreement is neither possible nor desirable: people are different, and have unique ideas; problems are inevitable, and progress consists of solving them.
Popper therefore applies his basic ‘how can we detect and eliminate errors?’ to political philosophy in the form how can we rid ourselves of bad governments without violence? Just as science seeks explanations that are experimentally testable, so a rational political system makes it as easy as possible to detect, and persuade others, that a leader or policy is bad, and to remove them without violence if they are. [210-11]
Rational policy-making
How can we formulate policies for the unknown? If we cannot derive them from our best existing knowledge, or from dogmatic rules of thumb like blind optimism or pessimism, where can we derive them from? 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 ‘How can we hope to detect and eliminate error?’ is echoed by Feynman’s remark that ‘science is what we have learned about how to keep from fooling ourselves’. And the answer is basically the same for human decision-making as it is for science: it requires a tradition of criticism, in which good explanations are sought – for example, explanations of what has gone wrong, what would be better, what effect various policies have had in the past and would have in the future.
But what use are explanations if they cannot make predictions and so cannot be tested through experience, as they can be in science? This is really the question: how is progress possible in philosophy? As I discussed in Chapter 5, it is obtained by seeking good explanations. The misconception that evidence can play no legitimate role in philosophy is a relic of empiricism. Objective progress is indeed possible in politics just as it is in morality generally and in science. [208-9]
Proof theory is computer science
So, 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. It is our window on the abstract. It works because we use such entities only in situations where we have good explanations saying that the relevant physical variables in those objects do indeed instantiate those abstract properties.
Consequently, the reliability of our knowledge of mathematics remains for ever subsidiary to that of our knowledge of physical reality. Every mathematical proof depends absolutely for its validity on our being right about the rules that govern the behaviour of some physical objects, like computers, or ink and paper, or brains. So, contrary to what Hilbert thought, and contrary to what most mathematicians since antiquity have believed and believe to this day, proof theory can never be made into a branch of mathematics. Proof theory is a science: specifically, it is computer science.
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 not random truths but good explanations. [188-9]
On the is–ought canard
Certainly you can’t derive an ought from an is, but you can’t derive a factual theory from an is either. That is not what science does. The growth of knowledge does not consist of finding ways to justify one’s beliefs. It consists of finding good explanations. And, although factual evidence and moral maxims are logically independent, factual and moral explanations are not. Thus factual knowledge can be useful in criticizing moral explanations. [120]
Liberating science from authority
Empiricism never did achieve its aim of liberating science from authority. It denied the legitimacy of traditional authorities, and that was salutary. But unfortunately it did this by setting up two other false authorities: sensory experience and whatever fictitios process of ‘derivation’, such as induction, one imagines is used to extract theories from experience.
The misconception that knowledge needs authority to be genuine or reliable dates back to antiquity, and it still prevails. To this day, most courses in the philosophy of knowledge teach that knowledge is some form of justified, true belief, where ‘justified’ means designated as true (or at least ‘probable’) by reference to some authoritative source or touchstone of knowledge. Thus ‘how do we know … ?’ is transformed into ‘by what authority do we claim … ?’ The latter question is a chimera that may well have wasted more philosophers’ time and effort than any other idea. It converts the quest for truth into a quest for certainty (a feeling) or for endorsement (a social status). This misconception is called justificationism.
The opposing position – namely the recognition that there are no authoritative sources of knowledge, nor any reliable means of justifying ideas as being true or probable – is called fallibilism. To believers in the justified-true-belief theory of knowledge, this recognition is the occasion for despair or cynicism, because to them it means that knowledge is unattainable. But to those of us for whom creating knowledge means understanding better what is really there, and how it really behaves and why, fallibilism is part of the very means by which this is achieved. Fallibilists expect even their best und most fundamental explanations to contain misconceptions in addition to truth, and so they are predisposed to try to change them for the better. In contrast, the logic of justificationism is to seek (and typically, to believe that one has found) ways of securing ideas against change. Moreover, the logic of fallibilism is that one not only seeks to correct the misconceptions of the past, but hopes in the future to find and change mistaken ideas that no one today questions or finds problematic. So it is fallibilism, not mere rejection of authority, that is essential for the initiation of unlimited knowledge growth – the beginning of infinity. [8-9]
Imagination and criticism in science
Diese spekualtiven Welten sind, wie in der Kunst, Produkte unserer Phantasie, unserer Intuition. Aber in der Wissenschaft werden sie von der Kritik kontrolliert: Die wissenschaftliche Kritik, die rationale Kritik, ist von der regulativen Idee der Wahrheit geleitet. Wir können unsere wissenschaftlichen Theorien niemals rechtfertigen, denn wir können nie wissen, ob sie sich nicht als falsch herausstellen werden. Aber wir können sie kritisch überprüfen: An die Stelle der Rechtfertigung tritt die rationale Kritik. Die Kritik zügelt die Phantasie, ohne sie zu fesseln. [67]
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