My job at Twitter is to ensure user trust, protect user rights and keep users safe, both from each other and, at times, from themselves. Let's talk about what scale looks like at Twitter. Back in January 2009, we saw more than two million new tweets each day on the platform. January 2014, more than 500 million. We were seeing two million tweets in less than six minutes. That's a 24,900-percent increase.
我在推特的工作 就是去确保用户的信赖, 保护用户之间的 以及他们自身的 权利和安全。 让我们讨论一下在推特,比例是什么样的。 在2009年1月, 每天,在推特上我们可以看见 超过两百万条推特更新。 2014年1月有超过五亿条。 我们那时在六分钟之内 就可以看见两百万条。 那是一个24,900%的增长。
Now, the vast majority of activity on Twitter puts no one in harm's way. There's no risk involved. My job is to root out and prevent activity that might. Sounds straightforward, right? You might even think it'd be easy, given that I just said the vast majority of activity on Twitter puts no one in harm's way. Why spend so much time searching for potential calamities in innocuous activities? Given the scale that Twitter is at, a one-in-a-million chance happens 500 times a day. It's the same for other companies dealing at this sort of scale. For us, edge cases, those rare situations that are unlikely to occur, are more like norms. Say 99.999 percent of tweets pose no risk to anyone. There's no threat involved. Maybe people are documenting travel landmarks like Australia's Heart Reef, or tweeting about a concert they're attending, or sharing pictures of cute baby animals. After you take out that 99.999 percent, that tiny percentage of tweets remaining works out to roughly 150,000 per month. The sheer scale of what we're dealing with makes for a challenge.
现在,推特上绝大多数的活动 都没有伤害到任何人。 不涉及任何风险。 我的工作就是铲除并防止这类事情的发生。 听起来简单明了,对吧? 你可能认为这件事很容易, 因为我刚说过绝大多数 在推特上的行为都是无害的。 为什么花这么多时间 在无害的行为中 搜寻潜在的危机呢? 考虑推特的规模, 百万分之一几率的可能, 一天会发生五百次。 对于其它公司来说, 他们面临的这个比例是一样的。 对于我们,边缘案例 那些不常有,也不大可能发生的情况 更像是家常便饭。 假设99.999%的推特 对任何人无害。 不涉及任何威胁。 人们可能在记录旅游胜地, 比如澳大利亚心型礁, 或者推文他们正在参加的演唱会, 或者分享可爱动物的图片。 在你剔除那99.999%之后, 剩下的那丁点推文 被计算出 每月约有15万条。 我们所应付的这个庞大规模 是一个挑战。
You know what else makes my role particularly challenging? People do weird things. (Laughter) And I have to figure out what they're doing, why, and whether or not there's risk involved, often without much in terms of context or background. I'm going to show you some examples that I've run into during my time at Twitter -- these are all real examples — of situations that at first seemed cut and dried, but the truth of the matter was something altogether different. The details have been changed to protect the innocent and sometimes the guilty. We'll start off easy.
你知道还有什么让我的职位 特别具有挑战性? 人们做奇怪的事情。 (笑声) 我必须弄明白他们在做什么, 为什么,以及涉及危险与否, 而这通常是在我没有掌握 来龙去脉的情况下。 我将要展示给你们几个例子, 是我在推特工作中遇到的--- 这些都是真实的例子- 这些情况乍看似乎直接了当, 但事情的真相 是截然不同的。 例子的细节有所改动 是为了去保护那些无辜者 有时也包括有过的那方。 让我们从简单的开始。
["Yo bitch"]
【“呦,bitch”】(bitch有母狗,婊子,娘们等意思)
If you saw a Tweet that only said this, you might think to yourself, "That looks like abuse." After all, why would you want to receive the message, "Yo, bitch." Now, I try to stay relatively hip to the latest trends and memes, so I knew that "yo, bitch" was also often a common greeting between friends, as well as being a popular "Breaking Bad" reference. I will admit that I did not expect to encounter a fourth use case. It turns out it is also used on Twitter when people are role-playing as dogs. (Laughter) And in fact, in that case, it's not only not abusive, it's technically just an accurate greeting. (Laughter)
如果你看到一条推文只有这一句话, 你可能认为 ”那看起来像是在谩骂。“ 毕竟,你为什么会想收到这条信息呢, “呦,婊子。” 现在,我试图与流行用语的 最新的释义保持同步, 所以我知道“呦,婊子” 有时候也是朋友之间常见的问候方式, 同时也是美剧《绝命毒师》中一个流行说法。 我要承认,我没有想到 我会遇到这个词的第四种用法。 在推特上 人们角色扮演狗的时候,也用这个词。 (笑声) 所以,在那种情况下, 这不仅不是谩骂, 严格的来说,那就是一个准确的问候。 (笑声)
So okay, determining whether or not something is abusive without context, definitely hard.
所以判断一些没有来龙去脉的东西 是否出于恶意 确实困难。
Let's look at spam. Here's an example of an account engaged in classic spammer behavior, sending the exact same message to thousands of people. While this is a mockup I put together using my account, we see accounts doing this all the time. Seems pretty straightforward. We should just automatically suspend accounts engaging in this kind of behavior. Turns out there's some exceptions to that rule. Turns out that that message could also be a notification you signed up for that the International Space Station is passing overhead because you wanted to go outside and see if you could see it. You're not going to get that chance if we mistakenly suspend the account thinking it's spam.
让我们来看一下垃圾邮件。 这是一个参与传播 常见垃圾邮件的账户, 它向数以千计的人 发送相同的信息。 虽然这是我用我的账号模仿的, 但我们总可以看到有账户在传播这样的垃圾信息。 看起来非常直白简单。 我们应该就自动暂停 参与这种行为的账号。 但结果中总有些例外情况。 那些信息也可能是公告提醒, 比如你想目睹国际空间站略过你上空的情形 而登记了这个信息。 希望可以收到提醒,尝试目睹它。 如果我们错误地认为这是垃圾信息, 并封了那个账号, 你将失去目睹国际空间站略过上空的机会。
Okay. Let's make the stakes higher. Back to my account, again exhibiting classic behavior. This time it's sending the same message and link. This is often indicative of something called phishing, somebody trying to steal another person's account information by directing them to another website. That's pretty clearly not a good thing. We want to, and do, suspend accounts engaging in that kind of behavior. So why are the stakes higher for this? Well, this could also be a bystander at a rally who managed to record a video of a police officer beating a non-violent protester who's trying to let the world know what's happening. We don't want to gamble on potentially silencing that crucial speech by classifying it as spam and suspending it. That means we evaluate hundreds of parameters when looking at account behaviors, and even then, we can still get it wrong and have to reevaluate.
让我们把赌注加高一些。 再来看我的帐号, 还是展现常见的行为。 这一次是发同样的信息和链接。 这通常意味着钓鱼式攻击,(注:一种网络诈骗的手段) 有人通过将一个人导向另一个网站 去盗取其账户信息。 很明显那不是什么好事。 我们想,也确实封了 从事那种行为的账户。 但为什么对这种行为的赌注更高呢? 这也可能是一个身处集会中的旁观者 录下了一段关于 警察殴打一个无辜抗议者的视频 他想让全世界知道发生了什么。 我们不想 在把那个关键演说通过分类为垃圾并暂停账号而可能导致的后果 上做冒险。 那也就意味着,当我们观察账户行为的时候 我们评估成百上千的因素 即使这样,我们仍然会犯错, 并需要重新评价。
Now, given the sorts of challenges I'm up against, it's crucial that I not only predict but also design protections for the unexpected. And that's not just an issue for me, or for Twitter, it's an issue for you. It's an issue for anybody who's building or creating something that you think is going to be amazing and will let people do awesome things. So what do I do? I pause and I think, how could all of this go horribly wrong? I visualize catastrophe. And that's hard. There's a sort of inherent cognitive dissonance in doing that, like when you're writing your wedding vows at the same time as your prenuptial agreement. (Laughter) But you still have to do it, particularly if you're marrying 500 million tweets per day. What do I mean by "visualize catastrophe?" I try to think of how something as benign and innocuous as a picture of a cat could lead to death, and what to do to prevent that. Which happens to be my next example. This is my cat, Eli. We wanted to give users the ability to add photos to their tweets. A picture is worth a thousand words. You only get 140 characters. You add a photo to your tweet, look at how much more content you've got now. There's all sorts of great things you can do by adding a photo to a tweet. My job isn't to think of those. It's to think of what could go wrong.
在这些挑战面前 关键在于我不仅要预测 而且防御不可预测的事情。 那不单是我的问题, 或者推特的问题,这也是你们的问题。 对于任何在创建美好事物, 或者为他人造福的人来说 都是一个问题。 那么我能做些什么呢? 我停下并思考, 这些事能如何 变得很糟糕的呢? 我想象灾难。 但是那很难。好像有一种 与生俱来的认知失调在作怪, 就像你同时写结婚誓言 和婚前协议一样。 (笑声) 但你还是得去做, 特别是当你一天得处理5亿条推文时。 我说的“想象灾难”是什么意思呢? 我试想,像猫的照片一样 温和并无害的东西 能如何导致死亡, 并想办法去阻止其发生。 这也是我的下一个例子。 这是我的猫,伊莱。 我们想要给予用户 将图片加到他们推文的能力。 一张图片胜过千言万语。 (一次推文)你只能输入140个字。 当你在推文里加一张图片时, 看看现在你发表的内容有多丰富。 通过在推文里添加图片, 你可以做各种各样神奇的事。 我的工作不是去想那些事情, 而是去想会发生什么问题。
How could this picture lead to my death? Well, here's one possibility. There's more in that picture than just a cat. There's geodata. When you take a picture with your smartphone or digital camera, there's a lot of additional information saved along in that image. In fact, this image also contains the equivalent of this, more specifically, this. Sure, it's not likely that someone's going to try to track me down and do me harm based upon image data associated with a picture I took of my cat, but I start by assuming the worst will happen. That's why, when we launched photos on Twitter, we made the decision to strip that geodata out. (Applause) If I start by assuming the worst and work backwards, I can make sure that the protections we build work for both expected and unexpected use cases.
这张图片能如何 导致我的死亡呢? 有一个可能性。 除了一只猫以外,这个图片里还有其它信息。 那里有地理信息。 当你用你的智能手机或数码相机 照一张照片时, 很多额外的信息 也会随着照片保留下来。 事实上,这张照图片还 指明了这个, 更加具体些,是这个。 没错,不大可能有人准备 根据我的猫的照片中数据 追踪我 并伤害我, 但是我开始假设最坏的事情会发生。 这也是为什么当我们推出加载图片功能的时候, 我们决定消除那些地理数据。 (掌声) 如果我从假设最坏的事开始, 并反向推理, 我可以确保我们所设置的保护 对于可预知与 不可预知的事件同时有效。
Given that I spend my days and nights imagining the worst that could happen, it wouldn't be surprising if my worldview was gloomy. (Laughter) It's not. The vast majority of interactions I see -- and I see a lot, believe me -- are positive, people reaching out to help or to connect or share information with each other. It's just that for those of us dealing with scale, for those of us tasked with keeping people safe, we have to assume the worst will happen, because for us, a one-in-a-million chance is pretty good odds.
假设我日夜 想象可能发生的最坏的事情, 我的世界观有些阴郁并不令人惊奇。 (笑声) 但这并不是事实。 我看到的绝大多数的(推特)互动 是积极的,相信我,我看过很多, 人们伸出援助之手, 或者相互连接或分享信息。 因为我们要应付安全风险, 我们承担着保证大众安全的责任, 我们必须假设最坏的事情会发生, 因为对于我们来说百万分之一的几率 是一个非常大的可能性。
Thank you.
谢谢
(Applause)
(掌声)