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You've probably heard of the uncanny valley before.
你以前可能听说过恐怖谷理论。
It's the sense of unease you feel when you encounter a slightly-too-lifelike robot or the feeling of yikes when you stumble across a very creepy doll.
当遇到一个稍显逼真的机器人时，你会感到不安；当偶然发现一个非常令人毛骨悚然的洋娃娃时，你会感到很惊讶。
The sense of nope, no thank you, do not want that you might get if you, say, very hypothetically, you kept seeing unsettling CGI cat-humans cavorting around your social media feeds.
假如你一直看到令人不安的计算机影像生成的猫样人类，在你的社交媒体订阅中嬉戏，你可能会都感到不要，谢谢你了，我不想要。
The uncanny valley is the steep drop off in how likable we find a character or robot to be when it gets… slightly too close to appearing human.
恐怖谷理论是当一个角色或机器人变得有点过于接近人类时，我们发现它的可爱程度猛烈下滑的变化体验。
These days, it's everywhere in pop culture, so it might surprise you to know that there's still a lot we don't understand about what causes it -- and whether it even really exists.
现在，流行文化无处不在，所以你可能会惊讶地发现，我们还不太清楚引发这种现象的原因，甚至不确定它是否真的存在。
The idea of the uncanny valley was first proposed in an essay written by a Japanese roboticist named Masahiro Mori in 1970.
恐怖谷理论概念最早是1970年，在日本机器人学家森正彦撰写的一篇文章中提出的。
He hypothesized that a person's affinity for a robot would increase as the robot became more and more human-like.
他假设，随着机器人越来越像人类，人们对机器人的喜好程度会增加。
And then, very abruptly, that affinity would drop off and be replaced by revulsion.
然后突然之间，这种喜爱就会消失，取而代之的是反感。
He provided examples by plotting human likeness against likability for things like robots and puppets, and came up with a graph with a sharp dip: that is the uncanny valley.
他通过绘制和人类的相似性与机器人和木偶之类物品的可爱性之间的对比，给出了一些例子，并得到一个急剧下降的图形：那就是恐怖谷理论。
This idea wasn't totally new.
这并非一个全新的说法。
Fifty years earlier, Freud had written about "the uncanny," and the terror caused by things that reminded us of the familiar.
五十年前，弗洛伊德曾写过《神秘》，以及对那些引起我们熟悉感事物的恐怖感。
But the obsession with the uncanny valley in pop culture didn't really take off until the early 2000s.
但是，人们对流行文化中恐怖谷理论的痴迷直到21世纪初才真正开始。
In particular, it's been attributed to -- go ahead and guess -- yes the 2004 Polar Express film starring Tom Hanks.
特别是，人们认为它源于，你们可以猜猜看，没错，2004年由汤姆·汉克斯主演的电影极地快车。
Plenty of early CGI movies flopped in large part because they freaked people out.
很多早期的CGI电影之所以失败，很大程度上是因为它们把观众吓坏了。
And scientists really do cite that freakiness as part of the history of the uncanny valley.
科学家们确实把这种怪诞作为恐怖谷理论由来的一部分。
Then, in 2005, Mori's essay was translated into English, and psychologists started to actually study the phenomenon in earnest.
然后，在2005年，莫里的文章被翻译成英语，心理学家开始认真研究这一现象。
Most of the research since then has looked at whether or not it's possible to recreate his uncanny valley-shaped plot with real data.
此后的大部分研究都着眼于，是否有可能用真实的数据重现他那不可思议的恐怖谷理论状的波形。
And the results have been mixed.
结果好坏参半。
An early study of 45 people in 2006 asked participants to rate the likeability of a series of morphed images, ranging from a mechanical robot through an android to a human.
2006年，一项针对45人的早期研究要求参与者对一系列变形图像的可爱程度打分，这些图像从机械机器人到机器人再到人类。
And they did see an uncanny valley-type effect.
他们确实看到一种恐怖谷理论型效应。
But even then, the researchers questioned whether a spectrum of morphed images would always produce an uncanny valley.
但即便如此，研究人员仍在质疑，一系列变形图像是否总能引发恐怖谷理论效应。
Basically, was the uncanny valley inevitable?
基本上，恐怖谷理论不可避免吗？
It might not be, because the effect doesn't always show up.
可能不是，因为这种效应并不总能显现出来。
In general, studies that use artificially manipulated images morphing between one thing and another have been more likely to support the valley's existence than those using images of real robots.
一般来说，使用人工操纵的图像在一个事物和另一个物体之间变形的研究，比使用真实机器人的图像更有可能支持这种效应。
But at least one study, published in 2016, where 342 participants looked at 80 real-life robot faces, did find an uncanny valley curve.
但至少在2016年发表的一项研究中，342名参与者观察了80张真实机器人的面孔，发现一条恐怖谷理论曲线。
So… it's kind of hard to say.
所以，有点难说。
Many of us feel something deep down when we see CGI Taylor Swift, but the research simply hasn't pinned it down yet.
我们看到CGI版的泰勒·斯威夫特时，很多人内心深处都产生了某种感觉，但这项研究还不能确定。
Neither is there a clear idea of what might cause it.
也不清楚是什么原因造成的。
There are tons of hypotheses!
有很多种假设！
Some of the less likely ones invoke our perceptions.
一些可能性比较小的假设激活了我们的感知。
Like the pathogen avoidance hypothesis, which suggests that disgust towards uncanny faces might have helped us avoid someone who might be carrying a transmissible disease.
就像病原体回避假说，它表明对鬼脸的厌恶有助于我们避开那些可能携带传染性疾病的人。
Or the mortality salience hypothesis, which suggests that uncanny faces, like clowns, dolls, wax figures, corpses, and zombies, might literally remind us of death.
或者按照死亡显著性假说，这种假说认为像鬼脸、洋娃娃、蜡像、尸体和僵尸这样的事物，可能会让我们想到死亡。
But none of these really have enough evidence to support them.
但这些都没有足够的证据来加以支持。
Other hypotheses invoke what's going on in our brains, rather than what we perceive.
其他假设激活了我们大脑中发生的事情，而不是我们感知到的事物。
The violation of expectation hypothesis suggests that uncanny faces might lead us to think they're going to behave in a way that is human-like and then violate that expectation.
违反预期假说表明，鬼脸可能会让我们认为它们的行为会像人类一样，但实际上却违反了这种预期。
The strongest evidence for this comes from research showing that robots and characters with a mismatch between their appearance and movements, or their appearance and voice, freak us out more than ones that just look creepy.
这方面最有力的证据，来自研究机器人和角色的外表和动作，或者外表和声音不匹配的研究，结果发现它们比那些只是看起来令人毛骨悚然的角色更让我们抓狂。
But researchers still believe this one doesn't answer all the questions.
但研究人员仍然认为，这并不能回答所有的问题。
The categorical uncertainty hypothesis also tries to make sense of how our brains are processing uncanny faces.
分类不确定性假设也试图解释我们的大脑如何对鬼脸进行处理。
This one argues that there's uncertainty at any category boundary.
这种假设认为在任何类别边界上都存在不确定性。
So it's not just humans vs. robots that freaks us out, it's anything that our brains can't put into a nice neat box.
所以不仅仅是人类和机器人让我们抓狂，还有我们大脑中的那些奇思怪想。
Like a cat person.
就像猫人一样。
But there's a problem:
但是有个问题：
A lot of this research relies on morphed images, but it's possible that the very process of morphing images creates visual artifacts our brains simply Do. Not. Like.
很多这项研究都依赖于变形图像，但变形图像的过程很可能创造出我们大脑不喜欢的视觉伪影。
That might confound a lot of these findings.
这可能会让很多发现变得混淆不清。
And then, there are the theories that look at what we think it means to be human.
还有一些理论来研究我们所认为的作为人类的意义。
The mind perception hypothesis suggests that we find robots uncanny when we think these non-human things might be capable of the human ability to think, plan, and feel.
心灵感知假说认为，当我们认为这些非人类的东西可能具有人类思考、计划和感觉的能力时，我们会发现机器人是不可思议的。
One 2012 study surveyed 165 participants and found that if they believed that a robot could sense and experience things, that played a role in making a human-like robot seem creepier than a mechanical one.
2012年的一项研究对165名参与者进行了调查，发现如果他们认为机器人能够感知和体验事物，就会使类似人类的机器人看起来比机械机器人更恐怖。
The study also found that a non-humanoid robot could be made creepy -- if participants were told that it was capable of human-like thinking, feeling, and planning.
这项研究还发现，如果参与者被告知一个非人形机器人能够像人类一样思考、感觉和规划，那么它可能会变得令人感到毛骨悚然。
The dehumanization hypothesis looks at the same idea from a different angle: robots aren't creepy because they look and act more like humans.
非人性化假说从不同的角度看待同一个观点，即机器人并不是因为其外表和行为更像人类，才令人毛骨悚然。
Rather, it's because they look like us, but don't act enough like us.
而是因为它们长得像我们，但行为却并不完全和我们相似。
Our brains are super good at recognizing faces.
我们的大脑非常善于识别面孔。
The idea here is that when we see one and it doesn't behave the way we expect actual human people to act, that triggers uncanny feelings
这种观点认为，当我们看到一个人，而他没有按照我们期望的人类那样行事时，就会引发异样的感觉。
There are arguments to be made, and at least some evidence, in favor of basically all of these hypotheses.
有一些论据，至少某些证据，支持所有这些假设。
So we don't have a lot of answers when it comes to the uncanny valley.
所以当我们谈到恐怖谷理论时，没有太多的答案。
It's a phenomenon many of us are pretty darn convinced is real.
这是一个很多人都确信真实存在的现象。
We feel it in our guts, even if psychologists can't really tell us why.
即使心理学家不能真正告诉我们原因，我们也能从内心感受到。
When Mori wrote his essay in 1970, he was interested in figuring out how roboticists and animators could overcome it -- and that's clearly something we're still struggling with.
莫里1970年写这篇文章时，他很想弄清楚机器人学家和动画师如何克服这种现象，这显然是我们仍在努力解决的问题。
Some researchers, though, argue that we may never overcome it -- and, in fact, that it's worth keeping around.
不过，一些研究人员认为，我们可能永远无法克服它，事实上，这个问题值得关注。
Lets us know that we can tell the difference between robots and humans, and that's actually a pretty cool thing for our brains to be able to do.
让我们了解，我们可以分辨机器人和人类的区别，这对我们的大脑来说是一件超酷的事。
And it might come in handy in the future.
而且将来可能会派上用场。
Our perceptions definitely filter the way we see the world -- not just androids.
我们的感知肯定会过滤我们看待世界的方式，不仅仅是机器人。
The CuriosityStream original What Is Reality is about that idea, looking at how our brains construct the world around us.
CuriosityStream的原创节目《什么是现实》所讲的就是这个观点，它关注于我们的大脑如何构建周围的世界。
And that's just one of the over 2,400 documentaries and nonfiction titles available on CuriosityStream, including exclusive originals, so there's something there for anyone who enjoys learning.
这只是CuriosityStream上2400多部纪录片和纪实片中的一部，CuriosityStream其中包括独家原创节目，对于喜欢学习的人来说，都能找到喜欢的视频。
And you're here, so you probably do.
现在你们在收看这个视频，所以可能也会去那里看看。
CuriosityStream is available worldwide, and their titles cover topics ranging from science to lifestyle, and nature to tech.
世界各地都能收看CuriosityStream，它们的节目涵盖了从科学到生活方式，从自然到技术的各个领域。
Right now, SciShow viewers can get unlimited access starting at just $2.99 a month,
现在，科学秀的观众可以每月花2.99美元无限制地观看，
and the first 31 days are completely free if you sign up at curiositystream.com/Psych and use the promo code "psych" during the sign-up proocess.
如果您在curiositystream.com/ Psych注册，并在注册过程中使用促销代码“psych”，前31天完全免费。
So thanks for checking them out -- and for supporting SciShow.
感谢你们去看那里的视频，也感谢你们支持科学秀节目。
