by Summary:
Important. I think Noah has this right. Fit the tool to the job, rather than the job to the tool. Aristotle defined speculative knowledge in terms of causal explanation. This definition stuck although Aristotle's analysis of causality did not. In the Posterior Analytics, Aristotle places the following crucial condition on proper knowledge: we think we have knowledge of a thing only when we have grasped its cause (APost. 71 b 9–11. Cf. APost. 94 a 20). That proper knowledge is knowledge of the cause is repeated in the Physics: we think we do not have knowledge of a thing until we have grasped its why, that is to say, its cause (Phys. 194 b 17–20). Since Aristotle obviously conceives of a causal investigation as the search for an answer to the question “why?”, and a why-question is a
Topics:
Mike Norman considers the following as important: Causality, correlation, data, Economics, evidence, explanation, logic, modeling, reasoning, scientific method, statistics, theory
This could be interesting, too:
Important. I think Noah has this right. Fit the tool to the job, rather than the job to the tool. Aristotle defined speculative knowledge in terms of causal explanation. This definition stuck although Aristotle's analysis of causality did not. In the Posterior Analytics, Aristotle places the following crucial condition on proper knowledge: we think we have knowledge of a thing only when we have grasped its cause (APost. 71 b 9–11. Cf. APost. 94 a 20). That proper knowledge is knowledge of the cause is repeated in the Physics: we think we do not have knowledge of a thing until we have grasped its why, that is to say, its cause (Phys. 194 b 17–20). Since Aristotle obviously conceives of a causal investigation as the search for an answer to the question “why?”, and a why-question is a
Topics:
Mike Norman considers the following as important: Causality, correlation, data, Economics, evidence, explanation, logic, modeling, reasoning, scientific method, statistics, theory
This could be interesting, too:
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Important.
I think Noah has this right. Fit the tool to the job, rather than the job to the tool.
In the Posterior Analytics, Aristotle places the following crucial condition on proper knowledge: we think we have knowledge of a thing only when we have grasped its cause (APost. 71 b 9–11. Cf. APost. 94 a 20). That proper knowledge is knowledge of the cause is repeated in the Physics: we think we do not have knowledge of a thing until we have grasped its why, that is to say, its cause (Phys. 194 b 17–20). Since Aristotle obviously conceives of a causal investigation as the search for an answer to the question “why?”, and a why-question is a request for an explanation, it can be useful to think of a cause as a certain type of explanation. (My hesitation is ultimately due to the fact that not all why-questions are requests for an explanation that identifies a cause, let alone a cause in the particular sense envisioned by Aristotle.) — Stanford Encyclopedia of Philosophy
There is a distinction between reasons and causes. Some types of explanation seek only reasons, while other seek causes. Causation subsequently came to be viewed in terms of articulating mechanisms or lines of transmission (models) that are substantiated in evidence.
Explanation by reasons is different since the strict criterion of articulating mechanisms or lines of transmission that can be checked against evidence is not required.
Explanation by reasons rather than strictly by establishing causation is based on the principle of sufficient reason, which is usually credited to Spinoza and Leibnitz.
In philosophical logic, two negative criteria are foundational. Valid reasoning is vitiated by 1) arguing in a circle and 2) infinite regress.
Without recourse to checking against evidence there is no stopping point in assigning causes other than stipulation, e.g. of a first cause.
However, there may be a reason for a stopping point that doesn't involve causality based on evidence from observation or only stipulation, for example, principles that are "self-evident" based on intuition such as Aristotle's conception of intellectual intuition, or Kant's synthetic a priori propositions as articulated in the Critique of Pure Reason.
On the other hand, Hume argued that causality is merely over-interpretation of constant correlation, there being no knowledge of the world other than that based on sense data. There is no observable causal link.
Cutting to the chase, scientific explanation based on causality is grounded in models that articulate causal mechanisms or lines of transmission that show how things change invariantly, which is the basis for deterministic functions. Where this is not possible, then there are two other avenues. The first is explanation by giving reasons, which is the domain of speculative philosophy. The second is employing statistics to explore patters of correlation. The question then is to what degree causal models can be gained from statistical methods, or whether it is possible at all.
This is the issue that Noah Smith's post is getting at.