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  • My job at Twitter

    我在推特的工作

  • is to ensure user trust,

    就是確保使用者對推特的信任,

  • protect user rights and keep users safe,

    以及保護使用者的權益及安全,

  • both from each other

    不只是使用者之間

  • and, at times, from themselves.

    有時是有關使用者本身的權益及安全。

  • Let's talk about what scale looks like at Twitter.

    讓我們談談推特訊息的規模。

  • Back in January 2009,

    2009 年 1 月,

  • we saw more than two million new tweets each day

    每一天,我們在推特平台上

  • on the platform.

    看到超過 200 萬條新訊息。

  • January 2014, more than 500 million.

    2014 年 1 月,則有超過 5 億條訊息。

  • We were seeing two million tweets

    六分鐘內,

  • in less than six minutes.

    就有 200 萬條推文。

  • That's a 24,900-percent increase.

    那是 24,900% 的成長。

  • Now, the vast majority of activity on Twitter

    今天,絶大部分在推特上的活動

  • puts no one in harm's way.

    不會傷害任何人。

  • There's no risk involved.

    沒有任何風險。

  • My job is to root out and prevent activity that might.

    我的工作則是根除 任何可能傷害他人權益的活動。

  • Sounds straightforward, right?

    聽起來很簡單,對吧?

  • You might even think it'd be easy,

    你或許會認為這個工作很簡單,

  • given that I just said the vast majority

    尤其當我說,推特上絕大部分的動作

  • of activity on Twitter puts no one in harm's way.

    並不會對任何人造成傷害。

  • Why spend so much time

    那為什麼要花費這麼多時間

  • searching for potential calamities

    在無害的網路活動中,

  • in innocuous activities?

    尋找可能的危機?

  • Given the scale that Twitter is at,

    以推特的規模來看,

  • a one-in-a-million chance happens

    百萬分之一的機率,

  • 500 times a day.

    相當於一天會有 500 條 可能造成危害的訊息。

  • It's the same for other companies

    這個訊息量,是其他公司

  • dealing at this sort of scale.

    所要處理的訊息量相同

  • For us, edge cases,

    對我們而言,那些稀少罕見,

  • those rare situations that are unlikely to occur,

    不太可能發生的極端事件,

  • are more like norms.

    有如家常便飯。

  • Say 99.999 percent of tweets

    假設百分之 99.999% 的推文

  • pose no risk to anyone.

    都不會傷害任何人,

  • There's no threat involved.

    不涉及任何風險。

  • Maybe people are documenting travel landmarks

    也許大家只是在記錄旅遊景點,

  • like Australia's Heart Reef,

    像是澳洲的心形礁,

  • or tweeting about a concert they're attending,

    或是傳些關於他們正在參加的演唱會,

  • or sharing pictures of cute baby animals.

    或者是分享一些可愛小動物的照片。

  • After you take out that 99.999 percent,

    當你除去那 99.999% 的機率,

  • that tiny percentage of tweets remaining

    剩下極微小的百分比

  • works out to roughly

    粗估下來

  • 150,000 per month.

    每月大約有十五萬條訊息。

  • The sheer scale of what we're dealing with

    管理這麼龐大的規模,

  • makes for a challenge.

    是個挑戰。

  • You know what else makes my role

    你知道還有什麼

  • particularly challenging?

    讓我的工作更具挑戰性的嗎?

  • People do weird things.

    人會做些奇怪的事。

  • (Laughter)

    (笑聲)

  • And I have to figure out what they're doing,

    而我則必須搞清楚他們在做什麼,

  • why, and whether or not there's risk involved,

    動機是什麼,還有是否有危險性,

  • often without much in terms of context

    且通常是在沒有資料

  • or background.

    或背景的情況下就要去搞清楚。

  • I'm going to show you some examples

    讓我舉幾個我在推特工作時

  • that I've run into during my time at Twitter --

    遇到的例子,

  • these are all real examples

    這些全都是真實的案例,

  • of situations that at first seemed cut and dried,

    一些原先看來簡單明瞭的情況,

  • but the truth of the matter was something

    但事情的真相

  • altogether different.

    又是截然不同。

  • The details have been changed

    有些細節已被更改,

  • to protect the innocent

    是為了保護無辜的人,

  • and sometimes the guilty.

    有時也包括罪犯。

  • We'll start off easy.

    我們從簡單的開始。

  • ["Yo bitch"]

    [嘿 賤女人]

  • If you saw a Tweet that only said this,

    當你在推特上看到這句話,

  • you might think to yourself,

    你可能會認為:

  • "That looks like abuse."

    「那是一種辱罵」。

  • After all, why would you want to receive the message,

    畢竟,誰會希望收到這樣的訊息:

  • "Yo, bitch."

    「嘿,賤女人。」

  • Now, I try to stay relatively hip

    現在,我試著跟上趨勢

  • to the latest trends and memes,

    及最新流行用語,

  • so I knew that "yo, bitch"

    所以我知道「嘿,賤女人」

  • was also often a common greeting between friends,

    也常被用作朋友間的招呼用語

  • as well as being a popular "Breaking Bad" reference.

    是來自於《絕命毒師》的說法。

  • I will admit that I did not expect

    我得承認我沒有想到

  • to encounter a fourth use case.

    這句話會有第四種用法。

  • It turns out it is also used on Twitter

    原來在推特上,扮成狗的人

  • when people are role-playing as dogs.

    也會用這個詞。

  • (Laughter)

    (笑聲)

  • And in fact, in that case,

    事實上,在這個情況下,

  • it's not only not abusive,

    不止沒有辱罵的意味,

  • it's technically just an accurate greeting.

    嚴格說來,這是一個準確的問候用語。

  • (Laughter)

    (笑聲)

  • So okay, determining whether or not

    所以,一條沒有來龍去脈的訊息

  • something is abusive without context,

    要去判定這個訊息是否有辱罵的意味,

  • definitely hard.

    絕對是很困難的。

  • Let's look at spam.

    我們來看看垃圾訊息。

  • Here's an example of an account engaged

    這是使用者傳送垃圾訊息

  • in classic spammer behavior,

    的典型例子,

  • sending the exact same message

    一直不斷地傳送相同的訊息

  • to thousands of people.

    給上千個人。

  • While this is a mockup I put together using my account,

    這是我用自己帳號作出的模擬範例,

  • we see accounts doing this all the time.

    我們總可以看到使用者傳送這樣的訊息。

  • Seems pretty straightforward.

    看起來相當簡單明瞭。

  • We should just automatically suspend accounts

    我們應該自動封鎖

  • engaging in this kind of behavior.

    涉及這種行為的帳號。

  • Turns out there's some exceptions to that rule.

    結果總有些例外。

  • Turns out that that message could also be a notification

    這些訊息,也有可能是通知

  • you signed up for that the International Space Station is passing overhead

    你登記參加國際太空站經過你上空的活動,

  • because you wanted to go outside

    你希望收到通知,即時走到戶外

  • and see if you could see it.

    可以親自目睹。

  • You're not going to get that chance

    你絶不會因為

  • if we mistakenly suspend the account

    誤認為這是垃圾訊息

  • thinking it's spam.

    而停用這個帳號的情況發生。

  • Okay. Let's make the stakes higher.

    好。讓我們再把風險的層級提高。

  • Back to my account,

    再來看我的帳號,

  • again exhibiting classic behavior.

    在推特上展示特定的行為。

  • This time it's sending the same message and link.

    這次是在持特上傳送相同的訊息和連結

  • This is often indicative of something called phishing,

    這通常是一種網路釣魚,

  • somebody trying to steal another person's account information

    有人試著去引導他人到另一個網站

  • by directing them to another website.

    然後盜用他的帳號

  • That's pretty clearly not a good thing.

    很明顯這不是一件好事。

  • We want to, and do, suspend accounts

    我們要,而且必須去阻止

  • engaging in that kind of behavior.

    可疑的帳號去做這樣的行為。

  • So why are the stakes higher for this?

    但是,為何這麼做風險更高?

  • Well, this could also be a bystander at a rally

    這像是遊行人潮當中的旁觀者

  • who managed to record a video

    拿著攝影機,對著

  • of a police officer beating a non-violent protester

    警察動手打一個 無暴力行為的抗議者攝影,

  • who's trying to let the world know what's happening.

    好讓全世界的人知道此事。

  • We don't want to gamble

    我們不想冒這個險

  • on potentially silencing that crucial speech

    把有可能很重要的訊息

  • by classifying it as spam and suspending it.

    歸類為垃圾訊息,然後停用帳號。

  • That means we evaluate hundreds of parameters

    那意味著,當我們在觀察使用者行為時

  • when looking at account behaviors,

    我們憑估成千上百個因素,

  • and even then, we can still get it wrong

    即使是這麼做了,百密仍有一疏,

  • and have to reevaluate.

    必須再重新評估這些訊息。

  • Now, given the sorts of challenges I'm up against,

    現在,面臨各式各樣的挑戰,

  • it's crucial that I not only predict

    重要的是,不但要去預測可能發生的事,

  • but also design protections for the unexpected.

    而且要對可能發生的事, 設計一套因應的保護措施。

  • And that's not just an issue for me,

    這不僅事關我和推特,

  • or for Twitter, it's an issue for you.

    這也關係到你。

  • It's an issue for anybody who's building or creating

    關係到任何想創造美好事物,

  • something that you think is going to be amazing

    以及想要讓他人也一起 做美好事物的推特使用者。

  • and will let people do awesome things.

    所以我要怎麼做呢?

  • So what do I do?

    我一再思考這問題

  • I pause and I think,

    這些事情

  • how could all of this

    到底怎麼會出錯?

  • go horribly wrong?

    我想像發生災難的情形。

  • I visualize catastrophe.

    這很困難,

  • And that's hard. There's a sort of

    因為這麼做, 有點像是內在認知不協調,

  • inherent cognitive dissonance in doing that,

    就像是寫結婚誓言時,

  • like when you're writing your wedding vows

    同時也寫婚前協議書。

  • at the same time as your prenuptial agreement.

    (笑聲)

  • (Laughter)

    但還是必須要去做,

  • But you still have to do it,

    特別是每天要處理 5 億條推文。

  • particularly if you're marrying 500 million tweets per day.

    我所說的「想像災難」是什麼意思呢?

  • What do I mean by "visualize catastrophe?"

    我試著去想像,

  • I try to think of how something as

    像是一張無害的貓咪照片

  • benign and innocuous as a picture of a cat

    為何可能導致死亡,

  • could lead to death,

    以及如何避免這種事情發生。

  • and what to do to prevent that.

    正是接下來我要說的例子。

  • Which happens to be my next example.

    這隻是我的貓,叫伊萊。

  • This is my cat, Eli.

    我們盡可能讓推特的使用者

  • We wanted to give users the ability

    在推特上傳送圖片,

  • to add photos to their tweets.

    一張圖勝過千言萬語,

  • A picture is worth a thousand words.

    而一次推文只能傳送 140 個字。

  • You only get 140 characters.

    你在推文加入圖片,

  • You add a photo to your tweet,

    你會發現推文的內容更加豐富。

  • look at how much more content you've got now.

    藉由推特加入圖片的功能,

  • There's all sorts of great things you can do

    你可以做各種麼美妙的事。

  • by adding a photo to a tweet.

    我的工作不是去想這些事情。

  • My job isn't to think of those.

    而是去想事情可能會出什麼差錯。

  • It's to think of what could go wrong.

    這張圖片

  • How could this picture

    如何導致我死亡?

  • lead to my death?

    有一個可能性。

  • Well, here's one possibility.

    這張圖的資訊不只是一隻貓。

  • There's more in that picture than just a cat.

    還有地理資訊在裡頭。

  • There's geodata.

    當你以智慧型手機

  • When you take a picture with your smartphone

    或數位相機拍照,

  • or digital camera,

    會有許多額外的資訊

  • there's a lot of additional information

    儲存在照片裡。

  • saved along in that image.

    事實上,這張照片還包含

  • In fact, this image also contains

    相當於這個的資訊,

  • the equivalent of this,

    更具體地說是這個。

  • more specifically, this.

    當然,不太可能有人嘗試

  • Sure, it's not likely that someone's going to try

    根據這張貓照片的相關資訊

  • to track me down and do me harm

    追蹤我以及傷害我。

  • based upon image data associated

    但我一開始就要假設 最壞的情況一定會發生,

  • with a picture I took of my cat,

    這就是為什麼我們 在開放上傳照片到推特時,

  • but I start by assuming the worst will happen.

    就決定把照片裡的地理資訊全刪掉。

  • That's why, when we launched photos on Twitter,

    (掌聲)

  • we made the decision to strip that geodata out.

    如果一開始,我就假設 可能發生最壞的情況,

  • (Applause)

    然後再往前倒推,

  • If I start by assuming the worst

    我可以確定我們建立的保護制度,

  • and work backwards,

    可以應付意料中

  • I can make sure that the protections we build

    以及意料外的事件。

  • work for both expected

    我日夜地

  • and unexpected use cases.

    想像發生最壞情況的情形,

  • Given that I spend my days and nights

    如果因此造成我憂鬱的世界觀, 也不會令人感到意外。

  • imagining the worst that could happen,

    (笶聲)

  • it wouldn't be surprising if my worldview was gloomy.

    其實並非如此。

  • (Laughter)

    我看到的絶大部份互動,

  • It's not.

    我看了很多,相信我, 它們都是正面的。

  • The vast majority of interactions I see --

    人們伸出援手互相幫忙,

  • and I see a lot, believe me -- are positive,

    彼此互相連絡或分享資訊。

  • people reaching out to help

    只是我們要處理龐大的資訊量,

  • or to connect or share information with each other.

    承擔保護使用者安全的責任,

  • It's just that for those of us dealing with scale,

    所以必須假設將發生最壞的情況,

  • for those of us tasked with keeping people safe,

    對我們來說,百萬分之一的可能性

  • we have to assume the worst will happen,

    是相當高的機率。

  • because for us, a one-in-a-million chance

    謝謝。

  • is pretty good odds.

    (掌聲)

  • Thank you.

  • (Applause)

My job at Twitter

我在推特的工作

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