认知心理学 (中文) 3 - 关于图灵测试的观点与评论

本期内容是关于图灵测试的观点与评论，如果不了解图灵测试可以移步第一期文章认知心理学 (中文) 1 - 什么是智能？谁能够思考？。

复杂认知/认知心理学系列文集中文版文集！我们如何变得如此聪明？我们是如何感知周围的世界、学习语言、制定决策、记得过去、并预测未来的？大量的神经组织如何思考？怎么样产生想法？这些都是本系列专栏将尝试回答或启发思考的问题。

本系列主要分为三种内容：第一种是传统的讲座形式的知识内容，涵盖不同的概念与例子；第二种是体验不同的认知科学实验；第三种是不定期地对丹尼尔·卡尼曼的《思考，快与慢》这本心理学著作的阅读与讨论。

本期思考：图灵测试是回答“机器可以思考吗 Can machines think?”这个问题的好方法吗？为什么或者为什么不？

值得注意的是，认知科学家们在这些问题上存在很大的分歧。每个人的观点都可能有各自的依据，这些问题并没有“标准答案”。

阅读下面的不同人的评论，思考上面的问题，并注意：

- 您在阅读的过程中有什么让你感到惊讶？出现了哪些主题？

- 您阅读这些评论时有何反应？有什么有趣，令人惊讶，令人困惑的地方？

• 人们都持什么观点？Where do we stand?

–“我对图灵测试及其评估计算机是否被认为正在思考的能力感到非常矛盾。我认为该测试有很多优点，并且可以与人类抗衡，但是在了解了可以通过图灵测试的人工智能系统之后，我不确定我是否会考虑它在“思考”。（意思是这位朋友认为有的通过图灵测试的人工智能系统很瓜批。）

– “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.”

–“我相信计算机的工作永远无法与人类的思想相提并论，而机器也永远无法去“思考”，这是一种种类似于人类的方式。”

– “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.”

–“我认为图灵测试是回答以下问题的好方法：‘机器可以证明它们与人类相似吗？’”

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

–“图灵测试在测试机器方面的表现非常出色，它能够给出满足人类受众的答案。”

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

–“我觉得图灵测试不是回答机器可以思考的好方法。图灵测试模仿了智能的行为，但是机器实际上不是智能的。”

– “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.”

–“我将思维定义为使用理性或逻辑判断来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.”

–“我个人认为，如果在特定情况下使用，图灵测试可能是一个不错的指标。 神经网络的概念是我们未多讲的一项人工智能技术。据我了解，他们从各种刺激中‘学习’，并可以根据以前的经验创建处理网络，以对新刺激做出反应。”

– “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.”

–“图灵测试是一种确定计算机是否可以思考的好方法，因为该测试涵盖了不同类型的询问。诸如亚马逊Alexa或苹果产品的Siri之类的新技术中的人工智能正在演变为将人类与计算机区分开来的更像人类的功能。”

– “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.”

–“尽管一台机器通常缺乏自由意志并且无法创造自己的思想，但我认为使用代码成为人类冒名顶替者的战略行为（因此欺骗询问者）确实在某种程度上暗示了思想。”

– “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.”

–“我很喜欢图灵的论文中，有一段内容解释了人们在将人工智能与我们的智能进行比较时如何如此轻描淡写，因为我们不希望任何东西威胁到我们自己对人类优于所有其他人类的看法。当我继续思考这个问题时，我将不得不进行自我检查，并确保我不会让这种偏见阻止我真正考虑所有可能性。”

– “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.”

–“我认为图灵测试可以帮助回答‘机器可以思考吗？’这个问题，但这不应是唯一的测试。”

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

–“图灵测试是回答机器是否可以思考的好方法。我们知道其他人的想法的唯一原因是，他们做着并说出使我们推断出他们可以思考的事情。图灵测试一旦通过，就会欺骗人们相信机器是人类，因为他们认为与之交流的事物像人类一样在思考。”

– “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.”

• 人与计算机之间有相似之处There are similarities between humans and computers.

–“人类和计算机的想法相似，因为我们都从过去的经验中学到东西。机器与人一样，会从奖惩中学习，而经验则可以指导他们的决策。”

– “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.”

–“从最基本的意义上讲，人与计算机的想法是相同的：它们从外界接收刺激和信息，然后根据一组规则进行处理和响应。”

– “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.”

–“机器在某种程度上确实像人一样思考。人们获得知识，评估他们认为正确的答案或正确的事情并采取行动。我们倾向于将相似性或差异性的信息分组，将信息组织成层次或模式，得出不同主题和思想之间的结论和联系。”

– “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.”

• 人与计算机之间存在差异There are differences between humans and computers.

–“但是，只有人类有学习的欲望。发展与变化是我们固有的，是有机的。”

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

–“我同意马库斯的观点，他认为机器与人类不同，因为机器主要依靠‘模式识别’，而不是真正的理解。人类的思维也会因情感而变得扭曲。例如，如果我们感到沮丧或饥饿，我们会失去精力，因此可能会屈服于我们的第一个想法（消耗最少脑力的想法）。电脑没有情感，因此他们的思维不会受到干扰。”

– “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.”

–“计算机与人类思维之间的区别在于，人类在思考时具有自主权，这意味着人类可以主动地随意思考。而计算机则不然，他们的编程决定（或限制）了他们的想法。”

– “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.”

–“我认为计算机不可能创造出像真实人类一样的新事物。但是，如果我们可以对一个系统进行编程，让计算机学习新事物并运用他们所学到的知识，则是很有可能的。”

– “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.”

–“即使我们知道某种行为可能会导致惩罚，我们仍会考虑导致我们继续进行的这种行为，因为尽管一再被警告，我们可能会坚持认为它是正确的行动方针。而机器是基于逻辑和被告知正确的思想来思考的。”

– “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.”

–“（人与机器）主要区别在于儿童可以成长为形成自己的意见，并选择拒绝接受所学的内容的个体。计算机无法这样做。我认为这是计算机工作方式与人类思维方式之间的主要区别，是人们能够结合情感和过去的经验来改变其行为的能力。”

– “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.”

–“人工智能可能能够模拟对话响应或开个玩笑，但仍无法根据个人经验来综合信息。因此，尽管通过了图灵测试，它仍无法像我们一样‘思考’。”

– “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.”

–“也许若重新评估了测试的参数，如文章所建议的那样；也许若我们可以确定机器是否可以学习并分析其所知道的知识，那将是一个更好的测试。”

– “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.”

–“我相信元认知（元认知是指对‘认知’的认知。例如对自己的各种认知活动进行积极的监控和调节；对自己的感知、记忆、思维等认知活动本身的再感知、再记忆、再思维就称为元认知）对于能够真正思考至关重要。如果没有某种自我认知或意识，元认知是不可能的，因为如果不先意识到自己有大脑，就无法考虑大脑的运作方式。

– “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.”

–“对于人类，我们遵循大脑中养成的思维习惯。很难说我们的情报是否真的比计算机复杂得多。”

– “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’.”

阅读完上面的不同评论，再次思考：

- 图灵测试是回答“机器可以思考吗Can machines think?”这个问题的好方法吗？为什么或者为什么不？

- 您阅读这些评论时有何反应？有什么有趣，令人惊讶，令人困惑的地方？

思考过后，您可以尝试写一篇短小的反思文章：

您认为图灵测试是回答“机器可以思考吗”这个问题的好方法吗？为什么？人与计算机的“思维”在哪些方面相似？它们有什么不同？

值得注意的是，认知科学家们在这些问题上存在很大的分歧。每个人的观点都可能有各自的依据，这些问题并没有“标准答案”。

本期内容到结束，感谢阅读！期待更多中文版专栏请多多支持UP主喔~