网范文：“Distributed Processes, Distributed Cognizers and Collaborative Cognition ”认知思维,似乎是思想家做的事情。我们并不知道思想家如何想,如何能够做他们能做的事，我们正等待认知科学发现。这篇哲学范文讲述的是对于这样的一个问题。认知科学通过测试假设过程，能产生什么做什么，英语论文题目，这就是所谓的图灵测试。它不能测试过程是否能产生感觉,因此思维是否可以生成行为。没有所谓的分布式认知,只有协作认知。电子邮件和网络催生了一种新的协作认知,利用个人大脑的实时互动潜在的方式来进行口语,书面或打印的交互。
在我们这个时代的虚拟现实,极限的分布式状态是我们的边界,如果国内经济形势是一个分布式状态,不是一个认知状态,尽管它可能在于场合认知状态。下面的范文进行详述。
ABSTRACT
Cognition is thinking; it feels like something to think, and only those who can feel can think. There are also things that thinkers can do. We know neither how thinkers can think nor how they are able do what they can do. We are waiting for cognitive science to discover how. Cognitive science does this by testing hypotheses about what processes can generate what doing (“know-how”) This is called the Turing Test. It cannot test whether a process can generate feeling, hence thinking only whether it can generate doing. The processes that generate thinking and know-how are “distributed” within the heads of thinkers, but not across thinkers’ heads. Hence there is no such thing as distributed cognition, only collaborative cognition. Email and the Web have spawned a new form of collaborative cognition that draws upon individual brains’ real-time interactive potential in ways that were not possible in oral, written or print interactions.
In our age of “virtual reality,” it is useful to remind ourselves now and again that a corporation cannot literally have a head-ache, though its (figurative) “head” (CEO) might. And that even if all N members of the Board of Directors have a head-ache, that’s N head-aches, not one distributed head-ache. And that although a head-ache itself may not be localized in one point of my brain, but distributed across many points, the limits of that distributed state are the boundaries of my head, or perhaps my body: the head-ache stops there, and so does cognition. If a mother’s head-ache is her three children, then her children get the distributed credit for causing the state, but they are not part of the state. And if the domestic economic situation is a “head-ache,” that distributed state is not a cognitive state, though it may be the occasion of a cognitive state within the single head of a single head of state (or several cognitive states in the individual heads of several individual heads of state).
The reason knowing is sometimes a useful stand-in for thinking is that it ties cognition closer to action: There is “knowing-that” – which is very much like “thinking-that,” as in thinking/knowing that “the cat is on the mat.” And there is “knowing-how,” as in knowing how to play chess or tennis. (Know-how has no counterpart when we speak only about thinking rather than knowing.) Skill or know-how is something I have, and its “proof” is in doing it (not just in thinking I can do it). Now an argument can be made for the fact that know-how is not cognition at all. Know-how may (or may not) be acquired consciously and explicitly; but once one has a bit of know-how, one simply has it; conscious thinking is not necessarily involved in its exercise (though one usually has to be awake and conscious to exercise it).
But if know-how were excluded from cognition because it did not necessarily involve conscious thinking, then we would have to exclude all the other unconscious processes underlying the “how” of thinking itself! So whereas thinking itself is the necessary and sufficient condition for being a cognitive system, thinking in turn has necessary conditions of its own too, and most of those are unconscious processes. The same is true of know-how: it is generated by unconscious processes, just as thinking is. Know-how may or may not be acquired, and if acquired, it may or may not be acquired via thinking (though one almost certainly must be awake and thinking while acquiring it); and know-how may or may not be exercised via thinking (though one almost certainly must be awake and thinking while exercising it). Moreover, just about all thinking (including knowing-that) also has a know-how dimension associated with it. If I think that “the cat is on the mat” is true then I know it follows that the “the cat is not on the mat” is false. Thoughts are not punctate.
They have implications. And the implications are part of the know-how implicit in the thought itself. I know how to reply to (many) questions about the whereabouts of the cat if I think that “the cat is on the mat.” And the know-how goes beyond the bounds of thinking and even talking about what I think: it includes doing things in the world. If I think that “the cat is on the mat,” I also know how to go and find the cat! All this belaboring of the obvious is intended to bring out the close link between thinking capacity and doing capacity (via know-how). Which brings us to the second case of cognition: “artificial cognition” (AC).
If there are things other than living creatures (e.g., certain machines) that can do the kinds of things that living/thinking things can do, then maybe they can think too. Note the “maybe.” It is quite natural to turn to machines in order to explain the “how” of cognition. Unlike the know-how of the heart or the lungs, the brain’s know-how is unlikely to be discoverable merely from observing what the brain can do and what’s going on inside it while it is doing so. That might have been sufficient if all the brain could do was to move (in the gross sense of navigating in space and manipulating objects). But the brain can do a lot of subtler things than just walking around and fiddling with objects: it can perceive, categorize, speak, understand and think. It is not obvious how the know-how underlying all those capacities can be read off of brain structure and function. At the very least, trying to design machines that can also do what brains (of humans and animals) can do is a way of testing theories about how such things can be done at all, any which way. In addition, it puts the power of both computation and neural simulation in the hands of the theorist.
So many potential cycles of productive interaction were lost: until the temporal gap between the conversational speed of interdigitating thought for which our brains are adapted and the much slower tempo of dissemination of written text was at last bridged again by email and the Internet, the fourth cognitive milestone: “scholarly skywriting” (Harnad 2017a). It is now possible for a text to be written, transmitted and responded to in real time, at almost conversational speed (i.e., the speed of thought), as if it were all being written in the sky, for all to see and respond to in real time if they wish. Perhaps just as important, it is possible to quote/comment text (by living and active or even long-dead authors) and to branch that collaborative interaction instantaneously to many other potential interlocutors, and potentially the whole planet, through email, hypermail, blogs, and web archives.
Now it was never the strength of the oral tradition to have several people speaking at once. Conversation is optimal when it is serial and one-on-one, or with several interlocutors turn-taking – again serially, but in real time. Moreover, not everyone has (or should have) something to say about everything. So there are no doubt constraints and optima that will emerge with skywriting as the practice develops. But right now, the problem is not an excess or embarrassment of skywritten riches, producing an unnavigable din, but a dearth of online scholarly content and CC: Most of cyberspace is still devoted to trivial pursuit, not to CC. This will soon change: Skywriting itself is one of its own sure rewards: It was the presence of an audience that inspired the eloquence of the bard, the oracle and the sage in the days of the oral tradition. Writing in the skies, instantly visible to one’s peers, is one incentive for scholarly CC.
So is the prospect (and provocation) of “creative disagreement” (Harnad 1979, 1990). The likelihood of their texts being seen, scrutinized , criticized , used, applied and built-upon by their peers inspires scholars both to skywrite and to be careful and rigorous; having their skywritings criticized or elaborated in turn inspires further iterations of skywriting. Soon shared research-data and joint data-analyses too will become part of the skywriting. This is all CC. The impact of scholarly writing was already being measured and rewarded in Gutenberg days (by counting journal citations); skywriting offers many new ways of monitoring, measuring, maximizing, evaluating and rewarding the impact of CC through the analysis of (distributed!) patterns in downloads, citations, co-citations, co-authorships, and even co-text (Brody & Harnad 2017). All of this is CC. It is the fruit of the collective , interactive know-how of many individual thinkers. If it goes wrong, it will inspire many individual head-aches, not one distributed one. And if it inspires pride, that will be felt by many individual cognizers, not one distributed one.
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