本期內(nèi)容是關(guān)于圖靈測(cè)試的觀點(diǎn)與評(píng)論，如果不了解圖靈測(cè)試可以移步第一期文章認(rèn)知心理學(xué) (中文) 1 - 什么是智能？誰(shuí)能夠思考？。

復(fù)雜認(rèn)知/認(rèn)知心理學(xué)系列文集中文版文集！我們?nèi)绾巫兊萌绱寺斆鳎课覀兪侨绾胃兄車(chē)氖澜?、學(xué)習(xí)語(yǔ)言、制定決策、記得過(guò)去、并預(yù)測(cè)未來(lái)的？大量的神經(jīng)組織如何思考？怎么樣產(chǎn)生想法？這些都是本系列專欄將嘗試回答或啟發(fā)思考的問(wèn)題。

本系列主要分為三種內(nèi)容：第一種是傳統(tǒng)的講座形式的知識(shí)內(nèi)容，涵蓋不同的概念與例子；第二種是體驗(yàn)不同的認(rèn)知科學(xué)實(shí)驗(yàn)；第三種是不定期地對(duì)丹尼爾·卡尼曼的《思考，快與慢》這本心理學(xué)著作的閱讀與討論。

本期思考：圖靈測(cè)試是回答“機(jī)器可以思考嗎 Can machines think?”這個(gè)問(wèn)題的好方法嗎？為什么或者為什么不？

值得注意的是，認(rèn)知科學(xué)家們在這些問(wèn)題上存在很大的分歧。每個(gè)人的觀點(diǎn)都可能有各自的依據(jù)，這些問(wèn)題并沒(méi)有“標(biāo)準(zhǔn)答案”。

閱讀下面的不同人的評(píng)論，思考上面的問(wèn)題，并注意：

- 您在閱讀的過(guò)程中有什么讓你感到驚訝？出現(xiàn)了哪些主題？

- 您閱讀這些評(píng)論時(shí)有何反應(yīng)？有什么有趣，令人驚訝，令人困惑的地方？

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? 人們都持什么觀點(diǎn)？Where do we stand?

–“我對(duì)圖靈測(cè)試及其評(píng)估計(jì)算機(jī)是否被認(rèn)為正在思考的能力感到非常矛盾。我認(rèn)為該測(cè)試有很多優(yōu)點(diǎn)，并且可以與人類(lèi)抗衡，但是在了解了可以通過(guò)圖靈測(cè)試的人工智能系統(tǒng)之后，我不確定我是否會(huì)考慮它在“思考”。（意思是這位朋友認(rèn)為有的通過(guò)圖靈測(cè)試的人工智能系統(tǒng)很瓜批。）

– “I feel very conflicted about the Turing test and its ability to assess whether or not a computer is considered thinking. I think that it has a lot of merit and that it makes sense to put it up against humans, but after reading about the AI system that has arguably passed the Turing test, I am not sure that I would consider it thinking.”

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–“我相信計(jì)算機(jī)的工作永遠(yuǎn)無(wú)法與人類(lèi)的思想相提并論，而機(jī)器也永遠(yuǎn)無(wú)法去“思考”，這是一種種類(lèi)似于人類(lèi)的方式。”

– “I don’t believe that the work of computers can ever parallel that of human thought and machines will never be able to “think” is a way that can resemble a human.”

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–“我認(rèn)為圖靈測(cè)試是回答以下問(wèn)題的好方法：‘機(jī)器可以證明它們與人類(lèi)相似嗎？’”

– “I think the Turing Test is a good way to answer the question, ‘Can machines prove they are similar to humans?’”

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–“圖靈測(cè)試在測(cè)試機(jī)器方面的表現(xiàn)非常出色，它能夠給出滿足人類(lèi)受眾的答案?！?/span>

– “The Turing test does a really good job testing machines’ ability to give the answer that will satisfy human audiences.”

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–“我覺(jué)得圖靈測(cè)試不是回答機(jī)器可以思考的好方法。圖靈測(cè)試模仿了智能的行為，但是機(jī)器實(shí)際上不是智能的。”

– “I feel as though that the Turing Test is not a good way to answer if machines can think. The Turing Test mimics the behaviour of intelligence but that machines are not actually intelligent.”

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–“我將思維定義為使用理性或邏輯判斷來(lái)理解和推理某些事物。”

– “I define thinking as using rational or logical judgement in order to comprehend and reason with something.”

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–“我個(gè)人認(rèn)為，如果在特定情況下使用，圖靈測(cè)試可能是一個(gè)不錯(cuò)的指標(biāo)。 神經(jīng)網(wǎng)絡(luò)的概念是我們未多講的一項(xiàng)人工智能技術(shù)。據(jù)我了解，他們從各種刺激中‘學(xué)習(xí)’，并可以根據(jù)以前的經(jīng)驗(yàn)創(chuàng)建處理網(wǎng)絡(luò)，以對(duì)新刺激做出反應(yīng)。”

– “I personally think that the Turing test can be a decent metric if used in specific circumstances. One piece of AI tech that we’ve not spoken a lot about is the concepts of neural networks. From what I understand, they ‘learn’ from various stimuli and can create networks of processing to respond to new stimuli based on previous experiences.”

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–“圖靈測(cè)試是一種確定計(jì)算機(jī)是否可以思考的好方法，因?yàn)樵摐y(cè)試涵蓋了不同類(lèi)型的詢問(wèn)。諸如亞馬遜Alexa或蘋(píng)果產(chǎn)品的Siri之類(lèi)的新技術(shù)中的人工智能正在演變?yōu)閷⑷祟?lèi)與計(jì)算機(jī)區(qū)分開(kāi)來(lái)的更像人類(lèi)的功能。”

– “The Turing Test is an okay way of finding out if computers can think because the test covers different types of interrogation. The AI in newer technology, such as the Amazon Alexa or Apple’s Siri, is evolving into those more human-like features that distinguish humans from computers.”

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–“盡管一臺(tái)機(jī)器通常缺乏自由意志并且無(wú)法創(chuàng)造自己的思想，但我認(rèn)為使用代碼成為人類(lèi)冒名頂替者的戰(zhàn)略行為（因此欺騙詢問(wèn)者）確實(shí)在某種程度上暗示了思想?！?/span>

– “Although a machine often lacks free will and is unable to create its own thoughts, I would argue that the strategic act of using code to become a human imposter (thus fooling the interrogator) does suggest thought to some degree.”

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–“我很喜歡圖靈的論文中，有一段內(nèi)容解釋了人們?cè)趯⑷斯ぶ悄芘c我們的智能進(jìn)行比較時(shí)如何如此輕描淡寫(xiě)，因?yàn)槲覀儾幌Ｍ魏螙|西威脅到我們自己對(duì)人類(lèi)優(yōu)于所有其他人類(lèi)的看法。當(dāng)我繼續(xù)思考這個(gè)問(wèn)題時(shí)，我將不得不進(jìn)行自我檢查，并確保我不會(huì)讓這種偏見(jiàn)阻止我真正考慮所有可能性?！?/span>

– “I really enjoyed the part in the reading which explained how people are so dismissive when comparing artificial intelligence to our own intelligence because we don’t want anything to threaten our own perception of humankind being superior to all other beings. As I continue to ponder this question, I will have to check myself and make sure that I am not letting this bias prevent me from truly considering all of the possibilities.”

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–“我認(rèn)為圖靈測(cè)試可以幫助回答‘機(jī)器可以思考嗎？’這個(gè)問(wèn)題，但這不應(yīng)是唯一的測(cè)試?！?/span>

– “I think the Turing test can aid in answering the question, ‘Can machines think?’, but it should not be the only test.”

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–“圖靈測(cè)試是回答機(jī)器是否可以思考的好方法。我們知道其他人的想法的唯一原因是，他們做著并說(shuō)出使我們推斷出他們可以思考的事情。圖靈測(cè)試一旦通過(guò)，就會(huì)欺騙人們相信機(jī)器是人類(lèi)，因?yàn)樗麄冋J(rèn)為與之交流的事物像人類(lèi)一樣在思考?！?/span>

– “The Turing Test is a good way to answer if machines can think. The only reason we know other humans think is that they do and say things that make us deduce that they can think. The Turing Test, if passed, tricks a human into believing a machine is a human because they think the thing they are communicating with is thinking like a human.”

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? 人與計(jì)算機(jī)之間有相似之處There are similarities between humans and computers.

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–“人類(lèi)和計(jì)算機(jī)的想法相似，因?yàn)槲覀兌紡倪^(guò)去的經(jīng)驗(yàn)中學(xué)到東西。機(jī)器與人一樣，會(huì)從獎(jiǎng)懲中學(xué)習(xí)，而經(jīng)驗(yàn)則可以指導(dǎo)他們的決策?！?/span>

– “Humans and computers think similarly because we both learn from past experiences. Same as human, a machine learns from rewards and punishment, and the experience informs their decision making.”

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–“從最基本的意義上講，人與計(jì)算機(jī)的想法是相同的：它們從外界接收刺激和信息，然后根據(jù)一組規(guī)則進(jìn)行處理和響應(yīng)。”

– “In the most basic sense, humans and computers think the same: they receive stimuli and information from the outside world, then process and respond to it according to a set of rules.”

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–“機(jī)器在某種程度上確實(shí)像人一樣思考。人們獲得知識(shí)，評(píng)估他們認(rèn)為正確的答案或正確的事情并采取行動(dòng)。我們傾向于將相似性或差異性的信息分組，將信息組織成層次或模式，得出不同主題和思想之間的結(jié)論和聯(lián)系?！?/span>

– “Machines, in a way, do think like humans. Humans gain knowledge, assess what they think is the right answer or thing to do and act on it. We tend to group information on similarities or differences, we organize information into levels or schemas, we draw conclusions and connections between different topics and ideas.”

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? 人與計(jì)算機(jī)之間存在差異There are differences between humans and computers.

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–“但是，只有人類(lèi)有學(xué)習(xí)的欲望。發(fā)展與變化是我們固有的，是有機(jī)的?！?/span>

– “However, only humans have a desire to learn. Development and change is inherent to us, being organic and all.”

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–“我同意馬庫(kù)斯的觀點(diǎn)，他認(rèn)為機(jī)器與人類(lèi)不同，因?yàn)闄C(jī)器主要依靠‘模式識(shí)別’，而不是真正的理解。人類(lèi)的思維也會(huì)因情感而變得扭曲。例如，如果我們感到沮喪或饑餓，我們會(huì)失去精力，因此可能會(huì)屈服于我們的第一個(gè)想法（消耗最少腦力的想法）。電腦沒(méi)有情感，因此他們的思維不會(huì)受到干擾?！?/span>

– “I agree with Marcus, who says that machines differ from humans in that they rely mostly on ‘pattern recognition,’ rather than true understanding. Human thinking can also become twisted by emotion. For instance, if we are frustrated or hungry, we lose energy and therefore may succumb to our first thought (one that saps the least amount of brain power). Computers don’t have emotions, therefore their thinking goes undisrupted.”

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–“計(jì)算機(jī)與人類(lèi)思維之間的區(qū)別在于，人類(lèi)在思考時(shí)具有自主權(quán)，這意味著人類(lèi)可以主動(dòng)地隨意思考。而計(jì)算機(jī)則不然，他們的編程決定（或限制）了他們的想法。”

– “The difference between computers and humans thinking is that humans have self-autonomy when thinking, meaning humans can be random on their initiative. However, computers are limited; their programming decides their thinking.”

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–“我認(rèn)為計(jì)算機(jī)不可能創(chuàng)造出像真實(shí)人類(lèi)一樣的新事物。但是，如果我們可以對(duì)一個(gè)系統(tǒng)進(jìn)行編程，讓計(jì)算機(jī)學(xué)習(xí)新事物并運(yùn)用他們所學(xué)到的知識(shí)，則是很有可能的?！?/span>

– “I think it is impossible for computers to create new things like real human beings; however, it’s highly possible if we could program a system to let computers learn new things and apply the knowledge they learned.”

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–“即使我們知道某種行為可能會(huì)導(dǎo)致懲罰，我們?nèi)詴?huì)考慮導(dǎo)致我們繼續(xù)進(jìn)行的這種行為，因?yàn)楸M管一再被警告，我們可能會(huì)堅(jiān)持認(rèn)為它是正確的行動(dòng)方針。而機(jī)器是基于邏輯和被告知正確的思想來(lái)思考的。”

– “Even if we know a certain behavior may lead to a punishment, we still think about that behavior which leads to us going through with it due to our insistence of it being the right course of action or pure curiosity on the outcome despite being repeatedly told no. Machines think based on logic and based on what it is told is right.”

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–“（人與機(jī)器）主要區(qū)別在于兒童可以成長(zhǎng)為形成自己的意見(jiàn)，并選擇拒絕接受所學(xué)的內(nèi)容的個(gè)體。計(jì)算機(jī)無(wú)法這樣做。我認(rèn)為這是計(jì)算機(jī)工作方式與人類(lèi)思維方式之間的主要區(qū)別，是人們能夠結(jié)合情感和過(guò)去的經(jīng)驗(yàn)來(lái)改變其行為的能力?！?/span>

– “The main difference is that children can grow to form their own opinions and choose to reject what they have been taught. A computer cannot do so. I think that is the main difference between the way computers work and human thinking, the ability to draw on emotions and past experiences together to change their behavior.”

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–“人工智能可能能夠模擬對(duì)話響應(yīng)或開(kāi)個(gè)玩笑，但仍無(wú)法根據(jù)個(gè)人經(jīng)驗(yàn)來(lái)綜合信息。因此，盡管通過(guò)了圖靈測(cè)試，它仍無(wú)法像我們一樣‘思考’?！?/span>

– “An artificial intelligence may be able to emulate a conversational response, or tell a joke, but it is not yet able to synthesize information from personal experience. Therefore, although the Turing Test has been successfully beaten, it is not yet able to ‘think’ as we do.”

–“也許若重新評(píng)估了測(cè)試的參數(shù)，如文章所建議的那樣；也許若我們可以確定機(jī)器是否可以學(xué)習(xí)并分析其所知道的知識(shí)，那將是一個(gè)更好的測(cè)試?！?/span>

– “Maybe if the parameters of the test are reevaluated, like how the article suggests that maybe if we can determine whether a machine can learn and analyze what it knows then that would possibly be a better test.”

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–“我相信元認(rèn)知（元認(rèn)知是指對(duì)‘認(rèn)知’的認(rèn)知。例如對(duì)自己的各種認(rèn)知活動(dòng)進(jìn)行積極的監(jiān)控和調(diào)節(jié)；對(duì)自己的感知、記憶、思維等認(rèn)知活動(dòng)本身的再感知、再記憶、再思維就稱為元認(rèn)知）對(duì)于能夠真正思考至關(guān)重要。如果沒(méi)有某種自我認(rèn)知或意識(shí)，元認(rèn)知是不可能的，因?yàn)槿绻幌纫庾R(shí)到自己有大腦，就無(wú)法考慮大腦的運(yùn)作方式。

– “I believe metacognition is vital to being able to truly think. This is impossible without some semblance of a consciousness/awareness of self, as you cannot contemplate how your brain is functioning without first being aware that you have a brain.”

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–“對(duì)于人類(lèi)，我們遵循大腦中養(yǎng)成的思維習(xí)慣。很難說(shuō)我們的情報(bào)是否真的比計(jì)算機(jī)復(fù)雜得多?！?/span>

– “For humans, we follow the thinking habits developed in our brains. It’s hard to say whether our intelligence is genuinely far more sophisticated than computers’.”

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閱讀完上面的不同評(píng)論，再次思考：

- 圖靈測(cè)試是回答“機(jī)器可以思考嗎Can machines think?”這個(gè)問(wèn)題的好方法嗎？為什么或者為什么不？

- 您閱讀這些評(píng)論時(shí)有何反應(yīng)？有什么有趣，令人驚訝，令人困惑的地方？

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思考過(guò)后，您可以嘗試寫(xiě)一篇短小的反思文章：

您認(rèn)為圖靈測(cè)試是回答“機(jī)器可以思考嗎”這個(gè)問(wèn)題的好方法嗎？為什么？人與計(jì)算機(jī)的“思維”在哪些方面相似？它們有什么不同？

值得注意的是，認(rèn)知科學(xué)家們在這些問(wèn)題上存在很大的分歧。每個(gè)人的觀點(diǎn)都可能有各自的依據(jù)，這些問(wèn)題并沒(méi)有“標(biāo)準(zhǔn)答案”。

本期內(nèi)容到結(jié)束，感謝閱讀！期待更多中文版專欄請(qǐng)多多支持UP主喔~