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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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1. Revolusi Industri Pertama (Akhir abad ke-18 hingga pertengahan abad ke-19)

Polusi Udara: Pemakaian batu bara sebagai sumber energi utama menyebabkan peningkatan emisi karbon dioksida (CO2) dan polutan lainnya ke atmosfer. Hal ini mengakibatkan kualitas udara yang buruk, terutama di kota-kota industri seperti London dan Manchester​

Deforestasi: Pembangunan infrastruktur dan pembukaan lahan untuk pertanian mengakibatkan penebangan hutan secara besar-besaran, yang memperburuk masalah pemanasan global dengan mengurangi jumlah pohon yang dapat menyerap CO2​

2. Revolusi Industri Kedua (Akhir abad ke-19 hingga awal abad ke-20)

Polusi Air: Limbah industri, termasuk limbah berbahaya dari pabrik tekstil dan kimia, mencemari sumber air seperti sungai dan danau. Ini tidak hanya mempengaruhi ekosistem akuatik tetapi juga mengancam kesehatan manusia melalui kontaminasi air minum​

Pencemaran Tanah: Penggunaan pupuk dan pestisida dalam pertanian, bersama dengan pembuangan limbah industri, mengubah komposisi tanah dan mengakibatkan pencemaran. Hal ini berdampak negatif pada kesuburan tanah dan kesehatan tanaman​

3. Revolusi Teknologi dan Informasi (Akhir abad ke-20 hingga saat ini)

Perubahan Iklim: Aktivitas industri yang terus berlanjut menyebabkan peningkatan emisi gas rumah kaca. Penelitian menunjukkan bahwa tanda-tanda perubahan iklim sudah terlihat sejak awal 1800-an, dan masalah ini semakin memburuk seiring dengan pertumbuhan industri dan populasi

Degradasi Sumber Daya Alam: Permintaan yang terus meningkat untuk sumber daya alam, seperti air dan bahan baku, menyebabkan eksploitasi berlebihan dan penurunan kualitas lingkungan secara keseluruhan. Penambangan dan eksploitasi sumber daya menyebabkan kerusakan habitat dan hilangnya biodiversitas​

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Environmental Impact Of The Industrial Revolution

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The Industrial Revolution, a turning point in human history, has left deep scars on our planet. This piece examines the ecological consequences of this era that linger today and offers insight into strategies for a sustainable future. Acknowledge the environmental impact of the Industrial Revolution, reflect, and then navigate towards solutions.

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Teknologi terus berkembang karena berbagai faktor saling berinteraksi, termasuk persaingan ekonomi, kemajuan ilmu pengetahuan, dan kebutuhan untuk meningkatkan produktivitas. Salah satu faktor utama adalah inovasi dan persaingan di antara perusahaan dan negara, yang mendorong pengembangan teknologi baru untuk meningkatkan efisiensi dan menciptakan keunggulan kompetitif. Persaingan ini mempercepat inovasi, menciptakan produk baru, dan memperbaiki teknologi yang sudah ada, sehingga meningkatkan produktivitas ekonomi secara keseluruhan.

Faktor lain yang berperan adalah dorongan untuk memecahkan masalah atau memenuhi kebutuhan yang terus berubah di masyarakat, seperti perubahan teknologi digital, kebutuhan energi yang lebih efisien, atau inovasi di sektor kesehatan. Dukungan pemerintah dan kebijakan yang mendorong inovasi juga dapat memberikan dampak signifikan, terutama dalam regulasi yang memungkinkan adanya persaingan sehat di pasar​

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In 1500, China's economy was the strongest in the world. But by the 19th century, the U.S., Western Europe, and Japan had leapfrogged over China by churning out goods and services in vast quantities while the former superpower stalled.

Why? Some economists argue that China's lack of free markets and unencumbered innovation in the West led to the shift. But what is the relationship between innovation and markets, productivity, and inequality?

The answer to that puzzle and others were explored during a recent forum on the relationship of innovation to economic growth at the Hoover Institution. Three Stanford professors, all Hoover fellows - Stephen Haber, Edward Lazear, and Amit Seru - spoke on a panel moderated by Jonathan Levin, dean of Stanford Graduate School of Business.

The panelists offered thoughts on how innovation is measured, the role of markets, and what types of firms are likely to innovate. They examined how productivity affects wages, skills, and social inequality, and considered what kind of policies might ensure that the pace of innovation remains brisk.

How Do You Measure Innovation?

Like art, everyone knows innovation when they see it, but defining and measuring it, says Amit Seru, "is a holy grail" for researchers. Studying patents might be key to answering that question.

Seru and his colleagues used big data techniques to analyze 9 million U.S. patents filed over two centuries. Although the Silicon Valley ethos holds that startups are the wellspring of innovation, the researchers found that established firms were also very innovative, as measured by high-quality patenting activity. They also concluded that both private and public firms contributed to innovation and that universities and some government entities were also quite innovative.

The first step in that analysis was to construct a measure of high-quality innovation. The researchers did so by comparing the texts of all the patents in the database and tabulating the occurrence of important words. If there was little overlap between the text of a patent and its predecessors, the patent was likely a novel innovation. If words in subsequent patents were similar, the subject patent was likely an important innovation that other patents had built upon. Patents meeting both criteria, i.e., novel and important, were considered "high quality," says Seru, a Stanford GSB professor of finance. As a check, the researchers compared their list of high-quality patents to those already deemed significant by economic historians. The two lists were quite similar, they found. Using this measure of high-quality innovation, the researchers examined which entities contributed to breakthrough innovations over time and what patterns were consistently associated with these events.

"What is consistent is the notion of creative destruction" and the rational reallocation of resources around such events, Seru says. When firms innovate, profits go up, and labor and financing flow to them and away from their competitors, who suffer from this creative destruction. For this to occur, labor and capital markets need to function efficiently. While creative destruction and associated patterns are not a new notion, what is different today is that innovation might occur across different entities - such as government as well as public or private firms - and inventors working across geographic boundaries. Innovation remains brisk, but if markets in the U.S., which have functioned efficiently for centuries, are hindered, innovation could falter, Seru argues.

What Happened to China?

Like Seru, Stephen Haber and his colleagues used big data to analyze economic growth. To build their geographical representation of economically powerful regions, they geocoded every major city in the world and, using a variety of sources, researched the level of economic activity at 100-year intervals. The study took three years.

During the period when China was economically more advanced than the West, it traded goods like spices, silk, and tea for silver. At the time, the West had little else that the Chinese needed, Haber says. But that changed, and by 1800 the West had pulled ahead. Innovation made the difference - modern chemistry, steam power applied to transportation, and interchangeable parts - but not just innovations in technology. Modern economic growth also came from organizational innovations in the military, transportation, and the legal and financial worlds, Haber says.

One major example: the concept of the patent as a tradable property right.

"Places where people were free to experiment, to simultaneously compete and cooperate through a market where no one was in charge of deciding which technologies would be adopted, which would be rejected, and which would be forbidden, flourished," Haber says.

Historically, China took the opposite approach: The state wielded the power to reject certain technologies. For example, the development of railroads was drastically slowed by China's emperor because he feared their spread would undo the agrarian society and threaten his rule, Haber says.

That lesson, he says, should not be lost on today's leaders. "If there is a threat to prosperity, it comes from people who believe they are doing good by using the power of the state to decide which innovations are just and which are unjust."

How Are Productivity and Inequality Linked?

There are two ways to achieve economic growth: Add population or make people more productive, says Edward Lazear, a professor of economics at Stanford GSB. Economic growth in the 20th century was tremendous. The standard of living doubled every 33 years, but that made a challenging target for the 21st century. Slower population growth and aging of the current population imply that we will need productivity increases to do more of the work in the future.

Productivity feeds into wage growth, but as productivity has slowed in recent years, so have wages, Lazear says. In the late 1990s, productivity grew by about 3% a year; now it's only about one-third of that. So it's no surprise that wages have also been flat. But the pain of flat wages is not shared equally throughout the population.

The productivity - and wages - of highly educated workers has soared over the last 30 years. But the opposite is true for less educated segments of the population.

Making matters worse, the industries that have grown are the ones that employ highly educated workers, while the industries that have shrunk are the ones employing people with less education.

However, artificial intelligence and other technologies are not to blame and will not put everyone out of work, Lazear says. As measured by participation in the labor force, jobs as a whole don't disappear when new technologies change the nature of work. There was never a transformation as radical as the Industrial Revolution, he notes, yet the labor force grew.

"The concern is not that people won't be working. The concern is that they will work in crummy jobs," Lazear says. To alleviate the problem, it will be necessary to rethink education and job training. The key, Lazear says, is this: "Lower the skills gap."

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In 1500, China's economy was the strongest in the world. But by the 19th century, the U.S., Western Europe, and Japan had leapfrogged over China by churning out goods and services in vast quantities while the former superpower stalled. Why? Some economists argue that China's lack of free markets and unencumbered innovation in the West led to the shift.

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Apa yang melatarbelakangi penemuan suatu teknologi?

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Apa yang melatarbelakangi penemuan suatu teknologi?

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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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produk dari pengetahuan dapat dikategorikan sebagai:

1. Teori atau konsep ilmiah – Misalnya, teori evolusi atau hukum gravitasi, yang dikembangkan dari observasi dan eksperimen.

2. Fakta yang terverifikasi – Informasi atau data yang telah terbukti benar melalui observasi atau eksperimen.

3. Pemahaman sistematis – Hasil dari analisis dan sintesis informasi yang membuat seseorang mampu memahami atau menjelaskan fenomena secara lebih menyeluruh.

4. Aplikasi praktis – Penerapan pengetahuan dalam kehidupan nyata, seperti teknologi, inovasi medis, atau praktik keberlanjutan.

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Epistemology is the study of knowledge. Epistemologists concern themselves with a number of tasks, which we might sort into two categories.

First, we must determine the nature of knowledge; that is, what does it mean to say that someone knows, or fails to know, something? This is a matter of understanding what knowledge is, and how to distinguish between cases in which someone knows something and cases in which someone does not know something. While there is some general agreement about some aspects of this issue, we shall see that this question is much more difficult than one might imagine.

Second, we must determine the extent of human knowledge; that is, how much do we, or can we, know? How can we use our reason, our senses, the testimony of others, and other resources to acquire knowledge? Are there limits to what we can know? For instance, are some things unknowable? Is it possible that we do not know nearly as much as we think we do? Should we have a legitimate worry about skepticism, the view that we do not or cannot know anything at all?

Although this article provides an overview of the important issues, it leaves the most basic questions unanswered; epistemology will continue to be an area of philosophical discussion as long as these questions remain.

Table of Contents

1. Kinds of Knowledge

The term "epistemology" comes from the Greek "episteme," meaning "knowledge," and "logos," meaning, roughly, "study, or science, of." "Logos" is the root of all terms ending in "-ology" - such as psychology, anthropology - and of "logic," and has many other related meanings.

The word "knowledge" and its cognates are used in a variety of ways. One common use of the word "know" is as an expression of psychological conviction. For instance, we might hear someone say, "I just knew it wouldn't rain, but then it did." While this may be an appropriate usage, philosophers tend to use the word "know" in a factive sense, so that one cannot know something that is not the case. (This point is discussed at greater length in section 2b below.)

Even if we restrict ourselves to factive usages, there are still multiple senses of "knowledge," and so we need to distinguish between them. One kind of knowledge is procedural knowledge, sometimes called competence or "know-how;" for example, one can know how to ride a bicycle, or one can know how to drive from Washington, D.C. to New York. Another kind of knowledge is acquaintance knowledge or familiarity; for instance, one can know the department chairperson, or one can know Philadelphia.

Epistemologists typically do not focus on procedural or acquaintance knowledge, however, instead preferring to focus on propositional knowledge. A proposition is something which can be expressed by a declarative sentence, and which purports to describe a fact or a state of affairs, such as "Dogs are mammals," "2+2=7," "It is wrong to murder innocent people for fun." (Note that a proposition may be true or false; that is, it need not actually express a fact.) Propositional knowledge, then, can be called knowledge-that; statements of propositional knowledge (or the lack thereof) are properly expressed using "that"-clauses, such as "He knows that Houston is in Texas," or "She does not know that the square root of 81 is 9." In what follows, we will be concerned only with propositional knowledge.

Propositional knowledge, obviously, encompasses knowledge about a wide range of matters: scientific knowledge, geographical knowledge, mathematical knowledge, self-knowledge, and knowledge about any field of study whatever. Any truth might, in principle, be knowable, although there might be unknowable truths. One goal of epistemology is to determine the criteria for knowledge so that we can know what can or cannot be known, in other words, the study of epistemology fundamentally includes the study of meta-epistemology (what we can know about knowledge itself).

We can also distinguish between different types of propositional knowledge, based on the source of that knowledge. Non-empirical or knowledge is possible independently of, or prior to, any experience, and requires only the use of reason; examples include knowledge of logical truths such as the law of non-contradiction, as well as knowledge of abstract claims (such as ethical claims or claims about various conceptual matters). Empirical or a posteriori knowledge is possible only subsequent, or posterior, to certain sense experiences (in addition to the use of reason); examples include knowledge of the color or shape of a physical object or knowledge of geographical locations. (Some philosophers, called rationalists, believe that all knowledge is ultimately grounded upon reason; others, called empiricists, believe that all knowledge is ultimately grounded upon experience.) A thorough epistemology should, of course, address all kinds of knowledge, although there might be different standards for a priori and a posteriori knowledge.

We can also distinguish between individual knowledge and collective knowledge. Social epistemology is the subfield of epistemology that addresses the way that groups, institutions, or other collective bodies might come to acquire knowledge.

2. The Nature of Propositional Knowledge

Having narrowed our focus to propositional knowledge, we must ask ourselves what, exactly, constitutes knowledge. What does it mean for someone to know something? What is the difference between someone who knows something and someone else who does not know it, or between something one knows and something one does not know? Since the scope of knowledge is so broad, we need a general characterization of knowledge, one which is applicable to any kind of proposition whatsoever. Epistemologists have usually undertaken this task by seeking a correct and complete analysis of the concept of knowledge, in other words a set of individually necessary and jointly sufficient conditions which determine whether someone knows something.

a. Belief

Let us begin with the observation that knowledge is a mental state; that is, knowledge exists in one's mind, and unthinking things cannot know anything. Further, knowledge is a specific kind of mental state. While "that"-clauses can also be used to describe desires and intentions, these cannot constitute knowledge. Rather, knowledge is a kind of belief. If one has no beliefs about a particular matter, one cannot have knowledge about it.

For instance, suppose that I desire that I be given a raise in salary, and that I intend to do whatever I can to earn one. Suppose further that I am doubtful as to whether I will indeed be given a raise, due to the intricacies of the university's budget and such. Given that I do not believe that I will be given a raise, I cannot be said to know that I will. Only if I am inclined to believe something can I come to know it. Similarly, thoughts that an individual has never entertained are not among his beliefs, and thus cannot be included in his body of knowledge.

Some beliefs, those which the individual is actively entertaining, are called occurrent beliefs. The majority of an individual's beliefs are non-occurrent; these are beliefs that the individual has in the background but is not entertaining at a particular time. Correspondingly, most of our knowledge is non-occurrent, or background, knowledge; only a small amount of one's knowledge is ever actively on one's mind.

b. Truth

Knowledge, then, requires belief. Of course, not all beliefs constitute knowledge. Belief is necessary but not sufficient for knowledge. We are all sometimes mistaken in what we believe; in other words, while some of our beliefs are true, others are false. As we try to acquire knowledge, then, we are trying to increase our stock of true beliefs (while simultaneously minimizing our false beliefs).

We might say that the most typical purpose of beliefs is to describe or capture the way things actually are; that is, when one forms a belief, one is seeking a match between one's mind and the world. (We sometimes, of course, form beliefs for other reasons - to create a positive attitude, to deceive ourselves, and so forth - but when we seek knowledge, we are trying to get things right.) And, alas, we sometimes fail to achieve such a match; some of our beliefs do not describe the way things actually are.

Note that we are assuming here that there is such a thing as objective truth, so that it is possible for beliefs to match or to fail to match with reality. That is, in order for someone to know something, there must be something one knows about. Recall that we are discussing knowledge in the factive sense; if there are no facts of the matter, then there's nothing to know (or to fail to know). This assumption is not universally accepted - in particular, it is not shared by some proponents of relativism - but it will not be defended here. However, we can say that truth is a condition of knowledge; that is, if a belief is not true, it cannot constitute knowledge. Accordingly, if there is no such thing as truth, then there can be no knowledge. Even if there is such a thing as truth, if there is a domain in which there are no truths, then there can be no knowledge within that domain. (For example, if beauty is in the eye of the beholder, then a belief that something is beautiful cannot be true or false, and thus cannot constitute knowledge.)

c. Justification

Knowledge, then, requires factual belief. However, this does not suffice to capture the nature of knowledge. Just as knowledge requires successfully achieving the objective of true belief, it also requires success with regard to the formation of that belief. In other words, not all true beliefs constitute knowledge; only true beliefs arrived at in the right way constitute knowledge.

What, then, is the right way of arriving at beliefs? In addition to truth, what other properties must a belief have in order to constitute knowledge? We might begin by noting that sound reasoning and solid evidence seem to be the way to acquire knowledge. By contrast, a lucky guess cannot constitute knowledge. Similarly, misinformation and faulty reasoning do not seem like a recipe for knowledge, even if they happen to lead to a true belief. A belief is said to be justified if it is obtained in the right way. While justification seems, at first glance, to be a matter of a belief's being based on evidence and reasoning rather than on luck or misinformation, we shall see that there is much disagreement regarding how to spell out the details.

The requirement that knowledge involve justification does not necessarily mean that knowledge requires absolute certainty, however. Humans are fallible beings, and fallibilism is the view that it is possible to have knowledge even when one's true belief might have turned out to be false. Between beliefs which were necessarily true and those which are true solely by luck lies a spectrum of beliefs with regard to which we had some defeasible reason to believe that they would be true. For instance, if I heard the weatherman say that there is a 90% chance of rain, and as a result I formed the belief that it would rain, then my true belief that it would rain was not true purely by luck. Even though there was some chance that my belief might have been false, there was a sufficient basis for that belief for it to constitute knowledge. This basis is referred to as the justification for that belief. We can then say that, to constitute knowledge, a belief must be both true and justified.

Note that because of luck, a belief can be unjustified yet true; and because of human fallibility, a belief can be justified yet false. In other words, truth and justification are two independent conditions of beliefs. The fact that a belief is true does not tell us whether or not it is justified; that depends on how the belief was arrived at. So, two people might hold the same true belief, but for different reasons, so that one of them is justified and the other is unjustified. Similarly, the fact that a belief is justified does not tell us whether it's true or false. Of course, a justified belief will presumably be more likely to be true than to be false, and justified beliefs will presumably be more likely or more probable to be true than unjustified beliefs. (As we will see in section 3 below, the exact nature of the relationship between truth and justification is contentious.)

d. The Gettier Problem

For some time, the justified true belief (JTB) account was widely agreed to capture the nature of knowledge. However, in 1963, Edmund Gettier published a short but widely influential article which has shaped much subsequent work in epistemology. Gettier provided two examples in which someone had a true and justified belief, but in which we seem to want to deny that the individual has knowledge, because luck still seems to play a role in his belief having turned out to be true.

Consider an example. Suppose that the clock on campus (which keeps accurate time and is well maintained) stopped working at 11:56pm last night, and has yet to be repaired. On my way to my noon class, exactly twelve hours later, I glance at the clock and form the belief that the time is 11:56. My belief is true, of course, since the time is indeed 11:56. And my belief is justified, as I have no reason to doubt that the clock is working, and I cannot be blamed for basing beliefs about the time on what the clock says. Nonetheless, it seems evident that I do not know that the time is 11:56. After all, if I had walked past the clock a bit earlier or a bit later, I would have ended up with a false belief rather than a true one.

This example and others like it, while perhaps somewhat far-fetched, seem to show that it is possible for justified true belief to fail to constitute knowledge. To put it another way, the justification condition was meant to ensure that knowledge was based on solid evidence rather than on luck or misinformation, but Gettier-type examples seem to show that justified true belief can still involve luck and thus fall short of knowledge. This problem is referred to as "the Gettier problem." To solve this problem, we must either show that all instances of justified true belief do indeed constitute knowledge, or alternatively refine our analysis of knowledge.

i. The No-False-Belief Condition

We might think that there is a simple and straightforward solution to the Gettier problem. Note that my reasoning was tacitly based on my belief that the clock is working properly, and that this belief is false. This seems to explain what has gone wrong in this example. Accordingly, we might revise our analysis of knowledge by insisting that to constitute knowledge, a belief must be true and justified and must be formed without relying on any false beliefs. In other words, we might say, justification, truth, and belief are all necessary for knowledge, but they are not jointly sufficient for knowledge; there is a fourth condition - namely, that no false beliefs be essentially involved in the reasoning that led to the belief - which is also necessary.

Unfortunately, this will not suffice; we can modify the example so that my belief is justified and true, and is not based on any false beliefs, but still falls short of knowledge. Suppose, for instance, that I do not have any beliefs about the clock's current state, but merely the more general belief that the clock usually is in working order. This belief, which is true, would suffice to justify my belief that the time is now 11:56; of course, it still seems evident that I do not know the time.

ii. The No-Defeaters Condition

However, the no-false-belief condition does not seem to be completely misguided; perhaps we can add some other condition to justification and truth to yield a correct characterization of knowledge. Note that, even if I didn't actively form the belief that the clock is currently working properly, it seems to be implicit in my reasoning, and the fact that it is false is surely relevant to the problem. After all, if I were asked, at the time that I looked at the clock, whether it is working properly, I would have said that it is. Conversely, if I believed that the clock wasn't working properly, I wouldn't be justified in forming a belief about the time based on what the clock says.

In other words, the proposition that the clock is working properly right now meets the following conditions: it is a false proposition, I do not realize that it is a false proposition, and if I had realized that it is a false proposition, my justification for my belief that it is 11:56 would have been undercut or defeated. If we call propositions such as this "defeaters," then we can say that to constitute knowledge, a belief must be true and justified, and there must not be any defeaters to the justification of that belief. Many epistemologists believe this analysis to be correct.

iii. Causal Accounts of Knowledge

Rather than modifying the JTB account of knowledge by adding a fourth condition, some epistemologists see the Gettier problem as reason to seek a substantially different alternative. We have noted that knowledge should not involve luck, and that Gettier-type examples are those in which luck plays some role in the formation of a justified true belief. In typical instances of knowledge, the factors responsible for the justification of a belief are also responsible for its truth. For example, when the clock is working properly, my belief is both true and justified because it's based on the clock, which accurately displays the time. But one feature that all Gettier-type examples have in common is the lack of a clear connection between the truth and the justification of the belief in question. For example, my belief that the time is 11:56 is justified because it's based on the clock, but it's true because I happened to walk by at just the right moment. So, we might insist that to constitute knowledge, a belief must be both true and justified, and its truth and justification must be connected somehow.

This notion of a connection between the truth and the justification of a belief turns out to be difficult to formulate precisely, but causal accounts of knowledge seek to capture the spirit of this proposal by more significantly altering the analysis of knowledge. Such accounts maintain that in order for someone to know a proposition, there must be a causal connection between his belief in that proposition and the fact that the proposition encapsulates. This retains the truth condition, since a proposition must be true in order for it to encapsulate a fact. However, it appears to be incompatible with fallibilism, since it does not allow for the possibility that a belief be justified yet false. (Strictly speaking, causal accounts of knowledge make no reference to justification, although we might attempt to reformulate fallibilism in somewhat modified terms in order to state this observation.)

While causal accounts of knowledge are no longer thought to be correct, they have engendered reliabilist theories of knowledge, which shall be discussed in section 3b below.

3. The Nature of Justification

One reason that the Gettier problem is so problematic is that neither Gettier nor anyone who preceded him has offered a sufficiently clear and accurate analysis of justification. We have said that justification is a matter of a belief's having been formed in the right way, but we have yet to say what that amounts to. We must now consider this matter more closely.

We have noted that the goal of our belief-forming practices is to obtain truth while avoiding error, and that justification is the feature of beliefs which are formed in such a way as to best pursue this goal. If we think, then, of the goal of our belief-forming practices as an attempt to establish a match between one's mind and the world, and if we also think of the application or withholding of the justification condition as an evaluation of whether this match was arrived at in the right way, then there seem to be two obvious approaches to construing justification: namely, in terms of the believer's mind, or in terms of the world.

a. Internalism

Belief is a mental state, and belief-formation is a mental process. Accordingly, one might reason, whether or not a belief is justified - whether, that is, it is formed in the right way - can be determined by examining the thought-processes of the believer during its formation. Such a view, which maintains that justification depends solely on factors internal to the believer's mind, is called internalism. (The term "internalism" has different meanings in other contexts; here, it will be used strictly to refer to this type of view about epistemic justification.)

According to internalism, the only factors that are relevant to the determination of whether a belief is justified are the believer's other mental states. After all, an internalist will argue, only an individual's mental states - her beliefs about the world, her sensory inputs (for example, her sense data) and her beliefs about the relations between her various beliefs - can determine what new beliefs she will form, so only an individual's mental states can determine whether any particular belief is justified. In particular, in order to be justified, a belief must be appropriately based upon or supported by other mental states.

This raises the question of what constitutes the basing or support relation between a belief and one's other mental states. We might want to say that, in order for belief A to be appropriately based on belief B (or beliefs B1 and B2, or B1, B2, and...Bn), the truth of B must suffice to establish the truth of A, in other words, B must entail A. (We shall consider the relationship between beliefs and sensory inputs below.) However, if we want to allow for our fallibility, we must instead say that the truth of B would give one good reason to believe that A is also true (by making it likely or probable that A is true). An elaboration of what counts as a good reason for belief, accordingly, is an essential part of any internalist account of justification.

However, there is an additional condition that we must add: belief B must itself be justified, since unjustified beliefs cannot confer justification on other beliefs. Because belief B be must also be justified, must there be some justified belief C upon which B is based? If so, C must itself be justified, and it may derive its justification from some further justified belief, D. This chain of beliefs deriving their justification from other beliefs may continue forever, leading us in an infinite regress. While the idea of an infinite regress might seem troubling, the primary ways of avoiding such a regress may have their own problems as well. This raises the "regress problem," which begins from observing that there are only four possibilities as to the structure of one's justified beliefs:

1. The series of justified beliefs, each based upon the other, continues infinitely.

2. The series of justified beliefs circles back to its beginning (A is based on B, B on C, C on D, and D on A).

3. The series of justified beliefs begins with an unjustified belief.

4. The series of justified beliefs begins with a belief which is justified, but not by virtue of being based on another justified belief.

These alternatives seem to exhaust the possibilities. That is, if one has any justified beliefs, one of these four possibilities must describe the relationships between those beliefs. As such, a complete internalist account of justification must decide among the four.

i. Foundationalism

Let us, then, consider each of the four possibilities mentioned above. Alternative 1 seems unacceptable because the human mind can contain only finitely many beliefs, and any thought-process that leads to the formation of a new belief must have some starting point. Alternative 2 seems no better, since circular reasoning appears to be fallacious. And alternative 3 has already been ruled out, since it renders the second belief in the series (and, thus, all subsequent beliefs) unjustified. That leaves alternative 4, which must, by process of elimination, be correct.

This line of reasoning, which is typically known as the regress argument, leads to the conclusion that there are two different kinds of justified beliefs: those which begin a series of justified beliefs, and those which are based on other justified beliefs. The former, called basic beliefs, are able to confer justification on other, non-basic beliefs, without themselves having their justification conferred upon them by other beliefs. As such, there is an asymmetrical relationship between basic and non-basic beliefs. Such a view of the structure of justified belief is known as "foundationalism." In general, foundationalism entails that there is an asymmetrical relationship between any two beliefs: if A is based on B, then B cannot be based on A.

Accordingly, it follows that at least some beliefs (namely basic beliefs) are justified in some way other than by way of a relation to other beliefs. Basic beliefs must be self-justified, or must derive their justification from some non-doxastic source such as sensory inputs; the exact source of the justification of basic beliefs needs to be explained by any complete foundationalist account of justification.

ii. Coherentism

Internalists might be dissatisfied with foundationalism, since it allows for the possibility of beliefs that are justified without being based upon other beliefs. Since it was our solution to the regress problem that led us to foundationalism, and since none of the alternatives seem palatable, we might look for a flaw in the problem itself. Note that the problem is based on a pivotal but hitherto unstated assumption: namely, that justification is linear in fashion. That is, the statement of the regress problem assumes that the basing relation parallels a logical argument, with one belief being based on one or more other beliefs in an asymmetrical fashion.

So, an internalist who finds foundationalism to be problematic might deny this assumption, maintaining instead that justification is the result of a holistic relationship among beliefs. That is, one might maintain that beliefs derive their justification by inclusion in a set of beliefs which cohere with one another as a whole; a proponent of such a view is called a coherentist.

A coherentist, then, sees justification as a relation of mutual support among many beliefs, rather than a series of asymmetrical beliefs. A belief derives its justification, according to coherentism, not by being based on one or more other beliefs, but by virtue of its membership in a set of beliefs that all fit together in the right way. (The coherentist needs to specify what constitutes coherence, of course. It must be something more than logical consistency, since two unrelated beliefs may be consistent. Rather, there must be some positive support relationship - for instance, some sort of explanatory relationship - between the members of a coherent set in order for the beliefs to be individually justified.)

Coherentism is vulnerable to the "isolation objection". It seems possible for a set of beliefs to be coherent, but for all of those beliefs to be isolated from reality. Consider, for instance, a work of fiction. All of the statements in the work of fiction might form a coherent set, but presumably believing all and only the statements in a work of fiction will not render one justified. Indeed, any form of internalism seems vulnerable to this objection, and thus a complete internalist account of justification must address it. Recall that justification requires a match between one's mind and the world, and an inordinate emphasis on the relations between the beliefs in one's mind seems to ignore the question of whether those beliefs match up with the way things actually are.

b. Externalism

Accordingly, one might think that focusing solely on factors internal to the believer's mind will inevitably lead to a mistaken account of justification. The alternative, then, is that at least some factors external to the believer's mind determine whether or not she is justified. A proponent of such a view is called an externalist.

According to externalism, the only way to avoid the isolation objection and ensure that knowledge does not include luck is to consider some factors other than the individual's other beliefs. Which factors, then, should be considered? The most prominent version of externalism, called reliabilism, suggests that we consider the source of a belief. Beliefs can be formed as a result of many different sources, such as sense experience, reason, testimony, memory. More precisely, we might specify which sense was used, who provided the testimony, what sort of reasoning is used, or how recent the relevant memory is. For every belief, we can indicate the cognitive process that led to its formation. In its simplest and most straightforward form, reliabilism maintains that whether or not a belief is justified depends upon whether that process is a reliable source of true beliefs. Since we are seeking a match between our mind and the world, justified beliefs are those which result from processes which regularly achieve such a match. So, for example, using vision to determine the color of an object which is well-lit and relatively near is a reliable belief-forming process for a person with normal vision, but not for a color-blind person. Forming beliefs on the basis of the testimony of an expert is likely to yield true beliefs, but forming beliefs on the basis of the testimony of compulsive liars is not. In general, if a belief is the result of a cognitive process which reliably (most of the time - we still want to leave room for human fallibility) leads to true beliefs, then that belief is justified.

The foregoing suggests one immediate challenge for reliabilism. The formation of a belief is a one-time event, but the reliability of the process depends upon the long-term performance of that process. (This can include counterfactual as well as actual events. For instance, a coin which is flipped only once and lands on heads nonetheless has a 50% chance of landing on tails, even though its actual performance has yielded heads 100% of the time.) And this requires that we specify which process is being used, so that we can evaluate its performance in other instances. However, cognitive processes can be described in more or less general terms: for example, the same belief-forming process might be variously described as sense experience, vision, vision by a normally-sighted person, vision by a normally-sighted person in daylight, vision by a normally-sighted person in daylight while looking at a tree, vision by a normally-sighted person in daylight while looking at an elm tree, and so forth. The "generality problem" notes that some of these descriptions might specify a reliable process but others might specify an unreliable process, so that we cannot know whether a belief is justified or unjustified unless we know the appropriate level of generality to use in describing the process.

Even if the generality problem can be solved, another problem remains for externalism. Keith Lehrer presents this problem by way of his example of Mr. Truetemp. Truetemp has, unbeknownst to him, had a tempucomp - a device which accurately reads the temperature and causes a spontaneous belief about that temperature - implanted in his brain. As a result, he has many true beliefs about the temperature, but he does not know why he has them or what their source is. Lehrer argues that, although Truetemp's belief-forming process is reliable, his ignorance of the tempucomp renders his temperature-beliefs unjustified, and thus that a reliable cognitive process cannot yield justification unless the believer is aware of the fact that the process is reliable. In other words, the mere fact that the process is reliable does not suffice, Lehrer concludes, to justify any beliefs which are formed via that process.

4. The Extent of Human Knowledge

a. Sources of Knowledge

Given the above characterization of knowledge, there are many ways that one might come to know something. Knowledge of empirical facts about the physical world will necessarily involve perception, in other words, the use of the senses. Science, with its collection of data and conducting of experiments, is the paradigm of empirical knowledge. However, much of our more mundane knowledge comes from the senses, as we look, listen, smell, touch, and taste the various objects in our environments.

But all knowledge requires some amount of reasoning. Data collected by scientists must be analyzed before knowledge is yielded, and we draw inferences based on what our senses tell us. And knowledge of abstract or non-empirical facts will exclusively rely upon reasoning. In particular, intuition is often believed to be a sort of direct access to knowledge of the a priori.

Once knowledge is obtained, it can be sustained and passed on to others. Memory allows us to know something that we knew in the past, even, perhaps, if we no longer remember the original justification. Knowledge can also be transmitted from one individual to another via testimony; that is, my justification for a particular belief could amount to the fact that some trusted source has told me that it is true.

b. Skepticism

In addition to the nature of knowledge, epistemologists concern themselves with the question of the extent of human knowledge: how much do we, or can we, know? Whatever turns out to be the correct account of the nature of knowledge, there remains the matter of whether we actually have any knowledge. It has been suggested that we do not, or cannot, know anything, or at least that we do not know as much as we think we do. Such a view is called skepticism.

We can distinguish between a number of different varieties of skepticism. First, one might be a skeptic only with regard to certain domains, such as mathematics, morality, or the external world (this is the most well-known variety of skepticism). Such a skeptic is a local skeptic, as contrasted with a global skeptic, who maintains that we cannot know anything at all. Also, since knowledge requires that our beliefs be both true and justified, a skeptic might maintain that none of our beliefs are true or that none of them are justified (the latter is much more common than the former).

While it is quite easy to challenge any claim to knowledge by glibly asking, "How do you know?", this does not suffice to show that skepticism is an important position. Like any philosophical stance, skepticism must be supported by an argument. Many arguments have been offered in defense of skepticism, and many responses to those arguments have been offered in return. Here, we shall consider two of the most prominent arguments in support of skepticism about the external world.

c. Cartesian Skepticism

In the first of his Meditations, René Descartes offers an argument in support of skepticism, which he then attempts to refute in the later Meditations. The argument notes that some of our perceptions are inaccurate. Our senses can trick us; we sometimes mistake a dream for a waking experience, and it is possible that an evil demon is systematically deceiving us. (The modern version of the evil demon scenario is that you are a brain-in-a-vat, because scientists have removed your brain from your skull, connected it to a sophisticated computer, and immersed it in a vat of preservative fluid. The computer produces what seem to be genuine sense experiences, and also responds to your brain's output to make it seem that you are able to move about in your environment as you did when your brain was still in your body. While this scenario may seem far-fetched, we must admit that it is at least possible.)

As a result, some of our beliefs will be false. In order to be justified in believing what we do, we must have some way to distinguish between those beliefs which are true (or, at least, are likely to be true) and those which are not. But just as there are no signs that will allow us to distinguish between waking and dreaming, there are no signs that will allow us to distinguish between beliefs that are accurate and beliefs which are the result of the machinations of an evil demon. This indistinguishability between trustworthy and untrustworthy belief, the argument goes, renders all of our beliefs unjustified, and thus we cannot know anything. A satisfactory response to this argument, then, must show either that we are indeed able to distinguish between true and false beliefs, or that we need not be able to make such a distinction.

d. Humean Skepticism

According to the indistinguishability skeptic, my senses can tell me how things appear, but not how they actually are. We need to use reason to construct an argument that leads us from beliefs about how things appear to (justified) beliefs about how they are. But even if we are able to trust our perceptions, so that we know that they are accurate, David Hume argues that the specter of skepticism remains. Note that we only perceive a very small part of the universe at any given moment, although we think that we have knowledge of the world beyond that which we are currently perceiving. It follows, then, that the senses alone cannot account for this knowledge, and that reason must supplement the senses in some way in order to account for any such knowledge. However, Hume argues, reason is incapable of providing justification for any belief about the external world beyond the scope of our current sense perceptions. Let us consider two such possible arguments and Hume's critique of them.

i. Numerical vs. Qualitative Identity

We typically believe that the external world is, for the most part, stable. For instance, I believe that my car is parked where I left it this morning, even though I am not currently looking at it. If I were to go peek out the window right now and see my car, I might form the belief that my car has been in the same space all day. What is the basis for this belief? If asked to make my reasoning explicit, I might proceed as follows:

I have had two sense-experiences of my car: one this morning and one just now.
The two sense-experiences were (more or less) identical.
Therefore, it is likely that the objects that caused them are identical.
Therefore, a single object - my car - has been in that parking space all day.

Similar reasoning would undergird all of our beliefs about the persistence of the external world and all of the objects we perceive. But are these beliefs justified? Hume thinks not, since the above argument (and all arguments like it) contains an equivocation. In particular, the first occurrence of "identical" refers to qualitative identity. The two sense-experiences are not one and the same, but are distinct; when we say that they are identical we mean that one is similar to the other in all of its qualities or properties. But the second occurrence of "identical" refers to numerical identity. When we say that the objects that caused the two sense-experiences are identical, we mean that there is one object, rather than two, that is responsible for both of them. This equivocation, Hume argues, renders the argument fallacious; accordingly, we need another argument to support our belief that objects persist even when we are not observing them.

ii. Hume's Skepticism about Induction

Suppose that a satisfactory argument could be found in support of our beliefs in the persistence of physical objects. This would provide us with knowledge that the objects that we have observed have persisted even when we were not observing them. But in addition to believing that these objects have persisted up until now, we believe that they will persist in the future; we also believe that objects we have never observed similarly have persisted and will persist. In other words, we expect the future to be roughly like the past, and the parts of the universe that we have not observed to be roughly like the parts that we have observed. For example, I believe that my car will persist into the future. What is the basis for this belief? If asked to make my reasoning explicit, I might proceed as follows:

My car has always persisted in the past.
Nature is roughly uniform across time and space (and thus the future will be roughly like the past).
Therefore, my car will persist in the future.

Similar reasoning would undergird all of our beliefs about the future and about the unobserved. Are such beliefs justified? Again, Hume thinks not, since the above argument, and all arguments like it, contain an unsupported premise, namely the second premise, which might be called the Principle of the Uniformity of Nature (PUN). Why should we believe this principle to be true? Hume insists that we provide some reason in support of this belief. Because the above argument is an inductive rather than a deductive argument, the problem of showing that it is a good argument is typically referred to as the "problem of induction." We might think that there is a simple and straightforward solution to the problem of induction, and that we can indeed provide support for our belief that PUN is true. Such an argument would proceed as follows:

PUN has always been true in the past.
Nature is roughly uniform across time and space (and thus the future will be roughly like the past).
Therefore, PUN will be true in the future.

This argument, however, is circular; its second premise is PUN itself! Accordingly, we need another argument to support our belief that PUN is true, and thus to justify our inductive arguments about the future and the unobserved.

5. Conclusion

The study of knowledge is one of the most fundamental aspects of philosophical inquiry. Any claim to knowledge must be evaluated to determine whether or not it indeed constitutes knowledge. Such an evaluation essentially requires an understanding of what knowledge is and how much knowledge is possible. While this article provides on overview of the important issues, it leaves the most basic questions unanswered; epistemology will continue to be an area of philosophical discussion as long as these questions remain.

6. References and Further Reading

Alston, William P., 1989. Epistemic Justification: Essays in the Theory of Knowledge. Ithaca, NY: Cornell University Press.

Chisholm, Roderick, 1966. Theory of Knowledge, Englewood Cliffs, NJ: Prentice-Hall.

Chisholm, Roderick, 1977. Theory of Knowledge, 2nd edition. Englewood Cliffs, NJ: Prentice-Hall.

Descartes, Rene, 1641. Meditations on First Philosophy. Reprinted in The Philosophical Writings of Descartes (3 volumes). Cottingham, Stoothoff and Murdoch, trans. Cambridge: Cambridge University Press.
Descartes presents an infallibilist version of foundationalism, and attempts to refute skepticism.

Dancy, Jonathan and Ernest Sosa (eds.), 1993. A Companion to Epistemology. Oxford: Blackwell.

DeRose, Keith, 1995. "Solving the Skeptical Problem" Philosophical Review, 104, pp. 1-52.

DeRose Keith and Ted Warfield (eds.), 1999. Skepticism: A Contemporary Reader. Oxford: Oxford University Press.

Goldman, Alvin, 1976. "A Causal Theory of Knowing." Journal of Philosophy, 64, pp. 357-372.

Hume, David, 1739. A Treatise on Human Nature. Oxford: Oxford University Press.

Hume, David, 1751. An Enquiry Concerning Human Understanding. Indianapolis: Hackett.

Lehrer, Keith and Stewart Cohen, 1983. "Justification, Truth, and Coherence." Synthese, 55, pp. 191-207.

Lewis, David, 1996. "Elusive Knowledge" Australasian Journal of Philosophy, 74, pp. 549-567.

Locke, John, 1689. An Essay Concerning Human Understanding. Oxford: Clarendon.

Plato, Meno and Theaetetus. In Complete Works. J. Cooper, ed. Indianapolis: Hackett.
Plato presents and defends a version of the JTB analysis of knowledge.

Author Information

David A. Truncellito
Email: truncell@aya.yale.edu
U. S. A.

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Epistemology is the study of knowledge. Epistemologists concern themselves with a number of tasks, which we might sort into two categories. First, we must determine the nature of knowledge; that is, what does it mean to say that someone knows, or fails to know, something?

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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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Saudara diminta untuk mempelajari resources yang diberikan pada setiap topik. Jika diperlukan kalian dapat melakukan penelusuran video dan resource lain yang sesuai di internet untuk menjawab pertanyaan pemantik.

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Saudara diminta untuk mempelajari resources yang diberikan pada setiap topik. Jika diperlukan kalian dapat melakukan penelusuran video dan resource lain yang sesuai di internet untuk menjawab pertanyaan pemantik.

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Saudara diminta untuk mempelajari resources yang diberikan pada setiap topik. Jika diperlukan kalian dapat melakukan penelusuran video dan resource lain yang sesuai di internet untuk menjawab pertanyaan pemantik

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Apakah dampak positif yang terjadi akibat adanya revolusi industri?

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Apakah dampak positif yang terjadi akibat adanya revolusi industri?

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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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Resources berisikan timeline penemuan berbagai teknologi di dunia, silahkan melakukan eksplorasi pada laman web tersebut.

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"Inventions and Discoveries" published on by HistoryWorld.

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Video tentang Epistemologi (teori pengetahuan) dari youtube

Kalian dapat melakukan penelusuran video dan resource lain yang sesuai di internet

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Video ini menceritakan fenomena london smog sebagai dampak ditemukanya mesin uap

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5th December 1952: The Great Smog of London begins

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beberapa dampak positif utama yang terjadi akibat revolusi ini:

1. Peningkatan Produksi dan Efisiensi: Teknologi baru, seperti mesin uap, memungkinkan produksi barang secara massal dengan biaya yang lebih rendah. Hal ini menghasilkan barang-barang konsumsi yang lebih terjangkau dan meningkatkan standar hidup masyarakat secara umum

2. Peningkatan Pendidikan dan Literasi: Seiring dengan pertumbuhan industri, ada peningkatan dalam akses pendidikan. Banyak orang mulai mendapatkan pendidikan dasar, dan buku-buku menjadi lebih terjangkau berkat teknologi percetakan yang lebih baik​

3. Peluang Kerja: Revolusi Industri menciptakan banyak lapangan kerja baru di pabrik dan sektor industri lainnya. Meskipun banyak pekerjaan tersebut adalah pekerjaan manual yang berat, mereka tetap memberikan kesempatan bagi banyak orang untuk mendapatkan pendapatan yang lebih baik dibandingkan dengan pertanian

4. Urbanisasi: Munculnya pabrik-pabrik besar menarik banyak orang ke kota-kota untuk mencari pekerjaan.

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The British Industrial Revolution (1760-1840) brought innovative mechanisation and deep social change. The process saw the invention of steam-powered machines, which were used in factories in ever-growing urban centres. Agriculture remained important, but cotton textiles became Britain's top export, capital replaced land as an indicator of wealth, and the labour force diversified to include many more women and children.

Defining a 'Revolution'

Dating the precise beginning and end of the Industrial Revolution in Britain is problematic. Historians do not all agree on precise dates as the 'revolution' was not a single dramatic event or even a series of them, but, rather, a long and gradual process of mechanisation of industry and agriculture, which in turn caused a number of important and long-lasting social changes, chief amongst them being accelerated urbanisation across Britain. The generally agreed range of the mid-18th century to the mid-19th century is useful but misses important, even necessary developments beforehand (for example, the increased efficiency in agriculture) and the continuation of machine inventions (such as the telephone) afterwards.

The term 'industrial revolution', coined by the historian Arnold Toynbee in 1884, is misleading since this process of change was neither quick nor driven by popular uprisings. In addition, the word 'industrial' denies the importance of significant changes in rural life through this period. What is more certain is that the imperfect label 'Industrial Revolution' does capture the idea that tremendous changes occurred so that the countryside, cities, and working life of the late 19th century would have seemed incredible to a visitor from the late 16th century. The author Thomas Hardy (1840-1928) noted that the steam-powered railways alone, probably the most visible element of the 'revolution' for most people, brought more change than any other development since the Norman conquest of England in 1066.

The Industrial Revolution happened first in Britain, and so, when referring to that country alone, it is often called the First Industrial Revolution. Where this mechanisation and urbanisation spread to other countries, it is called the Second Industrial Revolution, for example, in France from 1830, Germany from 1850, and the United States from 1865.

Causes of the Industrial Revolution

The Industrial Revolution began in Britain for a number of reasons. There was an efficient agricultural system that could feed a booming population. With its coalfields, Britain had abundant cheap fuel and, in 1700, was already skilled in mining, producing 80% of the coal in Europe. Another knowledge advantage for Britain was the use of coke as a fuel to make high-quality iron. Coke is made from baking coal in a furnace to remove as many impurities as possible. The first working blast furnace employing coke was used in 1709 at Coalbrookdale in Shropshire, a works owned by Abraham Darby (1678-1717). Britain, then, had both the material to make machines and the fuel to power them even before the Industrial Revolution proper began.

The high cost of labour meant that inventors had a profit motive to design machines that could reduce or replace humans in the workplace.

Labour in Britain was relatively expensive because of the expanding agricultural system, which was now using more and more enclosed land (land requisitioned for farming from common land). Farms needed more labourers, but fewer were available as urbanisation developed, and so wages rose. This fact meant that inventors had a profit motive to design machines that could reduce labour. Capitalists were given favourable conditions by governments to invest in these inventions and Britain's trade empire, particularly that established by the East India Company, could be used to exploit such innovations by providing markets for manufactured goods. There was, too, a trend for people to leave the countryside to find work, and this was exploited and accelerated by business owners able to set up machine-based factories, particularly textile mills. Once the urbanisation ball was rolling at a certain pace, inventions accelerated the 'revolution' as more machines were invented to make even better machines, and so mechanisation surged on. The railways continued the process by creating even more demand for coal, iron, and steel. The pace of urbanisation increased further, and a new middle-class consumer market was created, which drove demand for more innovation and more products. While some other countries had some of these causal factors in place, none had as many as Britain.

Inventors & Machines
The Steam Engine
Water, wind, and muscle power had long been harnessed for heavy machinery such as windmills and waterwheels. These early machines allowed business owners to replace the old cottage industry model, where, for example, skilled weavers worked in their own homes, with a factory system where a number of unskilled workers lived on the premises and operated the machines. The catalyst for even greater change was the invention of the steam engine. Steam power was first developed so that pumps could drain mine shafts and allow deeper mining. The steam pump was patented in 1698 by Thomas Savery (c. 1650-1715). In 1710, Thomas Newcomen (1664-1729) adjusted Savery's design and made the machine more efficient. Newcomen's machine could suck 5,000 gallons (22.7 K litres) every hour out of a 153-foot (46.6 metres) deep mine shaft. The problem was the amount of fuel needed for the machine. In 1769, the Watt steam engine, designed by James Watt (1736-1819) with developments added by Matthew Boulton (1728-1809), answered the market's demand for a powerful engine that could be used anywhere. By 1800, Britain boasted over 2,500 steam engines, most of them used in mines, cotton mills, and factories. This compares to 200 engines in France and fewer than 10 in the USA. Other inventors came along and added to the power capabilities of the steam engine so that, by the 1830s, they could be used to drive trains and steamships.

By the 1870s, trains were carrying over 300 million passengers each year.
Transportation
The steam-powered railways revolutionised travel and Britain itself. On 27 September 1825, the Locomotion 1 train invented by George Stephenson (1781-1848) transported the first railway passengers from Stockton to Darlington in the northeast of England. In 1829, George Stephenson's son, Robert Stephenson (1803-1859), created the Rocket, and he entered it in the Rainhill Trials. The Trials were competitions designed to find the best locomotive for use on the railway line connecting Manchester to Liverpool, which opened in 1830. In 1838, Birmingham was connected to London; in 1841, passengers could take the Great Western Railway line from the capital to Bristol. By 1845, there was a line from Manchester to London, which took eight hours of travel (the old stagecoaches would have taken 80 hours). The railways were booming. By the 1870s, there were over 15,000 miles (24,000 km) of rail lines, with trains carrying over 300 million passengers and over 150 million tonnes of goods each year.

Steam-powered shipping followed the trains. The engineer Isambard Kingdom Brunel (1806-1859) used a steam engine to power his giant ships the SS Great Western (1838), the innovative propellor-driven SS Great Britain (1843), and the SS Great Eastern (1858), the largest ship in the world at 692 feet (211 m) long. These ships and others crossed the Atlantic faster than ever before (10 days compared to 32 using just sail), and soon ambitious new routes to India and Australia were established.
Factories
From the 1790s, steam-powered machines were used with such success in the textile industry that by 1835 around 75% of cotton mills were using steam power. A series of machines had been invented which revolutionised how cotton was cleaned, spun, and woven. These devices were the flying shuttle (John Kay, 1733), spinning jenny (James Hargreaves, 1764), waterframe (Richard Arkwright, 1769), spinning mule ( Samuel Crompton, 1779), power loom (Edmund Cartwright, 1785), cotton gin (Eli Whitney, 1794), and Robert's loom and self-acting mule (Richard Roberts, 1822-5). Because of the mechanised factory system, the British "cotton mill of 1836 was so efficient that it could out-compete hand spinning anywhere in the world" (Allen, 187).

Some people protested at the increasing mechanisation. The period between 1811 and 1816 was particularly problematic for factory owners. The Luddites broke into factories and smashed the machines that had taken away their livelihoods. However, in the longer term, many more jobs were created in the factories than had been available in the old cottage industries. By 1830, one in 80 Britons worked in a textile mill.
Agriculture
The Industrial Revolution is often described as a move from an agrarian society to an industrial one, but agriculture remained an important sector of the British economy. Farming expanded to meet a growing population through the process of enclosure. In 55 years from 1760 to 1815, over 7 million acres (28,300 km²) of British communal land was enclosed. Better fertilisers improved crop yields. New breeding methods improved livestock.

The mobility and fuel efficiency of the Watt steam engine meant that farmers could use various machines anywhere and precisely when they were needed. Andrew Rodgers invented the winnowing machine in 1737 (which separated the wheat from the chaff). In 1787, Andrew Meikle (1719-1811) invented the first steam-powered threshing machine (which separated the grain from the husk). Steam-powered machines could uproot trees that blocked fields and drain waterlogged areas to make them arable. Machine-made tools were cheaper, had better cutting edges, and lasted longer than previously. Mass production allowed farmers to repair their machines with spare parts, rather than replace them entirely.

All of these factors made food cheaper for everyone. British agricultural products, along with imports, were able to feed a population which had risen from 6 million in 1750 to 21 million in 1851. A downside was that as farming became more productive, rents rocketed, which meant many small-scale farmers were forced to move elsewhere or try a different profession. Just like the Luddites, some protested violently at mechanisation. The Swing Riots of 1830 to 1832 saw a short-lived spurt of machine wrecking in the countryside. While it was true that people left rural areas to find new work and new lives in cities, many remained. In 1841, "just over 1 in 5, 22 percent of the country's workforce, worked on the land" (Shelley, 44).

Other Inventions

Other important inventions during the Industrial Revolution included Harrison's marine chronometer, invented by John Harrison (1693-1776) in 1770, which allowed navigators to accurately measure longitude. The world's first cast iron bridge was built across the River Severn in Shropshire by Abraham Darby III (1750-89), opened to the public in 1781. Frederick Albert Winsor (1763-1830) demonstrated in London in 1807 his new invention of street lights which used coal gas, a tremendously useful substance that was also used for home heating and cooking. The milling machine was invented around 1818, but, typical of many inventions in this period where ideas were shared, borrowed, and stolen, it is difficult to pin down exactly who invented it. The machine cut pieces of metal like bolts and nuts that would have been near-impossible to do by hand. Portland cement was a fast-setting cement invented in 1824 by Joseph Aspdin (1778-1859). The telegraph machine was invented in 1837 by William Fothergill Cook (1806-1879) and Charles Wheatstone (1802-1875), and it revolutionised communication. The steam hammer was developed in 1839 by James Nasmyth (1808-1890) and allowed huge metal pieces to be uniformly bent, essential for large steam engines, bridges, and ships. Finally, the Bessemer converter, invented by Henry Bessemer (1813-1898) in 1856, allowed for a much cheaper production of steel, which is stronger and lighter than iron.

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The Positive Impact of the Industrial Revolution

The impact of the British Industrial Revolution was dramatic. Steam-powered machines reduced production costs, made profits higher, and permitted mass-produced consumer goods to be cheaper. The transport revolution continued this trend because a single train could carry 20 times the cargo of a canal boat and reach its destination eight times faster. Mechanisation and the railways created a boom in the coal mining, iron, and steel industries. There was a whole raft of new jobs available, such as in the railway stations, on construction sites, and in the factories. Women gained more financial independence; women comprised over half the workforce in textile factories. Most people could afford a train excursion to the seaside once a year. The telegraph meant the speed of communication vastly increased.

Literacy improved thanks to the opportunities for basic schooling increasing and books becoming cheaper thanks to papermaking and printing machines. People in cities married younger and had more children. Life expectancy rose because of better diet and new vaccinations but much depended on a person's job, and infant mortality rates could be high in some periods.

The urban middle class expanded to around 25% of the population by 1800, and they were often able to live in the more pleasant leafy suburbs of cities. The middle classes could frequent the ever-increasing number of shops that stocked an increasingly wide range of goods from across Britain and its empire. They were enticed to spend their disposable income through new marketing strategies like mass advertising and elegant showrooms like those of the potter Josiah Wedgwood (1730-1795). The middle classes could employ servants and send their children to better schools or private tutors. The standard of living rose for most people during the Industrial Revolution, on average by around 30%, but only from the 1830s was this the experience of the lower classes.

The Negative Impact of the Industrial Revolution

The benefits of the 'revolution' came at a cost. Traditional industries like handweaving and stagecoaches were all but destroyed by the arrival of steam power. The demand for cheap labour was insatiable as the profit motive became more important to more business owners. From 1800 to 1850, children composed between 20-50% of the mining workforce, working on average from the age of eight. Exploited with lower pay but the same 12-hour shifts as adults, child labour was used in every industry. An 1851 commission found that "one-third of children under the age of 15 worked outside the home" (Horn, 57). These children too often lived short and uneducated lives.

The factories offered many new jobs, but much of the work was unskilled, dull, and repetitive. The pay was regular, but the working day was ruled by the clock. There was no minimum wage, salaries were not related to inflation, and employees faced the ever-present threat of instant dismissal. Factory workers had few transferable skills, and so they were stuck at their level of work. Further, opening a business now required significant capital to invest in machinery so that one's product could be competitively priced. In addition, in the factory system, where workers concentrated only on a specific part of the production process, workers had little sense of achievement in the finished article, something they might have done in the old domestic system where a worker worked alone on a single item.

For men, women, and children, factories were dangerous and unhealthy places. Cotton mills were always kept dark and damp to protect the cotton threads, a situation detrimental to the lungs of the workers. Mines had a similar hazard and others. Machines were dangerous and could cause serious injury when pieces broke off or when fast-moving parts trapped fingers and limbs. Factories were noisy, and workers often suffered from impaired hearing. The common use of toxic substances like lead and mercury was another health hazard. Managers imposed strict rules and dished out fines. Attempts to form trade unions met with a total ban from the government from 1799 and 1824. Gradually, there were reforms from the 1830s, and working conditions and workers' rights did improve as working days were limited to 10 hours and employers were obliged to pay more attention to hygiene and safety in the workplace.

Urbanisation greatly accelerated during the Industrial Revolution. The 1851 census revealed that, for the first time, more people were living in towns and cities than in the countryside. This trend caused unique problems. Cities became cramped, and workers often lived in cheap housing, with families sharing properties. The streets were polluted by a lack of sanitation. In 1837, 1839, and 1847, there were typhus epidemics. In 1831 and 1849, there were cholera epidemics. The air was polluted, too, with so many factories belching out smoke from their coal furnaces. Crime rose, although largely only petty crime, as the urban poor grew in number and escaping justice became easier in the anonymity of large cities. The state made a half-hearted attempt to help the unemployed by offering the workhouse, an institution that deliberately offered a worse life than even the lowest-paid labourer could gain in case it became an attractive alternative to employment. Despite all the problems, urbanisation continued so that by 1880 only 20% of Britain's population lived in rural areas, and land ownership was concentrated in just 5% of the population.

The Spread of the Industrial Revolution

Other countries caught up with Britain. Ideas in technology, industry, and farming easily crossed borders. Some countries with very cheap labour or expensive fuel had to wait until the machines became cheaper and more efficient. The spread of the railways was a good indicator of this process. In the United States, the first working railroad was completed in 1833 (New York to Philadelphia). The first railway line in Continental Europe was completed in Belgium in 1835 (Brussels to Malines). By 1870, Canada, Australia, India, and most of Europe had joined in the railway mania. So it was with other innovations. By the 20th century, whether directly or indirectly, few states in the world remained unaffected by the tentacles of 'progress' the Industrial Revolution put forth.

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The British Industrial Revolution (1760-1840) brought innovative mechanisation and deep social change. The process saw the invention of steam-powered machines, which were used in factories in ever-growing...

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Apakah dampak lingkungan yang ditimbulkan pada masing-masing era revolusi industri?

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Apakah dampak lingkungan yang ditimbulkan pada masing-masing era revolusi industri?

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Tuliskan jawabannya dalam padlet berikut. Jawaban harus menyertakan resources dari internet berupa link (video, artikel web, jurnal dll)

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Video ringkasan terhadap lini masa berbagai penemuan penting manusia.

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Technology Evolution | 100,000 BC - 2020

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Referensi Bacaan, Theory of Knowledge.

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Bertrand Russell (1926)

THEORY OF KNOWLEDGE is a product of doubt. When we have asked ourselves seriously whether we really know anything at all, we are naturally led into an examination of knowing, in the hope of being able to distinguish trustworthy beliefs from such as are untrustworthy. Thus Kant, the founder of modern theory of knowledge, represents a natural reaction against Hume's scepticism. Few philosophers nowadays would assign to this subject quite such a fundamental importance as it had in Kant's "critical" system; nevertheless it remains an essential part of philosophy. It is perhaps unwise to begin with a definition of the subject, since, as elsewhere in philosophical discussions, definitions are controversial, and will necessarily differ for different schools; but we may at least say that the subject is concerned with the general conditions of knowledge, in so far as they throw light upon truth and falsehood.

It will be convenient to divide our discussion into three stages, concerning respectively (1) the definition of knowledge, (2) data, (3) methods of inference. It should be said, however, that in distinguishing between data and inferences we are already taking sides on a debatable question, since some philosophers hold that this distinction is illusory, all knowledge being (according to them) partly immediate and partly derivative.

I. THE DEFINITION OF KNOWLEDGE

The question how knowledge should be defined is perhaps the most important and difficult of the three with which we shall deal. This may seem surprising: at first sight it might be thought that knowledge might be defined as belief which is in agreement with the facts. The trouble is that no one knows what a belief is, no one knows what a fact is, and no one knows what sort of agreement between them would make a belief true. Let us begin with belief.

Belief.

Traditionally, a "belief" is a state of mind of a certain sort. But the behaviourists deny that there are states of mind, or at least that they can be known; they therefore avoid the word "belief", and, if they used it, would mean by it a characteristic of bodily behaviour. There are cases in which this usage would be quite in accordance with common sense. Suppose you set out to visit a friend whom you have often visited before, but on arriving at your destination you find that he has moved, you would say "I thought he was still living at his old house." Yet it is highly probable that you did not think about it at all, but merely pursued the usual route from habit. A "thought" or "belief" may, therefore, in the view of common sense, be shown by behaviour, without any corresponding "mental" occurrence. And even if you use a form of words such as is supposed to express belief, you are still engaged in bodily behaviour, provided you pronounce the words out loud or to yourself. Shall we say, in such cases, that you have a belief? Or is something further required?

It must be admitted that behaviour is practically the same whether you have an explicit belief or not. People who are out of doors when a shower of rain comes on put up their umbrellas, if they have them; some say to themselves "it has begun to rain", others act without explicit thought, but the result is exactly the same in both cases. In very hot weather, both human beings and animals go out of the sun into the shade, if they can; human beings may have an explicit "belief " that the shade is pleasanter, but animals equally seek the shade. It would seem, therefore, that belief, if it is not a mere characteristic of behaviour, is causally unimportant. And the distinction of truth and error exists where there is behaviour without explicit belief, just as much as where explicit belief is present; this is shown by the illustration of going to where your friend used to live. Therefore, if theory of knowledge is to be concerned with distinguishing truth from error, we shall have to include the cases in which there is no explicit belief, and say that a belief may be merely implicit in behaviour. When old Mother Hubbard went to the cupboard, she "believed" that there was a bone there, even if she had no state of mind which could be called cognitive in the sense of introspective psychology.

Words.

In order to bring this view into harmony with the facts of human behaviour, it is of course necessary to take account of the influence of words. The beast that desires shade on a hot day is attracted by the sight of darkness; the man can pronounce the word "shade", and ask where it is to be found. According to the behaviourists, it is the use of words and their efficacy in producing conditional responses that constitutes "thinking". I It is unnecessary for our purposes to inquire whether this view gives the whole truth about the matter. What it is important to realise is that verbal behaviour has the characteristics which lead us to regard it as pre-eminently a mark of "belief", even when the words are repeated as a mere bodily habit. Just as the habit of going to a certain house when you wish to see your friend may be said to show that you "believe" he lives in that house, so the habit of saying "two and two are four", even when merely verbal, must be held to constitute "belief " in this arithmetical proposition. Verbal habits are, of course, not infallible evidences of belief. We may say every Sunday that we are miserable sinners, while really thinking very well of ourselves. Nevertheless, speaking broadly, verbal habits crystallise our beliefs, and afford the most convenient way of making them explicit. To say more for words is to fall into that superstitious reverence for them which has been the bane of philosophy throughout its history.

Belief and Behaviour

We are thus driven to the view that, if a belief is to be something causally important, it must be defined as a characteristic of behaviour. This view is also forced upon us by the consideration of truth and falsehood, for behaviour may be mistaken in just the way attributable to a false belief, even when no explicit belief is present-for example, when a man continues to hold up his umbrella after the rain has stopped without definitely entertaining the opinion that it is still raining. Belief in this wider sense may be attributed to animals-for example, to a dog who runs to the dining-room when he hears the gong. And when an animal behaves to a reflection in a looking-glass as if it were "real", we should naturally say that he "believes" there is another animal there; this form of words is permitted by our definition.

It remains, however, to say what characteristics of behaviour can be described as beliefs. Both human beings and animals act so as to achieve certain results, e.g. getting food. Sometimes they succeed, sometimes they fail-, when they succeed, their relevant beliefs are "true", but when they fail, at least one is false. There will usually be several beliefs involved in a given piece of behaviour, and variations of environment will be necessary to disentangle the causal characteristics which constitute the various beliefs. This analysis is effected by language, but would be very difficult if applied to dumb animals. A sentence may be taken as a law of behaviour in any environment containing certain characteristics; it will be "true" if the behaviour leads to results satisfactory to the person concerned, and otherwise it will be "false". Such, at least, is the pragmatist definition of truth and falsehood.

Truth in Logic.

There is also, however, a more logical method of discussing this question. In logic, we take for granted that a word has a "meaning"; what we signify by this can, I think, only be explained in behaviouristic terms, but when once we have acquired a vocabulary of words which have "meaning", we can proceed in a formal manner without needing to remember what "meaning" is. Given the laws of syntax in the language we are using, we can construct propositions by putting together the words of the language, and these propositions have meanings which result from those of the separate words and are no longer arbitrary. If we know that certain of these propositions are true, we can infer that certain others are true, and that vet others are false; sometimes this can be inferred with certainty, sometimes with greater or less probability. In all this logical manipulation, it is unnecessary to remember what constitutes meaning and what constitutes truth or falsehood. It is in this formal region that most philosophy has lived- and within this region a great deal can be said that is both true and important, without the need of' any fundamental doctrine about meaning. It even seems possible to define "truth" in terms of "meaning" and "fact", as opposed to the pragmatic definition which we gave a moment ago. If so, there will be two valid definitions of "truth", though of course both will apply to the same propositions.

The purely formal definition of "truth" may be illustrated by a simple case. The word "Plato" means a certain man; the word "Socrates" means a certain other man; the word "love" means a certain relation. This being given, the meaning of the complex symbol "Plato loves Socrates" is fixed; we say that this complex symbol is "true" if there is a certain fact in the world, namely the fact that Plato loves Socrates, and in the contrary case the complex symbol is false. I do not think this account is false, but, like everything purely formal, it does not probe very deep.

Uncertainty and Vagueness.

In defining knowledge, there are two further matters to be taken into consideration, namely the degree of certainty and the degree of precision. All knowledge is more or less uncertain and more or less vague. These are, in a sense, opposing characters: vague knowledge has more likelihood of truth than precise knowledge, but is less useful. One of the aims of science is to increase precision without diminishing certainty. But we cannot confine the word "knowledge" to what has the highest degree of both these qualities; we must include some propositions that are rather vague and some that are only rather probable. It Is important, however, to indicate vagueness and uncertainty where they are present, and, if possible, to estimate their degree. Where this can be done precisely, it becomes "probable error" and "probability". But in most cases precision in this respect is impossible.

II. THE DATA

In advanced scientific knowledge, the distinction between what is a datum and what is inferred is clear in fact, though sometimes difficult in theory. In astronomy, for instance, the data are mainly certain black and white patterns on photographic plates. These are called photographs of this or that part of the heavens, but of course much inference is involved in using them to give knowledge about stars or planets. Broadly speaking, quite different methods and a quite different type of skill are required for the observations which provide the data in a quantitative science, and for the deductions by which the data are shown to support this or that theory. There would be no reason to expect Einstein to be particularly good at photographing the stars near the sun during an eclipse. But although the distinction is practically obvious in such cases, It is far less so when we come to less exact knowledge. It may be said that the separation into data and inferences belongs to a well-developed stage of knowledge, and is absent in its beginnings.

Animal Inference.

But just as we found it necessary to admit that knowledge may be only a characteristic of behaviour, so we shall have to say about inference. What a logician recognises as inference is a refined operation, belonging to a high degree of intellectual development; but there is another kind of inference which is practised even by animals. We must consider this primitive form of inference before we can become clear as to what we mean by "data".

When a dog hears the gong and immediately goes into the dining-room, he is obviously, in a sense, practising inference. That is to say, his response is appropriate, not to the noise of the gong in itself, but to that of which the noise is a sign: his reaction is essentially similar to our reactions to words. An animal has the characteristic that, when two stimuli have been experienced together, one tends to call out the response which only the other could formerly call out. If the stimuli (or one of them) are emotionally powerful, one joint experience may be enough-, if not, many joint experiences may be required. This characteristic is totally absent in machines. Suppose, for instance, that you went every day for a year to a certain automatic machine, and lit a match in front of it at the same moment at which you inserted a penny-, it would not, at the end, have any tendency to give up its chocolate on the mere sight of a burning match. That is to say, machines do not display inference even in the form in which it is a mere characteristic of behaviour. Explicit inference, such as human beings practise, is a rationalising of the behaviour which we share with the animals. Having experienced A and B together frequently, we now react to A as we originally reacted to B. To make this seem rational, we say that A is a "sign" of B, and that B must really be present though out of sight. This is the principle of induction, upon which almost all science is based. And a great deal of philosophy is an attempt to make the principle seem reasonable.

Whenever, owing to past experience, we react to A in the manner in which we originally reacted to B, we may say that A is a "datum" and B is "Inferred". In this sense, animals practise inference. It is clear, also, that much inference of this sort is fallacious: the conjunction of A and B in past experience may have been accidental. What is less clear is that there is any way of refining this type of inference which will make it valid. That, however, is a question which we shall consider later. What I want consider now is the nature of those elements in our experiences which, to a reflective analysis, appear as "data" in the above-defined sense.

Mental and Physical Data.

Traditionally, there are two sorts of data, one physical, derived from the senses, the other mental, derived from introspection. It seems highly questionable whether this distinction can be validly made among data; it seems rather to belong to what is inferred from them. Suppose, for the sake of definiteness, that you are looking at a white triangle drawn on a black-board. You can make the two judgments: "There is a triangle there", and "I see a triangle." These are different propositions, but neither expresses a bare datum; the bare datum seems to be the same in both propositions. To illustrate the difference of the propositions: you might say "There is a triangle there", if you had seen it a moment ago but now had your eyes shut, and in this case you would not say "I see a triangle"; on the other hand, you might see a black dot which you knew to be due to indigestion or fatigue, and in this case you would not say "There is a black dot there." In the first of these cases, you have a clear case of inference, not of a datum.

In the second case, you refuse to infer a public object, open to the observation of others. This shows that "I see a triangle" comes nearer to being a datum than "There is a triangle there." But the words "I" and "see" both involve inferences, and cannot be included in any form of words which aims at expressing a bare datum. The word "I" derives its meaning, partly, from memory and expectation, since I do not exist only at one moment. And the word "see" is a causal word, suggesting dependence upon the eyes; this involves experience, since a new-born baby does not know that what it sees depends upon its eyes. However, we can eliminate this dependence upon experience, since obviously all seen objects have a common quality, not belonging to auditory or tactual or any other objects. Let us call this quality that of being "visual". Then we can say: "There is a visual triangle." This is about as near as we can get in words to the datum for both propositions: "There is a triangle there", and "I see a triangle." The difference between the propositions results from different inferences: in the first, to the public world of physics, involving perceptions of others; in the second, to the whole of my experience, in which the visual triangle is an element. The difference between the physical and the mental, therefore, would seem to belong to inferences and constructions, not to data.

It would thus seem that data, in the sense in which we are using the word, consist of brief events, rousing in us various reactions, some of which may be called "inferences", or may at least be said to show the presence of inference. The two-fold organisation of these events, on the one hand as constituents of the public world of physics, on the other hand as parts of a personal experience, belongs to what is inferred, not to what is given. For theory of knowledge, the question of the validity of inference is vital. Unfortunately, nothing very satisfactory can be said about it, and the most careful discussions have been the most sceptical. However, let us examine the matter without prejudice.

III. METHODS OF INFERENCE

It is customary to distinguish two kinds of inference, Deduction and Induction. Deduction is obviously of great practical importance, since it embraces the whole of mathematics. But it may be questioned whether it is, in any strict sense, a form of inference at all. A pure deduction consists merely of saying the same thing in another way. Application to a particular case may have importance, because we bring in the experience that there is such a case-for example, when we infer that Socrates is mortal because all men are mortal. But in this case we have brought in a new piece of experience, not involved in the abstract deductive schema. In pure deduction, we deal with x and y not with empirically given objects such as Socrates and Plato. However this may be, pure deduction does not raise the problems which are of most importance for theory of knowledge, and we may therefore pass it by.

Induction.

The important forms of inference for theory of knowledge are those in which we infer the existence of something having certain characteristics from the existence of something having certain other characteristics. For example: you read in the newspaper that a certain eminent man is dead, and you infer that he is dead. Sometimes, of course, the inference is mistaken. I have read accounts of my own death in newspapers, but I abstained from inferring that I was a ghost. In general, however, such inferences are essential to the conduct of life. Imagine the life of a sceptic who doubted the accuracy of the telephone book, or, when he received a letter, considered seriously the possibility that the black marks might have been made accidentally by an inky fly crawling over the paper. We have to accept merely probable knowledge in daily life, and theory of knowledge must help us to decide when it really is probable, and not mere animal prejudice.

Probability.

Far the most adequate discussion of the type of inference we are considering is obtained in J. M. Keynes's Treatise on Probability (1921). So superior is his work to that of his predecessors that it renders consideration of them unnecessary. Mr. Keynes considers induction and analogy together, and regards the latter as the basis of the former. The bare essence of an inference by analogy is as follows: We have found a number of instances in which two characteristics are combined, and no instances in which they are not combined; we find a new instance in which we know that one of the characteristics is present, but do not know whether the other is present or absent; we argue by analogy that probably the other characteristic is also present. The degree of probability which we infer will vary according to various circumstances. It is undeniable that we do make such inferences, and that neither science nor daily life would be possible without them. The question for the logician is as to their validity. Are they valid always, never or sometimes? And in the last case, can we decide when they are valid?

Limitation of Variety.

Mr. Keynes considers that mere increase in the number of instances in which two qualities are found together does not do much to strengthen the probability of their being found together in other instances. The important point, according to him, is that in the known cases the instances should have as few other qualities in common as possible. But even then a further assumption is required, which is called the principle of limitation of variety. This assumption is stated as follows : "That the objects in the field, over which our generalisations extend, do not have an infinite number of independent qualities; that, in other words, their characteristics, however numerous, cohere together in groups of invariable connection, which are finite in number." It is not necessary to regard this assumption as certain; it is enough if there is some finite probability in its favour.

It is not easy to find any arguments for or against an a priori finite probability in favour of the limitation of variety. It should be observed, however, that a "finite" probability, in Mr. Keynes's terminology, means a probability greater than some numerically measurable probability, e.g. the probability of a penny coming "heads" a million times running. When this is realised, the assumption certainly seems plausible. The strongest argument on the side of scepticism is that both men and animals are constantly led to beliefs (in the behaviouristic sense), which are caused by what may be called invalid inductions; this happens whenever some accidental collocation has produced an association not in accordance with any objective law. Dr. Watson caused an infant to be terrified of white rats by beating a gong behind its head at the moment of showing it a white rat (Behaviourism). On the whole, however, accidental collocations will usually tend to be different for different people, and therefore the inductions in which men are agreed have a good chance of being valid. Scientific inductive or analogical inferences may, in the best cases, be assumed to have a high degree of probability, if the above principle of limitation of variety is true or finitely probable. This result is not so definite as we could wish, but it is at least preferable to Hume's complete scepticism. And it is not obtained, like Kant's answer to Hume, by a philosophy ad hoc; it proceeds on the ordinary lines of scientific method.

Grades of Certainty.

Theory of knowledge, as we have seen, is a subject which is partly logical, partly psychological; the connection between these parts is not very close. The logical part may, perhaps, come to be mainly an organisation of what passes for knowledge according to differing grades of certainty: some portions of our beliefs involve more dubious assumptions than are involved in other parts. Logic and mathematics on the one hand, and the facts of perception on the other, have the highest grade of certainty; where memory comes in, the certainty is lessened; where unobserved matter comes in, the certainty is further lessened; beyond all these stages comes what a cautious man of science would admit to be doubtful. The attempt to increase scientific certainty by means of some special philosophy seems hopeless, since, in view of the disagreement of philosophers, philosophical propositions must count as among the most doubtful of those to which serious students give an unqualified assent. For this reason, we have confined ourselves to discussions which do not assume any definite position on philosophical as opposed to scientific questions.

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Bertrand Russell's entry on The Theory of Knowledge for the 1926 edition of the Encyclopaedia Britannica

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Video ringkasan mengenai revolusi industri yang berkembang dari revolusi industri 1 sampai revolusi industri 4

Kalian dapat melakukan penelusuran video dan resource lain yang sesuai di internet

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Beberapa Cara manusia mendapatkan ilmu pengetahuan

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Beberapa Cara manusia mendapatkan ilmu pengetahuan

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1. Persepsi Indra: Pengetahuan diperoleh melalui pengalaman langsung dari pancaindra, seperti melihat, mendengar, atau merasakan sesuatu di dunia eksternal. Ini adalah bentuk pengetahuan empiris yang didasarkan pada observasi.

2. Penalaran (Rasionalisme): Pengetahuan juga bisa diperoleh melalui penalaran logis. Dalam pendekatan ini, seseorang menggunakan deduksi dan induksi untuk menarik kesimpulan berdasarkan prinsip-prinsip atau informasi yang sudah diketahui sebelumnya.

3. Testimoni (Pengetahuan dari Orang Lain): Banyak pengetahuan manusia berasal dari informasi yang disampaikan oleh orang lain, seperti buku, guru, atau media. Hal ini disebut sebagai pengetahuan melalui testimoni.

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Epistemology is the study of knowledge. Epistemologists concern themselves with a number of tasks, which we might sort into two categories.

First, we must determine the nature of knowledge; that is, what does it mean to say that someone knows, or fails to know, something? This is a matter of understanding what knowledge is, and how to distinguish between cases in which someone knows something and cases in which someone does not know something. While there is some general agreement about some aspects of this issue, we shall see that this question is much more difficult than one might imagine.

Second, we must determine the extent of human knowledge; that is, how much do we, or can we, know? How can we use our reason, our senses, the testimony of others, and other resources to acquire knowledge? Are there limits to what we can know? For instance, are some things unknowable? Is it possible that we do not know nearly as much as we think we do? Should we have a legitimate worry about skepticism, the view that we do not or cannot know anything at all?

Although this article provides an overview of the important issues, it leaves the most basic questions unanswered; epistemology will continue to be an area of philosophical discussion as long as these questions remain.

Table of Contents

1. Kinds of Knowledge

The term "epistemology" comes from the Greek "episteme," meaning "knowledge," and "logos," meaning, roughly, "study, or science, of." "Logos" is the root of all terms ending in "-ology" - such as psychology, anthropology - and of "logic," and has many other related meanings.

The word "knowledge" and its cognates are used in a variety of ways. One common use of the word "know" is as an expression of psychological conviction. For instance, we might hear someone say, "I just knew it wouldn't rain, but then it did." While this may be an appropriate usage, philosophers tend to use the word "know" in a factive sense, so that one cannot know something that is not the case. (This point is discussed at greater length in section 2b below.)

Even if we restrict ourselves to factive usages, there are still multiple senses of "knowledge," and so we need to distinguish between them. One kind of knowledge is procedural knowledge, sometimes called competence or "know-how;" for example, one can know how to ride a bicycle, or one can know how to drive from Washington, D.C. to New York. Another kind of knowledge is acquaintance knowledge or familiarity; for instance, one can know the department chairperson, or one can know Philadelphia.

Epistemologists typically do not focus on procedural or acquaintance knowledge, however, instead preferring to focus on propositional knowledge. A proposition is something which can be expressed by a declarative sentence, and which purports to describe a fact or a state of affairs, such as "Dogs are mammals," "2+2=7," "It is wrong to murder innocent people for fun." (Note that a proposition may be true or false; that is, it need not actually express a fact.) Propositional knowledge, then, can be called knowledge-that; statements of propositional knowledge (or the lack thereof) are properly expressed using "that"-clauses, such as "He knows that Houston is in Texas," or "She does not know that the square root of 81 is 9." In what follows, we will be concerned only with propositional knowledge.

Propositional knowledge, obviously, encompasses knowledge about a wide range of matters: scientific knowledge, geographical knowledge, mathematical knowledge, self-knowledge, and knowledge about any field of study whatever. Any truth might, in principle, be knowable, although there might be unknowable truths. One goal of epistemology is to determine the criteria for knowledge so that we can know what can or cannot be known, in other words, the study of epistemology fundamentally includes the study of meta-epistemology (what we can know about knowledge itself).

We can also distinguish between different types of propositional knowledge, based on the source of that knowledge. Non-empirical or knowledge is possible independently of, or prior to, any experience, and requires only the use of reason; examples include knowledge of logical truths such as the law of non-contradiction, as well as knowledge of abstract claims (such as ethical claims or claims about various conceptual matters). Empirical or a posteriori knowledge is possible only subsequent, or posterior, to certain sense experiences (in addition to the use of reason); examples include knowledge of the color or shape of a physical object or knowledge of geographical locations. (Some philosophers, called rationalists, believe that all knowledge is ultimately grounded upon reason; others, called empiricists, believe that all knowledge is ultimately grounded upon experience.) A thorough epistemology should, of course, address all kinds of knowledge, although there might be different standards for a priori and a posteriori knowledge.

We can also distinguish between individual knowledge and collective knowledge. Social epistemology is the subfield of epistemology that addresses the way that groups, institutions, or other collective bodies might come to acquire knowledge.

2. The Nature of Propositional Knowledge

Having narrowed our focus to propositional knowledge, we must ask ourselves what, exactly, constitutes knowledge. What does it mean for someone to know something? What is the difference between someone who knows something and someone else who does not know it, or between something one knows and something one does not know? Since the scope of knowledge is so broad, we need a general characterization of knowledge, one which is applicable to any kind of proposition whatsoever. Epistemologists have usually undertaken this task by seeking a correct and complete analysis of the concept of knowledge, in other words a set of individually necessary and jointly sufficient conditions which determine whether someone knows something.

a. Belief

Let us begin with the observation that knowledge is a mental state; that is, knowledge exists in one's mind, and unthinking things cannot know anything. Further, knowledge is a specific kind of mental state. While "that"-clauses can also be used to describe desires and intentions, these cannot constitute knowledge. Rather, knowledge is a kind of belief. If one has no beliefs about a particular matter, one cannot have knowledge about it.

For instance, suppose that I desire that I be given a raise in salary, and that I intend to do whatever I can to earn one. Suppose further that I am doubtful as to whether I will indeed be given a raise, due to the intricacies of the university's budget and such. Given that I do not believe that I will be given a raise, I cannot be said to know that I will. Only if I am inclined to believe something can I come to know it. Similarly, thoughts that an individual has never entertained are not among his beliefs, and thus cannot be included in his body of knowledge.

Some beliefs, those which the individual is actively entertaining, are called occurrent beliefs. The majority of an individual's beliefs are non-occurrent; these are beliefs that the individual has in the background but is not entertaining at a particular time. Correspondingly, most of our knowledge is non-occurrent, or background, knowledge; only a small amount of one's knowledge is ever actively on one's mind.

b. Truth

Knowledge, then, requires belief. Of course, not all beliefs constitute knowledge. Belief is necessary but not sufficient for knowledge. We are all sometimes mistaken in what we believe; in other words, while some of our beliefs are true, others are false. As we try to acquire knowledge, then, we are trying to increase our stock of true beliefs (while simultaneously minimizing our false beliefs).

We might say that the most typical purpose of beliefs is to describe or capture the way things actually are; that is, when one forms a belief, one is seeking a match between one's mind and the world. (We sometimes, of course, form beliefs for other reasons - to create a positive attitude, to deceive ourselves, and so forth - but when we seek knowledge, we are trying to get things right.) And, alas, we sometimes fail to achieve such a match; some of our beliefs do not describe the way things actually are.

Note that we are assuming here that there is such a thing as objective truth, so that it is possible for beliefs to match or to fail to match with reality. That is, in order for someone to know something, there must be something one knows about. Recall that we are discussing knowledge in the factive sense; if there are no facts of the matter, then there's nothing to know (or to fail to know). This assumption is not universally accepted - in particular, it is not shared by some proponents of relativism - but it will not be defended here. However, we can say that truth is a condition of knowledge; that is, if a belief is not true, it cannot constitute knowledge. Accordingly, if there is no such thing as truth, then there can be no knowledge. Even if there is such a thing as truth, if there is a domain in which there are no truths, then there can be no knowledge within that domain. (For example, if beauty is in the eye of the beholder, then a belief that something is beautiful cannot be true or false, and thus cannot constitute knowledge.)

c. Justification

Knowledge, then, requires factual belief. However, this does not suffice to capture the nature of knowledge. Just as knowledge requires successfully achieving the objective of true belief, it also requires success with regard to the formation of that belief. In other words, not all true beliefs constitute knowledge; only true beliefs arrived at in the right way constitute knowledge.

What, then, is the right way of arriving at beliefs? In addition to truth, what other properties must a belief have in order to constitute knowledge? We might begin by noting that sound reasoning and solid evidence seem to be the way to acquire knowledge. By contrast, a lucky guess cannot constitute knowledge. Similarly, misinformation and faulty reasoning do not seem like a recipe for knowledge, even if they happen to lead to a true belief. A belief is said to be justified if it is obtained in the right way. While justification seems, at first glance, to be a matter of a belief's being based on evidence and reasoning rather than on luck or misinformation, we shall see that there is much disagreement regarding how to spell out the details.

The requirement that knowledge involve justification does not necessarily mean that knowledge requires absolute certainty, however. Humans are fallible beings, and fallibilism is the view that it is possible to have knowledge even when one's true belief might have turned out to be false. Between beliefs which were necessarily true and those which are true solely by luck lies a spectrum of beliefs with regard to which we had some defeasible reason to believe that they would be true. For instance, if I heard the weatherman say that there is a 90% chance of rain, and as a result I formed the belief that it would rain, then my true belief that it would rain was not true purely by luck. Even though there was some chance that my belief might have been false, there was a sufficient basis for that belief for it to constitute knowledge. This basis is referred to as the justification for that belief. We can then say that, to constitute knowledge, a belief must be both true and justified.

Note that because of luck, a belief can be unjustified yet true; and because of human fallibility, a belief can be justified yet false. In other words, truth and justification are two independent conditions of beliefs. The fact that a belief is true does not tell us whether or not it is justified; that depends on how the belief was arrived at. So, two people might hold the same true belief, but for different reasons, so that one of them is justified and the other is unjustified. Similarly, the fact that a belief is justified does not tell us whether it's true or false. Of course, a justified belief will presumably be more likely to be true than to be false, and justified beliefs will presumably be more likely or more probable to be true than unjustified beliefs. (As we will see in section 3 below, the exact nature of the relationship between truth and justification is contentious.)

d. The Gettier Problem

For some time, the justified true belief (JTB) account was widely agreed to capture the nature of knowledge. However, in 1963, Edmund Gettier published a short but widely influential article which has shaped much subsequent work in epistemology. Gettier provided two examples in which someone had a true and justified belief, but in which we seem to want to deny that the individual has knowledge, because luck still seems to play a role in his belief having turned out to be true.

Consider an example. Suppose that the clock on campus (which keeps accurate time and is well maintained) stopped working at 11:56pm last night, and has yet to be repaired. On my way to my noon class, exactly twelve hours later, I glance at the clock and form the belief that the time is 11:56. My belief is true, of course, since the time is indeed 11:56. And my belief is justified, as I have no reason to doubt that the clock is working, and I cannot be blamed for basing beliefs about the time on what the clock says. Nonetheless, it seems evident that I do not know that the time is 11:56. After all, if I had walked past the clock a bit earlier or a bit later, I would have ended up with a false belief rather than a true one.

This example and others like it, while perhaps somewhat far-fetched, seem to show that it is possible for justified true belief to fail to constitute knowledge. To put it another way, the justification condition was meant to ensure that knowledge was based on solid evidence rather than on luck or misinformation, but Gettier-type examples seem to show that justified true belief can still involve luck and thus fall short of knowledge. This problem is referred to as "the Gettier problem." To solve this problem, we must either show that all instances of justified true belief do indeed constitute knowledge, or alternatively refine our analysis of knowledge.

i. The No-False-Belief Condition

We might think that there is a simple and straightforward solution to the Gettier problem. Note that my reasoning was tacitly based on my belief that the clock is working properly, and that this belief is false. This seems to explain what has gone wrong in this example. Accordingly, we might revise our analysis of knowledge by insisting that to constitute knowledge, a belief must be true and justified and must be formed without relying on any false beliefs. In other words, we might say, justification, truth, and belief are all necessary for knowledge, but they are not jointly sufficient for knowledge; there is a fourth condition - namely, that no false beliefs be essentially involved in the reasoning that led to the belief - which is also necessary.

Unfortunately, this will not suffice; we can modify the example so that my belief is justified and true, and is not based on any false beliefs, but still falls short of knowledge. Suppose, for instance, that I do not have any beliefs about the clock's current state, but merely the more general belief that the clock usually is in working order. This belief, which is true, would suffice to justify my belief that the time is now 11:56; of course, it still seems evident that I do not know the time.

ii. The No-Defeaters Condition

However, the no-false-belief condition does not seem to be completely misguided; perhaps we can add some other condition to justification and truth to yield a correct characterization of knowledge. Note that, even if I didn't actively form the belief that the clock is currently working properly, it seems to be implicit in my reasoning, and the fact that it is false is surely relevant to the problem. After all, if I were asked, at the time that I looked at the clock, whether it is working properly, I would have said that it is. Conversely, if I believed that the clock wasn't working properly, I wouldn't be justified in forming a belief about the time based on what the clock says.

In other words, the proposition that the clock is working properly right now meets the following conditions: it is a false proposition, I do not realize that it is a false proposition, and if I had realized that it is a false proposition, my justification for my belief that it is 11:56 would have been undercut or defeated. If we call propositions such as this "defeaters," then we can say that to constitute knowledge, a belief must be true and justified, and there must not be any defeaters to the justification of that belief. Many epistemologists believe this analysis to be correct.

iii. Causal Accounts of Knowledge

Rather than modifying the JTB account of knowledge by adding a fourth condition, some epistemologists see the Gettier problem as reason to seek a substantially different alternative. We have noted that knowledge should not involve luck, and that Gettier-type examples are those in which luck plays some role in the formation of a justified true belief. In typical instances of knowledge, the factors responsible for the justification of a belief are also responsible for its truth. For example, when the clock is working properly, my belief is both true and justified because it's based on the clock, which accurately displays the time. But one feature that all Gettier-type examples have in common is the lack of a clear connection between the truth and the justification of the belief in question. For example, my belief that the time is 11:56 is justified because it's based on the clock, but it's true because I happened to walk by at just the right moment. So, we might insist that to constitute knowledge, a belief must be both true and justified, and its truth and justification must be connected somehow.

This notion of a connection between the truth and the justification of a belief turns out to be difficult to formulate precisely, but causal accounts of knowledge seek to capture the spirit of this proposal by more significantly altering the analysis of knowledge. Such accounts maintain that in order for someone to know a proposition, there must be a causal connection between his belief in that proposition and the fact that the proposition encapsulates. This retains the truth condition, since a proposition must be true in order for it to encapsulate a fact. However, it appears to be incompatible with fallibilism, since it does not allow for the possibility that a belief be justified yet false. (Strictly speaking, causal accounts of knowledge make no reference to justification, although we might attempt to reformulate fallibilism in somewhat modified terms in order to state this observation.)

While causal accounts of knowledge are no longer thought to be correct, they have engendered reliabilist theories of knowledge, which shall be discussed in section 3b below.

3. The Nature of Justification

One reason that the Gettier problem is so problematic is that neither Gettier nor anyone who preceded him has offered a sufficiently clear and accurate analysis of justification. We have said that justification is a matter of a belief's having been formed in the right way, but we have yet to say what that amounts to. We must now consider this matter more closely.

We have noted that the goal of our belief-forming practices is to obtain truth while avoiding error, and that justification is the feature of beliefs which are formed in such a way as to best pursue this goal. If we think, then, of the goal of our belief-forming practices as an attempt to establish a match between one's mind and the world, and if we also think of the application or withholding of the justification condition as an evaluation of whether this match was arrived at in the right way, then there seem to be two obvious approaches to construing justification: namely, in terms of the believer's mind, or in terms of the world.

a. Internalism

Belief is a mental state, and belief-formation is a mental process. Accordingly, one might reason, whether or not a belief is justified - whether, that is, it is formed in the right way - can be determined by examining the thought-processes of the believer during its formation. Such a view, which maintains that justification depends solely on factors internal to the believer's mind, is called internalism. (The term "internalism" has different meanings in other contexts; here, it will be used strictly to refer to this type of view about epistemic justification.)

According to internalism, the only factors that are relevant to the determination of whether a belief is justified are the believer's other mental states. After all, an internalist will argue, only an individual's mental states - her beliefs about the world, her sensory inputs (for example, her sense data) and her beliefs about the relations between her various beliefs - can determine what new beliefs she will form, so only an individual's mental states can determine whether any particular belief is justified. In particular, in order to be justified, a belief must be appropriately based upon or supported by other mental states.

This raises the question of what constitutes the basing or support relation between a belief and one's other mental states. We might want to say that, in order for belief A to be appropriately based on belief B (or beliefs B1 and B2, or B1, B2, and...Bn), the truth of B must suffice to establish the truth of A, in other words, B must entail A. (We shall consider the relationship between beliefs and sensory inputs below.) However, if we want to allow for our fallibility, we must instead say that the truth of B would give one good reason to believe that A is also true (by making it likely or probable that A is true). An elaboration of what counts as a good reason for belief, accordingly, is an essential part of any internalist account of justification.

However, there is an additional condition that we must add: belief B must itself be justified, since unjustified beliefs cannot confer justification on other beliefs. Because belief B be must also be justified, must there be some justified belief C upon which B is based? If so, C must itself be justified, and it may derive its justification from some further justified belief, D. This chain of beliefs deriving their justification from other beliefs may continue forever, leading us in an infinite regress. While the idea of an infinite regress might seem troubling, the primary ways of avoiding such a regress may have their own problems as well. This raises the "regress problem," which begins from observing that there are only four possibilities as to the structure of one's justified beliefs:

1. The series of justified beliefs, each based upon the other, continues infinitely.

2. The series of justified beliefs circles back to its beginning (A is based on B, B on C, C on D, and D on A).

3. The series of justified beliefs begins with an unjustified belief.

4. The series of justified beliefs begins with a belief which is justified, but not by virtue of being based on another justified belief.

These alternatives seem to exhaust the possibilities. That is, if one has any justified beliefs, one of these four possibilities must describe the relationships between those beliefs. As such, a complete internalist account of justification must decide among the four.

i. Foundationalism

Let us, then, consider each of the four possibilities mentioned above. Alternative 1 seems unacceptable because the human mind can contain only finitely many beliefs, and any thought-process that leads to the formation of a new belief must have some starting point. Alternative 2 seems no better, since circular reasoning appears to be fallacious. And alternative 3 has already been ruled out, since it renders the second belief in the series (and, thus, all subsequent beliefs) unjustified. That leaves alternative 4, which must, by process of elimination, be correct.

This line of reasoning, which is typically known as the regress argument, leads to the conclusion that there are two different kinds of justified beliefs: those which begin a series of justified beliefs, and those which are based on other justified beliefs. The former, called basic beliefs, are able to confer justification on other, non-basic beliefs, without themselves having their justification conferred upon them by other beliefs. As such, there is an asymmetrical relationship between basic and non-basic beliefs. Such a view of the structure of justified belief is known as "foundationalism." In general, foundationalism entails that there is an asymmetrical relationship between any two beliefs: if A is based on B, then B cannot be based on A.

Accordingly, it follows that at least some beliefs (namely basic beliefs) are justified in some way other than by way of a relation to other beliefs. Basic beliefs must be self-justified, or must derive their justification from some non-doxastic source such as sensory inputs; the exact source of the justification of basic beliefs needs to be explained by any complete foundationalist account of justification.

ii. Coherentism

Internalists might be dissatisfied with foundationalism, since it allows for the possibility of beliefs that are justified without being based upon other beliefs. Since it was our solution to the regress problem that led us to foundationalism, and since none of the alternatives seem palatable, we might look for a flaw in the problem itself. Note that the problem is based on a pivotal but hitherto unstated assumption: namely, that justification is linear in fashion. That is, the statement of the regress problem assumes that the basing relation parallels a logical argument, with one belief being based on one or more other beliefs in an asymmetrical fashion.

So, an internalist who finds foundationalism to be problematic might deny this assumption, maintaining instead that justification is the result of a holistic relationship among beliefs. That is, one might maintain that beliefs derive their justification by inclusion in a set of beliefs which cohere with one another as a whole; a proponent of such a view is called a coherentist.

A coherentist, then, sees justification as a relation of mutual support among many beliefs, rather than a series of asymmetrical beliefs. A belief derives its justification, according to coherentism, not by being based on one or more other beliefs, but by virtue of its membership in a set of beliefs that all fit together in the right way. (The coherentist needs to specify what constitutes coherence, of course. It must be something more than logical consistency, since two unrelated beliefs may be consistent. Rather, there must be some positive support relationship - for instance, some sort of explanatory relationship - between the members of a coherent set in order for the beliefs to be individually justified.)

Coherentism is vulnerable to the "isolation objection". It seems possible for a set of beliefs to be coherent, but for all of those beliefs to be isolated from reality. Consider, for instance, a work of fiction. All of the statements in the work of fiction might form a coherent set, but presumably believing all and only the statements in a work of fiction will not render one justified. Indeed, any form of internalism seems vulnerable to this objection, and thus a complete internalist account of justification must address it. Recall that justification requires a match between one's mind and the world, and an inordinate emphasis on the relations between the beliefs in one's mind seems to ignore the question of whether those beliefs match up with the way things actually are.

b. Externalism

Accordingly, one might think that focusing solely on factors internal to the believer's mind will inevitably lead to a mistaken account of justification. The alternative, then, is that at least some factors external to the believer's mind determine whether or not she is justified. A proponent of such a view is called an externalist.

According to externalism, the only way to avoid the isolation objection and ensure that knowledge does not include luck is to consider some factors other than the individual's other beliefs. Which factors, then, should be considered? The most prominent version of externalism, called reliabilism, suggests that we consider the source of a belief. Beliefs can be formed as a result of many different sources, such as sense experience, reason, testimony, memory. More precisely, we might specify which sense was used, who provided the testimony, what sort of reasoning is used, or how recent the relevant memory is. For every belief, we can indicate the cognitive process that led to its formation. In its simplest and most straightforward form, reliabilism maintains that whether or not a belief is justified depends upon whether that process is a reliable source of true beliefs. Since we are seeking a match between our mind and the world, justified beliefs are those which result from processes which regularly achieve such a match. So, for example, using vision to determine the color of an object which is well-lit and relatively near is a reliable belief-forming process for a person with normal vision, but not for a color-blind person. Forming beliefs on the basis of the testimony of an expert is likely to yield true beliefs, but forming beliefs on the basis of the testimony of compulsive liars is not. In general, if a belief is the result of a cognitive process which reliably (most of the time - we still want to leave room for human fallibility) leads to true beliefs, then that belief is justified.

The foregoing suggests one immediate challenge for reliabilism. The formation of a belief is a one-time event, but the reliability of the process depends upon the long-term performance of that process. (This can include counterfactual as well as actual events. For instance, a coin which is flipped only once and lands on heads nonetheless has a 50% chance of landing on tails, even though its actual performance has yielded heads 100% of the time.) And this requires that we specify which process is being used, so that we can evaluate its performance in other instances. However, cognitive processes can be described in more or less general terms: for example, the same belief-forming process might be variously described as sense experience, vision, vision by a normally-sighted person, vision by a normally-sighted person in daylight, vision by a normally-sighted person in daylight while looking at a tree, vision by a normally-sighted person in daylight while looking at an elm tree, and so forth. The "generality problem" notes that some of these descriptions might specify a reliable process but others might specify an unreliable process, so that we cannot know whether a belief is justified or unjustified unless we know the appropriate level of generality to use in describing the process.

Even if the generality problem can be solved, another problem remains for externalism. Keith Lehrer presents this problem by way of his example of Mr. Truetemp. Truetemp has, unbeknownst to him, had a tempucomp - a device which accurately reads the temperature and causes a spontaneous belief about that temperature - implanted in his brain. As a result, he has many true beliefs about the temperature, but he does not know why he has them or what their source is. Lehrer argues that, although Truetemp's belief-forming process is reliable, his ignorance of the tempucomp renders his temperature-beliefs unjustified, and thus that a reliable cognitive process cannot yield justification unless the believer is aware of the fact that the process is reliable. In other words, the mere fact that the process is reliable does not suffice, Lehrer concludes, to justify any beliefs which are formed via that process.

4. The Extent of Human Knowledge

a. Sources of Knowledge

Given the above characterization of knowledge, there are many ways that one might come to know something. Knowledge of empirical facts about the physical world will necessarily involve perception, in other words, the use of the senses. Science, with its collection of data and conducting of experiments, is the paradigm of empirical knowledge. However, much of our more mundane knowledge comes from the senses, as we look, listen, smell, touch, and taste the various objects in our environments.

But all knowledge requires some amount of reasoning. Data collected by scientists must be analyzed before knowledge is yielded, and we draw inferences based on what our senses tell us. And knowledge of abstract or non-empirical facts will exclusively rely upon reasoning. In particular, intuition is often believed to be a sort of direct access to knowledge of the a priori.

Once knowledge is obtained, it can be sustained and passed on to others. Memory allows us to know something that we knew in the past, even, perhaps, if we no longer remember the original justification. Knowledge can also be transmitted from one individual to another via testimony; that is, my justification for a particular belief could amount to the fact that some trusted source has told me that it is true.

b. Skepticism

In addition to the nature of knowledge, epistemologists concern themselves with the question of the extent of human knowledge: how much do we, or can we, know? Whatever turns out to be the correct account of the nature of knowledge, there remains the matter of whether we actually have any knowledge. It has been suggested that we do not, or cannot, know anything, or at least that we do not know as much as we think we do. Such a view is called skepticism.

We can distinguish between a number of different varieties of skepticism. First, one might be a skeptic only with regard to certain domains, such as mathematics, morality, or the external world (this is the most well-known variety of skepticism). Such a skeptic is a local skeptic, as contrasted with a global skeptic, who maintains that we cannot know anything at all. Also, since knowledge requires that our beliefs be both true and justified, a skeptic might maintain that none of our beliefs are true or that none of them are justified (the latter is much more common than the former).

While it is quite easy to challenge any claim to knowledge by glibly asking, "How do you know?", this does not suffice to show that skepticism is an important position. Like any philosophical stance, skepticism must be supported by an argument. Many arguments have been offered in defense of skepticism, and many responses to those arguments have been offered in return. Here, we shall consider two of the most prominent arguments in support of skepticism about the external world.

c. Cartesian Skepticism

In the first of his Meditations, René Descartes offers an argument in support of skepticism, which he then attempts to refute in the later Meditations. The argument notes that some of our perceptions are inaccurate. Our senses can trick us; we sometimes mistake a dream for a waking experience, and it is possible that an evil demon is systematically deceiving us. (The modern version of the evil demon scenario is that you are a brain-in-a-vat, because scientists have removed your brain from your skull, connected it to a sophisticated computer, and immersed it in a vat of preservative fluid. The computer produces what seem to be genuine sense experiences, and also responds to your brain's output to make it seem that you are able to move about in your environment as you did when your brain was still in your body. While this scenario may seem far-fetched, we must admit that it is at least possible.)

As a result, some of our beliefs will be false. In order to be justified in believing what we do, we must have some way to distinguish between those beliefs which are true (or, at least, are likely to be true) and those which are not. But just as there are no signs that will allow us to distinguish between waking and dreaming, there are no signs that will allow us to distinguish between beliefs that are accurate and beliefs which are the result of the machinations of an evil demon. This indistinguishability between trustworthy and untrustworthy belief, the argument goes, renders all of our beliefs unjustified, and thus we cannot know anything. A satisfactory response to this argument, then, must show either that we are indeed able to distinguish between true and false beliefs, or that we need not be able to make such a distinction.

d. Humean Skepticism

According to the indistinguishability skeptic, my senses can tell me how things appear, but not how they actually are. We need to use reason to construct an argument that leads us from beliefs about how things appear to (justified) beliefs about how they are. But even if we are able to trust our perceptions, so that we know that they are accurate, David Hume argues that the specter of skepticism remains. Note that we only perceive a very small part of the universe at any given moment, although we think that we have knowledge of the world beyond that which we are currently perceiving. It follows, then, that the senses alone cannot account for this knowledge, and that reason must supplement the senses in some way in order to account for any such knowledge. However, Hume argues, reason is incapable of providing justification for any belief about the external world beyond the scope of our current sense perceptions. Let us consider two such possible arguments and Hume's critique of them.

i. Numerical vs. Qualitative Identity

We typically believe that the external world is, for the most part, stable. For instance, I believe that my car is parked where I left it this morning, even though I am not currently looking at it. If I were to go peek out the window right now and see my car, I might form the belief that my car has been in the same space all day. What is the basis for this belief? If asked to make my reasoning explicit, I might proceed as follows:

I have had two sense-experiences of my car: one this morning and one just now.
The two sense-experiences were (more or less) identical.
Therefore, it is likely that the objects that caused them are identical.
Therefore, a single object - my car - has been in that parking space all day.

Similar reasoning would undergird all of our beliefs about the persistence of the external world and all of the objects we perceive. But are these beliefs justified? Hume thinks not, since the above argument (and all arguments like it) contains an equivocation. In particular, the first occurrence of "identical" refers to qualitative identity. The two sense-experiences are not one and the same, but are distinct; when we say that they are identical we mean that one is similar to the other in all of its qualities or properties. But the second occurrence of "identical" refers to numerical identity. When we say that the objects that caused the two sense-experiences are identical, we mean that there is one object, rather than two, that is responsible for both of them. This equivocation, Hume argues, renders the argument fallacious; accordingly, we need another argument to support our belief that objects persist even when we are not observing them.

ii. Hume's Skepticism about Induction

Suppose that a satisfactory argument could be found in support of our beliefs in the persistence of physical objects. This would provide us with knowledge that the objects that we have observed have persisted even when we were not observing them. But in addition to believing that these objects have persisted up until now, we believe that they will persist in the future; we also believe that objects we have never observed similarly have persisted and will persist. In other words, we expect the future to be roughly like the past, and the parts of the universe that we have not observed to be roughly like the parts that we have observed. For example, I believe that my car will persist into the future. What is the basis for this belief? If asked to make my reasoning explicit, I might proceed as follows:

My car has always persisted in the past.
Nature is roughly uniform across time and space (and thus the future will be roughly like the past).
Therefore, my car will persist in the future.

Similar reasoning would undergird all of our beliefs about the future and about the unobserved. Are such beliefs justified? Again, Hume thinks not, since the above argument, and all arguments like it, contain an unsupported premise, namely the second premise, which might be called the Principle of the Uniformity of Nature (PUN). Why should we believe this principle to be true? Hume insists that we provide some reason in support of this belief. Because the above argument is an inductive rather than a deductive argument, the problem of showing that it is a good argument is typically referred to as the "problem of induction." We might think that there is a simple and straightforward solution to the problem of induction, and that we can indeed provide support for our belief that PUN is true. Such an argument would proceed as follows:

PUN has always been true in the past.
Nature is roughly uniform across time and space (and thus the future will be roughly like the past).
Therefore, PUN will be true in the future.

This argument, however, is circular; its second premise is PUN itself! Accordingly, we need another argument to support our belief that PUN is true, and thus to justify our inductive arguments about the future and the unobserved.

5. Conclusion

The study of knowledge is one of the most fundamental aspects of philosophical inquiry. Any claim to knowledge must be evaluated to determine whether or not it indeed constitutes knowledge. Such an evaluation essentially requires an understanding of what knowledge is and how much knowledge is possible. While this article provides on overview of the important issues, it leaves the most basic questions unanswered; epistemology will continue to be an area of philosophical discussion as long as these questions remain.

6. References and Further Reading

Alston, William P., 1989. Epistemic Justification: Essays in the Theory of Knowledge. Ithaca, NY: Cornell University Press.

Chisholm, Roderick, 1966. Theory of Knowledge, Englewood Cliffs, NJ: Prentice-Hall.

Chisholm, Roderick, 1977. Theory of Knowledge, 2nd edition. Englewood Cliffs, NJ: Prentice-Hall.

Descartes, Rene, 1641. Meditations on First Philosophy. Reprinted in The Philosophical Writings of Descartes (3 volumes). Cottingham, Stoothoff and Murdoch, trans. Cambridge: Cambridge University Press.
Descartes presents an infallibilist version of foundationalism, and attempts to refute skepticism.

Dancy, Jonathan and Ernest Sosa (eds.), 1993. A Companion to Epistemology. Oxford: Blackwell.

DeRose, Keith, 1995. "Solving the Skeptical Problem" Philosophical Review, 104, pp. 1-52.

DeRose Keith and Ted Warfield (eds.), 1999. Skepticism: A Contemporary Reader. Oxford: Oxford University Press.

Goldman, Alvin, 1976. "A Causal Theory of Knowing." Journal of Philosophy, 64, pp. 357-372.

Hume, David, 1739. A Treatise on Human Nature. Oxford: Oxford University Press.

Hume, David, 1751. An Enquiry Concerning Human Understanding. Indianapolis: Hackett.

Lehrer, Keith and Stewart Cohen, 1983. "Justification, Truth, and Coherence." Synthese, 55, pp. 191-207.

Lewis, David, 1996. "Elusive Knowledge" Australasian Journal of Philosophy, 74, pp. 549-567.

Locke, John, 1689. An Essay Concerning Human Understanding. Oxford: Clarendon.

Plato, Meno and Theaetetus. In Complete Works. J. Cooper, ed. Indianapolis: Hackett.
Plato presents and defends a version of the JTB analysis of knowledge.

Author Information

David A. Truncellito
Email: truncell@aya.yale.edu
U. S. A.

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Epistemology is the study of knowledge. Epistemologists concern themselves with a number of tasks, which we might sort into two categories. First, we must determine the nature of knowledge; that is, what does it mean to say that someone knows, or fails to know, something?

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Penemuan teknologi sering kali didorong oleh berbagai faktor, termasuk kebutuhan praktis, perkembangan ilmiah, dan tuntutan sosial atau ekonomi. Misalnya, dalam konteks Revolusi Industri, kekurangan kayu sebagai bahan bakar di Inggris memicu peralihan ke batu bara, yang kemudian mendukung pengembangan mesin uap dan kemajuan besar dalam bidang manufaktur dan transportasi. Teknologi ini memacu pertumbuhan industri dan urbanisasi besar-besaran, merubah ekonomi dan kehidupan sosial masyarakat di Eropa pada abad ke-18

Selain itu, penemuan teknologi juga sering kali didorong oleh kebutuhan untuk meningkatkan efisiensi atau mengatasi masalah yang dihadapi oleh masyarakat. Misalnya, inovasi seperti sistem rotasi tanaman dan alat pertanian modern muncul untuk meningkatkan produktivitas pangan demi mendukung populasi yang semakin berkembang​

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Whether it was mechanical inventions or new ways of doing old things, innovations powered the Industrial Revolution.