I consider myself one part artist and one part designer. And I work at an artificial intelligence research lab. We're trying to create technology that you'll want to interact with in the far future. Not just six months from now, but try years and decades from now. And we're taking a moonshot that we'll want to be interacting with computers in deeply emotional ways. So in order to do that, the technology has to be just as much human as it is artificial. It has to get you. You know, like that inside joke that'll have you and your best friend on the floor, cracking up. Or that look of disappointment that you can just smell from miles away.
﻿我自认为既是一位艺术家， 又是一位设计师。 我在一个研究 人工智能的实验室工作。 我们正在尝试创造一项 在遥远的将来能和人类互动的科技。 不是在六个月之后， 而是几年甚至几十年之后。 我们正在实施一个“登月计划”， 我们希望能与电脑 进行深层次的情感方面的互动。 为了做到这些， 技术不仅要智能，还要人性。 它必须懂你。 就像一个朋友间的笑话， 能让你和你的朋友 在地板上笑得前仰后翻； 或者是，你远远就能 嗅到的失望气息。
I view art as the gateway to help us bridge this gap between human and machine: to figure out what it means to get each other so that we can train AI to get us.
我把艺术看作是帮助我们填补 人类与机器之间空白的途径： 使每个人都能相互了解对方， 使我们能训练 人工智能来“懂我们”。
See, to me, art is a way to put tangible experiences to intangible ideas, feelings and emotions. And I think it's one of the most human things about us. See, we're a complicated and complex bunch. We have what feels like an infinite range of emotions, and to top it off, we're all different. We have different family backgrounds, different experiences and different psychologies. And this is what makes life really interesting. But this is also what makes working on intelligent technology extremely difficult. And right now, AI research, well, it's a bit lopsided on the tech side. And that makes a lot of sense.
对我来说，艺术是把有形的经历， 转化为无形的想法、 感受、情感的方式。 我认为这是人性的一个重要特征。 我们是难懂的、复杂的群体。 我们拥有无限的情感， 而且，我们都是不同的。 我们拥有不同的家庭背景， 不同的经历，不同的心理活动。 这是为什么生活那么有趣的原因， 但这同时也是研究智能技术 最难的地方。 如今，对人工智能的研究 过于偏重技术， 这也很好理解。
See, for every qualitative thing about us -- you know, those parts of us that are emotional, dynamic and subjective -- we have to convert it to a quantitative metric: something that can be represented with facts, figures and computer code. The issue is, there are many qualitative things that we just can't put our finger on.
关于我们的每一个定性的特征， 比如属于我们情感的、 动态的、主观的部分—— 我们要把它转化为一个量化指标： 能通过一些事实、图形和 电脑代码表现出来。 问题是，有很多定性的东西 是很难量化的。
So, think about hearing your favorite song for the first time. What were you doing? How did you feel? Did you get goosebumps? Or did you get fired up? Hard to describe, right? See, parts of us feel so simple, but under the surface, there's really a ton of complexity. And translating that complexity to machines is what makes them modern-day moonshots. And I'm not convinced that we can answer these deeper questions with just ones and zeros alone.
想一想你第一次听到 你最喜欢的歌的时候， 你在做什么？ 你有什么感受？ 你起鸡皮疙瘩了吗？ 你有没有感到热血沸腾？ 很难描述，对吗？ 我们一些看似很简单的感受 背后其实是很复杂的。 而将这些复杂的东西 翻译成机器语言， 这就是我们需要实现的 现代“登月计划”。 我不相信我们可以仅仅 用0和1这两个数字 来解决这些难题。
So, in the lab, I've been creating art as a way to help me design better experiences for bleeding-edge technology. And it's been serving as a catalyst to beef up the more human ways that computers can relate to us. Through art, we're tacking some of the hardest questions, like what does it really mean to feel? Or how do we engage and know how to be present with each other? And how does intuition affect the way that we interact?
所以，在实验室，我通过创造艺术 来帮助我设计更好的 对尖端科技的体验。 艺术作为一种催化剂， 让电脑更加人类化， 更理解我们。 通过艺术，我们在解决一些 非常困难的问题， 就像，感受到底是什么意思？ 我们如何真正参与或投入其中？ 我们的直觉怎样影响 我们互动的方式？
So, take for example human emotion. Right now, computers can make sense of our most basic ones, like joy, sadness, anger, fear and disgust, by converting those characteristics to math. But what about the more complex emotions? You know, those emotions that we have a hard time describing to each other? Like nostalgia.
以人类的情感为例， 如今，电脑能够明白 我们的基本情感， 比如开心、伤心、 生气、恐惧、厌恶， 把这些特征转化为数学。 那较复杂的情感呢？ 比如那些很难 用文字向对方描述的情感， 比如，怀旧。
So, to explore this, I created a piece of art, an experience, that asked people to share a memory, and I teamed up with some data scientists to figure out how to take an emotion that's so highly subjective and convert it into something mathematically precise. So, we created what we call a nostalgia score and it's the heart of this installation. To do that, the installation asks you to share a story, the computer then analyzes it for its simpler emotions, it checks for your tendency to use past-tense wording and also looks for words that we tend to associate with nostalgia, like "home," "childhood" and "the past." It then creates a nostalgia score to indicate how nostalgic your story is. And that score is the driving force behind these light-based sculptures that serve as physical embodiments of your contribution. And the higher the score, the rosier the hue. You know, like looking at the world through rose-colored glasses.
所以，为了探索这个问题， 我创造了一件艺术品，一种体验， 要求人们分享他们的记忆， 我和一些数据科学家组成一个团队， 去研究高度主观的情感是怎样的， 如何将它们精确地转化为数学。 我们创造了一个叫怀旧分数的东西， 这是这个装置的核心。 这个装置会要求你分享一则故事， 电脑会分析它的一些简单的情感， 它会检测你使用 过去时态的词语的偏好， 还会寻找与怀旧有关的词语， 比如“家”、“童年”和“过去”。 它最后会给出一个怀旧分数， 代表着你的故事的怀旧程度， 这个分数会 让这个灯箱的颜色发生变化， 代表着你的贡献。 分数越高，色调越偏向玫瑰红色， 就像是通过玫红色的眼镜看世界。
So, when you see your score and the physical representation of it, sometimes you'd agree and sometimes you wouldn't. It's as if it really understood how that experience made you feel. But other times it gets tripped up and has you thinking it doesn't understand you at all. But the piece really serves to show that if we have a hard time explaining the emotions that we have to each other, how can we teach a computer to make sense of them?
当你看到你的分数， 以及它的外部反映时， 有时你会赞同，有时不赞同。 有的时候就好像它真的明白 故事里的你当时的感受， 但有的时候它也会出错， 会让你觉得它一点也不懂你。 但这个装置能够说明， 如果连我们都很难表述清楚的情感， 我们该如何教电脑明白呢？
So, even the more objective parts about being human are hard to describe. Like, conversation. Have you ever really tried to break down the steps? So think about sitting with your friend at a coffee shop and just having small talk. How do you know when to take a turn? How do you know when to shift topics? And how do you even know what topics to discuss? See, most of us don't really think about it, because it's almost second nature. And when we get to know someone, we learn more about what makes them tick, and then we learn what topics we can discuss. But when it comes to teaching AI systems how to interact with people, we have to teach them step by step what to do. And right now, it feels clunky. If you've ever tried to talk with Alexa, Siri or Google Assistant, you can tell that it or they can still sound cold. And have you ever gotten annoyed when they didn't understand what you were saying and you had to rephrase what you wanted 20 times just to play a song? Alright, to the credit of the designers, realistic communication is really hard. And there's a whole branch of sociology, called conversation analysis, that tries to make blueprints for different types of conversation. Types like customer service or counseling, teaching and others.
甚至很多关于 人性的客观方面也很难描述。 比如，对话。 你曾经尝试过分解谈话的步骤吗？ 试着想象一下， 你和你的朋友坐在咖啡馆， 进行简单的交谈， 你怎么知道轮到你说话了？ 你怎么知道什么时候该转换话题？ 你怎么知道要讨论些什么？ 大多数人都不会想这些问题， 因为这对我们来说是很自然的。 当我们认识一个人的时候， 我们会对他们越来越了解， 然后我们会知道能聊些什么话题。 但是，当你教人工智能 怎样与人类互动时， 我们需要一步一步教它们该如何做。 而现在，这个过程还感觉很笨拙。 如果你曾尝试和 Alexa, Siri  或谷歌助手聊天， 你可以感觉得到， 它们仍听上去冷冰冰的。 你是否曾经因为它们 不明白你说什么而变得恼怒， 比如为了让它们放一首歌， 你得说上20次？ 不过我们也要理解设计师，毕竟 让机器学会真实的沟通是非常难的。 有一个社会学的分支， 叫做会话分析， 它尝试做不同对话类型的蓝图， 例如像客户服务、心理咨询、 教授课程等等的会话类型。
I've been collaborating with a conversation analyst at the lab to try to help our AI systems hold more human-sounding conversations. This way, when you have an interaction with a chatbot on your phone or a voice-based system in the car, it sounds a little more human and less cold and disjointed. So I created a piece of art that tries to highlight the robotic, clunky interaction to help us understand, as designers, why it doesn't sound human yet and, well, what we can do about it. The piece is called Bot to Bot and it puts one conversational system against another and then exposes it to the general public. And what ends up happening is that you get something that tries to mimic human conversation, but falls short. Sometimes it works and sometimes it gets into these, well, loops of misunderstanding. So even though the machine-to-machine conversation can make sense, grammatically and colloquially, it can still end up feeling cold and robotic. And despite checking all the boxes, the dialogue lacks soul and those one-off quirks that make each of us who we are.
我已经在和会话分析学家 在实验室展开合作， 尝试帮助我们的人工智能系统 进行更多的人性化的对话。 这样，当你和手机 聊天机器人进行互动时， 或者和车载语音系统互动时， 这种声音就听上去更人性， 不那么冷淡和缺乏逻辑。 我创造的这个艺术品， 重点突显了机械化的、 笨拙的互动方式， 以帮助我们这些设计师明白， 为什么它听上去不像人类， 我们该如何解决这个问题。 这个艺术品叫 Bot to Bot， 它将一个会话系统 搭建在另一个会话系统之上， 然后展示给公众。 最终会发生的就是， 它尝试模仿人类的对话， 但是却明显有不足之处。 有的时候它还可以，而有的时候 会陷入误解的循环。 虽然机器与机器的对话 从语法、用意上 能让人明白， 但是你还是能感觉到 这个对话的冰冷和机械化。 尽管对话的其他要素都具备， 但却缺少了灵魂， 缺少了那些使我们 之所以为人类的特质。
So while it might be grammatically correct and uses all the right hashtags and emojis, it can end up sounding mechanical and, well, a little creepy. And we call this the uncanny valley. You know, that creepiness factor of tech where it's close to human but just slightly off. And the piece will start being one way that we test for the humanness of a conversation and the parts that get lost in translation.
尽管它的语法也许正确， 用对了所有的话题标签和符号表情， 但最终听起来还是有些呆板， 还有点儿吓人。 我们把这称为恐怖谷， 这种科技的恐怖之处在于， 它无比接近人类，却又缺了点什么。 这件艺术品能开始用于 测试交流的人性化， 以及被误解的部分。
So there are other things that get lost in translation, too, like human intuition. Right now, computers are gaining more autonomy. They can take care of things for us, like change the temperature of our houses based on our preferences and even help us drive on the freeway.
还有其他一些事情 也容易被电脑误解， 比如，人类的直觉。 如今，电脑拥有更多的自主权， 能为我们管理一些东西， 比如根据我们的偏好 调整房子的温度， 甚至帮助我们在高速公路驾驶。
But there are things that you and I do in person that are really difficult to translate to AI. So think about the last time that you saw an old classmate or coworker. Did you give them a hug or go in for a handshake? You probably didn't think twice because you've had so many built up experiences that had you do one or the other.
但是一些我和你会做的事， 是非常难翻译给人工智能的。 想一想你上一次 见到一位老同学或老同事时， 你跟他们拥抱还是握手了呢？ 你可能想都没想， 因为你有过许多这样的经历， 要么拥抱要么握手。
And as an artist, I feel that access to one's intuition, your unconscious knowing, is what helps us create amazing things. Big ideas, from that abstract, nonlinear place in our consciousness that is the culmination of all of our experiences. And if we want computers to relate to us and help amplify our creative abilities, I feel that we'll need to start thinking about how to make computers be intuitive.
作为一名艺术家，我认为 了解一个人的直觉， 你的潜意识的知觉， 能够帮助我们创造 令人惊叹的东西。 大的点子，我们潜意识中 抽象的，非线性的东西 是我们所有经历的总和。 如果我们想让电脑 帮我们提升创造力， 我认为我们需要思考 如何才能让电脑有直觉，
So I wanted to explore how something like human intuition could be directly translated to artificial intelligence. And I created a piece that explores computer-based intuition in a physical space. The piece is called Wayfinding, and it's set up as a symbolic compass that has four kinetic sculptures. Each one represents a direction, north, east, south and west. And there are sensors set up on the top of each sculpture that capture how far away you are from them. And the data that gets collected ends up changing the way that sculptures move and the direction of the compass. The thing is, the piece doesn't work like the automatic door sensor that just opens when you walk in front of it. See, your contribution is only a part of its collection of lived experiences. And all of those experiences affect the way that it moves. So when you walk in front of it, it starts to use all of the data that it's captured throughout its exhibition history -- or its intuition -- to mechanically respond to you based on what it's learned from others. And what ends up happening is that as participants we start to learn the level of detail that we need in order to manage expectations from both humans and machines. We can almost see our intuition being played out on the computer, picturing all of that data being processed in our mind's eye.
所以，我想探究 如何将像人类直觉的东西 直接地翻译给人工智能。 于是我创造了一台通过现实空间 探究电脑直觉的机器。 它叫 Wayfinding， 它有4个动态装置，像一个指南针。 每一个装置代表着一个方向， 北、东、南、西。 装在每个装置顶端的传感器， 能够捕获你离它们的距离有多远。 接着数据会被采集， 最终装置就会移动， 从而改变指南针的方向。 不过不像自动门的传感器那样—— 你走到它前面的时候，门就会打开， 你的行为只是它 搜集的体验的一部分， 所有的体验都会影响它的移动。 所以当你在它前面走动时， 它开始用所有之前 捕获的数据—— 或它的直觉—— 基于它从其他人那里学习到的， 对你做出机械的响应。 最终，作为参与者， 我们意识到我们需要怎样的细节 才能同时管理 人类和机器的预期。 我们几乎可以看到我们的直觉 在电脑中被展示出来， 想象所有的数据 被我们的心灵之眼所处理。
My hope is that this type of art will help us think differently about intuition and how to apply that to AI in the future.
我希望这种艺术方式， 能帮助我们从不同角度思考直觉， 以及将来如何 将它运用到人工智能中去。
So these are just a few examples of how I'm using art to feed into my work as a designer and researcher of artificial intelligence. And I see it as a crucial way to move innovation forward. Because right now, there are a lot of extremes when it comes to AI. Popular movies show it as this destructive force while commercials are showing it as a savior to solve some of the world's most complex problems.
这些都是我在自己的 人工智能设计和研究的工作中 如何利用艺术的例子。 我觉得这是一个 推动创新的重要方式。 因为现在说到人工智能， 两极分化的态度很严重。 比如一些流行电影 将其描绘成毁灭性的力量， 而一些广告则 把它们描绘为救世主—— 能解决一些世界上 极端复杂的问题。
But regardless of where you stand, it's hard to deny that we're living in a world that's becoming more and more digital by the second. Our lives revolve around our devices, smart appliances and more. And I don't think this will let up any time soon. So, I'm trying to embed more humanness from the start. And I have a hunch that bringing art into an AI research process is a way to do just that.
但是不管你站在哪一边， 我们都无法否认，我们正生活在一个 越来越数字化的世界中。 我们的生活被设备、智能家居等充斥， 而我不觉得这种状况会停止。 我想在一开始就植入更多的人性， 而我有预感，将艺术 带入人工智能研究 就是其中一个方法。
Thank you.
谢谢。
(Applause)
（掌声）