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Hume induction essay
David hume theory of induction
Hume induction essay
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Does reliabilism offer a viable solution to the problem of induction?
For the purpose of this paper I will refine the problem of induction to enumerative cases of induction. I shall explore whether reliabilism is a successful theory of knowledge, and propose that it is a viable solution to the problem of induction proposed by David Hume, but requires ad hoc amendments in attempt to satisfy the New Riddle of Induction put forth by Nelson Goodman.
The problem of induction, most notably attached to Hume, is the philosophical question of whether inductive reasoning leads to knowledge, in which Hume concluded that inductive inferences from observed instances to a general conclusion can never yield knowledge. Traditional philosophical epistemology assumes that knowledge requires certainty. Given such stipulations, inductive inference would have to guarantee complete certainty to warrant it being knowledge. Hence, because universal generalisations (all Fs are Gs) apply to indefinitely many instances, but we can only observe finitely many instances; no number of observations can entail that universal generalisations are necessarily true (there may possibly be a case where an F isn’t a G). Thus, it is logically possible that the premises (every rose I have ever seen is red) be true but the inferred conclusion (all roses are red) be false; accordingly, inductive inference is logically invalid and cannot yield knowledge.
Such problem, according to David Papineau, holds no grounds given the doctrines of reliabilism. Reliabilism is an externalist account of knowledge, which defines knowledge as true belief caused by a reliable process. Papineau maintains that reliabilism offers a viable solution to the problem of induction, but concedes...
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...regard certainty in the actual world. Subsequently all statements and claims, inductively inferred, are approximate, as opposed to being explicitly true.
Reliabilism puts forward a viable solution to the traditional problem of induction proposed by Hume, showing that despite enumerative induction being logically invalid, it can convincingly yield knowledge. Similarly, it can be shown the circularity involved in establishing inductive inference does not trivially guarantee its conclusion, unlike premise circularity. Nevertheless, Goodman’s New Riddle of Induction poses serious threat to what reliabilism can actually state as knowledge. If the reliabilist is willing to concede that inductive inferences are beliefs of less than full degree, they are faced with conceding that only deductive inferences and analytical truths yield certain knowledge in the actual world.
The purpose of this paper is to show that Goldman's causal theory of knowledge does not solve the Gettier problem. First, I will reiterate the Gettier problem. Second, I will show how Goldman's theory attempts to solve the Gettier problem. Next, I will show how over determination points out a major flaw for Goldman's theory. Finally, I will demonstrate that Goldman's theory does not work if the world we live in is not one of absolute truth and void of deception.
The Raven paradox includes three plausible premises, and derives from them a fairly implausible-looking conclusion about the confirmation of generalizations.
Even with the problem of induction, we are still justified to conclude that all emeralds are green. Either out of common sense, or due to certain constraints the “grue” hypothesis has, we find the induction that concludes that all emeralds are green more compelling.
This paper purports to re-examine the Lucas-Penrose argument against Artificial Intelligence in the light of Complexity Theory. Arguments against strong AI based on some philosophical consequences derived from an interpretation of Gödel's proof have been around for many years since their initial formulation by Lucas (1961) and their recent revival by Penrose (1989,1994). For one thing, Penrose is right in sustaining that mental activity cannot be modeled as a Turing Machine. However, such a view does not have to follow from the uncomputable nature of some human cognitive capabilities such as mathematical intuition. In what follows I intend to show that even if mathematical intuition were mechanizable (as part of a conception of mental activity understood as the realization of an algorithm) the Turing Machine model of the human mind becomes self-refuting.
...ion. Hempel’s solution provides to give a reason as to how induction can lead to confirmation and how the logical gap can be filled through the use of logically equivalent statements. However, his view and answer to the paradox prove to be a stretch and lead to the issue of common sense being broken and illogical observations being made to confirm the hypothesis. Good successfully brings attention to this rather blatant error on the part of Hempel to eventually lead to the Raven paradox being invalid. Not only is Good effective in highlighting errors within Hempel’s solution, but Popper, Scheffler, and Goodman are all equally successful in negating individual parts of Hempel’s argument as well. In the end, it is the addition of all these counterarguments that prove to exhibit that Hempel is unsuccessful in trying to come up with a valid answer to the raven paradox.
Inferential statistics establish the methods for the analyses used for conclusions drawing conclusions beyond the immediate data alone concerning an experiment or study for a population built on general conditions or data collected from a sample (Jackson, 2012; Trochim & Donnelly, 2008). With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. A requisite for developing inferential statistics supports general linear models for sampling distribution of the outcome statistic; researchers use the related inferential statistics to determine confidence (Hopkins, Marshall, Batterham, & Hanin, 2009).
The application of epistemology to practical life relies largely on a coherent set of parameters that determine whether someone has knowledge or not. While a traditional analysis at first glance seems to provide these parameters, this definition allows for cases to be considered knowledge though they are actually contrary to an intuitive definition of knowledge. In this paper, I will outline the traditional analysis of knowledge, present Gettier and Harman’s objections, analyze Harman’s proposed solutions in principles P and Q; and critique the necessity and consequences of Principle Q.
As humans, a crucial way we attempt to understand how the world around us works is by using previous experiences or evidence from our senses to make predictions about the future. However, how do we know that these predictions are accurate? How are we supposed to know whether future observations and experiences will resemble those of the past? In this essay, I plan to explain what induction is and Hume’s “Problem of Induction”: how he thinks that our beliefs about the future that are based on the past are unjustified. After that, I will present two arguments that he offers against his Problem of Induction, and show how they fail in counterarguing his claim.
In this paper I will argue that Roderick Chisholm gives a correct solution to the problem of the criterion. The philosophical problem with criterion is that we cannot know the extent of knowledge without knowing criteria, and vice versa. Chisholm approaches the problem of criterion by saying that in order to know whether things are as they seem to be we must have a procedure for recognizing things that are true from things that are false. He then states that to know if the procedure is a good one, we have to know if it really recognizes things that are true from things that are false. From that we cannot know whether it really does succeed unless we already know what things are true and what things are false. His two questions are more easily comprehended by asking what do we know, and how do we know that. He believes in the idea of particularism, this means that he thinks that paricularists have the answer the first question therefore giving them access to determine the answer to the second question. Chusholm’s main point is to be able to answer the question “What is the proper method for deciding which are the good beliefs and which are the bad ones— which beliefs are genuine cases of knowledge and which beliefs are not?” (3).
(2) Goldman, Alvin. "Reliabilism." Stanford University. Stanford University, 21 Apr. 2008. Web. 28 Feb. 2014.
I shall also expound Ayer's theory of knowledge, as related in his book. I will show this theory to contain logical errors, making his modified version of the principle flawed from a second angle.
The true-justified-belief theory of knowledge is an attempt to subject knowledge to analysis. The theory falls under the category of Epistemology, a branch of philosophy dealing with knowledge. The theory, in short, seeks to answer the question, what does it mean to know something? What parts lead up to a point, when someone can claim to have knowledge of something? The true-justified-belief theory of knowledge or “JTB” has three such components seeking to answer the aforementioned questions. The three components make up the theory’s analysis of knowledge. The analysis claims to demonstrate that in order to have sufficiency for knowledge, there must be a necessary justified, true belief.
Hume, D. (1748). Skeptical doubts concerning the operations of the understanding. In T.S. Gendler, S. Siegel, S.M. Cahn (Eds.) , The Elements of Philosophy: Readings from Past and Present (pp. 422-428). New York, NY: Oxford University Press.
Knowledge can be achieved either through the justification of a true belief or for the substantive externalist, through a “natural or law like connection between the truth of what is believed and the person’s belief” (P.135). Suppose a man named George was implanted with a chip at birth, which causes him to utter the time in a rare Russian dialect. His girlfriend Irina, who happens to speak the same Russian dialect, realizes that every time she taps his shoulder, he tells her the time and he is always right. She knows that he is right because she checks her watch. Because she thinks this is cute, she never tells him what it is that he is saying. One day, Irina’s watch breaks but instead of getting it fixed, she just taps George on the shoulder whenever she needs to ask for the time.
In this paper, I offer a solution to the Gettier problem by adding a fourth condition to the justified true belief analysis of knowledge. First though, a brief review. Traditionally, knowledge had been accounted for with the justified true belief analysis. To know something, three conditions had to be met: first, you had to have a belief; second, the belief had to be justified; third, this justified belief had to be true. So a justified true belief counts as knowledge. Gettier however showed this analysis to be inadequate as one can have a justified true belief that no one would want to count as knowledge.