身邊的邏輯學:常見邏輯謬誤的破解之道(附英文原稿)

身邊的邏輯學:常見邏輯謬誤的破解之道(附英文原稿)

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himalaya
2 小時 12 分鐘
himalaya
15 聲音

日常說話、寫議論文總被人說邏輯有誤? 


課程亮點


1. 邏輯推理能力是人類和大多數動物相比的寶貴生存優勢之一。如果我們要利用這種生存優勢,最大化地實現成功,我們應當學會聰明地進行邏輯推理。


2. 在本課程中,邏輯學不再遙不可及,Ram Neta博士將通過軼事和實用建議,幫助您學習如何避免邏輯和論點中的常見謬誤,或者被這類謬誤愚弄。 


3.  你將學到:什麼是邏輯謬誤,為什麼我們應該了解它們?謬誤是如何降低論證可信度和增加誤解的?如何發現謬誤,以及如何應對他們?


4. 本課程為英語原聲課程,完整還原講述,為你打造全英文的環境;另外配以逐字的英文文稿,幫助你快速提升英語水平,更好地吸收理解課程。



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作者
  • 拉姆·內塔博士(Ram Neta)
    拉姆·內塔博士(Ram Neta)
    北卡羅來納大學教堂山分校的哲學係教授
聲音
15聲音

8. Causal Slippery Slopes In the last two lectures, we saw how the vagueness of some of the terms that we ordinarily use to describe a relation between two things. The vagueness of those terms can make it easy for us to engage in fellowships. Reasoning makes it easy for us to engage in fallacious reasoning precisely by making it hard for us to notice that the reasoning is. [00:00:29] Fallacious, [00:00:33] both cases, both in the case of a conceptual slippery slope fallacy. And in the case of the fairness, slippery slope fallacy, what happens is we're reasoning about some relation that we're treating as transitive. Right. We think if one thing bears that relation to a second thing, and then a second thing bears that same relation to a third thing. [00:00:58] Then the first thing must bear that relation to the third thing. That's transitivity and for many relations, well, they are transitive, right? So for instance, consider the relation of being greater than. If the first th...

2. Misusing Useful Tools 2.濫用有用工具 In the lastlecture, I said, what fallacies are there? Errors of reasoning. And I also saidthat in this course, we're going to study those fallacies that occur mostcommonly, those errors of reasoning that people are most liable to make. Buthow do we know which fallacies occur most commonly or which errors of reasoningpeople are most liable to make? 上節課,我說,有什麼謬誤?推理錯誤。我還說過,在這門課中,我們將研究最常見的謬誤,人們最容易犯的推理錯誤。但是,我們如何知道哪些謬誤最常見,哪些是人們最容易犯的推理錯誤? It's not as ifanyone goes around tabulating the results of some survey, right? We don't checkevery time someone performs an act of reasoning and check what kind of errorthey made if they made an error and then add up those results to see whichkinds of errors occur most commonly. 並不是說有人會把調查結果做成表格,對吧?我們不會每次都檢查一個人的推理行為,如果他們犯了錯誤,我們會檢查他們犯了什麼樣的錯誤,然后把這...

3. Unclarity 3.不明確 In the first twolectures, I introduced you to the topics of this course. I explained whatfallacies are, why it's worthwhile to study them. And I said something aboutwhich ones we were going to study in this today. What I want to do is deuce youto one particular kind of fallacy that we're going to spend unit one of thecourse studying. 在前兩節課中,我向你們介紹了本課程的主題。我解釋了什麼是謬誤,為什麼值得研究。我說了一些我們今天要學習的東西。我要做的是讓你們明白一個特别的謬論,我們要用第一單元的課程來學習。 So today isgoing to be our introduction to unit one. In this first unit of the course,we're going to be studying fallacies of a kind that I call fallacies ofun-clarity. These are fallacies that people are prone to make because ofcertain kinds of un-clarity in the language that they use to reason. 今天是第一單元的介紹。在本課程的第一單元,我們將要研究一種謬誤,我稱之為不清晰的謬誤。這些都是人們容易犯的錯誤,因為他們用來推理的語言中存在某...

9. Ambiguity In the last few lectures, we've talked about the phenomenon of vagueness and the slippery slope fallacies to which vagueness gives rise today. I want to start talking about a different phenomenon from that vagueness. I'm going to be talking about ambiguity, and then I'll talk about fallacies of equivocation, which are fallacies to which ambiguity gives rise. [00:00:28] But before I talk about fallacies of equivocation, let's first discuss the phenomenon of ambiguity itself. What is ambiguity and how does it differ from vagueness? [00:00:43] Ambiguity is when an expression has two or more different meanings. Now an expression can be ambiguous, even if every meaning that that expression has is perfectly precise in that case, the expression would be ambiguous, but it wouldn't be vague. Let me give you an example, consider the expression, the third member of the series, that expression is ambiguous, but it's not vague. [00:01:19] Why is it ambiguous? Well, because w...

7. Fairness Slippery Slopes In the last lecture, we talked about conceptual slippery slope, fallacies. Those are fallacies that we can easily make when we neglect the fact that the phrase a significant difference is a matter of degree. So if we treat the phrase a significant difference as a yes or no matter, either a difference, a significant, or it isn't, then we'll be tempted into a conceptual slippery slope fallacy. [00:00:30] Today. I want to talk about another kind of slippery slope fallacy that we'll call a fairness, slippery slope fallacy. And let me explain what a fairness, slippery slope fallacy is. Once again, by giving an example. Suppose I'm teaching a course with a bunch of students. I'm grading their work in the course. [00:00:51] Now it's obvious that if a student gets 100% on all the assigned work in the course, then that student deserves an a plus in the course, they deserve the highest grade. Okay. But now suppose another student does. Almost exactly as well ...

6. Conceptual Slippery Slopes So far in our course, you've learned what paradoxes are and why it's important to study them. You've also learned what vagueness is, why vagueness is crucial for us to use in our thought and language, but how vagueness can give rise to paradoxes today? I want to start explaining how big this can give rise to fallacies as well. [00:00:22] And we're going to do that by spending today, studying a particular kind of fallacy that we call the conceptual slippery slope fallacy. [00:00:34] Let me explain what conceptual slippery slope fallacies are by giving an example, and then generalizing from that example. So here's a fact that we've learned from physics electromagnet, medic radiation with a wavelength of 620 nanometer is red light. We all, I also know from physics that electromagnetic radiation with a wavelength of 495 nanometers is Greenlight, but now a difference of one nanometer in wavelength. [00:01:10] Is not a significant difference. One nano...

4. Vagueness In the last lecture. I said something that may have surprised you. I said it would be a disaster for all of us. If we got rid of all of the un-clarity in our language and our thought in today's lecture, I want to begin to explain why that's true and I'll focus on the kind of un-clarity that's involved in vagueness. [00:00:25] Now. Remember vagueness. Is just lack of precision. It's just imprecision. So an example of bigness would be this suppose you asked me how many bones there are in the human skeleton. And I say there are about 200, well, that's a vague answer. It's true that there are about 200 bones in the human body. But it's not a precise answer. [00:00:53] I believe a precise answer would be 212. Maybe that's not quite accurate, but even if it's wrong, it's still a precise number 212 is a precise number. It's a precise answer to the question. How many bones are there in the human body? It might be a wrong answer. It might be an inaccurate answer, but wheth...

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